query: A Dark Side of the Cannula Injections: How Arterial Wall Perforations and Emboli Occur

positive:
Avoiding and Treating Blindness From Fillers: A Review of the World Literature. BACKGROUND
As the popularity of soft tissue fillers increases, so do the reports of adverse events. The most serious complications are vascular in nature and include blindness.

OBJECTIVE
To review the cases of blindness after filler injection, to highlight key aspects of the vascular anatomy, and to discuss prevention and management strategies.

METHODS
A literature review was performed to identify all the cases of vision changes from filler in the world literature.

RESULTS
Ninety-eight cases of vision changes from filler were identified. The sites that were high risk for complications were the glabella (38.8%), nasal region (25.5%), nasolabial fold (13.3%), and forehead (12.2%). Autologous fat (47.9%) was the most common filler type to cause this complication, followed by hyaluronic acid (23.5%). The most common symptoms were immediate vision loss and pain. Most cases of vision loss did not recover. Central nervous system complications were seen in 23.5% of the cases. No treatments were found to be consistently successful in treating blindness.

CONCLUSION
Although the risk of blindness from fillers is rare, it is critical for injecting physicians to have a firm knowledge of the vascular anatomy and to understand key prevention and management strategies.

positive:
Filler Rhinoplasty Evaluated by Anthropometric Analysis. BACKGROUND
There are no reports of objectively evaluating the efficacy of filler rhinoplasty by anthropometric techniques.

OBJECTIVE
To objectively demonstrate the effectiveness of filler rhinoplasty by anthropometric analysis.

MATERIALS AND METHODS
A total of 242 patients who revisited the clinic within 2 months of undergoing hyaluronic acid filler rhinoplasty were analyzed based on the injection site, injected volume, and the change in anthropometry.

RESULTS
Among the 242 patients, 112 (46.3%) were in the nasal dorsum augmentation group, 8 (3.3%) were in the tip rotation group, and 122 (50.4%) were in the whole nose augmentation group. Average injection volume was 1 ± 0.4 mL for nasal dorsum and 0.9 ± 0.3 mL for tip rotation, whereas 1.6 ± 0.5 mL was used for whole nose augmentation. On follow-up, the radix height, nasofrontal angle, and nasolabial angle (NLA) had increased by 78.3%, 5.7 ± 4.1°, and 9.4 ± 4.5°, respectively, whereas the modified nasofacial angle had decreased by 1.9 ± 2.9°. Three cases (1.2%) of vascular complications were encountered.

CONCLUSION
Filler rhinoplasty is a simple and effective treatment modality producing outcomes comparable with surgical augmentation rhinoplasty. Among various anthropometric measurements, the nasal radix height was the most useful for evaluating dorsum augmentation, whereas the NLA was the best for nasal tip rotation.

positive:
The anatomical origin and course of the angular artery regarding its clinical implications. BACKGROUND
The purposes of this study were to determine the morphological features and conceptualize the anatomical definition of the angular artery (AA) as an aid to practical operations in the clinical field.

MATERIALS AND METHODS
Thirty-one hemifaces from 17 Korean cadavers and 26 hemifaces from 13 Thai cadavers were dissected.

RESULTS
The topography of the AA was classified into 4 types according to its course: Type I (persistent pattern), in which the AA traverses the lateral side of the nose (11%); Type II (detouring pattern), in which the AA traverses the cheek and tear trough area (18%); Type III (alternative pattern), in which the AA traverses the medial canthal area through a branch of the ophthalmic artery (22.8%); and Type IV (latent pattern), in which the AA is absent (26.3%).

CONCLUSION
The findings of this study will contribute toward improved outcomes for cosmetic surgery involving the injection of facial filler by enhancing the understanding of AA anatomy.

positive: Ischemic oculomotor nerve palsy and skin necrosis caused by vascular embolization after hyaluronic acid filler injection: a case report. Hyaluronic acid filler injection is widely used for soft tissue augmentation. However, there can be disastrous complications by direct vascular embolization. We present a case of ischemic oculomotor nerve palsy and skin necrosis after hyaluronic acid filler injection on glabellar.blepharoptosis, exotropia and diplopia developed suddenly after the injection, and skin necrosis gradually occurred. Symptoms and signs of oculomotor nerve palsy continuously improved with steroid therapy. Skin defects healed with minimal scars through intensive wound care.Percutaneous filler injection of periorbital areas should be performed carefully by experienced surgeons, and the possibility of embolization should be considered promptly if symptoms develop.

positive: Complications of injectable fillers, part I. Dermal filling has rapidly become one of the most common procedures performed by clinicians worldwide. The vast majority of treatments are successful and patient satisfaction is high. However, complications, both mild and severe, have been reported and result from injection of many different types of dermal fillers. In this Continuing Medical Education review article, the author describes common technical errors, the signs and symptoms of both common and rare complications, and management of sequelae in clear, easily adaptable treatment algorithms.

negative: Developing a Research Agenda for Human-Centered Data Science The study and analysis of large and complex data sets offer a wealth of insights in a variety of applications. Computational approaches provide researchers access to broad assemblages of data, but the insights extracted may lack the rich detail that qualitative approaches have brought to the understanding of sociotechnical phenomena. How do we preserve the richness associated with traditional qualitative methods while utilizing the power of large data sets? How do we uncover social nuances or consider ethics and values in data use? These and other questions are explored by human-centered data science, an emerging field at the intersection of human-computer interaction (HCI), computer-supported cooperative work (CSCW), human computation, and the statistical and computational techniques of data science. This workshop, the first of its kind at CSCW, seeks to bring together researchers interested in human-centered approaches to data science to collaborate, define a research agenda, and form a community.

negative: MEASURING THE SIMILARITY OF TWO IMAGE SEQUENCES We propose a novel similarity measure of two image sequences based on shapeme histograms. The idea of shapeme histogram has been used for single image/texture recognition, but is used here to solve the sequence-tosequence matching problem. We develop techniques to represent each sequence as a set of shapeme histograms, which captures different variations of the object appearances within the sequence. These shapeme histograms are computed from the set of 2D invariant features that are stable across multiple images in the sequence, and therefore minimizes the effect of both background clutter, and 2D pose variations. We define sequence similarity measure as the similarity of the most similar pair of images from both sequences. This definition maximizes the chance of matching between two sequences of the same object, because it requires only part of the sequences being similar. We also introduce a weighting scheme to conduct an implicit feature selection process during the matching of two shapeme histograms. Experiments on clustering image sequences of tracked objects demonstrate the efficacy of the proposed method.

negative: Design and implementation of a 1.3 kW, 7-level flying capacitor multilevel AC-DC converter with power factor correction This work presents a 1.3 kW, single phase, AC-DC converter with power factor correction based on a 7-level flying capacitor multilevel converter. The topology features a tradeoff of active circuit complexity for dramatic reduction on the magnetic component size, while maintaining a high efficiency. In this work, we demonstrate these features through theoretical analysis as well as a hardware prototype. It has been experimentally demonstrated that the prototype can operate at an universal AC input from 90–230 VRMS and frequencies from 47–63 Hz with an output voltage of 400 V, achieving a box power density of 1.21 W/cm3 (19.8 W/in3) and a peak efficiency of 97.6%. This prototype is the first successful demonstration of a 7-level flying capacitor multilevel boost topology as an AC-DC converter with fully implemented digital PFC control and self-powered start-up from a universal AC input.

negative: Gender Identity and Adjustment in Middle Childhood Gender identity is a central construct in many accounts of psychosocial development, yet it has been defined in diverse ways. Kohlberg (1966) and Zucker et al. (1993) viewed gender identity as knowing that one is a member of one sex rather than the other; Kagan (1964) regarded gender identity as the degree to which one perceives the self as conforming to cultural stereotypes for one's gender; Bem (1981) saw gender identity as the degree to which one internalizes societal pressures for gender conformity; Green (1974) and Spence (1985) viewed gender identity as a fundamental sense of acceptance of, and of belonging to, one's gender. It is conceivable that all of the foregoing (and still other) conceptualizations of gender identity have merit but that different varieties or facets of gender identity serve different psychological functions or affect adjustment in different ways. Thus, it may be fruitful to regard gender identity as a multidimensional construct and to define gender identity as the collection of thoughts and feelings one has about one's gender category and one's membership in it. A recent study by Egan and Perry (2001) was built on this premise. Egan and Perry proposed that gender identity is composed of five major components: (a) membership knowledge (knowledge of membership in a gender category); (b) gender typicality (the degree to which one feels one is a typical member of one's gender category); (c) gender contentedness (the degree to which one is happy with one's gender assignment); (d) felt pressure for gender conformity (the degree to which one feels pressure from parents, peers, and self for conformity to gender stereotypes); and (e) intergroup bias (the extent to which one believes one's own sex is superior to the other). Egan and Perry (2001) measured the last four of these components of gender identity in preadolescent children and found the components to be relatively independent, to be fairly stable over a school year, and to relate to adjustment (i.e., self-esteem and peer acceptance) in different ways. Gender typicality and gender contentedness were favorably related to adjustment, whereas felt pressure and intergroup bias were negatively associated with adjustment. Links between the gender identity constructs and the adjustment indexes remained significant when children's perceptions of self-efficacy for a wide variety of sex-typed activities were statistically controlled. This suggests that the gender identity constructs carry implications for adjustment beyond self-perceptions of specific sex-linked competencies. The purposes of the …

negative: Load Forecasting via Deep Neural Networks Nowadays, electricity plays a vital role in national economic and social development. Accurate load forecasting can help power companies to secure electricity supply and scheduling and reduce wastes since electricity is difficult to store. In this paper, we propose a novel Deep Neural Network architecture for short term load forecasting. We integrate multiple types of input features by using appropriate neural network components to process each of them. We use Convolutional Neural Network components to extract rich features from historical load sequence and use Recurrent Components to model the implicit dynamics. In addition, we use Dense layers to transform other types of features. Experimental results on a large data set containing hourly loads of a North China city show the superiority of our method. Moreover, the proposed method is quite flexible and can be applied to other time series prediction tasks. c © 2017 The Authors. Published by Elsevier B.V. Selectio and/or peer-review under responsibility of ITQM2017.

negative: 3D-Printing of Meso-structurally Ordered Carbon Fiber/Polymer Composites with Unprecedented Orthotropic Physical Properties Here we report the first example of a class of additively manufactured carbon fiber reinforced composite (AMCFRC) materials which have been achieved through the use of a latent thermal cured aromatic thermoset resin system, through an adaptation of direct ink writing (DIW) 3D-printing technology. We have developed a means of printing high performance thermoset carbon fiber composites, which allow the fiber component of a resin and carbon fiber fluid to be aligned in three dimensions via controlled micro-extrusion and subsequently cured into complex geometries. Characterization of our composite systems clearly show that we achieved a high order of fiber alignment within the composite microstructure, which in turn allows these materials to outperform equivalently filled randomly oriented carbon fiber and polymer composites. Furthermore, our AM carbon fiber composite systems exhibit highly orthotropic mechanical and electrical responses as a direct result of the alignment of carbon fiber bundles in the microscale which we predict will ultimately lead to the design of truly tailorable carbon fiber/polymer hybrid materials having locally programmable complex electrical, thermal and mechanical response.

negative: Ten-year research update review: child sexual abuse. OBJECTIVE To provide clinicians with current information on prevalence, risk factors, outcomes, treatment, and prevention of child sexual abuse (CSA). To examine the best-documented examples of psychopathology attributable to CSA. METHOD Computer literature searches of and for key words. All English-language articles published after 1989 containing empirical data pertaining to CSA were reviewed. RESULTS CSA constitutes approximately 10% of officially substantiated child maltreatment cases, numbering approximately 88,000 in 2000. Adjusted prevalence rates are 16.8% and 7.9% for adult women and men, respectively. Risk factors include gender, age, disabilities, and parental dysfunction. A range of symptoms and disorders has been associated with CSA, but depression in adults and sexualized behaviors in children are the best-documented outcomes. To date, cognitive-behavioral therapy (CBT) of the child and a nonoffending parent is the most effective treatment. Prevention efforts have focused on child education to increase awareness and home visitation to decrease risk factors. CONCLUSIONS CSA is a significant risk factor for psychopathology, especially depression and substance abuse. Preliminary research indicates that CBT is effective for some symptoms, but longitudinal follow-up and large-scale "effectiveness" studies are needed. Prevention programs have promise, but evaluations to date are limited.

negative: Appropriateness of plantar pressure measurement devices: a comparative technical assessment. Accurate plantar pressure measurements are mandatory in both clinical and research contexts. Differences in accuracy, precision and reliability of the available devices have prevented so far the onset of standardization processes or the definition of reliable reference datasets. In order to comparatively assess the appropriateness of the most used pressure measurement devices (PMD) on-the-market, in 2006 the Institute the author is working for approved a two-year scientific project aimed to design, validate and implement dedicated testing methods for both in-factory and on-the field assessment. A first testing phase was also performed which finished in December 2008. Five commercial PMDs using different technologies-resistive, elastomer-based capacitive, air-based capacitive-were assessed and compared with respect to absolute pressure measurements, hysteresis, creep and COP estimation. The static and dynamic pressure tests showed very high accuracy of capacitive, elastomer-based technology (RMSE<0.5%), and quite a good performance of capacitive, air-based technology (RMSE<5%). High accuracy was also found for the resistive technology by TEKSCAN (RMSE<2.5%), even though a complex ad hoc calibration was necessary.

negative: Connectionist models of recognition memory: constraints imposed by learning and forgetting functions. Multilayer connectionist models of memory based on the encoder model using the backpropagation learning rule are evaluated. The models are applied to standard recognition memory procedures in which items are studied sequentially and then tested for retention. Sequential learning in these models leads to 2 major problems. First, well-learned information is forgotten rapidly as new information is learned. Second, discrimination between studied items and new items either decreases or is nonmonotonic as a function of learning. To address these problems, manipulations of the network within the multilayer model and several variants of the multilayer model were examined, including a model with prelearned memory and a context model, but none solved the problems. The problems discussed provide limitations on connectionist models applied to human memory and in tasks where information to be learned is not all available during learning.

negative: Finite Precision Error Analysis of Neural Network Hardware Implementations 29 computation. On the other hand, for network learning, at least 14-16 bits of precision must be used for the weights to avoid having the training process divert too much from the trajectory of the high precision computation. References [1] D. Hammerstrom. A VLSI architecture for high-performance, low cost, on-chip learning. Figure 10: The average squared dierences between the desired and actual outputs of the XOR problem after the network converges. The paper is devoted to the derivation of the nite precision error analysis techniques for neural network implementations, especially analysis of the back-propagation learning of MLP's. This analysis technique is proposed to be more versatile and to prepare the ground for a wider variety of neural network algorithms: recurrent neural networks, competitive learning networks, and etc. All these networks share similar computational mechanisms as those used in back-propagation learning. For the forward retrieving operations, it is shown that 8-bit weights are sucient to maintain the same performance as using high precision 27 ture of the XOR problem, a soft convergence is good enough for the termination of training. Therefore, at the predicted point of 12-13 bits of weights, the squared dierence curve dives. Another interesting observation is worthwhile to mention: the total nite precision error in a single iteration of weight updating is mainly generated in the nal jamming operators in the computation of the output delta, hidden delta, and weight update. Therefore, even though it is required to have at least 13 to 16 bits assigned to the computation of the weight update and stored as the total weight value, the number of weight bits in the computation of forward retrieving and hidden delta steps of learning can be as low as 8 bits without excessive degradation of learning convergence and accuracy.

negative: Multiple-resonator-based bandpass filters This article describes a class of recently developed multiple-mode-resonator-based bandpass filters for ultra-wide-band (UWB) transmission systems. These filters have many attractive features, including a simple design, compact size, low loss and good linearity in the UWB, enhanced out-of-band rejection, and easy integration with other circuits/antennas. In this article, we present a variety of multiple-mode resonators with stepped-impedance or stub-loaded nonuniform configurations and analyze their properties based on the transmission line theory. Along with the frequency dispersion of parallel-coupled transmission lines, we design and implement various filter structures on planar, uniplanar, and hybrid transmission line geometries.

negative: Rotation Invariant Multi-View Color Face Detection Based on Skin Color and Adaboost Algorithm As the training of Adaboost is complicated or does not work well in the multi-view face detection with large plane-rotated angle, this paper proposes a rotation invariant multi-view color face detection method combining skin color segmentation and multi-view Adaboost algorithm. First the possible face region is fast detected by skin color table, and the skin-color background adhesion of face is separated by color clustering. After region merging, the candidate face region is received. Then the face direction in plane is calculated by K-L transform, and finally the candidate face region corrected by rotating is scanned by multi-view Adaboost classifier to locate the face accurately. The experiments show that the method can effectively detect the plane large-angle multi-view face image which the conventional Adaboost can not do. It can be effectively applied to the cases of multi-view and multi-face image with complex background.

negative: Amorphous Silicon Solar Vivaldi Antenna An ultrawideband solar Vivaldi antenna is proposed. Cut from amorphous silicon cells, it maintains a peak power at 4.25 V, which overcomes a need for lossy power management components. The wireless communications device can yield solar energy or function as a rectenna for dual-source energy harvesting. The solar Vivaldi performs with 0.5-2.8 dBi gain from 0.95-2.45 GHz , and in rectenna mode, it covers three bands for wireless energy scavenging.

negative: Automating metadata generation: the simple indexing interface In this paper, we focus on the development of a framework for automatic metadata generation. The first step towards this framework is the definition of an Application Programmer Interface (API), which we call the Simple Indexing Interface (SII). The second step is the definition of a framework for implementation of the SII. Both steps are presented in some detail in this paper. We also report on empirical evaluation of the metadata that the SII and supporting framework generated in a real-life context.

negative: Four common anatomic variants that predispose to unfavorable rhinoplasty results: a study based on 150 consecutive secondary rhinoplasties. A retrospective study was conducted of 150 consecutive secondary rhinoplasty patients operated on by the author before February of 1999, to test the hypothesis that four anatomic variants (low radix/low dorsum, narrow middle vault, inadequate tip projection, and alar cartilage malposition) strongly predispose to unfavorable rhinoplasty results. The incidences of each variant were compared with those in 50 consecutive primary rhinoplasty patients. Photographs before any surgery were available in 61 percent of the secondary patients; diagnosis in the remaining individuals was made from operative reports, physical diagnosis, or patient history. Low radix/low dorsum was present in 93 percent of the secondary patients and 32 percent of the primary patients; narrow middle vault was present in 87 percent of the secondary patients and 38 percent of the primary patients; inadequate tip projection was present in 80 percent of the secondary patients and 31 percent of the primary patients; and alar cartilage malposition was present in 42 percent of the secondary patients and 18 percent of the primary patients. In the 150-patient secondary group, the most common combination was the triad of low radix, narrow middle vault, and inadequate tip projection (40 percent of patients). The second largest group (27 percent) had shared all four anatomic points before their primary rhinoplasties. Seventy-eight percent of the secondary patients had three or all four anatomic variants in some combination; each secondary patient had at least one of the four traits; 99 percent had two or more. Seventy-eight percent of the primary patients had at least two variants, and 58 percent had three or more. Twenty-two percent of the primary patients had none of the variants and therefore would presumably not be predisposed to unfavorable results following traditional reduction rhinoplasty. This study supports the contention that four common anatomic variants, if unrecognized, are strongly associated with unfavorable results following primary rhinoplasty. It is important for all surgeons performing rhinoplasty to recognize these anatomic variants to avoid the unsatisfactory functional and aesthetic sequelae that they may produce by making their correction a deliberate part of each preoperative surgical plan.

negative: Categorization of Anomalies in Smart Manufacturing Systems to Support the Selection of Detection Mechanisms An important issue in anomaly detection in smart manufacturing systems is the lack of consistency in the formal definitions of anomalies, faults, and attacks. The term anomaly is used to cover a wide range of situations that are addressed by different types of solutions. In this letter, we categorize anomalies in machines, controllers, and networks along with their detection mechanisms, and unify them under a common framework to aid in the identification of potential solutions. The main contribution of the proposed categorization is that it allows the identification of gaps in anomaly detection in smart manufacturing systems.

negative: Multimodal Machine Learning: A Survey and Taxonomy Our experience of the world is multimodal - we see objects, hear sounds, feel texture, smell odors, and taste flavors. Modality refers to the way in which something happens or is experienced and a research problem is characterized as multimodal when it includes multiple such modalities. In order for Artificial Intelligence to make progress in understanding the world around us, it needs to be able to interpret such multimodal signals together. Multimodal machine learning aims to build models that can process and relate information from multiple modalities. It is a vibrant multi-disciplinary field of increasing importance and with extraordinary potential. Instead of focusing on specific multimodal applications, this paper surveys the recent advances in multimodal machine learning itself and presents them in a common taxonomy. We go beyond the typical early and late fusion categorization and identify broader challenges that are faced by multimodal machine learning, namely: representation, translation, alignment, fusion, and co-learning. This new taxonomy will enable researchers to better understand the state of the field and identify directions for future research.

negative:
NCDawareRank: a novel ranking method that exploits the decomposable structure of the web Research about the topological characteristics of the hyperlink graph has shown that Web possesses a nested block structure, indicative of its innate hierarchical organization. This crucial observation opens the way for new approaches that can usefully regard Web as a Nearly Completely Decomposable(NCD) system; In recent years, such approaches gave birth to various efficient methods and algorithms that exploit NCD from a computational point of view and manage to considerably accelerate the extraction of the PageRank vector. However, very little have been done towards the qualitative exploitation of NCD.
 In this paper we propose NCDawareRank, a novel ranking method that uses the intuition behind NCD to generalize and refine PageRank. NCDawareRank considers both the link structure and the hierarchical nature of the Web in a way that preserves the mathematically attractive characteristics of PageRank and at the same time manages to successfully resolve many of its known problems, including Web Spamming Susceptibility and Biased Ranking of Newly Emerging Pages. Experimental results show that NCDawareRank is more resistant to direct manipulation, alleviates the problems caused by the sparseness of the link graph and assigns more reasonable ranking scores to newly added pages, while maintaining the ability to be easily implemented on a large-scale and in a computationally efficient manner.

negative: Motion Detection Techniques Using Optical Flow Motion detection is very important in image processing. One way of detecting motion is using optical flow. Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. The method used for finding the optical flow in this project is assuming that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image. This technique is later used in developing software for motion detection which has the capability to carry out four types of motion detection. The motion detection software presented in this project also can highlight motion region, count motion level as well as counting object numbers. Many objects such as vehicles and human from video streams can be recognized by applying optical flow technique. Keywords—Background modeling, Motion detection, Optical flow, Velocity smoothness constant, motion trajectories.

negative: What ’ s good for the goose is good for the GANder Comparing Generative Adversarial Networks for NLP Generative Adversarial Nets (GANs), which use discriminators to help train a generative model, have been successful particularly in computer vision for generating images. However, there are many restrictions in its applications to natural language tasks–mainly, it is difficult to back-propagate through discrete-value random variables. Yet recent publications have applied GAN with promising results. Sequence GAN (Yu et al. 2017) introduces a solution by modeling the data generator as a reinforcement learning (RL) policy to overcome the generator differentiation problem, with the RL reward signals produced by the discriminator after it judges complete sequences. However, problems with this model persist, as the GAN training objective is inherently unstable, producing a large variation of results that make it difficult to fool the discriminator. Maximum-Likelihood Augmented Discrete GAN (Che at al. 2017) suggests a new low-variance objective for the generator, using a normalized reward signal from the discriminator that corresponds to log-likelihood. Our project explores both proposed implementations: we produce experimental results on both synthetic and real-world discrete datasets to explore the effectiveness of GAN over strong baselines.

negative: Design and implementation of intrusion detection system using convolutional neural network for DoS detection Nowadays, network is one of the essential parts of life, and lots of primary activities are performed by using the network. Also, network security plays an important role in the administrator and monitors the operation of the system. The intrusion detection system (IDS) is a crucial module to detect and defend against the malicious traffics before the system is affected. This system can extract the information from the network system and quickly indicate the reaction which provides real-time protection for the protected system. However, detecting malicious traffics is very complicating because of their large quantity and variants. Also, the accuracy of detection and execution time are the challenges of some detection methods. In this paper, we propose an IDS platform based on convolutional neural network (CNN) called IDS-CNN to detect DoS attack. Experimental results show that our CNN based DoS detection obtains high accuracy at most 99.87%. Moreover, comparisons with other machine learning techniques including KNN, SVM, and Naïve Bayes demonstrate that our proposed method outperforms traditional ones.

negative: Is multiagent deep reinforcement learning the answer or the question? A brief survey Deep reinforcement learning (DRL) has achieved outstanding results in recent years. This has led to a dramatic increase in the number of applications and methods. Recent works have explored learning beyond single-agent scenarios and have considered multiagent scenarios. Initial results report successes in complex multiagent domains, although there are several challenges to be addressed. In this context, first, this article provides a clear overview of current multiagent deep reinforcement learning (MDRL) literature. Second, it provides guidelines to complement this emerging area by (i) showcasing examples on how methods and algorithms from DRL and multiagent learning (MAL) have helped solve problems in MDRL and (ii) providing general lessons learned from these works. We expect this article will help unify and motivate future research to take advantage of the abundant literature that exists in both areas (DRL and MAL) in a joint effort to promote fruitful research in the multiagent community.

negative: Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization This work proposes a new algorithm for automated and simultaneous phenotyping of multiple co–occurring medical conditions, also referred as comorbidities, using clinical notes from the electronic health records (EHRs). A basic latent factor estimation technique of non-negative matrix factorization (NMF) is augmented with domain specific constraints to obtain sparse latent factors that are anchored to a fixed set of chronic conditions. The proposed anchoring mechanism ensures a one-to-one identifiable and interpretable mapping between the latent factors and the target comorbidities. Qualitative assessment of the empirical results by clinical experts suggests that the proposed model learns clinically interpretable phenotypes while being predictive of 30 day mortality. The proposed method can be readily adapted to any non-negative EHR data across various healthcare institutions.

negative: Integrating perceived playfulness into expectation-confirmation model for web portal context This paper investigated the value of including "playfulness" in expectation-confirmation theory (ECT) when studying continued use of a web site. Original models examined cognitive beliefs and effects that influence a person's intention to continue to use an information system. Here, an extended ECT model (with an additional relationship between perceived playfulness and satisfaction) was shown to provide a better fit than a simple path from perceived usefulness to satisfaction. The results indicated that perceived playfulness, confirmation to satisfaction, and perceived usefulness all contributed significantly to the users' intent to reuse a web site. Thus, we believe that the extended ECT model is an appropriate tool for the study of web site effects.

negative: Survey of review spam detection using machine learning techniques Online reviews are often the primary factor in a customer’s decision to purchase a product or service, and are a valuable source of information that can be used to determine public opinion on these products or services. Because of their impact, manufacturers and retailers are highly concerned with customer feedback and reviews. Reliance on online reviews gives rise to the potential concern that wrongdoers may create false reviews to artificially promote or devalue products and services. This practice is known as Opinion (Review) Spam, where spammers manipulate and poison reviews (i.e., making fake, untruthful, or deceptive reviews) for profit or gain. Since not all online reviews are truthful and trustworthy, it is important to develop techniques for detecting review spam. By extracting meaningful features from the text using Natural Language Processing (NLP), it is possible to conduct review spam detection using various machine learning techniques. Additionally, reviewer information, apart from the text itself, can be used to aid in this process. In this paper, we survey the prominent machine learning techniques that have been proposed to solve the problem of review spam detection and the performance of different approaches for classification and detection of review spam. The majority of current research has focused on supervised learning methods, which require labeled data, a scarcity when it comes to online review spam. Research on methods for Big Data are of interest, since there are millions of online reviews, with many more being generated daily. To date, we have not found any papers that study the effects of Big Data analytics for review spam detection. The primary goal of this paper is to provide a strong and comprehensive comparative study of current research on detecting review spam using various machine learning techniques and to devise methodology for conducting further investigation.

negative: Intravesical stone formation on intrauterine contraceptive device Since more than 30 years, intrauterine contraceptive devices (IUCD) have been used for a contraceptive opportunity. Although they are termed to be a safe and effective method for contraception, they also have some type of complications and uterine perforation, septic abortion, pelvic abscess are the serious complications of these devices. The incidence of uterine perforation is very low, but in the literature nearly 100 cases were reported about the extra uterine localization of IUCD. Migration may occur to the adjacent organs. We here in describe a case of a 31 year-old woman who had an IUCD with stone formation in the bladder. In the literature all of the cases were reported as IUCD migration, but although it seems technically impossible, IUCD placement into the bladder should also be considered in misplaced IUCDs.

negative: A model for concentric tube continuum robots under applied wrenches Continuum robots made from telescoping precurved elastic tubes enable base-mounted actuators to specify the curved shapes of robots as thin as standard surgical needles. While free space beam mechanics-based models of the shape of these ‘active cannulas’ exist, current models cannot account for external forces and torques applied to the cannula by the environment. In this paper we apply geometrically exact beam theory to solve the statics problem for concentric-tube continuum robots. This yields the equivalent of forward kinematics for an active cannula with general tube precurvature functions and arbitrarily many tubes, under loading from a general wrench distribution. The model achieves average experimental tip errors of less than 3 mm over the workspace of a prototype active cannula subject to various tip forces.

negative: Safe Planes for Injection Rhinoplasty: A Histological Analysis of Midline Longitudinal Sections of the Asian Nose Dorsal nasal augmentation is an essential part of injection rhinoplasty on the Asian nose. Aesthetic physicians require detailed knowledge of the nasal anatomy to accurately and safely inject filler. One hundred and thirty-five histological cross sections were examined from 45 longitudinal strips of soft tissue harvested from the midline of the nose, beginning from the glabella to the nasal tip. Muscles and nasal cartilage were used as landmarks for vascular identification. At the nasal tip, a midline longitudinal columellar artery with a diameter of 0.21 ± 0.09 mm was noted in 14 cadavers (31.1 %). At the infratip, subcutaneous tissue contained cavernous tissue similar to that of the nasal mucosa. The feeding arteries of these dilated veins formed arteriovenous shunts, into which retrograde injection of filler may be possible. All of the nasal arteries present were identified as subcutaneous arteries. They coursed mainly in the superficial layer of the subcutaneous tissues, with smaller branches forming subdermal plexuses. A substantial arterial anastomosis occurred at the supratip region, in which the artery lay in the middle of the subcutaneous tissue at the level of the major alar cartilages. These arteries had a diameter ranging between 0.4 and 0.9 mm and were found in 29 of 45 specimens (64.4 %). This was at the level midway between the rhinion above the supratip and the infratip. This anastomotic artery also crossed the midline at the rhinion superficial to the origin of the procerus on the lower end of the nasal bone. Here the arterial diameter ranged between 0.1 and 0.3 mm, which was not large enough to cause arterial emboli. Fascicular cross sections of the nasalis muscle directly covered the entire upper lateral cartilage. The subdermal tissue contained few layers of fat cells along with the occasional small artery. The procerus arose from the nasal bone and was continuous with the nasalis in 16 cadavers (35.6 %). There was fatty areolar tissue between the procerus and the periosteal layer and no significant arteries present. The procerus ascended beyond the brow to insert into the frontalis muscle with very few cutaneous insertions. The supratrochlear vessels and accompanying nerve were occasionally found on the surface of the frontalis muscle. Most nasal arteries found in the midline are subcutaneous arteries. Filler should be injected deeply to avoid vascular injury leading to compromised perfusion at the dorsum or filler emboli at the nasal tip. This journal requires that the authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

negative: Special Perforated Steel Plate Shear Walls with Reduced Beam Section Anchor Beams . I : Experimental Investigation This paper presents results of an experimental investigation of specially detailed ductile perforated steel plate shear walls SPSWs designed to accommodate utility passage, and having anchor beams with reduced beam sections connections. Single-story, single-bay SPSW frames are subjected to quasi-static cyclic loading up to their maximum strength and displacement capacity. The tested specimens also had low yield strength steel infill panels. Two specimens make allowances for penetration of the panel by utilities. The first, having multiple holes specially laid out in the steel panel, also has the characteristic of reduced panel strength and stiffness compared to the corresponding SPSW having a solid panel. The second such specimen utilizes quarter-circle cutouts in the panel corners, which are reinforced to transfer the panel forces to the adjacent framing. A SPSW with solid panel is also tested for reference purposes. All specimens resisted an imposed input history of increasing displacements to a minimum drift of 3%. The perforated panel reduced the elastic stiffness and overall strength of the specimen by 15% as compared with the solid panel specimen. DOI: 10.1061/ ASCE 0733-9445 2009 135:3 211 CE Database subject headings: Steel plates; Beams; Anchors; Experimentation; Shear walls.

negative: Gain Improvement of Rectangular Dielectric Resonator Antenna by Engraving Grooves on Its Side Walls A new technique for increasing the boresight gain of a rectangular dielectric resonator antenna (DRA) operating at its fundamental radiating <inline-formula><tex-math notation="LaTeX">$TE_{111}^y$</tex-math></inline-formula> mode is introduced. The idea is to increase the radiations from the side walls of the DRA compared to that of its top wall by engraving grooves on the side walls. A model based on the array theory is developed to explain the high-gain nature of the antenna. The measured results demonstrate that the proposed antenna achieves an impedance bandwidth of 21% over a band of 3.24–4 GHz, with a maximum gain of 9.6 dB. This is significantly higher with respect to available data in the literature.

negative: Heat-induced post-mortem defect of the skull simulating an exit gunshot wound of the calvarium. A severely burned body was found in a burnt-out apartment following a house fire. At the death scene, police investigators noted a defect at the back of the head of the deceased. This defect perforated the occipital bone and showed external bevelling. To clarify whether this skull wound corresponded to a gunshot exit wound and for identification purposes, a medico-legal autopsy was ordered. External examination of the body showed intense charring with skin burned away and musculature exposed, fourth degree burns of the remaining skin and heat flexures of the limbs as well as heat-related rupture of both the abdominal cavity and chest wall (Fig. 1). An oval defect of the occipital bone with cratering of the external table of the cranium was found (Fig. 2). The defect measured 2 cm in diameter, was sharp-edged and the excavation of the outer table of the cranium showed no charring in contrast to the surrounding parts of the occipital bone (Fig. 3). Apart from this finding, radiology of the body before autopsy was unremarkable. At autopsy, gross sections of the mucosa of the trachea and main bronchi were covered by a thick layer of soot with soot particles also present within the esophageus and the stomach. The brain showed a reduced volume, flattening of gyri and obliteration of sulci but no signs of trauma. Except for the defect of the occipital bone, no other signs of ante-mortem or post-mortem trauma could be detected. The level of carboxyhemoglobin in heart blood was 65% and the blood alcohol level was 285 mg/dL.

negative: The dark side of the sharing economy ... and how to lighten it Improving the sharing economy will require addressing myriad problems.


query: Online Social Networks anatomy: On the analysis of Facebook and WhatsApp in cellular networks

positive: Internet inter-domain traffic In this paper, we examine changes in Internet inter-domain traffic demands and interconnection policies. We analyze more than 200 Exabytes of commercial Internet traffic over a two year period through the instrumentation of 110 large and geographically diverse cable operators, international transit backbones, regional networks and content providers. Our analysis shows significant changes in inter-AS traffic patterns and an evolution of provider peering strategies. Specifically, we find the majority of inter-domain traffic by volume now flows directly between large content providers, data center / CDNs and consumer networks. We also show significant changes in Internet application usage, including a global decline of P2P and a significant rise in video traffic. We conclude with estimates of the current size of the Internet by inter-domain traffic volume and rate of annualized inter-domain traffic growth.

positive: Strategies and struggles with privacy in an online social networking community Online social networking communities such as Facebook and MySpace are extremely popular. These sites have changed how many people develop and maintain relationships through posting and sharing personal information. The amount and depth of these personal disclosures have raised concerns regarding online privacy. We expand upon previous research on users’ under-utilization of available privacy options by examining users’ current strategies for maintaining their privacy, and where those strategies fail, on the online social network site Facebook. Our results demonstrate the need for mechanisms that provide awareness of the privacy impact of users’ daily interactions.

positive: Moving beyond untagging: photo privacy in a tagged world Photo tagging is a popular feature of many social network sites that allows users to annotate uploaded images with those who are in them, explicitly linking the photo to each person's profile. In this paper, we examine privacy concerns and mechanisms surrounding these tagged images. Using a focus group, we explored the needs and concerns of users, resulting in a set of design considerations for tagged photo privacy. We then designed a privacy enhancing mechanism based on our findings, and validated it using a mixed methods approach. Our results identify the social tensions that tagging generates, and the needs of privacy tools to address the social implications of photo privacy management.

positive: Information revelation and privacy in online social networks Participation in social networking sites has dramatically increased in recent years. Services such as Friendster, Tribe, or the Facebook allow millions of individuals to create online profiles and share personal information with vast networks of friends - and, often, unknown numbers of strangers. In this paper we study patterns of information revelation in online social networks and their privacy implications. We analyze the online behavior of more than 4,000 Carnegie Mellon University students who have joined a popular social networking site catered to colleges. We evaluate the amount of information they disclose and study their usage of the site's privacy settings. We highlight potential attacks on various aspects of their privacy, and we show that only a minimal percentage of users changes the highly permeable privacy preferences.

positive: Persona: an online social network with user-defined privacy Online social networks (OSNs) are immensely popular, with some claiming over 200 million users. Users share private content, such as personal information or photographs, using OSN applications. Users must trust the OSN service to protect personal information even as the OSN provider benefits from examining and sharing that information. We present Persona, an OSN where users dictate who may access their information. Persona hides user data with attribute-based encryption (ABE), allowing users to apply fine-grained policies over who may view their data. Persona provides an effective means of creating applications in which users, not the OSN, define policy over access to private data. We demonstrate new cryptographic mechanisms that enhance the general applicability of ABE. We show how Persona provides the functionality of existing online social networks with additional privacy benefits. We describe an implementation of Persona that replicates Facebook applications and show that Persona provides acceptable performance when browsing privacy-enhanced web pages, even on mobile devices.

negative: Estimating the Customer-Level Demand for Electricity Under Real-Time Market Prices This paper presents estimates of the customer-level demand for electricity by industrial and commercial customers purchasing electricity according to the half-hourly energy prices from the England and Wales (E&W) electricity market. These customers also face the possibility of a demand charge on their electricity consumption during the three half-hour periods that are coincident with E&W system peaks. Although energy charges are largely known by 4:00 P.M. the day prior to consumption, a fraction of the energy charge and the identity of the half-hour periods when demand charges occur are only known with certainty ex post of consumption. Four years of data from a Regional Electricity Company (REC) in the United Kingdom is used to quantify the half-hourly customer-level demands under this real-time pricing program. The econometric model developed and estimated here quantifies the extent of intertemporal substitution in electricity consumption across pricing periods within the day due to changes in all of the components of the day-ahead E&W electricity prices, the level of the demand charge and the probability that a demand charge will be imposed. The results of this modeling framework can be used by retail companies supplying consumers purchasing electricity according to real-time market prices to construct demand-side bids into an electricity market open to competition. The paper closes with several examples of how this might be done.

negative: Application of Spreading Activation Techniques in Information Retrieval This paper surveys the use of Spreading Activation techniques onSemantic Networks in Associative Information Retrieval. The majorSpreading Activation models are presented and their applications toIR is surveyed. A number of works in this area are criticallyanalyzed in order to study the relevance of Spreading Activation forassociative IR.

negative: Combined digital signature and digital watermark scheme for image authentication Conventional digital signature schemes for image authentication encode the signature in a file separate from the original image, thus require extra bandwidth to transmit it. Meantime, the watermark technique embeds some information in the host image. In this paper, a combined digital watermark and digital signature scheme for image authentication is proposed. The scheme extracts signature from the original image and embeds them back into the image as watermark, avoiding additional signature file. Since images are always compressed before transmission in the Internet, the proposed scheme is tested for compression tolerance and shows good robustness against JPEG coding. Furthermore, the scheme not only can verify the authenticity and the integrity of images, but also can locate the illegal modifications.

negative: Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction Stock trend prediction plays a critical role in seeking maximized profit from the stock investment. However, precise trend prediction is very difficult since the highly volatile and non-stationary nature of the stock market. Exploding information on the Internet together with the advancing development of natural language processing and text mining techniques have enabled investors to unveil market trends and volatility from online content. Unfortunately, the quality, trustworthiness, and comprehensiveness of online content related to stock market vary drastically, and a large portion consists of the low-quality news, comments, or even rumors. To address this challenge, we imitate the learning process of human beings facing such chaotic online news, driven by three principles: sequential content dependency, diverse influence, and effective and efficient learning. In this paper, to capture the first two principles, we designed a Hybrid Attention Networks(HAN) to predict the stock trend based on the sequence of recent related news. Moreover, we apply the self-paced learning mechanism to imitate the third principle. Extensive experiments on real-world stock market data demonstrate the effectiveness of our framework. A further simulation illustrates that a straightforward trading strategy based on our proposed framework can significantly increase the annualized return.

negative: FinDroidHR: Smartwatch Gesture Input with Optical Heartrate Monitor We present FinDroidHR, a novel gesture input technique for off-the-shelf smartwatches. Our technique is designed to detect 10 hand gestures on the hand wearing a smartwatch. The technique is enabled by analysing features of the Photoplethysmography (PPG) signal that optical heart-rate sensors capture. In a study with 20 participants, we show that FinDroidHR achieves 90.55% accuracy and 90.73% recall. Our work is the first study to explore the feasibility of using optical sensors on the off-the-shelf wearable devices to recognise gestures. Without requiring bespoke hardware, FinDroidHR can be readily used on existing smartwatches.

negative: Humanoid robotics platforms developed in HRP This paper presents humanoid robotics platform that consists of a humanoid robot and an open architecture software platform developed in METI’s Humanoid Robotics Project (HRP). The final version of the robot, called HRP-2, has 1540 mm height, 58 kg weight and 30 degrees of the freedom. The software platform includes a dynamics simulator and motion controllers of the r ns and is e ©

negative: Using web security scanners to detect vulnerabilities in web services Although web services are becoming business-critical components, they are often deployed with critical software bugs that can be maliciously explored. Web vulnerability scanners allow detecting security vulnerabilities in web services by stressing the service from the point of view of an attacker. However, research and practice show that different scanners have different performance on vulnerabilities detection. In this paper we present an experimental evaluation of security vulnerabilities in 300 publicly available web services. Four well known vulnerability scanners have been used to identify security flaws in web services implementations. A large number of vulnerabilities has been observed, which confirms that many services are deployed without proper security testing. Additionally, the differences in the vulnerabilities detected and the high number of false-positives (35% and 40% in two cases) and low coverage (less than 20% for two of the scanners) observed highlight the limitations of web vulnerability scanners on detecting security vulnerabilities in web services.

negative: Development of Generalized Photovoltaic Model Using MATLAB / SIMULINK temperature into consideration, the output current and power characteristics of PV model are simulated and optimized using the proposed model. This enables the dynamics of PV power system to be easily simulated, analyzed, and optimized.

negative: Social-Aware Video Recommendation for Online Social Groups Group recommendation plays a significant role in today's social media systems, where users form social groups to receive multimedia content together and interact with each other, instead of consuming the online content individually. Limitations of traditional group recommendation approaches are as follows. First, they usually infer group members’ preferences by their historical behaviors, failing to capture inactive users’ preferences from the sparse historical data. Second, relationships between group members are not studied by these approaches, which fail to capture the inherent personality of members in a group. To address these issues, we propose a social-aware group recommendation framework that jointly utilizes both social relationships and social behaviors to not only infer a group's preference, but also model the tolerance and  altruism characteristics of group members. Based on the observation that the following relationship in the online social network reflects common interests of users, we propose a group preference model based on external experts of group members. Furthermore, we model users’ tolerance (willingness to receive content not preferred) and altruism (willingness to receive content preferred by friends). Finally, based on the group preference model, we design recommendation algorithms for users under different social contexts. Experimental results demonstrate the effectiveness of our approach, which significantly improves the recommendation accuracy against traditional approaches, especially in the cases of inactive group members.

negative: ScreenerNet: Learning Curriculum for Neural Networks We propose to learn a curriculum or a syllabus for supervised learning with deep neural networks. Specifically, we learn weights for each sample in training by an attached neural network, called ScreenerNet, to the original network and jointly train them in an end-to-end fashion. We show the networks augmented with our ScreenerNet achieve early convergence with better accuracy than the state-of-the-art rule-based curricular learning methods in extensive experiments using three popular vision datasets including MNIST, CIFAR10 and Pascal VOC2012, and a Cartpole task using Deep Q-learning.

negative: ICTs for Improving Patients Rehabilitation Research Techniques The world population is rapidly aging and becoming a burden to health systems around the world. In this work we present a conceptual framework to encourage the research community to develop more comprehensive and adaptive ICT solutions for prevention and rehabilitation of chronic conditions in the daily life of the aging population and beyond health facilities. We first present an overview of current international standards in human functioning and disability, and how chronic conditions are interconnected in older age. We then describe innovative mobile and sensor technologies, predictive data analysis in healthcare, and game-based prevention and rehabilitation techniques. We then set forth a multidisciplinary approach for the personalized prevention and rehabilitation of chronic conditions using unobtrusive and pervasive sensors, interactive activities, and predictive analytics, which also eases the tasks of health-related researchers, caregivers and providers. Our proposal represents a conceptual basis for future research, in which much remains to be done in terms of standardization of technologies and health terminology, as well as data protection and privacy legislation.

negative: An Evaluation of Parser Robustness for Ungrammatical Sentences For many NLP applications that require a parser, the sentences of interest may not be well-formed. If the parser can overlook problems such as grammar mistakes and produce a parse tree that closely resembles the correct analysis for the intended sentence, we say that the parser is robust. This paper compares the performances of eight state-of-the-art dependency parsers on two domains of ungrammatical sentences: learner English and machine translation outputs. We have developed an evaluation metric and conducted a suite of experiments. Our analyses may help practitioners to choose an appropriate parser for their tasks, and help developers to improve parser robustness against ungrammatical sentences.

negative: Microglia-mediated recovery from ALS-relevant motor neuron degeneration in a mouse model of TDP-43 proteinopathy Though motor neurons selectively degenerate in amyotrophic lateral sclerosis, other cell types are likely involved in this disease. We recently generated rNLS8 mice in which human TDP-43 (hTDP-43) pathology could be reversibly induced in neurons and expected that microglia would contribute to neurodegeneration. However, only subtle microglial changes were detected during disease in the spinal cord, despite progressive motor neuron loss; microglia still reacted to inflammatory triggers in these mice. Notably, after hTDP-43 expression was suppressed, microglia dramatically proliferated and changed their morphology and gene expression profiles. These abundant, reactive microglia selectively cleared neuronal hTDP-43. Finally, when microgliosis was blocked during the early recovery phase using PLX3397, a CSF1R and c-kit inhibitor, rNLS8 mice failed to regain full motor function, revealing an important neuroprotective role for microglia. Therefore, reactive microglia exert neuroprotective functions in this amyotrophic lateral sclerosis model, and definition of the underlying mechanism could point toward novel therapeutic strategies. Using an inducible mouse model of sporadic ALS, Spiller et al. show that spinal microgliosis is not a major feature of TDP-43-triggered disease. Instead, microglia mediate TDP-43 clearance and motor recovery, suggesting a neuroprotective role in ALS.

negative: MazeBase: A Sandbox for Learning from Games This paper introduces an environment for simple 2D maze games, designed as a sandbox for machine learning approaches to reasoning and planning. Within it, we create 10 simple games based on algorithmic tasks (e.g. embodying simple if-then statements). We deploy a range of neural models (fully connected, convolutional network, memory network) on these games, with and without a procedurally generated curriculum. We show that these architectures can be trained with reinforcement to respectable performance on these tasks, but are still far from optimal, despite their simplicity. We also apply these models to games involving combat, including StarCraft, demonstrating their ability to learn non-trivial tactics which enable them to consistently beat the in-game AI.

negative: Multilabel Text Classification for Automated Tag Suggestion The increased popularity of tagging during the last few years can be mainly attributed to its embracing by most of the recently thriving user-centric content publishing and management Web 2.0 applications. However, tagging systems have some limitations that have led researchers to develop methods that assist users in the tagging process, by automatically suggesting an appropriate set of tags. We have tried to model the automated tag suggestion problem as a multilabel text classification task in order to participate in the ECML/PKDD 2008 Discovery Challenge.

negative: Deep and Broad Learning on Content-Aware POI Recommendation POI recommendation has attracted lots of research attentions recently. There are several key factors that need to be modeled towards effective POI recommendation - POI properties, user preference and sequential momentum of check- ins. The challenge lies in how to synergistically learn multi-source heterogeneous data. Previous work tries to model multi-source information in a flat manner, using either embedding based methods or sequential prediction models in a cross-related space, which cannot generate mutually reinforce results. In this paper, a deep and broad learning approach based on a Deep Context- aware POI Recommendation (DCPR) model was proposed to structurally learn POI and user characteristics. The proposed DCPR model includes three collaborative layers, a CNN layer for POI feature mining, an RNN layer for sequential dependency and user preference modeling, and an interactive layer based on matrix factorization to jointly optimize the overall model. Experiments over three data sets demonstrate that DCPR model achieves significant improvement over state-of-the-art POI recommendation algorithms and other deep recommendation models.

negative: A taxonomy for user-healthcare robot interaction This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologies and user acceptance of robotics. Characterization of the user, or in this case the patient, is a primary focus of the paper, as they present a unique new role as robot users. While therapeutic and monitoring-related applications for robots are still relatively uncommon, we believe they will begin to grow and thus it is important that the spurring relationship between robot and patient is well understood.

negative: Multiple Physical Layer Pipes performance for DVB-T2 The DVB-T2 terrestrial television standard is becoming increasingly important, and have been extensively studied and developed to provide many types of services with higher spectral efficiency and better performance. The Physical Layer Pipes in DVB-S2 are logical channels carrying one or more services with modulation scheme and robustness. The main changes are found in the physical layer where DVB-T2 incorporates a new physical layer pipe (PLP). Each physical layer pipe contains an individual configuration of modulation, coding and interleaving. This new concept allows a transmission with multiple physical layer pipes where each service can be transmitted with different physical layer configuration. The Advanced Television Systems Committee (ATSC3.0) standard will add value to broadcasting services, allowing a extending reach by adding new business models, providing higher quality, improved accessibility, personalization and interactivity and more flexible and efficient use of the spectrum.

negative: Precision CMOS current reference with process and temperature compensation This paper presents a new first-order temperature compensated CMOS current reference. To achieve a compact architecture able to operate under low voltage with low power consumption, it is based on a self-biasing beta multiplier current generator. Compensation against temperature is achieved by using instead of an ordinary resistor two triode transistors in parallel, acting as a negative and a positive temperature coefficient resistor, that generate a proportional to absolute temperature and a complementary to absolute temperature current which can be directly added to attain a temperature compensated current. Programmability is included to adjust the temperature coefficient and the reference current magnitude over process variations. Results for a 0.18 μm CMOS implementation show that the proposed 500 nA reference operate with supplies down to 1.2 V accomplishing over a (-40 to +120°C) range temperature drifts below 120 ppm/°C.

negative: Modified post-filter to recover modulation spectrum for HMM-based speech synthesis This paper proposes a modified post-filter to recover a Modulation Spectrum (MS) in HMM-based speech synthesis. To alleviate the over-smoothing effect which is one of the major problems in HMM-based speech synthesis, the MS-based post-filter has been proposed. It recovers the utterance-level MS of the generated speech trajectory, and we have reported its benefit to the quality improvement. However, this post-filter is not applicable to various lengths of speech parameter trajectories, such as phrases or segments, which are shorter than an utterance. To address this problem, we propose two modified post-filters, (1) the time-invariant filter with a simplified conversion form and (2) the segment-level post-filter which applicable to a short-term parameter sequence. Furthermore, we also propose (3) the post-filter to recover the phoneme-level MS of HMM-state duration. Experimental results show that the modified post-filters also yield significant quality improvements in synthetic speech as yielded by the conventional post-filter.

negative: Fully convolutional network and sparsity-based dictionary learning for liver lesion detection in CT examinations

negative: TABLA: A unified template-based framework for accelerating statistical machine learning A growing number of commercial and enterprise systems increasingly rely on compute-intensive Machine Learning (ML) algorithms. While the demand for these compute-intensive applications is growing, the performance benefits from general-purpose platforms are diminishing. Field Programmable Gate Arrays (FPGAs) provide a promising path forward to accommodate the needs of machine learning algorithms and represent an intermediate point between the efficiency of ASICs and the programmability of general-purpose processors. However, acceleration with FPGAs still requires long development cycles and extensive expertise in hardware design. To tackle this challenge, instead of designing an accelerator for a machine learning algorithm, we present TABLA, a framework that generates accelerators for a class of machine learning algorithms. The key is to identify the commonalities across a wide range of machine learning algorithms and utilize this commonality to provide a high-level abstraction for programmers. TABLA leverages the insight that many learning algorithms can be expressed as a stochastic optimization problem. Therefore, learning becomes solving an optimization problem using stochastic gradient descent that minimizes an objective function over the training data. The gradient descent solver is fixed while the objective function changes for different learning algorithms. TABLA provides a template-based framework to accelerate this class of learning algorithms. Therefore, a developer can specify the learning task by only expressing the gradient of the objective function using our high-level language. Tabla then automatically generates the synthesizable implementation of the accelerator for FPGA realization using a set of hand-optimized templates. We use Tabla to generate accelerators for ten different learning tasks targeted at a Xilinx Zynq FPGA platform. We rigorously compare the benefits of FPGA acceleration to multi-core CPUs (ARM Cortex A15 and Xeon E3) and many-core GPUs (Tegra K1, GTX 650 Ti, and Tesla K40) using real hardware measurements. TABLA-generated accelerators provide 19.4x and 2.9x average speedup over the ARM and Xeon processors, respectively. These accelerators provide 17.57x, 20.2x, and 33.4x higher Performance-per-Watt in comparison to Tegra, GTX 650 Ti and Tesla, respectively. These benefits are achieved while the programmers write less than 50 lines of code.

negative:
Testing the reliability and efficiency of the pilot Mixed Methods Appraisal Tool (MMAT) for systematic mixed studies review. BACKGROUND
Systematic literature reviews identify, select, appraise, and synthesize relevant literature on a particular topic. Typically, these reviews examine primary studies based on similar methods, e.g., experimental trials. In contrast, interest in a new form of review, known as mixed studies review (MSR), which includes qualitative, quantitative, and mixed methods studies, is growing. In MSRs, reviewers appraise studies that use different methods allowing them to obtain in-depth answers to complex research questions. However, appraising the quality of studies with different methods remains challenging. To facilitate systematic MSRs, a pilot Mixed Methods Appraisal Tool (MMAT) has been developed at McGill University (a checklist and a tutorial), which can be used to concurrently appraise the methodological quality of qualitative, quantitative, and mixed methods studies.

OBJECTIVES
The purpose of the present study is to test the reliability and efficiency of a pilot version of the MMAT.

METHODS
The Center for Participatory Research at McGill conducted a systematic MSR on the benefits of Participatory Research (PR). Thirty-two PR evaluation studies were appraised by two independent reviewers using the pilot MMAT. Among these, 11 (34%) involved nurses as researchers or research partners. Appraisal time was measured to assess efficiency. Inter-rater reliability was assessed by calculating a kappa statistic based on dichotomized responses for each criterion. An appraisal score was determined for each study, which allowed the calculation of an overall intra-class correlation.

RESULTS
On average, it took 14 min to appraise a study (excluding the initial reading of articles). Agreement between reviewers was moderate to perfect with regards to MMAT criteria, and substantial with respect to the overall quality score of appraised studies.

CONCLUSION
The MMAT is unique, thus the reliability of the pilot MMAT is promising, and encourages further development.

negative: YAGO2: exploring and querying world knowledge in time, space, context, and many languages We present YAGO2, an extension of the YAGO knowledge base with focus on temporal and spatial knowledge. It is automatically built from Wikipedia, GeoNames, and WordNet, and contains nearly 10 million entities and events, as well as 80 million facts representing general world knowledge. An enhanced data representation introduces time and location as first-class citizens. The wealth of spatio-temporal information in YAGO can be explored either graphically or through a special time- and space-aware query language.

negative: Stretchable Heater Using Ligand-Exchanged Silver Nanowire Nanocomposite for Wearable Articular Thermotherapy. Thermal therapy is one of the most popular physiotherapies and it is particularly useful for treating joint injuries. Conventional devices adapted for thermal therapy including heat packs and wraps have often caused discomfort to their wearers because of their rigidity and heavy weight. In our study, we developed a soft, thin, and stretchable heater by using a nanocomposite of silver nanowires and a thermoplastic elastomer. A ligand exchange reaction enabled the formation of a highly conductive and homogeneous nanocomposite. By patterning the nanocomposite with serpentine-mesh structures, conformal lamination of devices on curvilinear joints and effective heat transfer even during motion were achieved. The combination of homogeneous conductive elastomer, stretchable design, and a custom-designed electronic band created a novel wearable system for long-term, continuous articular thermotherapy.

negative: Too Much of a Good Thing? The Relationship Between Number of Friends and Interpersonal Impressions on Facebook A central feature of the online social networking system, Facebook, is the connection to and links among friends. The sum of the number of one’s friends is a feature displayed on users’ profiles as a vestige of the friend connections a user has accrued. In contrast to offline social networks, individuals in online network systems frequently accrue friends numbering several hundred. The uncertain meaning of friend status in these systems raises questions about whether and how sociometric popularity conveys attractiveness in non-traditional, non-linear ways. An experiment examined the relationship between the number of friends a Facebook profile featured and observers’ ratings of attractiveness and extraversion. A curvilinear effect of sociometric popularity and social attractiveness emerged, as did a quartic relationship between friend count and perceived extraversion. These results suggest that an overabundance of friend connections raises doubts about Facebook users’ popularity and desirability. Zu viel des Guten? Zur Beziehung zwischen der Anzahl der Freunde und interpersonalen Eindrücken bei Facebook Eine zentrale Eigenschaft des sozialen Online-Netzwerks Facebook ist die Verbindung von Freunden. Die Gesamtanzahl der Freunde eines Nutzers wird als Merkmal im Benutzerprofil angezeigt und dient als eine Statistik der Freundeverbindungen, die ein Nutzer gesammelt hat. Im Gegensatz zu Offline-Netzwerken, haben Personen in OnlineNetzwerken oft mehrere Hundert Freunde. Die unklare Bedeutung des Freundestatus in diesem System wirft die Frage auf, ob und wie soziometrische Popularität die Attraktivität auf nicht-traditionelle, nichtlineare Weise ausdrückt. In einem Experiment wurde die Beziehung zwischen der Anzahl der Freunde im Facebook-Profil und der Einschätzung von Attraktivität und Extraversion durch den Beobachter untersucht. Es zeigten sich ein kurvilinearer Effekt von soziometrischer Popularität und sozialer Attraktivität, sowie eine biquatratische Beziehung zwischen der Anzahl der Freunde und wahrgenommener Extraversion. Diese Ergebnisse deuten an, dass eine übermäßig hohe Zahl an Freunden Zweifel an der Popularität und Attraktivität des Facebook-Nutzers

negative: Social collaborative filtering for cold-start recommendations We examine the cold-start recommendation task in an online retail setting for users who have not yet purchased (or interacted in a meaningful way with) any available items but who have granted access to limited side information, such as basic demographic data (gender, age, location) or social network information (Facebook friends or page likes). We formalize neighborhood-based methods for cold-start collaborative filtering in a generalized matrix algebra framework that does not require purchase data for target users when their side information is available. In real-data experiments with 30,000 users who purchased 80,000+ books and had 9,000,000+ Facebook friends and 6,000,000+ page likes, we show that using Facebook page likes for cold-start recommendation yields up to a 3-fold improvement in mean average precision (mAP) and up to 6-fold improvements in Precision@k and Recall@k compared to most-popular-item, demographic, and Facebook friend cold-start recommenders. These results demonstrate the substantial predictive power of social network content, and its significant utility in a challenging problem - recommendation for cold-start users.

negative: The Use of Alternative Social Networking Sites in Higher Educational Settings: A Case Study of the E-Learning Benefits of Ning in Education Distance education as a primary means of instruction is expanding significantly at the college and university level. Simultaneously, the growth of social networking sites (SNS) including Facebook, LinkedIn, and MySpace is also rising among today’s college students. An increasing number of higher education instructors are beginning to combine distance education delivery with SNSs. However, there is currently little research detailing the educational benefits associated with the use of SNSs. Non-commercial, education-based SNSs, such as Ning in Education, have been recently shown to build communities of practice and facilitate social presence for students enrolled in distance education courses. In order to evaluate the largely unexplored educational benefits of SNSs, we surveyed graduate students enrolled in distance education courses using Ning in Education, an education-based SNS, based on their attitudes toward SNSs as productive online tools for teaching and learning. The results of our study suggest that education-based SNSs can be used most effectively in distance education courses as a technological tool for improved online communications among students in higher distance education courses. Introduction The use of distance education courses as a primary instructional delivery option, especially in the higher education community, is expanding at an unprecedented rate. The 9.7% growth rate in the number of college and university students enrolled in at least one online class reported by Allen and Seaman (2007) significantly exceeded the 1.5% growth rate in the overall higher education student population during the same period. Simultaneously, the emergence and growth of commercial social networking sites (SNSs) such as Facebook, Friendster, LinkedIn, LiveJournal, and MySpace has been extensive and widespread (Boyd & Ellison, 2007). Facebook, for example, is currently the fastest growing commercial SNS in the world, with more than 300 million active user profiles (Facebook, 2009). Given the rising popularity of both distance education and SNSs, it seems logical to merge these popular two technologies with the goal of improving online teaching and learning (National School Boards Association [NSBA], 2007; University of Minnesota, 2008). Research has shown that distance education courses are often more successful when they develop communities of practice (Barab & Duffy, 2000; Journal of Interactive Online Learning Brady, Holcomb, and Smith 152 DeSchryver, Mishra, Koehler, & Francis, 2009) as well as encourage high levels of online social presence among students (Anderson, 2005). Fostering a sense of community is critically important, especially in an online environment where students often do not get the opportunity to meet face-to-face with other students or the instructor in the course. Since they facilitate the sharing of information—personal and otherwise—the technologies used in SNSs aid discussion and create intimacy among online students, as they have they ability to connect and build community in a socially and educationally constructed network (Educause Learning Initiative [ELI], 2007). In contrast to SNS, course management systems (CMS), such as Blackboard and Moodle, tend to be very focused and lack the personal touch and networking capacity that SNSs offer. For example, instructors using CMS may pose a question in an online discussion board and each student posts a response. However, these student posts are really not interactions at all, but merely question and answer sessions. Using an SNS that is user centered, rather than class centered, such as a CMS, has the potential to increase student engagement. SNSs can actively encourage online community building, extending learning beyond the boundaries of the classroom (Smith, 2009). A comparison of typical SNS and a traditional CMS appears in Table 1.

negative: Users of the world , unite ! The challenges and opportunities of Social Media As of January 2009, the online social networking application Facebook registered more than 175 million active users. To put that number in perspective, this is only slightly less than the population of Brazil (190 million) and over twice the population of Germany (80 million)! At the same time, every minute, 10 hours of content were uploaded to the video sharing platform YouTube. And, the image hosting site Flickr provided access to over 3 billion photographs, making the world-famous Louvre Museum’s collection of 300,000 objects seem tiny in comparison. According to Forrester Research, 75% of Internet surfers used ‘‘Social Media’’ in the second quarter of 2008 by joining social networks, reading blogs, or contributing reviews to shopping sites; this represents a significant rise from 56% in 2007. The growth is not limited to teenagers, either; members of Generation X, now 35—44 years old, increasingly populate the ranks of joiners, spectators, and critics. It is therefore reasonable to say that Social Media represent a revolutionary new trend that should be of interest to companies operating in online space–—or any space, for that matter. Yet, not overly many firms seem to act comfortably in a world where consumers can speak so freely Business Horizons (2010) 53, 59—68

negative: Using the Facebook group as a learning management system: An exploratory study Facebook is a popular social networking site. It, like many other new technologies, has potential for teaching and learning because of its unique built-in functions that offer pedagogical, social and technological affordances. In this study, the Facebook group was used as a learning management system (LMS) in two courses for putting up announcements, sharing resources, organizing weekly tutorials and conducting online discussions at a teacher education institute in Singapore. This study explores using the Facebook group as an LMS and the students’ perceptions of using it in their courses. Results showed that students were basically satisfied with the affordances of Facebook as the fundamental functions of an LMS could be easily implemented in the Facebook group. However, using the Facebook group as an LMS has certain limitations. It did not support other format files to be uploaded directly, and the discussion was not organized in a threaded structure. Also, the students did not feel safe and comfortable as their privacy might be revealed. Constraints of using the Facebook group as an LMS, implications for practice and limitations of this study are discussed. Practitioner notes What is already known about this topic • Facebook has been popularly used by tertiary students, but many students do not want their teachers to be friends on Facebook • Teacher’s self-disclosure on Facebook can promote classroom atmosphere, teacher’s credibility and student–teacher relationship • Commercial learning management systems (LMSs) have limitations What this paper adds • The Facebook group can be used an LMS as it has certain pedagogical, social and technological affordances • Students are satisfied with the way of using the Facebook group as an LMS British Journal of Educational Technology (2011) doi:10.1111/j.1467-8535.2011.01195.x © 2011 The Authors. British Journal of Educational Technology © 2011 Bera. Published by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA. • Younger students are more acceptable with the idea of using the Facebook group as an LMS • Using the Facebook group as an LMS has limitations: it does not support other format files; its discussions are not listed in threads; and it is not perceived as a safe environment Implications for practice and/or policy • The Facebook group can be used an LMS substitute or supplement • Third-party applications are needed to extend the capability of the Facebook group as an LMS • Using Facebook seems to be more appropriate for young learners than adults • Teachers do not have to be students’ friends on Facebook. Introduction Social networking sites (SNSs) are virtual spaces where people of similar interest gather to communicate, share photos and discuss ideas with one another (Boyd & Ellison, 2008; Raacke & Bonds-Raacke, 2008). In recent years, Facebook has become one of the most prominent SNSs. Like any new technology, Facebook seems to offer great potentials for teaching and learning as many students are using Facebook daily. One possible way of using Facebook for teaching and learning is to use its group as an LMS. Research shows that using LMSs possesses numerous benefits for teaching and learning. It enables faculty to shift the focus from content-based learning to process-based learning (Vogel & Klassen, 2001) and helps to “facilitate change from passive to active learning” (Herse & Lee, 2005, p. 51). Using LMSs also has the potential to increase student enrollment (Nunes & McPherson, 2003) and to promote interaction between students and faculty members (Lonn & Teasley, 2009; West, Waddoups & Graham, 2007). Using existing commercial LMSs like Blackboard, however, often has practical constraints (Sanchez-Franco, 2010). For example, LMSs tend to be expensive and that not every school can afford to purchase and maintain them over the long run. Trainee teachers cannot access certain features such as creating a course, enrolling students and setting up student groups as these functions are usually open to instructors or administrators only. The resources in the present LMS are often no longer accessible to trainee teachers after their graduation. Also, the LMS used at school in the future may be different from the one being currently used. They have to shift to a new LMS, and research shows learning a new system is often a painful experience (Black, Beck, Dawson, Jinks & DiPietro, 2007). If the Facebook group can be used as an alternative LMS, it would help to overcome some of the abovementioned constraints. For instance, it would enable a teacher to easily create a new course and enroll students in person if the class size is small. As presented in the following literature review section, many research studies have investigated the usage of Facebook, the effect of teacher’s self-disclosure via Facebook on teacher–student relationship improvement and the academic performance of Facebook users. However, few studies have examined if and how Facebook can be effectively used as an LMS. In this exploratory study, the Facebook group was used as an LMS to put up announcements, share resources, organize weekly tutorial sessions and conduct online discussions. The purpose of this paper is to describe how the Facebook group was used as an LMS in the study and to report students’ perceptions on it. Literature review on Facebook

negative:
Exposure of Children and Adolescents to Alcohol Marketing on Social Media Websites AIMS
In 2011, online marketing became the largest marketing channel in the UK, overtaking television for the first time. This study aimed to describe the exposure of children and young adults to alcohol marketing on social media websites in the UK.

METHODS
We used commercially available data on the three most used social media websites among young people in the UK, from December 2010 to May 2011. We analysed by age (6-14 years; 15-24 years) and gender the reach (proportion of internet users who used the site in each month) and impressions (number of individual pages viewed on the site in each month) for Facebook, YouTube and Twitter. We further analysed case studies of five alcohol brands to assess the marketer-generated brand content available on Facebook, YouTube and Twitter in February and March 2012.

RESULTS
Facebook was the social media site with the highest reach, with an average monthly reach of 89% of males and 91% of females aged 15-24. YouTube had a similar average monthly reach while Twitter had a considerably lower usage in the age groups studied. All five of the alcohol brands studied maintained a Facebook page, Twitter page and YouTube channel, with varying levels of user engagement. Facebook pages could not be accessed by an under-18 user, but in most cases YouTube content and Twitter content could be accessed by those of all ages.

CONCLUSION
The rise in online marketing of alcohol and the high use of social media websites by young people suggests that this is an area requiring further monitoring and regulation.

negative: Successful failure: what Foucault can teach us about privacy self-management in a world of Facebook and big data The “privacy paradox” refers to the discrepancy between the concern individuals express for their privacy and the apparently low value they actually assign to it when they readily trade personal information for low-value goods online. In this paper, I argue that the privacy paradox masks a more important paradox: the self-management model of privacy embedded in notice-and-consent pages on websites and other, analogous practices can be readily shown to underprotect privacy, even in the economic terms favored by its advocates. The real question, then, is why privacy self-management occupies such a prominent position in privacy law and regulation. Borrowing from Foucault’s late writings, I argue that this failure to protect privacy is also a success in ethical subject formation, as it actively pushes privacy norms and practices in a neoliberal direction. In other words, privacy self-management isn’t about protecting people’s privacy; it’s about inculcating the idea that privacy is an individual, commodified good that can be traded for other market goods. Along the way, the self-management regime forces privacy into the market, obstructs the functioning of other, more social, understandings of privacy, and occludes the various ways that individuals attempt to resist adopting the market-based view of themselves and their privacy. Throughout, I use the analytics practices of Facebook and social networking sites as a sustained case study of the point.