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2,700 | A Unified Maximum Likelihood Framework for Simultaneous Motion and T-1 Estimation in Quantitative MR T-1 Mapping | In quantitative MR T-1 mapping, the spin-lattice relaxation time T-1 of tissues is estimated from a series of T-1-weighted images. As the T-1 estimation is a voxel-wise estimation procedure, correct spatial alignment of the T-1-weighted images is crucial. Conventionally, the T-1-weighted images are first registered based on a general-purpose registration metric, after which the T-1 map is estimated. However, as demonstrated in this paper, such a two-step approach leads to a bias in the final T-1 map. In our work, instead of considering motion correction as a preprocessing step, we recover the motion-free T-1 map using a unified estimation approach. In particular, we propose a unified framework where the motion parameters and the T-1 map are simultaneously estimated with a Maximum Likelihood (ML) estimator. With our framework, the relaxation model, the motion model as well as the data statistics are jointly incorporated to provide substantially more accurate motion and T-1 parameter estimates. Experiments with realistic Monte Carlo simulations show that the proposed unified ML framework outperforms the conventional two-step approach as well as state-of-the-art model-based approaches, in terms of both motion and T-1 map accuracy and mean-square error. Furthermore, the proposed method was additionally validated in a controlled experiment with real T-1-weighted data and with two in vivo human brain T-1-weighted data sets, showing its applicability in real-life scenarios. |
2,701 | Art in Urban Spaces | This study investigates the effect of art on promoting the meaning of the urban space. After considering the semantic dimension of the urban space and the mechanism of transferring the meanings of art through the views of experts, a model is presented for examining the art's cooperation in promoting urban space meaning. In the first stage, the categories of space meanings influenced by art were extracted using the qualitative method of interpretative phenomenological analysis, and by examining 61 in-depth interviews in 6 urban spaces eligible for urban art in Tehran. In the second stage, these categories were surveyed in these spaces through 600 questionnaires after converting to the questionnaire items. Based on the results, "experience and perception capability", "social participation", and "relationship with context" were the main themes of the semantic relationships between art and urban space. Further, the lower scores related to the theme of "social participation" in the quantitative investigations indicate that this theme was weaker than the other themes in promoting the meaning of the urban space through the art in the selected urban spaces. |
2,702 | Ancient DNA evidence for the ecological globalization of cod fishing in medieval and post-medieval Europe | Understanding the historical emergence and growth of long-range fisheries can provide fundamental insights into the timing of ecological impacts and the development of coastal communities during the last millennium. Whole-genome sequencing approaches can improve such understanding by determining the origin of archaeological fish specimens that may have been obtained from historic trade or distant water. Here, we used genome-wide data to individually infer the biological source of 37 ancient Atlantic cod specimens (ca 1050-1950 CE) from England and Spain. Our findings provide novel genetic evidence that eleventh- to twelfth-century specimens from London were predominantly obtained from nearby populations, while thirteenth- to fourteenth-century specimens were derived from distant sources. Our results further suggest that Icelandic cod was indeed exported to London earlier than previously reported. Our observations confirm the chronology and geography of the trans-Atlantic cod trade from Newfoundland to Spain starting by the early sixteenth century. Our findings demonstrate the utility of whole-genome sequencing and ancient DNA approaches to describe the globalization of marine fisheries and increase our understanding regarding the extent of the North Atlantic fish trade and long-range fisheries in medieval and early modern times. |
2,703 | Knema retusa is antibacterial and antibiofilm against antibiotic resistant Staphylococcus aureus and S. haemolyticus isolated in bovine mastitis | This study aimed to assess antibacterial activity of Knema retusa wood extract (KRe) against antibiotic resistant staphylococci which are causative agents of bovine mastitis. From 75 cases of intramammary infections in dairy cows, 66 staphylococcal isolates were collected, including 11 Staphylococcus aureus isolates (17%) and 55 coagulase-negative staphylococci (83%). Sixty isolates (91%) formed strong biofilms. KRe had minimal inhibitory concentrations (MIC) and minimal bactericidal concentrations (MBC) against the isolates ranging 32-256 ug/mL and 64-512 ug/mL, respectively. Two-hour KRe exposures at 4×MIC, viabilities of S. aureus and S. haemolyticus decreased by 3 log10 compared to the control. Scanning EM (SEM) showed that KRe disrupted the bacterial cells of both species. KRe at 1/16×MIC significantly inhibited biofilm formation (P < 0.05) in both S. aureus and S. haemolyticus. At 1/2×MIC, S. aureus and S. haemolyticus biofilm inhibition ranged from 75 to 99%. Cells within established biofilms were disrupted 66-83% by KRe at 32×MIC. Moreover, 1/2×MIC KRe reduced bacterial adhesion to glass surfaces observed by SEM. According to GC-MS analysis, the major compound in KRe was endo-2-hydroxy-9,9-(ethylenedioxy)-1-carbethoxy bicyclo [3.3.1] nonane (E2N). Molecular docking analysis of E2N has a high affinity for staphylococcal accessory regulator A (SarA), binding free-energy - 6.40kcal/mol. The results suggested that KRe may have medicinal benefits by inhibiting the growth, biofilm, and adhesion of antibiotic resistant staphylococci isolated from bovine mastitis. |
2,704 | RESEARCH ON THE APPLICATION OF ECOLOGICAL CONCEPTS IN INDOOR ENVIRONMENTAL ART DESIGN | At present. with the continuous improvement of the economic level of our society, people's quality of life has also been significantly improved. In recent years. our society has vigorously advocated the concept of eco-environmental protection and strived to create an environment-friendly indoor environment in the field of architecture. Therefore, ecological concept should be integrated into indoor environment design to provide people with a green and healthy living environment. Therefore, the next research will focus on the concept of ecology and its application in indoor environmental art design. In this paper, the basic principles of environment, art and ecology arc interrelated, and the basic basis and conception of ecological philosophy in environmental art design are deeply explored, providing reference for the artificial transformation of natural and modern environmental art design. |
2,705 | Molecular hallmarks of long non-coding RNAs in aging and its significant effect on aging-associated diseases | Aging is linked to the deterioration of many physical and cognitive abilities and is the leading risk factor for Alzheimer's disease. The growing aging population is a significant healthcare problem globally that researchers must investigate to better understand the underlying aging processes. Advances in microarrays and sequencing techniques have resulted in deeper analyses of diverse essential genomes (e.g., mouse, human, and rat) and their corresponding cell types, their organ-specific transcriptomes, and the tissue involved in aging. Traditional gene controllers such as DNA- and RNA-binding proteins significantly influence such programs, causing the need to sort out long non-coding RNAs, a new class of powerful gene regulatory elements. However, their functional significance in the aging process and senescence has yet to be investigated and identified. Several recent researchers have associated the initiation and development of senescence and aging in mammals with several well-reported and novel long non-coding RNAs. In this review article, we identified and analyzed the evolving functions of long non-coding RNAs in cellular processes, including cellular senescence, aging, and age-related pathogenesis, which are the major hallmarks of long non-coding RNAs in aging. |
2,706 | Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach | Establishing accurate electrical load prediction is vital for pricing and power system management. However, the unpredictable behavior of private and industrial users results in uncertainty in these power systems. Furthermore, the utilization of renewable energy sources, which are often variable in their production rates, also increases the complexity making predictions even more difficult. In this paper an interval type-2 intuitionist fuzzy logic system whose parameters are trained in a hybrid fashion using gravitational search algorithms with the ridge least square algorithm is presented for short-term prediction of electrical loading. Simulation results are provided to compare the performance of the proposed approach with that of state-of-the-art electrical load prediction algorithms for Poland, and five regions of Australia. The simulation results demonstrate the superior performance of the proposed approach over seven different current state-of-the-art prediction algorithms in the literature, namely: SVR, ANN, ELM, EEMD-ELM-GOA, EEMD-ELM-DA, EEMD-ELM-PSO and EEMD-ELM-GWO. |
2,707 | Concentrations, sources, and health risk assessment of metals in indoor dust collected from visual arts studios of selected tertiary institutions in Southern Nigeria | This study provides data on the concentrations and occupational risk of Cd, Pb, Cr, Ni, Cu, Co, Mn, Zn, and Fe in indoor dust from visual arts studios of nine tertiary institutions in southern Nigeria. The dust samples were digested in aqua regia and their metal concentrations were quantified by atomic absorption spectrometry. The concentrations of metals in dust from visual arts studios ranged from not detected (nd) to 91.5 mg kg(-1) Cd, 4.5 to 540 mg kg(-1) Pb, 0.10 to 1,100 mg kg(-1) Cr, 0.50 to 1,150 mg kg(-1) Ni, 10 to 15,600 mg kg(-1) Cu, 0.5 to 146 mg kg(-1) Co, 3.0 to 3,680 mg kg(-1) Mn, 93.5 to 9,600 mg kg(-1) Zn, and 853 to 237,000 mg kg(-1) Fe. The degree of contamination of the dust particles by metals was assessed by making use of the contamination/pollution index, geoaccumulation index and enrichment factor. These indices suggested that dusts from these visual arts studios were impacted with Cd, Pb, Cu, and Zn. The hazard index (HI) and cancer risk values relating to adults' exposure to metals in dust from these arts studios were within safe limits. Principal component analysis indicated that the sources of metal contamination in dust from these visual arts studios were related to inputs from constituents of the artist's materials and vehicular emissions. |
2,708 | A Review on Organic Fluorimetric and Colorimetric Chemosensors for the Detection of Ag(I) Ions | Organic compounds display several electronic and structural features which enable their application in various fields, ranging from biological to non-biological. These compounds contain heteroatoms like sulfur, nitrogen and oxygen, which provide coordination sites to act as ligands in the field of coordination chemistry and are used as chemosensors to detect various metal ions. This review article covers different organic compounds including thiourea, Schiff base, pyridine, thiophene, coumarin, triazolyl pyrenes, imidazole, fluorescein, thiazole, tricarbocyanine, rhodanine, porphyrin, hydrazone, benzidine and other functional groups based chemosensors, that contain heteroatoms like sulfur, nitrogen and, oxygen for fluorimetric and colorimetric detection of Ag+ in different environmental, agricultural, and biological samples. Further, the sensing mechanism and performances of these chemosensors have been discussed, which could help the readers for the future design of highly efficient, selective, and sensitive chemosensors for the detection and determination of Ag+ ions. |
2,709 | Partitioning Histopathological Images: An Integrated Framework for Supervised Color-Texture Segmentation and Cell Splitting | For quantitative analysis of histopathological images, such as the lymphoma grading systems, quantification of features is usually carried out on single cells before categorizing them by classification algorithms. To this end, we propose an integrated framework consisting of a novel supervised cell-image segmentation algorithm and a new touching-cell splitting method. For the segmentation part, we segment the cell regions from the other areas by classifying the image pixels into either cell or extra-cellular category. Instead of using pixel color intensities, the color-texture extracted at the local neighborhood of each pixel is utilized as the input to our classification algorithm. The color-texture at each pixel is extracted by local Fourier transform (LFT) from a new color space, the most discriminant color space (MDC). The MDC color space is optimized to be a linear combination of the original RGB color space so that the extracted LFT texture features in the MDC color space can achieve most discrimination in terms of classification (segmentation) performance. To speed up the texture feature extraction process, we develop an efficient LFT extraction algorithm based on image shifting and image integral. For the splitting part, given a connected component of the segmentation map, we initially differentiate whether it is a touching-cell clump or a single nontouching cell. The differentiation is mainly based on the distance between the most likely radial-symmetry center and the geometrical center of the connected component. The boundaries of touching-cell clumps are smoothed out by Fourier shape descriptor before carrying out an iterative, concave-point and radial-symmetry based splitting algorithm. To test the validity, effectiveness and efficiency of the framework, it is applied to follicular lymphoma pathological images, which exhibit complex background and extracellular texture with nonuniform illumination condition. For comparison purposes, the results of the proposed segmentation algorithm are evaluated against the outputs of superpixel, graph-cut, mean-shift, and two state-of-the-art pathological image segmentation methods using ground-truth that was established by manual segmentation of cells in the original images. Our segmentation algorithm achieves better results than the other compared methods. The results of splitting are evaluated in terms of under-splitting, over-splitting, and encroachment errors. By summing up the three types of errors, we achieve a total error rate of 5.25% per image. |
2,710 | Deep Renyi entropy graph kernel | Graph kernels are applied heavily for the classification of structured data. In this paper, we propose a deep Renyi entropy graph kernel for this purpose. We gauge the deep information through a family of h-layer expansion subgraphs rooted at a vertex, and define a h-layer depth-based second-order Renyi entropy representation for each vertex. The second-order Renyi entropy representation is used together with Euclidean distance to build a deep second-order Renyi entropy graph kernel (SREGK). For graphs with n vertices, the time complexity for our kernel is O(n(3)). This low-order polynomial complexity enables our subgraph kernels to easily scale up to graphs of reasonably large sizes and thus overcome the size limits arising in state-of-the-art graph kernels. Experimental results on fourteen real world graph datasets are shown to demonstrate the overall superior performance of our approach over a number of state-of-the-art methods. (C) 2020 Elsevier Ltd. All rights reserved. |
2,711 | Real-time tracking based on deep feature fusion | Deep learning-based methods have recently attracted significant attention in visual tracking community, leading to an increase in state-of-the-art tracking performance. However, due to the utilization of more complex models, it has also been accompanied with a decrease in speed. For real-time tracking applications, a careful balance of performance and speed is required. We propose a real-time tracking method based on deep feature fusion, which combines deep learning with kernel correlation filter. First, hierarchical features are extracted from a lightweight pre-trained convolutional neural network. Then, original features of different levels are fused using canonical correlation analysis. Fused features, as well as some original deep features, are used in three kernel correlation filters to track the target. An adaptive update strategy, based on dispersion analysis of response maps for the correlation filters, is proposed to improve robustness to target appearance changes. Different update frequencies are adopted for the three filters to adapt to severe appearance changes. We perform extensive experiments on two benchmarks: OTB-50 and OTB-100. Quantitative and qualitative evaluations show that the proposed tracking method performs favorably against some state-of-the-art methods - even better than algorithms using complex network model. Furthermore, proposed algorithm runs faster than 20 frame per second (FPS) and hence able to achieve near real-time tracking. |
2,712 | Improving Large-Scale Image Retrieval Through Robust Aggregation of Local Descriptors | Visual search and image retrieval underpin numerous applications, however the task is still challenging predominantly due to the variability of object appearance and ever increasing size of the databases, often exceeding billions of images. Prior art methods rely on aggregation of local scale-invariant descriptors, such as SIFT, via mechanisms including Bag of Visual Words (BoW), Vector of Locally Aggregated Descriptors (VLAD) and Fisher Vectors (FV). However, their performance is still short of what is required. This paper presents a novel method for deriving a compact and distinctive representation of image content called Robust Visual Descriptor with Whitening (RVD-W). It significantly advances the state of the art and delivers world-class performance. In our approach local descriptors are rank-assigned to multiple clusters. Residual vectors are then computed in each cluster, normalized using a direction-preserving normalization function and aggregated based on the neighborhood rank. Importantly, the residual vectors are de-correlated and whitened in each cluster before aggregation, leading to a balanced energy distribution in each dimension and significantly improved performance. We also propose a new post-PCA normalization approach which improves separability between the matching and non-matching global descriptors. This new normalization benefits not only our RVD-W descriptor but also improves existing approaches based on FV and VLAD aggregation. Furthermore, we show that the aggregation framework developed using hand-crafted SIFT features also performs exceptionally well with Convolutional Neural Network (CNN) based features. The RVD-W pipeline outperforms state-of-the-art global descriptors on both the Holidays and Oxford datasets. On the large scale datasets, Holidays1M and Oxford1M, SIFT-based RVD-W representation obtains a mAP of 45.1 and 35.1 percent, while CNN-based RVD-W achieve a mAP of 63.5 and 44.8 percent, all yielding superior performance to the state-of-the-art. |
2,713 | Charge-driven arrested phase-separation of polyelectrolyte-gold nanoparticle assemblies leading to plasmonic oligomers | Aggregates of charged metal particles obtained by electrostatic coupling with a compound of opposite charge in the vicinity of the net zero charge ratio are of interest in the field of plasmonics because the inter-particle distance is minimal, which favours plasmonic coupling. However, these structures present a low colloidal stability limiting the development of applications. In this article we show that globally neutral aggregates formed by electrostatic complexation of citrate-stabilized gold particles and a quaternized chitosan (i.e., polycation) around the net zero charge ratio could be stabilized at a nanometric size by the subsequent addition of polyelectrolyte chains. Furthermore, the sign of the charge carried by the stabilizing chains determines the sign of the global charge carried by the stabilized complexes. The stabilization is demonstrated in saline environment on a broad pH range as well as in a cell culture media over periods of several days. Contrarily to stabilization by charged particles, our stabilized complexes are found to retain their initial characteristics (i.e. shape, size, internal structure and optical properties) after stabilization. Hence, the plasmonic coupling allows to maximize the optical absorption around the 800 nm wavelength at which the lasers used for thermoplasmonic and surface enhanced Raman scattering analysis operate. |
2,714 | Survival benefit of combinatorial osimertinib rechallenge and entrectinib in an EGFR-mutant NSCLC patient with acquired LMNA-NTRK1 fusion following osimertinib resistance | Acquired resistance to osimertinib is inevitable and heterogeneous despite its documented efficacy against EGFR-mutated non-small cell lung cancer (NSCLC). Subsequent therapeutic options assume the dominant form of the resistance mechanism; however, the more rare oncogenic driver, NTRK1 fusion, has also reportedly conferred osimertinib resistance. Nevertheless, clear-cut options when NSCLCs are driven by EGFR mutation and the subsequent NTRK fusion are lacking. This is a case of NSCLC wherein exon 19 deletion in EGFR (19del) and acquired LMNA-NTRK1 fusion were accompanied by the persistence of EGFR T790M. The patient underwent peritoneal metastasis after multiple targeted therapies: gefitinib, osimertinib, chemotherapy, and anlotinib plus docetaxel (in clinical trials). Osimertinib was subsequently re-administered with the NTRK fusion inhibitor entrectinib, resulting in remission of peritoneal metastases even after slow progression of pancreatic metastasis over the following 5 months. An extensive literature review to identify the efficacies of therapies for NTRK fusion as the means to acquired resistance to EGFR TKIs revealed that blocking both the EGFR mutation and the subsequent NTRK fusion can provide clinical benefits following EGFR TKIs resistance; however, the efficacy and safety of combination therapies must be further investigated. To precisely manage EGFR-mutated NSCLCs, it is also essential to identify the resistance mechanisms by repeating biopsies. |
2,715 | Application of a new integrated sediment quality assessment method to Huelva estuary and its littoral of influence (Southwestern Spain) | A new integrated sediment quality assessment method composed of several assays (particle size profile, total metal content, protease K extraction, total organic carbon, toxicity bioassay with Photobacterium phosphoreum and macrobenthic community alteration) that provides a single result, the environmental degradation index (EDI), has been developed. The new method was tested on the Huelva estuary (southwest of Spain), a highly polluted area where metals dissolved in the water of the Tinto and Odiel rivers precipitate after flowing through the Iberian Pyrite Belt, one of the largest metallogenic areas of massive sulphide deposits in the world. The proposed method satisfactorily was able to reflect different degrees of pollution on the environmental degradation index. Thus, EDI categorized littoral samples as slightly degraded and all the Tinto and some of the Odiel as very highly degraded, emphasizing the lower zone of the Tinto estuary as the most deeply degraded of the entire study area. |
2,716 | Centroidal Voronoi Tessellations- A New Approach to Random Testing | Although Random Testing (RT) is low cost and straightforward, its effectiveness is not satisfactory. To increase the effectiveness of RT, researchers have developed Adaptive Random Testing (ART) and Quasi-Random Testing (QRT) methods which attempt to maximize the test case coverage of the input domain. This paper proposes the use of Centroidal Voronoi Tessellations (CVT) to address this problem. Accordingly, a test case generation method, namely, Random Border CVT (RBCVT), is proposed which can enhance the previous RT methods to improve their coverage of the input space. The generated test cases by the other methods act as the input to the RBCVT algorithm and the output is an improved set of test cases. Therefore, RBCVT is not an independent method and is considered as an add-on to the previous methods. An extensive simulation study and a mutant-based software testing investigation have been performed to demonstrate the effectiveness of RBCVT against the ART and QRT methods. Results from the experimental frameworks demonstrate that RBCVT outperforms previous methods. In addition, a novel search algorithm has been incorporated into RBCVT reducing the order of computational complexity of the new approach. To further analyze the RBCVT method, randomness analysis was undertaken demonstrating that RBCVT has the same characteristics as ART methods in this regard. |
2,717 | Keeping Watch on Intangible Cultural Heritage: Live Transmission and Sustainable Development of Chinese Lacquer Art | Countries all over the world have been constantly exploring ways to rescue and protect intangible cultural heritage. While learning from other countries' protection measures, the Chinese government is also constantly exploring ways that conform to China's national conditions. As China's first batch of intangible cultural heritage, lacquer art boasts a brilliant history, but many people are not familiar with it today. Moreover, in the process of modernization, the lacquer art transmission is declining day by day, and it is facing unprecedented major crises such as loss and division of history into periods. Hence, it is essential to verify and reveal the challenges and dilemmas in the lacquer art transmission, and come up with corresponding protection measures around these problems. First of all, this research, through literature review, horizontally explores the current research status and the universal problems of lacquer art transmission from the macro level. With a view to make up for the deficiencies of the existing research and further supplement the empirical evidence, the current research, with the transmission of Chengdu lacquer art as an example and through in-depth interviews, tracks and investigates the whole process of transmission of Chengdu Lacquer Art Training Institute, and vertically analyzes the survival situation of lacquer art transmission and the core problems affecting transmission behaviors from the micro level. In the final conclusion, the research comes up with corresponding countermeasures and suggestions for the identified key problems, which is of significant reference value for facilitating the live transmission and sustainable development of Chinese lacquer art. |
2,718 | A 36 mu W 2.8-3.4 dB Noise Figure Impedance Boosted and Noise Attenuated LNA for NB-IoT | This paper describes an ultra-low-power low-noise amplifier (LNA) targeting the 617-652 MHz narrowband-IoT (NB-IoT) frequency band. The design breaks the trade-off in practice between the input matching, minimum required DC current, and minimum NF by using a step-down transformer with an equivalent turns ratio of less than 1, resulting in input impedance boosting and noise attenuation of the main transistor. A local feedback loop is also employed to use the LNA current source transconductance to further attenuate the main transistor noise without additional power cost. The LNA power consumption scales efficiently with the required overall transconductance without being limited to the input matching condition, in practice, while enabling a sub-3dB minimum NF, making it a suitable option for a wide range of applications. A comparison between the proposed, conventional, and state-of-the-art low-power LNA structures is presented with both analytical and simulation models, while measurement results of a prototype designed in a 65 nm technology show a sub-3dB minimum noise figure (NF), -8.8 dBm IIP3, 15 dB gain, and a state-of-the-art FoM of 39.74 dB while consuming only 36 mu W from a 0.55 V supply. |
2,719 | An Educational Needs Assessment for Outpatient Palliative Care Clinicians | Introduction: As the field of palliative medicine continues to grow in community-based settings, outpatient palliative care clinics have become an important site for providing upstream palliative care to patients and families. It is unclear whether current training models, focused predominantly on the inpatient setting, adequately prepare clinicians for outpatient palliative care practice. Methods: We performed an online educational needs assessment survey of physicians and advanced practice providers working in outpatient palliative care clinics. Survey questions focused on the importance of specific palliative care knowledge, skills, and attitudes in outpatient practice using the Accreditation Council of Graduate Medical Education Hospice and Palliative Medicine (HPM) curricular milestones to guide survey development. We also explored clinician perception of training adequacy and current educational needs relevant to outpatient practice. Results: One hundred sixty-four clinicians, including 122 (74.4%) physicians, 32 (19.5%) nurse practitioners, and 8 (4.9%) physician assistants, completed our survey. Clinicians had a median of 10 years of HPM experience and 6 years of outpatient experience. We identified two main areas of perceived knowledge or skill deficit: navigating insurance and prior authorizations and co-management of pain and opioid use disorder. Conclusion: Addressing gaps in education and preparedness for outpatient practice is essential to improve clinician competence and efficiency as well as patient care, safety, and care coordination. This study identifies practice management and opioid stewardship as potential targets for educational interventions. The development of curricula related to these outpatient skills may improve clinicians' ability to provide safe, patient-centered care with confidence. |
2,720 | Locating Facial Landmarks Using Probabilistic Random Forest | Random forest is a useful tool for face alignment/tracking. The method of regressing local binary features learned from random forest has achieved state-of-the-art performance both in fitting accuracy and speed. Despite the great success of this method, it has certain weaknesses: the number of available local binary features is rather limited and is not optimal for face alignment; the binary features inevitably lead to serious jitter when tracking a video sequence. To address these problems, we propose learning probability features from probabilistic random forest (PRF). The proposed PRF is the same as standard random forest except that it models the probability of a sample belonging to the nodes of a tree. By using the probability features, our method significantly outperforms the state-of-the-art in terms of accuracy. It also achieves about 60 fps for locating a few facial landmarks. In addition, our method shows excellent stability in face tracking. |
2,721 | Improving Chamfer Template Matching Using Image Segmentation | This letter proposes an effective method to improve object location in Chamfer template matching (CTM) based object detection using image segmentation. In our method, object bounding boxes are iteratively adjusted to fit with the object images obtained from image segmentation in a probabilistic model. The proposed method was tested with state-of-the-art CTM-based object detectors. Experimental results have shown the proposed method improved the location accuracy of the object detectors and reduce the false alarms rate. |
2,722 | Using a 2x-thru standard to achieve accurate de-embedding of measurements | The broadband measurement of interconnects and on-board devices requires the usage of test fixtures in order to connect to the measurement instrumentation. Proper assessment of the device performance requires removal of the effects of these test fixtures which is done using a de-embedding procedure. Previous de-embedding procedures such as Thru-Reflect-Line (TRL), Line-Reflect-Match (LRM) and other similar methods require the measurement of multiple standards. Alternatively, some methods such as thru de-embedding techniques require measurement of one standard with explicit computation of only two or three of the four error terms. This is justified by using the sometimes questionable assumption of fixture reciprocity. Prior art also does not include derivation of all of the required equations. Proposed and explained in detail here is the usage of a 2x-thru standard which is manipulated to derive complete fixture models without making assumptions about reciprocity or symmetry. Subsequently these models are mathematically removed from the indirect measurement, thus isolating the performance of the DUT. In contrast to prior art, this method uses only one standard instead of three, and it computes all four terms to make a complete fixture model. Several test cases are presented which illustrate the accuracy and validity of the 2x-thru method for broadband applications. |
2,723 | Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images | Despite the promise of Convolutional neural network (CNN) based classification models for histopathological images, it is infeasible to quantify its uncertainties. Moreover, CNNs may suffer from overfitting when the data is biased. We show that Bayesian-CNN can overcome these limitations by regularizing automatically and by quantifying the uncertainty. We have developed a novel technique to utilize the uncertainties provided by the Bayesian-CNN that significantly improves the performance on a large fraction of the test data (about 6% improvement in accuracy on 77% of test data). Further, we provide a novel explanation for the uncertainty by projecting the data into a low dimensional space through a nonlinear dimensionality reduction technique. This dimensionality reduction enables interpretation of the test data through visualization and reveals the structure of the data in a low dimensional feature space. We show that the Bayesian-CNN can perform much better than the state-of-the-art transfer learning CNN (TL-CNN) by reducing the false negative and false positive by 11% and 7.7% respectively for the present data set. It achieves this performance with only 1.86 million parameters as compared to 134.33 million for TL-CNN. Besides, we modify the Bayesian-CNN by introducing a stochastic adaptive activation function. The modified Bayesian-CNN performs slightly better than Bayesian-CNN on all performance metrics and significantly reduces the number of false negatives and false positives (3% reduction for both). We also show that these results are statistically significant by performing McNemar's statistical significance test. This work shows the advantages of Bayesian-CNN against the state-of-the-art, explains and utilizes the uncertainties for histopathological images. It should find applications in various medical image classifications. |
2,724 | Associations of urinary phthalate metabolites and lipid peroxidation with sperm mitochondrial DNA copy number and deletions | Background: Phthalates, a chemical class of plasticizers, are ubiquitous environmental contaminants that have been associated with oxidative stress. Mitochondria DNA copy number (mtDNAcn) and DNA deletions (mtDNAdel) are emerging biomarkers for cellular oxidative stress and environment exposures. Objectives: To examine associations of urinary phthalate metabolite and isoprostane concentrations on sperm mtDNAcn and mtDNAdel in male partners undergoing assisted reproductive technologies (ART). Methods: Ninety-nine sperm samples were collected from male partners undergoing ART at Baystate Medical Center in Springfield, MA as part of the Sperm Environmental Epigenetics and Development Study (SEEDS). Seventeen urinary phthalate metabolite concentrations were analyzed by the Centers for Disease Control using tandem mass spectrometry. Urinary 15-F2t-isoprostane concentrations, a biomarker of lipid peroxidation, were measured using a competitive enzyme-linked immunosorbent assay. A triplex qPCR method was used to determine the relative quantification of mtDNAcn and mtDNAdel. Results: Sperm mtDNAcn and mtDNAdel were positively correlated (Spearman rho = 0.31; p =.002). Adjusting for age, BMI, current smoking, race, and measurement batch, urinary monocarboxy-isononyl phthalate (MCNP) concentrations were positively associated with mtDNAcn (13 = 1.63, 95% CI: 0.14, 3.11). Other urinary phthalate metabolite and isoprostane concentrations were not associated with sperm mtDNAcn or mtDNAdel. Conclusions: Among this cohort of male ART participants, those with higher MCNP had higher mtDNAcn; other phthalate metabolites and isoprostane were not associated with mtDNAcn and mtDNAdel. Given our relatively small sample size, our results should be interpreted with caution. Future research is needed to replicate the findings in larger studies and among sperm samples obtained from the general population. |
2,725 | An approach to collaboration of growing self-organizing maps and adaptive resonance theory maps | Collaboration of growing self-organizing maps (GSOM) and adaptive resonance theory maps (ART) is considered through traveling sales-person problems (TSP). The ART is used to parallelize the GSOM: it divides the input space of city positions into subspaces automatically. One GSOM is allocated to each subspace and grows following the input data. After all the GSOMs grow sufficiently they are connected and we obtain a tour. Basic experimental results suggest that we can find semi-optimal solution much faster than serial methods. |
2,726 | Site-specific Interaction Mapping of Phosphorylated Ubiquitin to Uncover Parkin Activation | Damaged mitochondria are eliminated through autophagy machinery. A cytosolic E3 ubiquitin ligase Parkin, a gene product mutated in familial Parkinsonism, is essential for this pathway. Recent progress has revealed that phosphorylation of both Parkin and ubiquitin at Ser(65) by PINK1 are crucial for activation and recruitment of Parkin to the damaged mitochondria. However, the mechanism by which phosphorylated ubiquitin associates with and activates phosphorylated Parkin E3 ligase activity remains largely unknown. Here, we analyze interactions between phosphorylated forms of both Parkin and ubiquitin at a spatial resolution of the amino acid residue by site-specific photo-crosslinking. We reveal that the in-between-RING (IBR) domain along with RING1 domain of Parkin preferentially binds to ubiquitin in a phosphorylation-dependent manner. Furthermore, another approach, the Fluoppi (fluorescent-based technology detecting protein-protein interaction) assay, also showed that pathogenic mutations in these domains blocked interactions with phosphomimetic ubiquitin in mammalian cells. Molecular modeling based on the site-specific photo-crosslinking interaction map combined with mass spectrometry strongly suggests that a novel binding mechanism between Parkin and ubiquitin leads to a Parkin conformational change with subsequent activation of Parkin E3 ligase activity. |
2,727 | Analysis of Per- and Poly(fluoroalkyl) Substances (PFASs) in Highly Consumed Seafood Products from U.S. Markets | Seafood consumption has been identified as one of the major contributors of per- and poly(fluoroalkyl) substances (PFASs) to the human diet. To assess dietary exposure, highly consumed seafood products in the United States were selected for analysis. The analytical method previously used for processed food was extended to include four additional long-chain perflurocarboxylic acids (PFCAs), which have been reported in seafood samples. This method was single-lab-validated, and method detection limits were reported at 345 ng kg-1 for perfluorobutanoic acid (PFBA) and 207 ng kg-1 for perfluoropentanoic acid (PFPeA) and below 100 ng kg-1 for the rest of the PFAS analytes. The 81 seafood samples (clams, crab, tuna, shrimp, tilapia, cod, salmon, pollock) were analyzed for 20 PFASs using the updated analytical method. Most of the seafood packaging was also analyzed by Fourier transform infrared-attenuated total reflectance (FTIR-ATR) to identify packaging potentially coated with PFASs. None of the packaging samples in this study were identified as having PFASs. A wide range of concentrations was observed among the seafood samples, ranging from below the method detection limit to the highest concentration of 23 μg kg-1 for the sum of PFASs in one of the canned clam samples. Such a wide range is consistent with those reported in previous studies. The highest concentrations were reported in clams and crabs, followed by cod, tuna, pollock, tilapia, salmon, and shrimp. Technical perfluorooctanoic acid (PFOA) dominated the profile of the clam samples, which has been consistently found in other clam samples, especially in Asia. Long-chain PFCAs, specifically perfluoroundecanoic (PFUdA) and perfluorododecanoic (PFDoA), were the most frequently detected analytes across all seafood samples. The trends observed are comparable with those in the literature where benthic organisms tend to have the highest PFAS concentrations, followed by lean fish, fatty fish, and aquaculture. The results from this study will be used to prioritize future studies and to inform steps to reduce consumer exposure to PFASs. |
2,728 | Economic appraisal of hybrid solar-biomass thermophotovoltaic power generation | The techno-economic parameters that influence the commercial deployment of hybrid thermophotovoltaic (TPV) solar power generation are determined using annual system simulations. It has been found that a TPV cell price of (sic)5/cm(2) or less together with a TPV operating temperature under 800 degrees C is required for a hybrid solar-biomass TPV power plant to be economically competitive with the state-of-the-art hybrid solar-biomass Rankine cycle power plants. |
2,729 | Carbon Nanotube FET Technology for Radio-Frequency Electronics: State-of-the-Art Overview | Carbon-based electronics is an emerging field. Its present progress is largely dominated by the materials science community due to the many still existing materials-related obstacles for realizing practically competitive transistors. Compared to graphene, carbon nanotubes provide better properties for building field-effect transistors, and thus, have higher chances for eventually becoming a production technology. This paper provides an overview on the state-of-the-art of CNTFET technology from an electrical engineering and radio frequency analog applications point of view. Important material properties, resulting device structures, their fabrication, and the most relevant modeling concepts are briefly reviewed. Furthermore, recent results on device and circuit performance and the future prospects are presented in the context of practical requirements and applications. |
2,730 | Investigating Typed Syntactic Dependencies for Targeted Sentiment Classification Using Graph Attention Neural Network | Targeted sentiment classification predicts the sentiment polarity on given target mentions in input texts. Dominant methods employ neural networks for encoding the input sentence and extracting relations between target mentions and their contexts. Recently, graph neural network has been investigated for integrating dependency syntax for the task, achieving the state-of-the-art results. However, existing methods do not consider dependency label information, which can be intuitively useful. To solve the problem, we investigate a novel relational graph attention network that integrates typed syntactic dependency information. Results on standard benchmarks show that our method can effectively leverage label information for improving targeted sentiment classification performances. Our final model significantly outperforms state-of-the-art syntax-based approaches. |
2,731 | Sex differences in body fluid homeostasis: Sex chromosome complement influences on bradycardic baroreflex response and sodium depletion induced neural activity | Clinical and basic findings indicate that angiotensin II (ANG II) differentially modulates hydroelectrolyte and cardiovascular responses in male and female. But are only the activational and organizational hormonal effects to blame for such differences? Males and females not only differ in their sex (males are born with testes and females with ovaries) but also carry different sex chromosome complements and are thus influenced throughout life by different genomes. In this review, we discuss our recent studies in order to evaluate whether sex chromosome complement is in part responsible for gender differences previously observed in ANG II bradycardic-baroreflex response and sodium depletion-induced sodium appetite and neural activity. To test the hypothesis that XX or XY contributes to the dimorphic ANG II bradycardic-baroreflex response, we used the four core genotype mouse model, in which the effects of gonadal sex (testes or ovaries) and sex chromosome complement (XX or XY) are dissociated. The results indicate that ANG II bradycardic-baroreflex sexual dimorphic response may be ascribed to differences in sex chromosomes, indicating an XX-sex chromosome complement facilitatory bradycardic-baroreflex control of heart rate. Furthermore, we evaluated whether genetic differences within the sex chromosome complement may differentially modulate the known sexually dimorphic sodium appetite as well as basal or induced brain activity due to physiological stimulation of the renin-angiotensin system by furosemide and low-sodium treatment. Our studies demonstrate an organizational hormonal effect on sexually dimorphic induced sodium intake in mice, while at the brain level (subfornical organ and area postrema) we showed a sex chromosome complement effect in sodium-depleted mice, suggesting a sex chromosome gene participation in the modulation of neural pathways underlying regulatory response to renin-angiotensin stimulation. |
2,732 | Non-traumatic bladder rupture | Spontaneous bladder rupture, while rare, carries a high risk of morbidity and mortality if left untreated. Here, we describe a case report of spontaneous bladder rupture in a patient initially presenting with foley malfunction. Despite foley replacement, the patient continued to endorse abdominal pain and clinically deteriorate, thus raising our suspicion for possible bladder rupture. Recognizing and understanding the different variations of spontaneous bladder rupture is paramount for timely appropriate intervention. |
2,733 | Evolving Type-2 Fuzzy Classifier | Evolving fuzzy classifiers (EFCs) have achieved immense success in dealing with nonstationary data streams because of their flexible characteristics. Nonetheless, most real-world data streams feature highly uncertain characteristics, which cannot be handled by the type-1 EFC. A novel interval type-2 fuzzy classifier, namely evolving type-2 classifier (eT2Class), is proposed in this paper, which constructs an evolving working principle in the framework of interval type-2 fuzzy system. The eT2Class commences its learning process from scratch with an empty or initially trained rule base, and its fuzzy rules can be automatically grown, pruned, recalled, and merged on the fly referring to summarization power and generalization power of data streams. In addition, the eT2Class is driven by a generalized interval type-2 fuzzy rule, where the premise part is composed of the multivariate Gaussian function with an uncertain nondiagonal covariance matrix, while employing a subset of the nonlinear Chebyshev polynomial as the rule consequents. The efficacy of the eT2Class has been rigorously assessed by numerous real-world and artificial study cases, bench-marked against state-of-the-art classifiers, and validated through various statistical tests. Our numerical results demonstrate that the eT2Class produces more reliable classification rates, while retaining more compact and parsimonious rule base than state-of-the-art EFCs recently published in the literature. |
2,734 | Low-depth shotgun sequencing resolves complete mitochondrial genome sequence of Labeo rohita | Labeo rohita, popularly known as rohu, is a widely cultured species in whole Indian subcontinent. In the present study, we used in-silico approach to resolve complete mitochondrial genome of rohu. Low-depth shotgun sequencing using Roche 454 GS FLX (Branford, Connecticut, USA) followed by de novo assembly in CLC Genomics Workbench version 7.0.4 (Aarhus, Denmark) revealed the complete mitogenome of L. rohita to be 16 606 bp long (accession No. KR185963). It comprised of 13 protein-coding genes, 22 tRNAs, 2 rRNAs and 1 putative control region. The gene order and organization are similar to most vertebrates. The mitogenome in the present investigation has 99% similarity with that of previously reported mitogenomes of rohu and this is also evident from the phylogenetic study using maximum-likelihood (ML) tree method. This study was done to determine the feasibility, accuracy and reliability of low-depth sequence data obtained from NGS platform as compared to the Sanger sequencing. Thus, NGS technology has proven to be competent and a rapid in-silico alternative to resolve the complete mitochondrial genome sequence, thereby reducing labors and time. |
2,735 | Dynamic trophic shifts in bacterial and eukaryotic communities during the first 30 years of microbial succession following retreat of an Antarctic glacier | We examined microbial succession along a glacier forefront in the Antarctic Peninsula representing ∼30 years of deglaciation to contrast bacterial and eukaryotic successional dynamics and abiotic drivers of community assembly using sequencing and soil properties. Microbial communities changed most rapidly early along the chronosequence, and co-occurrence network analysis showed the most complex topology at the earliest stage. Initial microbial communities were dominated by microorganisms derived from the glacial environment, whereas later stages hosted a mixed community of taxa associated with soils. Eukaryotes became increasingly dominated by Cercozoa, particularly Vampyrellidae, indicating a previously unappreciated role for cercozoan predators during early stages of primary succession. Chlorophytes and Charophytes (rather than cyanobacteria) were the dominant primary producers and there was a spatio-temporal sequence in which major groups became abundant succeeding from simple ice Chlorophytes to Ochrophytes and Bryophytes. Time since deglaciation and pH were the main abiotic drivers structuring both bacterial and eukaryotic communities. Determinism was the dominant assembly mechanism for Bacteria, while the balance between stochastic/deterministic processes in eukaryotes varied along the distance from the glacier front. This study provides new insights into the unexpected dynamic changes and interactions across multiple trophic groups during primary succession in a rapidly changing polar ecosystem. |
2,736 | Polymorphism of Purpurin and Low-level Detection of the Noncentrosymmetric form by Second Harmonic Generation Microscopy | Nonlinear optical imaging based on second harmonic generation (SHG) provides rapid and highly selective detection of polar crystals. Purpurin (PUR) is a natural product with multiple pharmacological activities. Two polymorphs of PUR show distinct crystal packing and structural symmetry, where form I crystallizes in a polar space group and form II crystallizes in a centrosymmetric crystal structure. The two polymorphs are monotropically related, with form I being the thermodynamically stable form, as suggested by slurry experiments, in-situ Raman spectroscopy and crystal structure prediction (CSP). The specificity of SHG to the polar crystals of form I allows rapid polymorphism detection at the limit of individual crystals. SHG is also able to detect low levels of form I in a tablet matrix dominated by amorphous excipients. This study shows that SHG microscopy can achieve the rapid and sensitive detection of noncentrosymmetric crystals in solid dosage forms, which is especially helpful for the early detection of unwanted polymorphic conversion or crystallization of amorphous drugs in formulations and final products. |
2,737 | Multilingual evaluation of pre-processing for BERT-based sentiment analysis of tweets | Social media offer a big amount of information, to exploit in many fields of research. However, while methods for Natural Language Processing are being developed with good results when applied to well-formed datasets made of written text with a clear syntax, these sources present text written in informal language, unstructured syntax, and with peculiar symbols; therefore, particular approaches are required for text processing in this case. In this paper, the task of sentiment analysis of tweets is regarded. In particular, in order to avoid noise constituted by some web constructs like URLs and mentions and by other text fragments, and to exploit information hidden in symbols like emoticons, emojis and hashtags, the pre-processing of tweets is analyzed. More in detail, a number of experiments, performed by a state-of-the-art classification model (BERT), are designed, to evaluate many currently available operations for pre-processing tweets, in terms of the statistical significance of their influence on sentiment analysis performances. Moreover, available data in two languages are considered, i.e., English and Italian, in order to also evaluate dependence on the language. Results allow to individuate the most convenient strategy to pre-process tweets, and thus to improve the state of the art in both languages for the considered task of sentiment analysis. |
2,738 | A precise resonance frequency measurement method based on ISO-standardized setups for contactless chip cards | A method for measuring the resonance frequency of contactless chip cards is proposed in this article. Compared to the vector network analyzer (VNA) based state-of-the-art method, the method gives a more accurate definition of resonance frequency, removes the subjectivity associated with the state-of-the-art method, and makes the measurement integrable into ISO-standardized test setups. Signal processing and system modeling are applied in order to determine the maximum active power in the chip card over a chosen frequency range. This is achieved by using a transfer function obtained from the model and by setting a chirp signal as input to the system. The determined maximum of active power is mapped to the corresponding frequency in the chirp signal, which is defined as the resonance frequency. The proposed method is verified by simulations and by comparing measurement results with the state-of-the-art. The results show that the proposed method offers significant advantages over the state-of-the-art method. |
2,739 | HFNet-SLAM: An Accurate and Real-Time Monocular SLAM System with Deep Features | Image tracking and retrieval strategies are of vital importance in visual Simultaneous Localization and Mapping (SLAM) systems. For most state-of-the-art systems, hand-crafted features and bag-of-words (BoW) algorithms are the common solutions. Recent research reports the vulnerability of these traditional algorithms in complex environments. To replace these methods, this work proposes HFNet-SLAM, an accurate and real-time monocular SLAM system built on the ORB-SLAM3 framework incorporated with deep convolutional neural networks (CNNs). This work provides a pipeline of feature extraction, keypoint matching, and loop detection fully based on features from CNNs. The performance of this system has been validated on public datasets against other state-of-the-art algorithms. The results reveal that the HFNet-SLAM achieves the lowest errors among systems available in the literature. Notably, the HFNet-SLAM obtains an average accuracy of 2.8 cm in EuRoC dataset in pure visual configuration. Besides, it doubles the accuracy in medium and large environments in TUM-VI dataset compared with ORB-SLAM3. Furthermore, with the optimisation of TensorRT technology, the entire system can run in real-time at 50 FPS. |
2,740 | Low-Complexity and High-Speed Architecture Design Methodology for Complex Square Root | In this paper, we propose a low-complexity and high-speed VLSI architecture design methodology for complex square root computation using COordinate Rotation DIgital Computer (CORDIC). The proposed methodology is independent of angle computation in the CORDIC unlike the state-of-the-art methodologies. The proposed methodology is modelled in VHDL and synthesized under the TSMC 45-nm CMOS technology @ 1 GHz frequency. The synthesis results show that the proposed design saves 18.39%, 4.06% and 17.26%, 2.56% on chip area and power consumption when compared with the state-of-the-art methodologies without loss in accuracy. The proposed design saves the latency of 16 and 14 clock cycles when compared with the state-of-the-art implementations. The proposed design can process 23.4 and 127.344 billion additional samples per one joule energy when compared with the state-of-the-art designs. |
2,741 | Learning Temporal Relations from Semantic Neighbors for Acoustic Scene Classification | Convolutional networks have achieved the state-of-the-art performance on Acoustic Scene Classification (ASC). Given the Log Mel-Spectrogram of an audio sample, the network can extract useful semantic contents in a certain range receptive field by stacking local convolutional operations. However, the temporal relations between different receptive fields are not captured explicitly. In this letter, we propose an end-to-end 3D Convolutional Neural Network (CNN) for ASC, named SeNoT-Net, which can generate effective audio representations by capturing temporal relations from semantic neighbors of different receptive fields over time. The SeNoT-Net treats the Log-Mel spectrogram as an ordered segment-level sequence. For each segment, the residual block can produce the semantic feature maps, then the semantic neighbors over time (SeNoT) module is applied to capture the relations between each feature point in the feature maps and its top-$k$ semantic neighbors. The proposed SeNoT-Net outperforms most of the state-of-the-art CNN models on both DCASE 2018 and 2019 ASC datasets. |
2,742 | Distributed Consensus-Based Coordination of Flexible Demand and Energy Storage Resources | Distributed, consensus-based algorithms have emerged as a promising approach for the coordination of distributed energy resources (DER) due to their communication, computation, privacy and reliability advantages over centralized approaches. However, state-of-the-art consensus-based algorithms address the DER coordination problem in independent time periods and therefore are inherently unable to capture the time-coupling operating characteristics of flexible demand (FD) and energy storage (ES) resources. This paper demonstrates that state-of-the-art algorithms fail to converge when these time-coupling characteristics are considered. In order to address this fundamental limitation, a novel consensus-based algorithm is proposed which includes additional consensus variables. These variables express relative maximum power limits imposed on the FD and ES resources which effectively mitigate the concentration of the FD and ES responses at the same time periods and steer the consensual outcome to a feasible and optimal solution. The convergence and optimality of the proposed algorithm are theoretically proven while case studies numerically demonstrate its convergence, optimality, robustness to initialization and information loss, and plug-and-play adaptability. |
2,743 | A Rare Case of Recurrent Hematometra of Unknown Etiology | An abnormal blood collection in the uterus is referred to as hematometra. Obstruction of the genitourinary outflow system caused by earlier surgeries or congenital defects is most frequently related to this rare disorder. The symptoms of hematometra include acute pelvic pain and a history of absent menarche. Here is a case of a 42-year-old female who presented with complaints of severe lower abdominal pain, and pain during urination that was accompanied by vulval itching in June 2021. She had undergone two Caesarean sections and a myomectomy in the past. She was given three monthly injections of gonadotropin-releasing hormone (GnRH) analogue after receiving USG-guided drainage because of a diagnosis of hematometra in January 2021. However, in June 2021, she experienced a recurrence of the same symptoms, necessitating a total abdominal hysterectomy and bilateral salpingo-oophorectomy, which completely resolved the patient's complaints. For a deeper understanding of this issue, further case reporting is necessary. |
2,744 | Moving Object Detection Using Adaptive Blind Update and RGB-D Camera | A novel background subtraction approach using an RCB-D camera and an adaptive blind updating policy is introduced. This method in the initialization creates a model to store background pixels to compare each pixel of the new frame with the model in the same location to identify background pixels. The background-model update presented in this paper uses regular and blind updates which also has different criteria from existing methods. In particular, blind update frequently changes based on the background changes and the speed of moving object. This will allow the scene model to adapt to the changes in the background, detecting the stationary moving object and reducing the ghost phenomenon. In addition, the proposed bootstrapping segmentation and shadow detection are added to the system to improve the accuracy of the algorithm in shadow and depth camouflage scenarios. The proposed method is compared with the original method and the other state of the art algorithms. The experimental results show significant improvement in those videos that stationary object appears. In addition, the benchmark results also indicate strong and stable results compared to the other state of the art algorithms. |
2,745 | Exploring the Role of Deep Learning Technology in the Sustainable Development of the Music Production Industry | This study explores the role of deep learning technology in the sustainable development of the music production industry. This article surveys the opinions of Taiwanese music creation professionals and uses partial least squares (PLS) regression to analyze and elucidate the importance of deep learning technology in the music production industry. We found that deep learning cannot replace human creativity, but greater investment in this technology can improve the quality of music creation. In order to achieve sustainable development in the music production industry, industry participants need to awaken consumers' awareness of music quality, actively enhance the unique value of their art, and strengthen cooperation between industries to provide a friendly environment for listeners. |
2,746 | Deep Texture Features for Robust Face Spoofing Detection | Biometric systems are quite common in our everyday life. Despite the higher difficulty to circumvent them, nowadays criminals are developing techniques to accurately simulate physical, physiological, and behavioral traits of valid users, process known as spoofing attack. In this context, robust countermeasure methods must be developed and integrated with the traditional biometric applications in order to prevent such frauds. Despite face being a promising trait due to its convenience and acceptability, face recognition systems can be easily fooled with common printed photographs. Most of state-of-the-art antispoofing techniques for face recognition applications extract handcrafted texture features from images, mainly based on the efficient local binary patterns (LBP) descriptor, to characterize them. However, recent results indicate that high-level (deep) features are more robust for such complex tasks. In this brief, a novel approach for face spoofing detection that extracts deep texture features from images by integrating the LBP descriptor to a modified convolutional neural network is proposed. Experiments on the NUAA spoofing database indicate that such deep neural network (called LBPnet) and an extended version of it (n-LBPnet) outperform other state-of-the-art techniques, presenting great results in terms of attack detection. |
2,747 | DeepDFML-NILM: A New CNN-Based Architecture for Detection, Feature Extraction and Multi-Label Classification in NILM Signals | In the subsequent decades, the increasing energy will demand renewable resources and intelligent solutions for managing consumption. In this sense, Non-Intrusive Load Monitoring (NILM) techniques detail consumption information for users, allowing better electric power management and avoiding energy losses. In high-frequency NILM methods, state-of-the-art approaches, mainly based on deep learning solutions, do not provide a complete NILM architecture, including all the required steps. To overcome this gap, this work presents an integrated method for detection, feature extraction, and classification of high-frequency NILM signals for the publicly available LIT-Dataset. In terms of detection, the results were above 90% for most cases, whilst the state-of-the-art methods were below 70% for eight loads. For classification, the final accuracies were comparable with other recent works (around 97%). We also include a multi-label procedure to avoid the disaggregation stage, indicating the loads connected at a given time, increasing the recognition of multiple loads. Finally, we present results in an embedded system, a subject also underexplored in the recent literature, demonstrating the proposal's feasibility for real-time signal analysis and practical applications involving NILM. |
2,748 | InP Photonic Integrated Circuits | InP is an ideal integration platform for optical generation, switching, and detection components operating in the range of 1.3-1.6 mu m wavelength, which is preferred for data transmission in the most prevalent silica-based optical fiber. We review the current state of the art in advanced InP photonic ICs. |
2,749 | Domain Adaptation Meets Zero-Shot Learning: An Annotation-Efficient Approach to Multi-Modality Medical Image Segmentation | Due to the lack of properly annotated medical data, exploring the generalization capability of the deep model is becoming a public concern. Zero-shot learning (ZSL) has emerged in recent years to equip the deep model with the ability to recognize unseen classes. However, existing studies mainly focus on natural images, which utilize linguistic models to extract auxiliary information for ZSL. It is impractical to apply the natural image ZSL solutions directly to medical images, since the medical terminology is very domain-specific, and it is not easy to acquire linguistic models for the medical terminology. In this work, we propose a new paradigm of ZSL specifically for medical images utilizing cross-modality information. We make three main contributions with the proposed paradigm. First, we extract the prior knowledge about the segmentation targets, called relation prototypes, from the prior model and then propose a cross-modality adaptation module to inherit the prototypes to the zero-shot model. Second, we propose a relation prototype awareness module to make the zero-shot model aware of information contained in the prototypes. Last but not least, we develop an inheritance attention module to recalibrate the relation prototypes to enhance the inheritance process. The proposed framework is evaluated on two public cross-modality datasets including a cardiac dataset and an abdominal dataset. Extensive experiments show that the proposed framework significantly outperforms the state of the arts. |
2,750 | Evaluation of Small-Molecule HDAC Inhibitors Through In Vitro and In Cellulo Approaches | The aberrant activity of histone deacetylases (HDACs) across a broad range of cancers and other disease indications has led to the development of small-molecule inhibitors that target one or more members of the HDAC protein family. Emerging HDAC inhibitors that show promise in drug discovery programs must be assessed across a range of in vitro assays to establish an inhibitor profile for potency and cellular selectivity towards target HDAC(s) as well as preliminary absorption, distribution, metabolism, and excretion (ADME) features. Here we provide an overview of methods to determine a subset of pivotal in vitro drug-like parameters for HDAC inhibitors (HDACi). We initially describe protocols for parallel artificial membrane permeability assays (PAMPA) to evaluate the passive permeability of small molecules across lipid membranes. Subsequently, we elaborate on cytotoxicity assays using CellTiter-Blue to determine HDACi-induced cell death in healthy/diseased cellular models. We next focus on assessing the target engagement of inhibitors with the appropriate HDAC isoforms in a cellular environment via Western blotting of acetylated HDAC substrates. Finally, we provide detailed guidelines on how to assess the metabolic stability of HDACi through whole blood stability assays. Collectively, these assays provide an overview of the permeability, selectivity, and stability of the HDAC inhibitor under development. |
2,751 | 400 GHz HBT Differential Amplifier Using Unbalanced Feed Networks | A terahertz differential eight-stage amplifier fabricated using state-of-the-art 125 nm double-heterojunction bipolar transistors (DHBT) is presented. The four-port unit-cell chain is designed for optimum forward differential gain with no even and odd-mode reverse gains. Unbalanced single-ended feed networks are added to preserve the amplifier gain without inducing oscillations. The proposed feed scheme is validated by a stable amplifier operation in 325-to-450 GHz range with the peak gain of 22 dB at 375 GHz. |
2,752 | Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation | Unsupervised domain adaptation has increasingly gained interest in medical image computing, aiming to tackle the performance degradation of deep neural networks when being deployed to unseen data with heterogeneous characteristics. In this work, we present a novel unsupervised domain adaptation framework, named as Synergistic Image and Feature Alignment (SIFA), to effectively adapt a segmentation network to an unlabeled target domain. Our proposed SIFA conducts synergistic alignment of domains from both image and feature perspectives. In particular, we simultaneously transform the appearance of images across domains and enhance domain-invariance of the extracted features by leveraging adversarial learning in multiple aspects and with a deeply supervised mechanism. The feature encoder is shared between both adaptive perspectives to leverage their mutual benefits via end-to-end learning. We have extensively evaluated our method with cardiac substructure segmentation and abdominal multi-organ segmentation for bidirectional cross-modality adaptation between MRI and CT images. Experimental results on two different tasks demonstrate that our SIFA method is effective in improving segmentation performance on unlabeled target images, and outperforms the state-of-the-art domain adaptation approaches by a large margin. |
2,753 | Enhancing Differential Evolution With Novel Parameter Control | In this paper, we proposed a novel DE variant named DE-NPC for real parameter single objective optimization. In DE-NPC algorithm, a novel adaptation scheme for the scale factor Sis first proposed, which is based on the location information of the population rather than the fitness difference. The adaptation scheme of crossover rate in our DE-NPC is based on its success probability. Furthermore, a novel population size reduction scheme is also employed in DE-NPC, which can get a better perception of the landscape of objectives and consequently obtain an overall better performance. The algorithm validation is conducted under our test suite containing 88 benchmarks from CEC2013, CEC2014 and CEC2017 in comparison with several state-of-the-art DE variants. The experiment results show that our novel DE-NPC algorithm is competitive with these state-of-the-art DE variants. |
2,754 | Multi-atlas segmentation of optic disc in retinal images via convolutional neural network | Multi-atlas segmentation is widely accepted as an essential image segmentation approach. Through leveraging on the information from the atlases instead of utilizing the model-based segmentation techniques, the multi-atlas segmentation could significantly enhance the accuracy of segmentation. However, label fusion, which plays an important role for multi-atlas segmentation still remains the primary challenge. Bearing this in mind, a deep learning-based approach is presented through integrating feature extraction and label fusion. The proposed deep learning architecture consists of two independent channels composing of continuous convolutional layers. To evaluate the performance our approach, we conducted comparison experiments between state-of-the-art techniques and the proposed approach on publicly available datasets. Experimental results demonstrate that the accuracy of the proposed approach outperforms state-of-the-art techniques both in efficiency and effectiveness. |
2,755 | A Survey on Observability of Distributed Edge & Container-Based Microservices | Edge computing is proposed as a technical enabler for meeting emerging network technologies (such as 5G and Industrial Internet of Things), stringent application requirements and key performance indicators (KPIs). It aims to alleviate the problems associated with centralized cloud computing systems by placing computational resources to the network's edge, closer to the users. However, the complexity of distributed edge infrastructures grows when hosting containerized workloads as microservices, resulting in hard to detect and troubleshoot outages on critical use cases such as industrial automation processes. Observability aims to support operators in managing and operating complex distributed infrastructures and microservices architectures by instrumenting end-to-end runtime performance. To the best of our knowledge, no survey article has been recently proposed for distributed edge and containerized microservices observability. Thus, this article surveys and classifies state-of-the-art solutions from various communities. Besides surveying state-of-the-art, this article also discusses the observability concept, requirements, and design considerations. Finally, we discuss open research issues as well as future research directions that will inspire additional research in this area. |
2,756 | State of the Art Review of Reinforcement Strategies and Technologies for 3D Printing of Concrete | This state of the art review paper aims to discuss the results of a literature survey on possible ways to reinforce printed concrete based on existing reinforcement strategies. Just as conventional concrete, for 3D printed concrete to be suitable for large-scale construction, reinforcement is needed to increase the tensile capacity of concrete members and reduce temperature and shrinkage cracking. Despite efforts that are currently underway, the development of proper reinforcement suitable for printed concrete is still very active on the research agenda. As an initial step for designing suitable reinforcement for printed concrete, the existing reinforcement methods for printed concrete as well as conventional cast concrete from the literature are reviewed and summarized. Through the preliminary evaluation of the suitability and effectiveness of various reinforcement methods, guidelines are proposed to better understand possible solutions to reinforce printed concrete and inspire new practical ideas to fill the current technology void. The conclusions also include the possible improvements of the existing reinforcement methods to be considered in future applications. |
2,757 | Interplay between hydrogen and chalcogen bonds in cysteine | Protein structures are stabilized by several types of chemical interactions between amino acids, which can compete with each other. This is the case of chalcogen and hydrogen bonds formed by the thiol group of cysteine, which can form three hydrogen bonds with one hydrogen acceptor and two hydrogen donors and a chalcogen bond with a nucleophile along the extension of the CS bond. A survey of the Protein Data Bank shows that hydrogen bonds are about 40-50 more common than chalcogen bonds, suggesting that they are stronger and, consequently, prevail, though not always. It is also observed that frequently a thiol group that forms a chalcogen bond is also involved, as a hydrogen donor, in a hydrogen bond. |
2,758 | Tricuspid Valve-in-Valve Procedure with An Edwards S3 Valve in a 15-kg Child in Latin America | A 5-year-old child, weighing 15 kg, with three previous sternotomies, presented with right heart failure due to severe stenosis and regurgitation of the bioprosthetic tricuspid valve. A percutaneous tricuspid valve-in-valve procedure with an Edwards S3 valve was ofered for compassionate use, performed with no complications and with a significant clinical condition improvement. |
2,759 | Two decades of stem cell transplantation in patients with Fanconi anemia: Analysis of factors affecting transplant outcomes | Allogeneic hematopoietic stem cell transplantation (HSCT) is currently the only curative treatment for the hematological complications of patients with Fanconi anemia (FA). Over the last two decades, HSCT outcomes have improved dramatically following the development of regimens tailored for FA patients. In this study, we analyzed genetic, clinical, and transplant data of 41 patients with FA who underwent HSCT at Hadassah Medical Center between November 1996 and September 2020. Overall survival (OS) was 82.9% with a median follow-up time of 2.11-years (95% CI, .48-16.56). Thirteen patients (31.7%) developed acute graft-versus-host disease (GVHD), three of them with grades 3-4. Nine patients developed chronic GVHD, five had extensive disease. Twelve patients (29.3%) developed stable mixed-chimerism with complete resolution of bone marrow failure (BMF); none of them had acute nor chronic GVHD. Significantly higher GVHD rates were observed in transplants from peripheral blood stem cell grafts as compared to other stem cell sources (p = .002 for acute and p = .004 for chronic GVHD). Outcome parameters were comparable between HSCT from matched-sibling (n = 20) to other donors (n = 21), including survival rates (p = .1), time to engraftment (p = .69 and p = .14 for neutrophil and platelet engraftment time, respectively), chimerism status (p = .36 and p = .83 for full-donor and mixed chimerism, respectively), and GVHD prevalence (p = 1). Our results demonstrate the vast improvements in HSCT outcomes of patients with FA, narrowing the gap between matched-sibling versus alternative donor transplantations. Our data identifies factors that may significantly affect transplant outcomes such as graft source and chimerism status. |
2,760 | Deep softmax collaborative representation for robust degraded face recognition | Deep convolutional neural networks (DCNN) have attracted much attention in the field of face recognition because they have achieved high performance than other approaches in the so-called in-the-wild datasets. However, in many real-world applications of face recognition, the performance of CNN-based algorithms is significantly decreased when images contain various kinds of degradations caused by random noise, motion blur, compression artifacts, uncontrolled illumination, and occlusion. Moreover, this is because the main weakness of existing DCNN models is the overfitting problem. To boost the recognition performance of stateof-the-art deep learning networks, we propose a deep softmax collaborative representation-based network, which can be used as a divide-and-conquer algorithm to help multiple DCCNs work together more effectively to solve multiple sub-problems of face reconstruction and classification. We demonstrated several experiments with challenging face recognition datasets. Our extensive experiments demonstrate that our proposed method is more robust and efficient in dealing with the challenging real-world problems in face recognition compared to related state-of-the-art methods. |
2,761 | Application Areas of Information-Centric Networking: State-of-the-Art and Challenges | The Information-Centric Network (ICN) paradigm has gained popularity since its inception. The host-based IP networks were not primarily designed to handle scenarios that it is exposed to on the current Internet. In that direction lot of research has been happening to develop applications such as web applications, multimedia streaming, the Internet of Things, Wireless Sensor Networks and Vehicular networks. In addition, new ICN application areas, such as social networks, Industrial IoTs, etc., are emerging. This review investigates the possible application areas and their deficiencies evenly, broadly and at a certain level of depth with focus on security, scalability, IP interoperability, modularity and other application specific aspects. We discuss the current state-of-the-art in these ICN-based applications and the existing limitations. A comparative analysis of the literary works available is performed to understand the research gaps available, and a detailed discussion of the challenges in each area is provided. We conclude the review with future challenges in the application development with the ICN paradigm to reap its architectural benefits. |
2,762 | Pattern-Based Dynamic Compilation System for CGRAs With Online Configuration Transformation | Prevailing data-intensive applications, such as artificial intelligence and internet of things, demand considerable compute capability. Coarse-grained reconfigurable architectures (CGRAs) can meet this demand via providing abundant compute resources. However, compilation has become an essential problem because the increasing resources need to be orchestrated efficiently. Static compilation is insufficient due to conservative resource allocation and exponentially increasing time cost while state-of-the-art dynamic compilation still performs poorly in both generality and efficiency. This article proposes a dynamic compilation system for CGRAs through online pattern-based configuration transformation, which enables virtualization to improve resource utilization and flexibility. It utilizes statically-generated patterns to straightforwardly determine dynamic placement of registers and operations so that the transformation algorithm has a low complexity. Domain-specific features are extracted by a k-means clustering algorithm to help improve the quality of patterns. The experimental results show that statically compiled applications can be transformed onto arbitrary resources at runtime, reserving 73.5 (22.8-163.3 percent) of the original performance/resource on average, 9.1 (0-52.9 percent) better than the state-of-the-art non-general methods. |
2,763 | Multiresolution Reservoir Graph Neural Network | Graph neural networks are receiving increasing attention as state-of-the-art methods to process graph-structured data. However, similar to other neural networks, they tend to suffer from a high computational cost to perform training. Reservoir computing (RC) is an effective way to define neural networks that are very efficient to train, often obtaining comparable predictive performance with respect to the fully trained counterparts. Different proposals of reservoir graph neural networks have been proposed in the literature. However, their predictive performances are still slightly below the ones of fully trained graph neural networks on many benchmark datasets, arguably because of the oversmoothing problem that arises when iterating over the graph structure in the reservoir computation. In this work, we aim to reduce this gap defining a multiresolution reservoir graph neural network (MRGNN) inspired by graph spectral filtering. Instead of iterating on the nonlinearity in the reservoir and using a shallow readout function, we aim to generate an explicit k-hop unsupervised graph representation amenable for further, possibly nonlinear, processing. Experiments on several datasets from various application areas show that our approach is extremely fast and it achieves in most of the cases comparable or even higher results with respect to state-of-the-art approaches. |
2,764 | IDRLP: Image Dehazing Using Region Line Prior | In this work, a novel and ultra-robust single image dehazing method called IDRLP is proposed. It is observed that when an image is divided into $n$ regions, with each region having a similar scene depth, the brightness of both the hazy image and its haze-free correspondence are positively related with the scene depth. Based on this observation, this work determines that the hazy input and its haze-free correspondence exhibit a quasi-linear relationship after performing this region segmentation, which is named as region line prior (RLP). By combining RLP and the atmospheric scattering model (ASM), a recovery formula (RF) can be easily obtained with only two unknown parameters, i.e., the slope of the linear function and the atmospheric light. A 2D joint optimization function considering two constraints is then designed to seek the solution of RF. Unlike other comparable works, this "joint optimization" strategy makes efficient use of the information across the entire image, leading to more accurate results with ultra-high robustness. Finally, a guided filter is introduced in RF to eliminate the adverse interference caused by the region segmentation. The proposed RLP and IDRLP are evaluated from various perspectives and compared with related state-of-the-art techniques. Extensive analysis verifies the superiority of IDRLP over state-of-the-art image dehazing techniques in terms of both the recovery quality and efficiency. A software release is available at https://sites.google.com/site/renwenqi888/. |
2,765 | Hippocampal blood flow rapidly and preferentially increases after a bout of moderate-intensity exercise in older adults with poor cerebrovascular health | Over the course of aging, there is an early degradation of cerebrovascular health, which may be attenuated with aerobic exercise training. Yet, the acute cerebrovascular response to a single bout of exercise remains elusive, particularly within key brain regions most affected by age-related disease processes. We investigated the acute global and region-specific cerebral blood flow (CBF) response to 15 minutes of moderate-intensity aerobic exercise in older adults (≥65 years; n = 60) using arterial spin labeling magnetic resonance imaging. Within 0-6 min post-exercise, CBF decreased across all regions, an effect that was attenuated in the hippocampus. The exercise-induced CBF drop was followed by a rebound effect over the 24-minute postexercise assessment period, an effect that was most robust in the hippocampus. Individuals with low baseline perfusion demonstrated the greatest hippocampal-specific CBF effect post-exercise, showing no immediate drop and a rapid increase in CBF that exceeded baseline levels within 6-12 minutes postexercise. Gains in domain-specific cognitive performance postexercise were not associated with changes in regional CBF, suggesting dissociable effects of exercise on acute neural and vascular plasticity. Together, the present findings support a precision-medicine framework for the use of exercise to target brain health that carefully considers age-related changes in the cerebrovascular system. |
2,766 | Hyperspectral Nonlinear Unmixing by Using Plug-and-Play Prior for Abundance Maps | Spectral unmixing (SU) aims at decomposing the mixed pixel into basic components, called endmembers with corresponding abundance fractions. Linear mixing model (LMM) and nonlinear mixing models (NLMMs) are two main classes to solve the SU. This paper proposes a new nonlinear unmixing method base on general bilinear model, which is one of the NLMMs. Since retrieving the endmembers' abundances represents an ill-posed inverse problem, prior knowledge of abundances has been investigated by conceiving regularizations techniques (e.g., sparsity, total variation, group sparsity, and low rankness), so to enhance the ability to restrict the solution space and thus to achieve reliable estimates. All the regularizations mentioned above can be interpreted as denoising of abundance maps. In this paper, instead of investing effort in designing more powerful regularizations of abundances, we use plug-and-play prior technique, that is to use directly a state-of-the-art denoiser, which is conceived to exploit the spatial correlation of abundance maps and nonlinear interaction maps. The numerical results in simulated data and real hyperspectral dataset show that the proposed method can improve the estimation of abundances dramatically compared with state-of-the-art nonlinear unmixing methods. |
2,767 | Technological parameters of rock art at the Kalgutinsky Rudnik site on the Ukok Plateau, Russian Altai region | One of the most common problems encountered in research on open-air petroglyph sites is determining the age of the imagery. Most images are not covered by calcite or other deposits which can be directly dated. Archaeological layers located under petroglyph panels may allow connections between imagery and datable cultural contexts to be established. When archaeological layers are lacking, the analysis of stylistic elements of petroglyphs themselves can be highly significant for temporal and cultural attribution. We regard style a Bos including not only artistic characteristics of images but also the ways in which rock panels were modified as well. Technological features can be important for understanding the broader concept of style in rock art. As illustrated by the open-air Kalgutinsky Rudnik site in the Russian Altai region, natural substrate characteristics often demanded specific technological adaptations that can be revealed by the analysis of anthropogenic and natural traces on rock surfaces. These data supplement the discussion of dating the earliest petroglyphs from the Kalgutinsky Rudnik rock art site. |
2,768 | Functions of MDA5 and its domains in response to GCRV or bacterial PAMPs | Melanoma differentiation-associated gene 5 (MDA5) is a member of retinoic acid-inducible gene I (RIG-I)-like receptor (RLR) family which can initiate type I IFN expression in response to RNA virus infection. In this study, we constructed six mutants of Ctenopharyngodon idella MDA5 (CiMAD5) overexpression plasmids and generated stable transfected C. idella kidney (CIK) cell lines to study the function of different domains of CiMAD5. After ploy(I:C) stimulation, the downstream genes of CiMDA5 in transfected cells was repressed. Overexpression of CiMDA5 or its variant repressed the replication of grass carp reovirus (GCRV) in CIK cells and decreased the viral titer of GCRV more or less compared to that in control cells. After GCRV or bacterial pathogen-associated molecular patterns (PAMPs) stimulation, overexpression of CiMDA5 or CARD domain significantly induced the expression of CiIFN-I, CiIL-1β and CiMx1. The deletion of Helicase or RD domain reduced the inductive effect of CiMDA5 on CiIFN-I, CiIL-1β and CiMx1 expression. RD overexpression resulted in an enhanced expression of CiIFN-I, CiIL-1β and CiMx1. These observations collectively demonstrate that, in CIK cells, after GCRV or bacterial PAMPs stimulation, CARD domain alone can mediate signaling; Helicase or RD domain alone negatively regulates CARD function by intramolecular interaction with CARD. However, RD domain acts as an enhancer by intermolecular interaction. These results enlarge the response spectrum of MDA5 and contribute to a further understanding of the functions of MDA5 and its domains in evolution. |
2,769 | DICER1 Mutations Occur in More Than One-Third of Follicular-Patterned Pediatric Papillary Thyroid Carcinomas and Correlate with a Low-Risk Disease and Female Gender Predilection | Some pediatric papillary thyroid carcinoma (PPTC) cohorts have suggested a preliminary correlation with respect to DICER1 mutation status and histomorphology in both benign and malignant follicular cell-derived nodules; however, the data regarding correlates of DICER1-related sporadic PPTCs subtyped based on the 2022 WHO classification criteria are largely unavailable. The current study investigated the status of hotspot DICER1 mutations with clinical, histological and outcome features in a series of 56 patients with PPTCs with no clinical or family history of DICER1-related syndromic manifestation. Fifteen (27%) PPTCs harbored BRAF p.V600E. Eight (14%) cases of PPTCs harbored DICER1 mutations with no associated BRAF p.V600E. DICER1 mutations were identified in exons 26 and 27. A novel D1810del (c.5428_5430delGAT) mutation was also detected. We also confirmed the absence of hotspot DICER1 mutations in the matched non-tumor tissue DNA in all 8 DICER1-related PPTCs. The mean age of DICER1-harboring PPTCs was 15.1 (range: 9-18) years whereas the rest of this cohort had a mean age of 14.8 (range 6-18) years. With the exception of one PPTC, all DICER1-related PPTCs were seen in females (female-to-male ratio: 7). The female to male ratio was 3.8 in 48 DICER1-wild type PPTCs. In terms of histological correlates, 5 of 8 (63%) DICER1-mutant PPTCs were invasive encapsulated follicular variant papillary thyroid carcinomas (FVPTCs) including 4 minimally invasive FVPTCs and 1 encapsulated angioinvasive FVPTC, whereas the remaining 3 PPTCs were infiltrative classic papillary thyroid carcinomas (p < 0.05). The incidence of DICER1 mutations was 19.5% in BRAF p.V600E-wild type PPTCs. Sixty-three percent of DICER1 hotspot mutations occurred in invasive encapsulated FVPTCs, and this figure represents 38% of invasive encapsulated FVPTCs. Only one (12%) patient with DICER1-related disease showed a single lymph node with micro-metastasis. Unlike DICER1-wild type patients, no distant metastasis is identified in patients with DICER1-related PPTCs. The current series expands on the surgical epidemiology of somatic DICER1-related PPTCs by correlating the mutation status with the clinicopathological variables. Our findings underscore that female gender predilection and enrichment in low-risk follicular-patterned PTCs are characteristics of DICER1-related PPTCs. |
2,770 | PnP-3D: A Plug-and-Play for 3D Point Clouds | With the help of the deep learning paradigm, many point cloud networks have been invented for visual analysis. However, there is great potential for development of these networks since the given information of point cloud data has not been fully exploited. To improve the effectiveness of existing networks in analyzing point cloud data, we propose a plug-and-play module, PnP-3D, aiming to refine the fundamental point cloud feature representations by involving more local context and global bilinear response from explicit 3D space and implicit feature space. To thoroughly evaluate our approach, we conduct experiments on three standard point cloud analysis tasks, including classification, semantic segmentation, and object detection, where we select three state-of-the-art networks from each task for evaluation. Serving as a plug-and-play module, PnP-3D can significantly boost the performances of established networks. In addition to achieving state-of-the-art results on four widely used point cloud benchmarks, we present comprehensive ablation studies and visualizations to demonstrate our approach's advantages. The code will be available at https://github.com/ShiQiu0419/pnp-3d. |
2,771 | Prevention of microbes-induced spoilage in sodium chloride-free cucumber fermentations employing preservatives | This study evaluated preservatives to stabilize sodium chloride (NaCl)-free-cucumber fermentations. The brining of air-purged laboratory cucumber fermentations with 100.0 mM calcium chloride (CaCl2 ) and 25.0 mM acetic acid resulted in immediate rises in pH, the chemical reduction of the medium, and malodors. Supplementation with 3.0 mM sodium benzoate or 3.0 mM potassium sorbate enabled a decline in pH, a continuous oxidative state of the medium, and delayed rising pH spoilage. However, lactic and acetic acids eventually disappeared in fermentations supplemented with preservatives. The amount of preservatives needed to suppress growth of brined-cucumber-spoilage microbes was determined in Fermented Cucumber Juice Medium (FCJM). Supplementation of FCJM with 10.0 mM sodium benzoate was inhibitory for the spoilage yeasts, Issatchenkia occidentalis and Pichia manshurica, and the lactobacilli, Lentilactobacillus buchneri and Lentilactobacillus parafarraginis, but not of Zygosaccharomyces globiformis. Potassium sorbate inhibited the spoilage yeasts at 15.0 mM in FCJM but not the lactobacilli. Supplementation of FCJM with 20.0 mM fumaric acid had a bactericidal effect on the spoilage-associated lactobacilli. As expected, NaCl-free-commercial cucumber fermentations brined with 100 mM CaCl2 , no acetic acid, and 6 mM potassium sorbate resulted in complete fermentations, but supported rising pH, microbially induced spoilage during long-term storage. Post-fermentation supplementation with 12 mM sodium benzoate, 10 mM fumaric acid, a combination of the two, or 10 mM fumaric acid and 2 mM AITC prevented microbial activity during long-term bulk storage. PRACTICAL APPLICATION: Several preservative-based strategies for stabilizing NaCl-free cucumber fermentation in a commercial production setting were developed, enabling the implementation of a processing technology that reduces wastewater volumes and environmental impact. |
2,772 | On the Optimal Encoding Ladder of Tiled 360 degrees Videos for Head-Mounted Virtual Reality | Dynamic Adaptive Streaming over HTTP (DASH) has been widely used by several popular streaming services, such as YouTube, Netflix, and Facebook. Adopting DASH requires to pre-determine a set of encoding configurations, called encoding ladder, to generate a set of representations stored on the streaming server. These representations are adaptively requested by clients according to their network conditions during streaming sessions. In this article, we aim to solve the optimal laddering problem that determines the optimal encoding ladder to maximize the client viewing quality. In particular, we consider video models, viewing probability, and client distribution to formulate the mathematical problem. We use a divide-and-conquer approach to decompose the problem into two subproblems: (i) per-class optimization for clients with different bandwidths and (ii) global optimization to maximize the overall viewing quality under the storage limit of the streaming server. We propose two algorithms for each of the per-class optimization and global optimization problems. Analytical analysis and real experiments are conducted to evaluate the performance of our proposed algorithms, compared to other state-of-the-art algorithms. Based on the results, we recommend a combination of the proposed algorithms to solve the optimal laddering problem. The evaluation results show the merits of our recommended algorithms, which: (i) outperform the state-of-the-art algorithms by up to 52.17 and 26.35 in Viewport Video Multi-Method Assessment Fusion (V-VMAF) in per-class optimization, (ii) outperform the state-of-the-art algorithms by up to 43.14 in V-VMAF for optimal laddering in global optimization, (iii) achieve good scalability under different storage limits and number of bandwidth classes, and (iv) run faster than the state-of-the-art algorithms. |
2,773 | Geometric Constraints in Sensing Matrix Design for Compressed Sensing | Compressed Sensing (CS) has been proposed as a method able to reduce the amount of data needed to represent sparse signals. Nowadays, different approaches have been proposed in order to increase the performance of this technique in each stage that composes it. Particularly, this paper provides a critical review of the state-of-the art of some CS adaptations in the sensing stage to identify the strengths and limitations of each of them. In addition, a new method is proposed (Nearly Orthogonal Rakeness-based CS) that aims to overcome limits of the CS adaptations covered in this work. After intensive numerical simulations on synthetic signals and electroencephalographic (EEG) signals, the proposed approach outperforms discussed state-of-the-art approaches in terms of compression capability required to achieve a target quality of service. (C) 2020 Elsevier B.V. All rights reserved. |
2,774 | Person re-identification by multi-statistics on pyramid of covariance matrices | A novel and efficient covariance-based method for person re-identification is proposed. The approach exploits three colourspaces and intensity gradients as covariance features and extracts multiple statistical feature vectors from the pyramid of region covariance matrices. The distance measure of the covariance pyramid is designed to be the weighted combination of four vectorised statistical features by cascading on the covariance pyramid. The method is compared with the state-of-the-art methods using a benchmark dataset and is demonstrated to outperform other state-of-the-art methods. |
2,775 | Probing the origin of prion protein misfolding via reconstruction of ancestral proteins | Prion diseases are fatal neurodegenerative diseases caused by pathogenic misfolding of the prion protein, PrP. They are transmissible between hosts, and sometimes between different species, as with transmission of bovine spongiform encephalopathy to humans. Although PrP is found in a wide range of vertebrates, prion diseases are seen only in certain mammals, suggesting that infectious misfolding was a recent evolutionary development. To explore when PrP acquired the ability to misfold infectiously, we reconstructed the sequences of ancestral versions of PrP from the last common primate, primate-rodent, artiodactyl, placental, bird, and amniote. Recombinant ancestral PrPs were then tested for their ability to form β-sheet aggregates, either spontaneously or when seeded with infectious prion strains from human, cervid, or rodent species. The ability to aggregate developed after the oldest ancestor (last common amniote), and aggregation capabilities diverged along evolutionary pathways consistent with modern-day susceptibilities. Ancestral bird PrP could not be seeded with modern-day prions, just as modern-day birds are resistant to prion disease. Computational modeling of structures suggested that differences in helix 2 could account for the resistance of ancestral bird PrP to seeding. Interestingly, ancestral primate PrP could be converted by all prion seeds, including both human and cervid prions, raising the possibility that species descended from an ancestral primate have retained the susceptibility to conversion by cervid prions. More generally, the results suggest that susceptibility to prion disease emerged prior to ~100 million years ago, with placental mammals possibly being generally susceptible to disease. |
2,776 | Confirmed cases of severe fever with thrombocytopenia syndrome in companion cats with a history of tick exposure in the Republic of Korea | Severe fever with thrombocytopenia syndrome (SFTS) is a zoonotic disease, and its clinical information and prevalence are important. This study was conducted on 22 feline patients from the Republic of Korea (ROK), suspected to suffer from a tick-borne disease. Four cats were positive for SFTS, and genotypes B-1, B-3, D, and F were identified. Clinical symptoms, such as anorexia, jaundice, thrombocytopenia, leukopenia, and hyperbilirubinemia, were detected. This is the first report of SFTS virus genotypes B-1, D, and F from cats in the ROK. Moreover, our results suggest that jaundice may be an indicator of SFTS in cats. |
2,777 | Cecal Perforation Secondary to Large Bowel Obstruction From a Tubo-Ovarian Abscess | With the continued specialization of medicine, we as physicians often fall into the trap of placing pathologies into silos, focusing on what we are most practiced in caring for. When managing acute patients, it is important that we consider complications that can arise across systems and specialties which could place our patients at increased risk for morbidity and mortality. Tubo-ovarian abscesses (TOAs) are complex infections often arising in the setting of pelvic inflammatory disease. The resultant reactive inflammation is frequently the culprit of potentially fatal sequelae. This article looks to highlight a case of TOA that resulted in inflammation and obstruction of the adjacent large bowel which subsequently led to large bowel obstructions (LBOs) and perforation. Although LBO management is well described in the literature, perforation secondary to inflammatory compression from a TOA is rarely documented. We present the case of a middle-aged female with significant comorbid conditions and recent prolonged retention of a tampon which likely acted as the nidus for the infection that led to her presenting pathology and need for admission, a left-sided TOA measuring 8.1 × 4.7 × 3.4 cm. Consultation by obstetrics-gynecology and interventional radiology determined that admission for observation and intravenous antibiotics alone was appropriate. The patient's hospital course was complicated by enlarging TOA with peri-colonic abscess and acute decompensation in the setting of LBO and cecal perforation. Emergency laparotomy and right hemicolectomy by the acute care surgical team were performed. Postoperative management was complicated by septic shock which prolonged her hospital stay. Following inpatient optimization of nutrition and management of comorbid conditions, the patient was able to make a full recovery. In patients with suspected TOA, special consideration should be given to surrounding structures, and potentially fatal complications should be kept in the forefront of the primary team's minds. This case report aims to urge physicians caring for patients with TOA to maintain a high level of suspicion and consider how the benefits of aggressive management may outweigh those of conservative options. |
2,778 | Elemental sulphur recovery from a sulphate-rich aqueous stream in a single hybrid linear flow channel reactor is mediated through microbial community dynamics and adaptation to reactor zones | The coupled application of biological sulphate reduction (BSR) and partial sulphide oxidation to treat sulphate-rich wastewater is an effective strategy to mitigate pollution and recover elemental sulphur for repurposing. The recent development of the hybrid linear flow channel reactor (LFCR) achieves simultaneous BSR and partial sulphide oxidation with biosulphur recovery via a floating sulphur biofilm (FSB). Here, we explore the microbial community zoning and dynamics facilitating the process. A total of three continuous LFCRs were used to evaluate the effect of reactor zones, hydraulic residence time (HRT), carbon source, namely lactate and acetate, as well as reactor geometry and scale on process performance and microbial community dynamics. Community composition of sessile and planktonic microbial consortia were resolved at a 5- and 2-day HRT through 16S rRNA amplicon sequencing. Preferential attachment and prevalence of specific phylotypes within the sessile and planktonic communities revealed clear adaptation of key microorganisms to different microenvironments. Key microbial taxa affiliated with sulphate reduction and sulphide oxidation as well as those implicated in fermentation and syntrophic metabolism, fluctuated in response to changes in HRT and process performance. Through understanding the relationship between microbial community dynamics and process performance, this research will inform better process design and optimization of the hybrid LFCR. |
2,779 | Tenosynovial giant cell tumor | Tenosynovial Giant Cell Tumor (TGCT) is a group of typically benign lesions arising from the synovium of joints, bursae and tendon sheaths. Depending on their growth pattern and clinical course, they are divided into localized and diffuse types. It is predominantly caused by a mutation in the stromal cells of the synovial membrane leading to overexpression of the colony stimulating factor 1 that recruits CSF1R-expressing cells of the mononuclear phagocyte lineage into the tumor mass. The lesions contain mainly histiocyte-like and synovial cells accompanied by varying numbers of multinucleated giant cells, mononuclear cells, foam cells, inflammatory cells and hemosiderin deposits. The gold standard for detect- ing and monitoring the disease is MRI, where the characteristic hemosiderin accumulation can be best appreciated, but it is a histological examination that is most conclusive. The main treatment is surgical resection of all pathological tissue, but radio- and chemotherapy are also viable options for certain groups of patients. |
2,780 | Kinematic Analysis of Mae-Geri Kicks in Beginner and Advanced Kyokushin Karate Athletes | Background: Each of the techniques used in sport is a complex technique requiring a combination of neuromuscular conduction, motor anticipation, and extremely developed proprioception. This is especially the case in martial arts when we deal with a kick or a blow to a specific target. Methods: The main purpose of this study was to determine the kinematic differences in the tested movement pattern among athletes with different levels of advancement in the conditions of kicking: in the air, at a target (a shield), and in direct contact with a competitor. Comparative analysis was performed among 26 players: 13 advanced (group G1) and 13 beginners (group G2). Kinematic data was recorded using an optical motion capture system. The examination consisted of performing three tests of mae-geri kick in sequences of three kicks in three different conditions (without a target, with a static target, and with an opponent). The examination was performed with the back leg and only the moment of kick was analyzed. Results: The most significant differences were observed in the movement of head, torso, hip, knee, and ankle segments, especially during a kick at a shield. Based on the conducted analysis, we can assume that karate training changes the strategy of neuromuscular control, promoting improvement of mobility pattern efficiency. Conclusion: Acquiring this type of knowledge can lead to better results, elimination of errors in training, especially in the initial period of training, and the prevention of possible injuries that occur during exercise or competition. |
2,781 | A Hybrid Approach for Segmentation and Tracking of Myxococcus Xanthus Swarms | Cell segmentation and motion tracking in time-lapse images are fundamental problems in computer vision, and are also crucial for various biomedical studies. Myxococcus xanthus is a type of rod-like cells with highly coordinated motion. The segmentation and tracking of M. xanthus are challenging, because cells may touch tightly and form dense swarms that are difficult to identify individually in an accurate manner. The known cell tracking approaches mainly fall into two frameworks, detection association and model evolution, each having its own advantages and disadvantages. In this paper, we propose a new hybrid framework combining these two frameworks into one and leveraging their complementary advantages. Also, we propose an active contour model based on the Ribbon Snake, which is seamlessly integrated with our hybrid framework. Evaluated by 10 different datasets, our approach achieves considerable improvement over the state-of-the-art cell tracking algorithms on identifying complete cell trajectories, and higher segmentation accuracy than performing segmentation in individual 2D images. |
2,782 | Mechano-regulation of gap junction communications between tendon cells is dependent on the magnitude of tensile strain | Large magnitudes of mechanical strain applied to tendon cells induce catabolic and inflammatory responses, whereas a moderate level of strain promotes anabolism. Gap junction intercellular communication (GJIC) plays an essential role in these responses, however direct regulation of GJIC by mechanical loading has not been characterised in detail. Here, we show that the GJIC between tenocytes are enhanced or inhibited depending on the magnitude of the tensile strain. The GJIC was analysed using fluorescence loss in photobleaching (FLIP), combined with a molecular diffusion model. Intercellular and intracellular transport of fluorescence tracer molecules, calcein, across multiple cells through the gap junctions was evaluated by determining the intercellular and intracellular diffusion coefficients of calcein. It was demonstrated that the intercellular diffusion coefficient was significantly higher when the cells were subjected to a physiological static tensile strain (4%) for 1 h, but significantly lower when subjected to a strain with non-physiological amplitude (8%). The intracellular diffusion coefficient was not altered by the application of static strain at any level. Connexin 43 proteins were localised within cytoplasm and at cell-cell boundaries in no strained state and were also localised near cell nuclei by the 4% strain, but the localisation was reduced by the 8% strain. The findings suggest that the increase in GJIC in response to 4% strain involves opening of gap junction pores via mechanotransduction events of tenocytes, whereas the inhibition in response to 8% strain involves mechanical disruption of the junctions. |
2,783 | On maximization of the modularity index in network psychometrics | The modularity index (Q) is an important criterion for many community detection heuristics used in network psychometrics and its subareas (e.g., exploratory graph analysis). Some heuristics seek to directly maximize Q, whereas others, such as the walktrap algorithm, only use the modularity index post hoc to determine the number of communities. Researchers in network psychometrics have typically not employed methods that are guaranteed to find a partition that maximizes Q, perhaps because of the complexity of the underlying mathematical programming problem. In this paper, for networks of the size commonly encountered in network psychometrics, we explore the utility of finding the partition that maximizes Q via formulation and solution of a clique partitioning problem (CPP). A key benefit of the CPP is that the number of communities is naturally determined by its solution and, therefore, need not be prespecified in advance. The results of two simulation studies comparing maximization of Q to two other methods that seek to maximize modularity (fast greedy and Louvain), as well as one popular method that does not (walktrap algorithm), provide interesting insights as to the relative performances of the methods with respect to identification of the correct number of communities and the recovery of underlying community structure. |
2,784 | Benthic studies adjacent to Sakhalin Island, Russia, 2015 I: benthic biomass and community structure in the nearshore gray whale feeding area | Okhotsk or western gray whales feed in summer along the northeastern coast of Sakhalin Island, Russia, a region with oil and gas extraction facilities. Seismic surveys increased sound levels in the nearshore feeding area in 2015 for part of the summer, potentially displacing whales from preferred foraging habitat or reducing foraging efficiency. Since lost foraging opportunities might lead to vital rate effects on this endangered species, detailed benthic surveys were conducted to characterize benthic community biomass patterns and spatial and temporal differences. Benthic biomass demonstrated strong spatial-temporal interactions indicating that prey biomass differences among locations were dependent on sampling period. Of greatest interest, Amphipoda biomass declined from June to October in the northern and southern portions of the nearshore study area but increased in the middle and Actinopterygii biomass increased in the northern area in mid-summer. Water depth and sediment type were significant covariates with community structure, and water depth strongly covaried with bivalve biomass. Total average prey biomass was ~ 100 g/m2 within the nearshore feeding area with no evidence of reduced biomass among sampling periods or locations, although there were fewer amphipods in the south. Multi-prey investigations provide a stronger basis for inferences than single-prey studies of amphipods when gray whales feed on diverse prey. Benthic community-level variability was moderate to high as would be expected for a shallow-water nearshore area. Overall, spatial and temporal changes in dominant macrofauna biomass reflected small to medium-sized effects that were well within the natural boundaries expected for benthic communities. |
2,785 | Semi-Supervised Capsule cGAN for Speckle Noise Reduction in Retinal OCT Images | Speckle noise is the main cause of poor optical coherence tomography (OCT) image quality. Convolutional neural networks (CNNs) have shown remarkable performances for speckle noise reduction. However, speckle noise denoising still meets great challenges because the deep learning-based methods need a large amount of labeled data whose acquisition is time-consuming or expensive. Besides, many CNNs-based methods design complex structure based networks with lots of parameters to improve the denoising performance, which consume hardware resources severely and are prone to overfitting. To solve these problems, we propose a novel semi-supervised learning based method for speckle noise denoising in retinal OCT images. First, to improve the model's ability to capture complex and sparse features in OCT images, and avoid the problem of a great increase of parameters, a novel capsule conditional generative adversarial network (Caps-cGAN) with small number of parameters is proposed to construct the semi-supervised learning system. Then, to tackle the problem of retinal structure information loss in OCT images caused by lack of detailed guidance during unsupervised learning, a novel joint semi-supervised loss function composed of unsupervised loss and supervised loss is proposed to train the model. Compared with other state-of-the-art methods, the proposed semi-supervised method is suitable for retinal OCT images collected from different OCT devices and can achieve better performance even only using half of the training data. |
2,786 | Freestanding 3D-interconnected carbon nanofibers as high-performance transducers in miniaturized electrochemical sensors | 3D-carbon nanomaterials have proven to be high-performance transducers in electrochemical sensors but their integration into miniaturized devices is challenging. Herein, we develop printable freestanding laser-induced carbon nanofibers (f-LCNFs) with outstanding analytical performance that furthermore can easily allow such miniaturization through a paper-based microfluidic strategy. The f-LCNF electrodes were generated from electrospun polyimide nanofibers and one-step laser carbonization. A three-electrode system made of f-LCNFs exhibited a limit of detection (LOD) as low as 1 nM (S/N = 8) for anodic stripping analysis of silver ions, exhibiting the peak at ca. 100 mV vs f-LCNFs RE, without the need of stirring. The as-described system was implemented in miniaturized devices via wax-based printing, in which their electroanalytical performance was characterized for both outer- and inner-sphere redox markers and then applied to the detection of dopamine (the peak appeared at ca. 200 mV vs f-LCNFs RE) with a remarkable LOD of 55 pM. When modified with Nafion, the f-LCNFs were highly selective to dopamine even against high concentrations of uric and ascorbic acids. Especially the integration into closed microfluidic systems highlights the strength 3D porous structures provides excellent analytical performance paving the way for their translation to affordable lab-on-a-chip devices where mass-production capability, unsophisticated fabrication techniques, transfer-free, and customized electrode designs can be realized. |
2,787 | Realistic Lung Nodule Synthesis With Multi-Target Co-Guided Adversarial Mechanism | The important cues for a realistic lung nodule synthesis include the diversity in shape and background, controllability of semantic feature levels, and overall CT image quality. To incorporate these cues as the multiple learning targets, we introduce the Multi-Target Co-Guided Adversarial Mechanism, which utilizes the foreground and background mask to guide nodule shape and lung tissues, takes advantage of the CT lung and mediastinal window as the guidance of spiculation and texture control, respectively. Further, we propose a Multi-Target Co-Guided Synthesizing Network with a joint loss function to realize the co-guidance of image generation and semantic feature learning. The proposed network contains a Mask-Guided Generative Adversarial Sub-Network (MGGAN) and a Window-Guided Semantic Learning Sub-Network (WGSLN). The MGGAN generates the initial synthesis using the mask combined with the foreground and background masks, guiding the generation of nodule shape and background tissues. Meanwhile, the WGSLN controls the semantic features and refines the synthesis quality by transforming the initial synthesis into the CT lung and mediastinal window, and performing the spiculation and texture learning simultaneously. We validated our method using the quantitative analysis of authenticity under the Frechet Inception Score, and the results show its state-of-the-art performance. We also evaluated our method as a data augmentation method to predict malignancy level on the LIDC-IDRI database, and the results show that the accuracy of VGG-16 is improved by 5.6%. The experimental results confirm the effectiveness of the proposed method. |
2,788 | Similar in vitro response of rat brain nerve terminals, colon preparations and COLO 205 cells to smoke particulate matter from different types of wood | Major source of carbon-containing air born particular matter that significantly pollutes environment and provokes development of neuropathology is forest fires and wood combustion. Here, water-suspended smoke particulate matter preparations (SPs) were synthesized from birch, pine, poplar wood, and also birch bark and pine needles. Taking into account importance of the gut-brain communication system, SP properties were compared regarding their capability to modulate functioning of nerve terminals and gut cells/preparations. In cortex nerve terminals, poplar wood SP was more effective in decreasing uptake and increasing the extracellular levels of excitatory and inhibitory neurotransmitters L-[14C]glutamate and [3H]GABA, respectively. Spontaneous and H2O2-stimulated ROS generation in nerve terminals decreased by SPs, the most efficient one was from poplar wood. SPs from birch, pine and poplar wood caused membrane depolarization, poplar wood SP effect was 5-fold higher vs. birch and pine wood ones. Functional characteristics of gut cells/preparations, which tightly related to nerve terminal experiments, were assessed. SPs increased paracellular permeability of proximal colon mucosal-submucosal preparations monitored in Ussing chamber system (FITC-dextran, 4 kDa), where the most prominent effect had poplar wood SP. The latter demonstrated more considerable influence on COLO 205 cell causing 30 % loss of cell viability. PM emitted to the environment during combustion of various wood caused similar unidirectional harmful effects on brain and gut cell functioning, thereby triggering development of pathologies in gut and brain and gut-brain communication system. |
2,789 | A multi-approach to community question answering | In this paper we face the problem of Community Question Answering for the Arabic language. In this setting, a member of the community posts an initial query expressed in Natural Language. Other participants post their own interventions: answers, comments, additional questions, etc. contributing to building a rather tangled thread of nodes containing Natural Language short texts. The task consists in answering the initial query using the thread as the space of possible answers. The task can be approached as a classification, a regression or a ranking problem. In our case we select the set of possible candidates, we assign a relevance score to each candidate and we rank them accordingly. We propose a bunch of unsupervised models and show that a model based on Latent Semantic Indexing approach outperforms state of the art models for this task. We also use transfer learning to power the embeddings layer of various deep learning models and prove that the pairwise approaches outperform their pointwise counterparts. All the proposed models have been evaluated on Semeval 2017 Task 3 Subtask D: Arabic Community Question Answering and achieve state of the art or near performance. (C) 2019 Elsevier Ltd. All rights reserved. |
2,790 | Bone Marrow Grafts From Pediatric Donors May Contain A Considerable Number of Hematogones | During CD34 + stem cell count to determine the number of stem cells in the allografts from pediatric donors, we noticed a considerable amount of early hematogones (eHGs) within the stem cell gate in flow cytometry. Since the number of hematogones causes a decrease in the total number of stem cells counted within the graft, we planned a retrospective study to analyze the effect of eHGs on transplant outcomes. We also wanted to show how allografts containing high amounts of early HGs affect transplant outcomes. Quantification of CD34 numbers and the number of eHGs were determined by flow cytometry. Patients were divided into 2 groups according to the number of CD 34+ cells calculated after subtracting the number of hematogones within the allograft. Those who received < 2 × 106/kg CD34+ cells and ≥ 2 × 106/kg were defined as group 1 and 2, respectively. Twenty-six patients and their 26 donors were included in the study. The median age of patients was 6.5 years and 5.4 years in Group 1 and 2, respectively. The median donor age was 9 years in Group 1 and 7 years in Group 2. The ages and genders were similar in the two groups (p > 0.05). The number of nucleated cells given to both groups was not different. The number of early hematogones given to both groups was similar (p = 0.93). The mean times to myeloid and platelet engraftments were also similar in the two groups. In this study, we provided trilineage engraftment to all patients in two groups. We could not find a considerable effect of these eHGs in myeloid and platelet engraftments. However, the number of patients included in our study is low, therefore we suggest a study including a large number of donors in order to confirm our findings. |
2,791 | Automated and Interactive Lesion Detection and Segmentation in Uterine Cervix Images | This paper presents a procedure for automatic extraction and segmentation of a class-specific object (or region) by learning class-specific boundaries. We describe and evaluate the method with a specific focus on the detection of lesion regions in uterine cervix images. The watershed segmentation map of the input image is modeled using a Markov random field (MRF) in which watershed regions correspond to binary random variables indicating whether the region is part of the lesion tissue or not. The local pairwise factors on the arcs of the watershed map indicate whether the arc is part of the object boundary. The factors are based on supervised learning of a visual word distribution. The final lesion region segmentation is obtained using a loopy belief propagation applied to the watershed arc-level MRF. Experimental results on real data show state-of-the-art segmentation results on this very challenging task that, if necessary, can be interactively enhanced. |
2,792 | 2D Orthogonal Locality Preserving Projection for Image Denoising | Sparse representations using transform-domain techniques are widely used for better interpretation of the raw data. Orthogonal locality preserving projection (OLPP) is a linear technique that tries to preserve local structure of data in the transform domain as well. Vectorized nature of OLPP requires high-dimensional data to be converted to vector format, hence may lose spatial neighborhood information of raw data. On the other hand, processing 2D data directly, not only preserves spatial information, but also improves the computational efficiency considerably. The 2D OLPP is expected to learn the transformation from 2D data itself. This paper derives mathematical foundation for 2D OLPP. The proposed technique is used for image denoising task. Recent state-of-the-art approaches for image denoising work on two major hypotheses, i.e., non-local self-similarity and sparse linear approximations of the data. Locality preserving nature of the proposed approach automatically takes care of self-similarity present in the image while inferring sparse basis. A global basis is adequate for the entire image. The proposed approach outperforms several state-of-the-art image denoising approaches for gray-scale, color, and texture images. |
2,793 | Integrity Monitoring of GNSS/INS Based Positioning Systems for Autonomous Vehicles: State-of-the-Art and Open Challenges | Positioning and navigation are critical functions of automated driving functions, which help autonomous vehicles determine their absolute and relative positions in the environment that they operate. Integrity Monitoring (IM) systems, which are intended to assess the reliability and trustworthiness of the information provided by the navigation systems, are crucial for ensuring the safety of automated driving functions. This paper provides a comprehensive review of the existing IM frameworks for safety-critical navigation applications and expands on the state-of-the-art of the most recent development of such systems for connected automated vehicles. We mainly focus on IM methods for Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). However, we also cover IM for map assisted and wireless signal augmented navigation systems, which are promising for high-performance navigation applications, such as automated driving functions. For each main category of solutions, key aspects such as the characteristics of measurement errors and faults related to various data sources are discussed to provide deeper insights into designing of reliable IM systems. Also, some of the major open research challenges to the best knowledge of the authors have been identified and discussed. |
2,794 | Dating the Paleolithic: Trapped charge methods and amino acid geochronology | Despite the vast array of different geochronological tools available, dating the Paleolithic remains one of the discipline's greatest challenges. This review focuses on two different dating approaches: trapped charge and amino acid geochronology. While differing in their fundamental principles, both exploit time-dependent changes in signals found within crystals to generate a chronology for the material dated and hence, the associated deposits. Within each method, there is a diverse range of signals that can be analyzed, each covering different time ranges, applicable to different materials and suitable for different paleoenvironmental and archaeological contexts. This multiplicity of signals can at first sight appear confusing, but it is a fundamental strength of the techniques, allowing internal checks for consistency and providing more information than simply a chronology. For each technique, we present an overview of the basis for the time-dependent signals and the types of material that can be analyzed, with examples of their archaeological application, as well as their future potential. |
2,795 | Structural representation learning for network alignment with self-supervised anchor links | Network alignment, the problem of identifying similar nodes across networks, is an emerging research topic due to its ubiquitous applications in many data domains such as social-network reconciliation and protein-network analysis. While traditional alignment methods struggle to scale to large graphs, the state-of-the-art representation-based methods often rely on pre-defined anchor links, which are unavailable or expensive to compute in many applications. In this paper, we propose NAWAL, a novel, end-to-end unsupervised embedding-based network alignment framework emphasizing on structural information. The model first embeds network nodes into a low-dimension space where the structural neighborhoodship on original network is captured by the distance on the space. As the space for the input networks are learnt independently, we further leverage a generative adversarial deep neural network to reconcile the spaces without relying on hand-crafted features or domain-specific supervision. The empirical results on three real-world datasets show that NAWAL significantly outperforms state-of-the-art baselines, by over 13% of accuracy against unsupervised methods and on par or better than supervised methods. Our technique also demonstrate the robustness against adversarial conditions, such as structural noises and graph size imbalance. |
2,796 | Urban climate and resiliency: A synthesis report of state of the art and future research directions | The Urban Climate and Resiliency-Science Working Group (i.e., The WG) was convened in the summer of 2018 to explore the scientific grand challenges related to climate resiliency of cities. The WG leveraged the presentations at the 10th International Conference on Urban Climate (ICUC10) held in New York City (NYC) on 6-10 August 2018 as input forum. ICUC10 was a collaboration between the International Association of Urban Climate, American Meteorological Society, and World Meteorological Organization. It attracted more than 600 participants from more than 50 countries, resulting in close to 700 oral and poster presentations under the common theme of "Sustainable & Resilient Urban Environments". ICUC10 covered topics related to urban climate and weather processes with far-reaching implications to weather forecasting, climate change adaptation, air quality, health, energy, urban planning, and governance. This article provides a synthesis of the analysis of the current state of the art and of the recommendations of the WG for future research along each of the four Grand Challenges in the context of urban climate and weather resiliency; Modeling, Observations, Cyber-Informatics, and Knowledge Transfer & Applications. |
2,797 | Detection and Localization of PMU Time Synchronization Attacks via Graph Signal Processing | Time Synchronization Attacks (TSAs) against Phasor Measurement Units (PMUs) constitute a major threat to modern smart grid applications. By compromising the time reference of a set of PMUs, an attacker can change the phase angle of their measured phasors, with potentially detrimental impact on grid operation and control. Going beyond traditional residual-based techniques in detecting TSAs, in this paper we propose the use of Graph Signal Processing (GSP) to model the power grid so as to facilitate the detection and localization of TSAs. We analytically show that modeling the state of the power system as a low-pass graph signal can significantly improve the resilience of the grid against TSAs. We propose TSA detection and localization methods based on GSP, leveraging state-of-the-art machine learning algorithms. We provide empirical evidence for the efficiency of the proposed methods based on extensive simulations on five IEEE benchmark systems. In fact, our methods can detect at least 77% more TSAs of significant impact and localize an additional 70% of the attacked PMUs compared to state-of-the-art techniques. |
2,798 | Metallosphaera javensis sp. nov., a novel species of thermoacidophilic archaea, isolated from a volcanic area | A novel thermoacidophilic archeaon, strain J1T (=DSM 112778T,=JCM 34702T), was isolated from a hot pool in a volcanic area of Java, Indonesia. Cells of the strain were irregular, motile cocci of 1.0-1.2 µm diameter. Aerobic, organoheterotrophic growth with casamino acids was observed at an optimum temperature of 70 °C in a range of 55-78 °C and at an optimum pH of 3 in a range of 1.5 to 5. Various organic compounds were utilized, including a greater variety of sugars than has been reported for growth of other species of the genus. Chemolithoautotrophic growth was observed with reduced sulphur compounds, including mineral sulphides. Ferric iron was reduced during anaerobic growth with elemental sulphur. Cellular lipids were calditoglycerocaldarchaeol and caldarchaeol with some derivates. The organism contained the respiratory quinone caldariellaquinone. On the basis of phylogenetic and chemotaxonomic comparison with its closest relatives, it was concluded that strain J1T represents a novel species, for which the name Metallosphaera javensis is proposed. Low DNA-DNA relatedness values (16S rRNA gene <98.4%, average nucleotide identity (ANI) <80.1%) distinguished J1T from other species of the genus Metallosphaera and the DNA G+C content of 47.3% is the highest among the known species of the genus. |
2,799 | Stable and sensitive sensor for alkaline phosphatase based on target-triggered wavelength tuning of fluorescent copper nanoclusters | Generally, the volatility and vulnerability of intensity signal largely reduced the reproducibility and stability of fluorescent nanosensor. Herein, we proposed a novel and stable fluorescent sensor by employing the wavelength shift of copper nanoclusters (CuNCs) as signal readout. The thymine-templated CuNCs were prepared by facile and rapid one-pot reduction method. Interestingly and importantly, it was found that the fluorescence wavelength of CuNCs could be precisely tuned by manganese ion (Mn2+). Through systematic investigation, it was further proved that the wavelength readout of CuNCs is significantly more stable than intensity readout. Since alkaline phosphatase (ALP) can catalyze the hydrolysis of phosphorylated ascorbic acid into ascorbic acid (AA) which can trigger the decomposition of MnO2 nanosheets (NS) into Mn2+, a stable sensor for sensitive ALP detection was constructed based on precise wavelength tuning of fluorescent CuNCs. The sensor exhibited good linear response to ALP over the range from 0.025 to 10 U/L with a detection limit of 0.008 U/L. Additionally, this sensor was also extended to assay two typical ALP inhibitors (Na3VO4 and EDTA) with reasonable results. Last but not least, it was confirmed that the detection results of ALP in real serum samples with this sensor were highly consistent with the data from clinical test, which was mainly attributed to the improved stability and practicability of wavelength readout-based sensor. |
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