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Advanced Life Sciences has entered into a CRADA with The Walter Reed Army Institute of Research that allows the latter to perform advanced animal efficacy testing of Restanza (cethromycin) against the various species of Plasmodium that cause malaria.
Preliminary in vitro and in vivo studies have been conducted to test the efficacy of Restanza against different types of malaria-causing Plasmodium. The drug shows two- to ten-fold greater efficacy against Plasmodium falciparum, with the IC50 and IC90 levels, respectively, ranging from 0.2 to 2.7 and 0.6 to 6.2 ug/mL, regardless of chloroquine susceptibility, according to Advanced Life Sciences. In the in vivo study, Restanza has shown 100% efficacy in treating mice infected with Plasmodium berghei and is approximately three times more potent than azithromycin at half of the same dose.
"Developing new treatments for malaria is a high-priority for the U.S. military because of malaria's global prevalence, debilitating nature, potential lethality, and tendency to become resistant to current drugs," says Michael T. Flavin, CEO of Advanced Life Sciences. "We share the U.S. Army's mission to protecting our troops in the field with novel therapies that can combat infectious diseases such as malaria."
Restanza is a once-a-day, oral antibiotic that is in late-stage development for the treatment of adults with mild-to-moderate community-acquired pneumonia and biodefense pathogens. Tests have shown higher in vitro potency and a broader range of activity than macrolides against Gram-positive bacteria associated with respiratory tract infections, according to Advanced Life Sciences. The drug also appears to be effective against penicillin-, macrolide-, and flouroquinolone-resistant bacteria.
Restanza is also being investigated for the prophylactic treatment of inhalation anthrax postexposure and other high-priority biodefense pathogens including plague and tularemia.
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While Zika continues to garner a lot of news coverage, a Mayo Clinic survey reveals that Americans believe the country's most significant healthcare challenge is cancer. Compared to other diseases, does the possibility of developing cancer worry you the most?
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|Publication number
|Publication type
|Application number
|Publication date
|Jul 19, 1994
|Filing date
|Feb 11, 1993
|Priority date
|Mar 5, 1991
|Fee status
|Also published as
|Publication number
|Richard G. Stafford, daniel J. Mickewich, Jacob Beutel
|Original Assignee
|E. I. Du Pont De Nemours And Company
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (12), Non-Patent Citations (14), Referenced by (138), Classifications (35), Legal Events (10)
|External Links: USPTO, USPTO Assignment, Espacenet
This application is a continuation-in-part of application Ser. No. 07/664,906, filed Mar. 5, 1991, now abandoned.
1. Field of the Invention
The present invention relates to the computer-aided analysis of digitized images and, in particular, to the location of possible anomalies in medical diagnostic and/or industrial images.
2. Description of the Related Art
It has become an established and wide-spread medical practice to perform mammograms to determine the possible presence of breast cancer or other pathological conditions. The amount of time spent by health care professionals in scanning a large number of screening exam images tends to be very short and statistics indicate that diagnostic accuracy may suffer. Also, some features of these radiological images are such that their significance can only be recognized by specialized experts.
While diagnostic uncertainty may not exist in those instances in which a tumor or cancerous tissue is well developed and, thus, clearly visible to all, it will be appreciated that in the very early stages of the development of such tissue abnormalities, a reliable diagnosis based upon a brief examination of radiological images is much more difficult. Yet early diagnosis is a very important factor in arresting and effectively treating cancerous tissues and tissues which exhibit conditions precursory to cancer, particularly breast cancer.
In addition to the benefits of early determination of pathology in medical diagnostic images, such as mammograms, many types of defects in industrial images must also be detected during product manufacture to prevent catastrophic failure, e.g. in airplane turbine blades. Many types of anomalies in industrial materials have been identified and classified by computer analysis of an X-ray image. For example, in some cases, metal cracks or incomplete welds have precisely identifiable characteristics which may be programmed into a standard algorithmic computer for automated analysis. However, in most cases they cannot. Still other types of defects, such as corrosion pits and delaminations in honeycombed or layered materials, are even more difficult to characterize due to their variety of manifestations.
Both the medical diagnostic images and the latter variety of industrial x-ray images are not easily and simply classifiable and do not lend themselves to precise programmable characterizations, such as an expert system, Conventional algorithmic computers excel in applications where the knowledge can be readily represented by means of an explicit set of rules, e.g. a decision tree. Where this is not the case, conventional computers encounter difficulty. While conventional computers can execute an algorithm much more rapidly than any human, they are challenged to match human performance in nonalgorithmic tasks such as visual pattern recognition.
However, parallel distributed processing networks, also known as "neural networks", have been shown to be useful in recognizing patterns in a number of applications involving multiple variables whose precise interactions are not well-understood or quantifiable.
In contrast to algorithmic computer systems (including so-called "expert systems"), a neural net computing system is not formulated to exhibit an explicit algorithm or a set of explicit rules. Instead, a neural network is "trained" to recognize patterns in input data by an iterative adjustment of the connection weights associated with each processing element. These connection weights are adjusted to minimize a preselected output error function. This adjustment of the weights may be accomplished by various well-known techniques.
In traditional image analysis (and/or processing), background subtraction and image normalization have been used to obtain better image resolution with reduced noise. However, when at least some of the areas of interest in the data are sufficiently close to the noise, removal of background from the entire image and subsequent normalization may not satisfactorily distinguish such data from the overall noise. There is thus a need in image analysis for an improvement in the separation of various areas of interest from the effects of overall noise in the image.
The present invention employs analysis by a parallel distributed processing system to accurately provide information about the location of possible anomalies in medical diagnostic and industrial images.
The invention is more particularly described as a method for computer-aided detection of possible anomalies in a digitized image comprising a plurality of M×N picture elements each representing an optical density in the digitized image, the method comprising the steps of:
a) subdividing the digitized image into a plurality of predetermined regions each comprising m×n picture elements, where m<M and n<N;
b) subtracting background from each predetermined region of the digitized image;
c) selecting a subregion comprising p×q picture elements, where p<m and q<n;
d) normalizing the image data from the p×q subregion;
e) using a neural network system, analyzing each predetermined subregion of the digitized image to recognize any pattern indicative of an occurrence of a possible anomaly, the neural network system comprising at least two member neural networks each trained to recognize a particular preselected anomaly-type of a preselected size and to produce an output signal value indicative of the presence of said preselected anomaly type;
f) comparing the output values of each of the member neural networks to a first predetermined threshold value above which the presence of a possible anomaly is indicated;
g) comparing the output values that exceed the first threshold(s) to select the maximum signal value;
h) comparing the maximum signal value to a second predetermined threshold value above which the presence of a possible anomaly is indicated;
i) based upon these comparisons, determining the location within the digitized image of each possible anomaly;
j) using a clustering analysis, identifying each vicinity on the digitized image at which a cluster of locations of possible anomalies occurs; and,
k) marking the location on an original image corresponding to the digitized locations of the clusters.
The invention will be more fully understood from the following detailed description thereof, taken in connection with the accompanying drawings, which form a part of this application and in which:
FIG. 1 represents a block diagram of the overall process in accordance with the present invention;
FIG. 2 is a more detailed block diagram of the analysis executed by a digital computer operating in accordance with a program in accordance with the present invention;
FIG. 3A is a plot of optical density values versus distance along a line Z--Z in the digitized image of FIG. 2, while FIG. 3B is a representation of the plot of FIG. 3A following background subtraction.
Throughout the following detailed description, similar reference numerals refer to similar elements in all Figures of the drawings.
The present invention, illustrated by an overall block in FIG. 1, relates to a method of computer-aided analysis of an analog image 2 to determine the presence of anomalies therein. The anomalies are indicted by the reference character A. Although the analog image 2 is indicated as an x-ray film containing a medical diagnostic image such as a mammogram, it should be understood that the invention may be used with any form of medical diagnostic image containing possible pathologies, such as X-ray images, computerized axial tomography (CAT) scans, positron emission tomography (PET) scans, magnetic resonance images (MRIs), and sonogram images. In addition, the invention may be applied to detect defects in various industrial images, such as radiographs or sonogram images of parts, equipment, and/or welds. It is noted that, as used herein, the term "anomaly(ies)" is meant to encompass within it the terms "pathology(ies)" and "defect(s)".
As a first step the analog image 2 is raster-scanned and digitized by a digitizing apparatus 4, such as a scanning laser digitizer 4. The resultant digitized output image 2' from the digitizer 4 comprises a matrix of M rows by N columns (M×N) of adjacent individual picture elements ("pixels"). In a typical medical diagnostic application of the invention the digitized image comprises a matrix on the order of four thousand by four thousand five hundred (4000×4500) pixels. Each element in the M×N matrix is an optical density value.
Scanned pixel sizes generally range in size from ten micrometers (10 μm)to two hundred micrometers (200 μm). For medical images, such as a mammogram, the scanning aperture of the digitizer 4 is chosen to produce pixels on the order of thirty micrometers (30 μm) to seventy micrometers (70 μm), and more preferably, fifty micrometers (50 μm).
In medical or industrial applications where an image 2' may pre-exist in a digital format, as in the case of some digital modalities such as PET scans, CAT scans, MRIs and sonograms, scanning to digitize the image is not required.
The digitized image 2' from the digitizer 4 is submitted for image analysisto a digital computer 10 operating in accordance with this invention. The digitized image 2' may be stored temporarily in a memory buffer in the digitizer 4 and then transferred to the memory of the computer 10 or may be immediately transferred and stored in the memory of computer 10. The digitized image 2' is stored as an M×N matrix of optical density values representing the sampled adjacent pixel locations in the image 2'.
A more detailed block diagram of the analysis steps executed within the computer 10 is shown in FIG. 2. For analysis purposes the digitized image 2' from the digitizer 4 is subdivided into a predetermined number of regions, each of which contains a matrix of m rows by n columns (m×n), where m<M and n<N. In the preferred embodiment, the matrix defining each region of the image is on the order of sixty four by sixty four (64×64) pixels.
In the preferred case, as is suggested in FIG. 2, each matrix representing a region of the overall digitized image 2' may be envisioned as being generated as the result of the raster scan of an m×n (64×64) pixel "window" 12 moving across the digitized image 2'. Starting from the upper left hand comer of the image 2' the window 12 may be horizontally incremented across the image 2' by any convenient predetermined number of pixels. Preferably, the window 12 is incremented one pixel at a time. Similarly, at the end of each horizontal scan, the window 12 is verticallyincremented by any convenient predetermined number of pixels (again, preferably, one pixel at a time).
In some instances, to minimize the digital computational requirements and the analysis time required for interpretation, the original digitized image is subjected to segmentation analysis to identify the image within the window. The output of this process is the set of pixel coordinates defining the boundary of the image which determines the region of interestfor further image processing. Raster scanning is then performed only over the region of interest defined by the segmentation analysis process.
Each subdivided region of the image 2' as defined by the window 12 is preprocessed in preparation for analysis, as generally indicated by the block 14. In one aspect image preprocessing 14 includes background subtraction, as indicated at 16. Another aspect of image preprocessing is a two-stage normalization, as indicated at 18.
After image preprocessing, image analysis is performed using a parallel distributed processing system ("neural network system") 20 comprised of a plurality of at least two, or more, trained member parallel distributed processing networks 22 ("neural networks").
Background subtraction is performed to narrow the range of optical density information that must be analyzed. As seen in FIG. 2, one region of the image 2' as defined by the matrix window 12 is shown to contain an anomalyA. FIG. 3A is a plot of the optical density values versus distance along the line Z--Z extending through the window with the anomaly A therein. Sections 50 and 54 of the plot of FIG. 3A show a gradual decrease in optical density readings across the window 12. Section 52 of the plot represents a significant change in optical density due to the presence of the anomaly A. After background subtraction, as seen in FIG. 3B, sections 50' and 54' respectively represent the leading and trailing sections 50, 54 of the original plot (FIG. 3A), while section 52' represents the optical density difference of the anomaly A.
Any one of a number of ways of background subtraction from a data sample known in the art may be used. For example, the "least squares" approach may be used.
For each pixel position in the region defined by the window 12 a plane is fitted by a least-squares algorithm to all of the pixels within the window:
Di,j =a0 +a1 i+a2 j
where D:bari,j is the estimated pixel value at the position (i,j) in the sixty-four by sixty-four pixel window 12 and the coefficients (a0, a1, a2) are obtained by least-squares fitting. The estimated planar fit is then subtracted from the original pixel value in the upper left hand pixel closest to the window center:
ΔDi,j =Di,j -Di,j
where Di,j is the original pixel value at (i,j). The resultant pixel value (optical density difference, ΔDi,j) is then stored in a secondary image at its respective coordinates.
Through use of the least squares plane the background may be subtracted from the original optical density values of matrix window 12.
In the preferred embodiment, the area of the anomaly A should be significantly smaller than the area of the region of the image 2' defined by the window 12. For example, a window 12 may be sized so that the largest pathology or defect examined would be perhaps a factor of ten times smaller than the window 12. In such a case most of the pixels are associated with the, background. Thus, in effect, a high-pass spatial frequency filtering operation is performed. When the least squares plane is subtracted, the optical density values in the region of interest increase in proportion to the background optical density values and, thereby, the signal to noise ratio is improved (FIG. 3B).
Following background subtraction a subregion 12' of p×q pixels, wherep<m and q<n, is selected from within the m×n region 12, preferably from the center thereof. In the preferred case subregion 12' is on the order of sixteen by sixteen pixels. As indicated at 18 in FIG. 2, a two-stage normalization operation is then performed on the pixels in the subregion 12',
The first normalization stage is a scale invariance transformation 18A. When imaged, a specific anomaly will exhibit quantitatively different spatial optical density profiles depending on different exposure conditions, film sensitivities, and film sensitometries. To reduce the computational classification requirements for pattern recognition of suspect anomalies, a normalization procedure is required for identifying anomalies of the same type, regardless of image capture conditions. In addition, even if the exposure conditions, film sensitivities, and film sensitometries are the same, there are classes of anomalies that exhibit different optical density profiles, which, after undergoing a linear transformation, will exhibit the same normalized spatial profile. Again itis advantageous to consider such anomalies as belonging to the same class. A straightforward method for performing this classification normalization is by transforming the vector quantized image onto a unit sphere in n-dimensional pixel space for each p×q window to be analyzed for thepresence of an anomaly. A specific anomaly shape class is then recognized by its phase angle in this normalized n-dimensional space.
The high-pass filter image undergoes a second raster scan using the smallerp×q window 12'. Using a fifty micrometer (50 μm) pixel scanning aperture diameter this smaller (16×16) pixel window 12' is sufficient to allow anomalies of approximately fifty to two hundred fifty micrometers (50-250 μm) diameter to be recognized. The upper left hand pixel nearest the center of the window is again tagged. All of the pixels within this window are assumed to form an orthogonal vector space of two hundred fifty six (256) dimensions, where each dimension represents the range of possible preprocessed optical densities (ΔDi,j values)for its respective pixel. All pixel values within the window are linearly transformed to fit the normalized range of zero to one: ##EQU1##where θi,j is the direction arccosine of the normalized pixel value at (i,j). The spatial shape of an object within the original window is now encoded as a phase angle vector, θ, within this 256-dimensional vector space and the tip of each vector representing an object lies on a unit sphere.
The second normalization stage 18B is a dynamic range normalization, wherein the set of transformed optical density difference values of the subregion 12' are normalized to fit the input dynamic range of each memberneural network 22 in the neural network system 20. For example, if the functions employed in any hidden and output layers of the member neural networks yield values within the ranges of - 1.0 to + 1.0, the valises at the input layer should be normalized to fit within this range.
It should be noted that both the background subtraction 16 (performed on the region 12) and the two-stage normalization (18 performed on the subregion 12') are local to each predetermined region or subregion, as thecase may be. Since background subtraction 16 and two-stage normalization 18are performed locally, small changes within each region or subregion are not masked or hidden by the overall noise characteristics of the image 2'.
The actual anomaly recognition is performed using the neural network system20 comprised of a plurality of at least two trained member neural networks 22A through 22N. Each member neural network 22A through 22N is, in the preferred instance, a feedforward neural network having at least three layers, an input layer 23I, an intermediate or "hidden" layer 23H, and an output layer 23L. Each node in each layer is connected through connection weights to every node in an adjoining layer. A three-layer neural network is the minimum network topology required to obtain an arbitrary nonlinear mapping of input to output. Each input and hidden layer 24I and 24H, respectively, in each member neural network 22A through 22N is comprised of a plurality of nodes. Each output layer 24L in each member neural network 22A through 22N is comprised of one or more nodes. Each member neural network 2A through 22N should be fully connected.
Each node, or processing element, in the input layer has, as its input, a stored digital value representing the preprocessed values of each element in the subregion 12'. Each node in each succeeding layer has as its input the signal present at the output of the nodes of an adjoining layer, as multiplied by their associated connection weights. Each node has a constant bias input, or offset, value which is multiplied by its own weighting factor. The inputs to each node are summed and scaled by a nonlinear transformation to produce an output signal value. In the preferred case the hyperbolic tangent function, whose output range is - 1 to + 1, is employed as the nonlinear function. The topology,structure, and organization of a three-layer neural network is fully discussed in U.S. Pat. No. 5,046,020 (Filkin), which is hereby incorporated by reference.
Each member neural network 22A through 22N is trained to recognize a particular anomaly type and/or size. For example, in the analysis of mammograms, a subsystem comprising one or more member neural network(s) 22detects a first anomaly type, such as a microcalcification, while a second subsystem comprising one or more other member neural network(s) may be trained to recognize a second anomaly type, such as a lesion. Furthermore,each subsystem of member neural networks 22 may detect a given type of anomaly whose size falls within particular predetermined size ranges, e.g.fifty (50 μm) to one hundred micrometers (100 μm), one hundred micrometers (100 μm) to one hundred fifty micrometers (150 μm), etc.Such a grouping of member neural networks to detect various sizes of an anomaly of a given type provides a measure of redundancy in detecting thatparticular anomaly type and, thereby, adds significantly to the accuracy ofthe results.
Training may be accomplished using the back propagation paradigm as discussed in "Parallel Distributed Processing", D. E. Rumelhart, G. E. Hinton, and R. J. Williams, Volume 1, Chapter 8, "Learning Internal Representations by Error Propagation", Bradford Books, 1986. The software package ANSim, version 2.30 (©1988, Science Applications International Corporation, San Diego, Calif.), may be employed for this purpose. Alternately, the training method disclosed in U.S. Pat. No. 5,046,020 (Filkin), assigned to the assignee of the present invention, wherein the connection weights are generated using stiff differential equations may be used.
As is well understood by those skilled in the art, training of each member neural network uses a "training set" containing an adequate sampling of digitized images of regions of analog images that either manifest an anomaly of interest or that are anomaly-free. A record is kept correlatingthe digitized sample images to their location in the original analog images. In addition, in the preferred embodiment, a value is stored with each training sample to indicate whether an anomaly is present (e.g. +1.0)or to indicate that a window is anomaly-free (e.g. -1.0).
As the neural network is interpolative in nature, its level of accuracy when in ultimate use depends in large part on whether the data used in training the member neural networks is a statistically significant representative sampling. Some of the factors to consider in selecting a statistically significant number of samples to adequately train a member neural network to identify a particular anomaly include the type of anomaly, the variation in characteristics of the anomaly, the size of the neural network (number of weights, number of layers, number of nodes), andthe noise in the analog images. However chosen, the number of samples in a training set must be a statistically significant number of samples having a particular characteristic (e.g. size, shape, intensity profile, etc.) topresent to a neural network to allow it be adequately trained. "Adequate training" means trained to recognize an anomaly within a user-defined accuracy. Each neural network is separately trained to identify a predetermined size range of a predetermined type of anomaly, with all other member neural networks de-activated, so that a given member network will respond most strongly only when the characteristics that it has elicited from its training set are present in an image outside the training set.
The iterative process through which initial weight values are incrementallychanged until the error in the output of the network ceases to be reduced significantly (i.e., a local minimum is reached) is discussed in the above-referenced U.S. Pat. No. 5,046,020 (Filkin) and need not be repeatedhere.
Once a member neural network is trained, testing of each member neural network must be undertaken to determine if the local minimum produced through training will satisfy desired accuracy requirements for anomaly identification. Testing will determine if further training of the various member neural networks is required.
As indicated in FIG. 2 at block 24, the output signal values of each memberneural network is compared to a first predetermined anomaly threshold valueabove which the presence of a possible anomaly of the given type is indicated. Also, a user may define separate anomaly threshold values for each member neural network. Alternatively, a single threshold value may bedefined to which the outputs of all member neural networks are compared.
Those output signal values exceeding the first threshold value(s) are compared to each other by a winner-take-all (WTA) algorithm 26 to select the maximum signal value. The output value selected by the WTA algorithm 26 is compared to a second predetermined threshold, above which the presence of a possible anomaly of the given type is also indicated. The comparison to the second threshold is shown in FIG. 2 at block 28. Depending upon the magnitude of the second threshold value the output of the thresholded WTA 26 may detect a fraction of image features which do not actually represent anomalies ("false positives") or may fail to detecta fraction of image features which do actually represent anomalies ("false negatives"). The second threshold must be larger than or equal to the minimum value of the first threshold(s).
In assigning either of the thresholds 24 or 28 it should be noted that the lower its value, the higher is the number of false positives. Conversely, the higher the threshold values the greater the possibility of yielding false negatives. For example, given an output range of -1.0 to +1.0, a user may set the threshold for detecting a particular anomaly at +0.3. If the single value from the WTA algorithm 26 exceeds +0.3, a particular anomaly type may be present within subregion 12', e. g., 95% of the time. That is, in 95% of cases a physician's diagnosis will agree that the neural network detected a particular pathology. If greater accuracy is needed, the threshold level may be adjusted higher, e.g. to +0.4, during network training to achieve, say, 98% accuracy. However, the false negative rate will also increase. That is, a number of actual pathologies having presented output signal values between +0.3 and +0.4 will now remain undetected at the higher threshold value.
As indicated at block 30 in FIG. 2 if an anomaly is detected the location within the subregion 12' containing the anomaly is recorded for future analysis. In the preferred embodiment, the location of the subregion 12' is defined by the coordinates of the pixel in the upper left hand corner.
Each scan of the regions of the image defined by the stepwise raster scanning of the window 12 is analyzed in the manner discussed until eitherthe entire digital image or the region of interest defined by the segmentation process has been examined. After the entire image has been thus analyzed by the neural network system, the coordinates of all detected possible anomalies are transmitted to block 32 for further analysis. For instance, a two-stage clustering analysis algorithm may be applied which detects the presence of a predetermined number (e.g., more than three) of possible anomalies within a predetermined radius.
The two-stages of the clustering analysis include microclustering binding and macroclustering binding. Microclustering binding of the thresholded image is required to remove multiple counts of the same anomaly. Since thenonlinear convolution transform in the second scan involved the p×q (16×16) window 12', microclustering requires a third image raster scan with the same window size. All locations in which an anomaly occurs within the window are interpreted as belonging to the same anomaly. A final map is then generated, representing the location of all recognized individual anomalies in the image.
The interpretive significance of anomalies within the image 2 depends on many factors, but one of primary significance is related to the number of anomalies within an area of specified size. Macroclustering accepts the possibility of an anomaly when at least four positive events are detected within a diameter of approximately one centimeter. This filtering operation eliminates single anomalous events due to highly localized film defects and questionable interpretations of events associated with the detection of anomaly sizes at the minimum spatial resolution of the film digitizing system.
The final scan of the image with this macroclustering criterion generates the final map representing regions of interest in which possible anomalieshave been detected. Due to the stochastic distribution of anomaly occurrences within a specific image 2 the boundary lines enclosing these regions of interest can be irregular and can extend beyond the one centimeter diameter threshold.
With reference again to FIG. 1, if at least one cluster of anomalies is detected a signal is sent to a printer 36. The printer 36 produces a transparency overlay sheet 38 containing at least one marker 40 which, when superimposed upon the original image 2, calls a viewer's attention tothe location of possible anomalies. In the preferred embodiment the marker 40 takes the form of a closed contour centered on the location of an anomaly. The positioning of the closed contour may be accomplished by a conventional center of mass technique.
If the analog image is digitized from a video signal, markers may be placedon an overlay transparency or a superimposable graphics layer to indicate the positions of suspected abnormalities on the video monitor displaying the original video image.
However, if the user is unable to achieve specified percentages of true positives and false positives from iterative training of the neural network, it may be necessary to select different initial weights, e.g. by choosing a new random weight vector. One might also increase the number ofhidden layers to reduce the error percentage or increase the number of nodes in the hidden layer to further reduce the error.
An adequately trained neural network comprises a set of trained weights which meet the specified requirements for the incidence of false positivesand false negatives.
Those skilled in the art, having the benefit of the teachings of the present invention as hereinbefore set forth, may effect numerous modifications thereto. Such modifications are to be construed as lying within the contemplation of the present invention, as defined by the appended claims.
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|Jun 29, 1993
Owner name: E.I. DU PONT DE NEMOURS AND COMPANY, DELAWARE
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Owner name: TEXAS COMMERCE BANK NATIONAL ASSOCIATION, TEXAS
Free format text: SECURITY INTEREST;ASSIGNOR:STERLING DIAGNOSTIC IMAGING, INC.;REEL/FRAME:007919/0405
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Free format text: SECURITY AGREEMENT;ASSIGNOR:STERLING DIAGNOSTIC IMAGING, INC.;REEL/FRAME:008698/0513
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|Maintenance fee reminder mailed
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Travaasa's entire mission is to promote the health and well-being of guests, which is why their Hawaiian property, Travaasa Hana, has such a diverse fitness and activities schedule, including morning restorative yoga, coastal walking and stretching courses, pilates, hula, and meditation. Guests can also take advantage of the healthy and seasonal fare on offer, including a huge selection of vegetarian dishes and a few indulgences like an impressive wine list and Hawaiian cocktails.
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Promotions android App based on a Joomla / MySQL website
This project received 22 bids from talented freelancers with an average bid price of $767 USD.Get free quotes for a project like this
Skills Required
Project Budget$250 - $750 USD
Total Bids22
Project Description
We are looking for a freelancer to help develop an Android application for local promotions that fetches data from a Joomla/MySQL based website.
The following features are required.
Arabic and English (RTL and LTR interface)
Facebook connect: Email, Gender, age and location
1. Gender
2. Age
3. Location (drop menu)
4. Categories of interest (checkboxes)
Customized notifications based on (Frequency and Categories of choice)
1. Frequency and type (radio button)
A. Instant
B. Daily
C. Weekly
2. Category of notification (according to the category of interest)
Tabs (to be placed on top of the screen)
1. Categories
2. Recent Promotions (fetched from the website)
3. My Promotions (based on the categories the user chose in the profile)
4. Favorites (Promotions that the user favoured using the "add to favorites" on the promotions page.
5. Shops (fetched from the website)
Promotions screen to contain Promotion + reference to store + share + favorite
Store screen: Store-fetch + call + Location (navigation option)+ promotions by store
We are almost done with wireframes and will be provided to the developer before the development work starts.
Looking to make some money?
- Set your budget and the timeframe
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An Evening with Peter Troy
Fundraiser includes dinner and talk with the author.
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Cost: $25
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134 South St. Albion.
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IMPACT Conference
November 29 & 30, 2016
Apply Now to be a Featured Company – DEADLINE EXTENDED
About IMPACT Capital Conference
As a premier signature event of PACT, IMPACT Capital Conference has a long tradition of uniting key players from the private equity, venture capital, and entrepreneurial communities. As the oldest, most established venture conference in the Northeast, IMPACT draws more than 1,000 participants and has been the catalyst for billions of dollars in venture funding and entrepreneurial success.
Growth through Disruption at IMPACT
Disruption = dis-ruhp-shuh n] shakes the box. It's a radical change in an industry or business strategy. Disruption can be intentional; out of necessity. Disruption works as a tool, a catalyst and a result of change.
Through best practices in technology, healthcare and early stage innovation, the IMPACT 2016 Capital Conference will examine disruptions in the marketplace of ideas. IMPACT will use disruption to inform, to educate and to shake business executives out of their comfort zone. Together we will look at how growth through disruption is achieved in entrepreneurship (innovation), investment (funding) and politics (society). Join us November 29 & 30!
We welcome our new Host and Chairperson's Grant Thornton and Chairman, Sean Denham, Office Managing Partner, and Vice Chairman, Dave Maturo.
See What IMPACT 2016 Offers
NETWORKING – At this day and a half event, there are scheduled break sessions, one-on-one business meetings, exclusive investor dinners and cocktail receptions leading up to the official Gala Reception. At IMPACT 2016 you will have many opportunities to meet, greet and develop new relationships.
BUSINESS DEVELOPMENT – With influential business leaders and legends, up-and-coming movers & shakers in the emerging growth community, the opportunities to build and expand your business networks are as inevitable as they prove invaluable.
COMPANY PRESENTATIONS – View emerging business models in technology, healthcare, and early stage industry specific tracks. See the latest technologies and cutting-edge innovations as companies and CEOs tell their stories.
COST SAVINGS – There are special rates for entrepreneurs, investors and early bird registrants for IMPACT 2016.
Video Resources
Want to learn more about the IMPACT Capital Conference? Listen to a few words from our leaders.
Is IMPACT 2015 Worth Attending By Entrepreneurs? – Sandra Stoneman, Partner, Duane Morris
Why should I attend IMPACT 2015 and who else and be there? – Lori Reiner, Partner-in-Charge, Philadelphia Region, EisnerAmper
What value & exposure does IMPACT 2015 offer companies & attendees? – Louis Rappaport, Partner, Blank Rome LLP
Who attends IMPACT and what is the value for me? – Immanuel John, Partner, Grant Thornton
Who will attending companies and investors gain exposure to at IMPACT 2015? – Michael Verrill, Director, Business Development, McGladrey
Take a look back when we celebrated 20 YEARS of connecting companies and capital.
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Hardwood threat causes lockdown, is found to be a hoaxNovember 17,2012DUXBURY Vermont State Police say the threat reported at Harwood Union High School Friday turned out to be bogus.
The state police said they received the reported threat from the school at 8:30 a.m. The school was temporarily locked down as a result of the threat.
According to state police, no threat was found after school officials searched the school grounds. Classes then resumed.
The state police did not say what kind of threat it was and no arrests have been made. The investigation is ongoing.MORE IN This Just InMONTPELIER After sitting on the Vermont Supreme Court for nearly 30 years, Justice John Dooley... Full StoryBRATTLEBORO Entergy Nuclear says it has found a potential source of water infiltration into... Full StoryMANCHESTER A little more than a week after it was shut down, the website for the town of... Full Story
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Home :: Wedding Bands :: Gold Wedding Bands :: Designer White Gold Bands :: White Gold
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24 years of experience
Accepting new patients
Union, NJ 07083 Phone number & directions
A medical license is required for a doctor to practice medicine in a particular state. Requirements vary by state but most require, at a minimum, post-graduate training in the doctor's specific specialty. An NPI number is a national identifier unique to an individual health care provider and is managed by the Center for Medicare & Medicaid Services (CMS).
Learn more about Dr. Jeffrey Gold:
View the full profile to get information on:
- Qualifications
- What's important to you
View full profile
Patient Reviews
The overall average patient rating of Dr. Jeffrey Gold is Excellent.
Prepare before visiting Dr. Gold
Erectile Dysfunction Patient Education What is ED? Read our erectile dysfunction patient education guide to learn all about ED and how to treat erection problems.Before Visiting Dr. Gold Learn More
Specialties & Research
Dr. Jeffrey Gold, DMD, DO, MD is board certified in Cardiovascular Disease and Interventional Cardiology.
- He has special expertise in 5 areas:
- Acute Coronary Syndrome (ACS)
- Heart Block
- High Blood Pressure (Hypertension)
- High Cholesterol (Hypercholesterolemia)
- Unstable Angina
Education & Awards
Dr. Gold graduated from New York Institute of Technology, Old Westbury.
Dr. Gold has 23 hospital affiliations:
- Union Hospital
- Monmouth Medical Center
- Spanish
- Italian
- English
Similar doctors nearby
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- Additional Information
- Dr. Jeffrey Gold DMD, DO, and MD is a male Internist, has 24 years of experience and practices in Cardiovascular Disease, Cardiology, and Interventional Cardiology.
- Where does Dr. Jeffrey Gold practice?
- Dr. Jeffrey Gold has 1 office location.
Dr. Jeffrey Gold practices Cardiovascular Disease, Cardiology, and Interventional Cardiology near Union, NJ.
See Union Cardiologists.


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Windsor Symphony Orchestra conductor laureate John Morris Russell conducted while violinist and concertmaster Lillian Scheirich performed during the Russell and Scheirich Reunited concert at the Capitol Theatre in Windsor, Ont., on Saturday, May 11, 2013.
Photos: Russell And Scheirich Reunited Concert
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Just when I thought the World Cup had lost some of its luster, along comes Luis Suarez.
You know, Luis Suarez, the soccer player from Uruguay who was so hungry that he took a bite out of Italy's Giorgiio Chiellini's shoulder.
Yep, a buffoon from Uruguay took the word Ciao out of context and took a bite out of one of my people.
Of course, with his mouth full Suarez isn't saying much, so I imagined what a conversation with him would be like.
Samuel G. Mustari — Hey palso, what the heck were you thinking?
Luis Suarez — Well, his shoulder was right there and I figured why not.
SGM — They don't feed you very well in Uruguay, or what?
LS — Or what.
SGM — Don't get smart with me. If this was real football, and you were taking on the U.S. team, on the very next play, you'd be whistling dixie and counting sheep. We call it a concussion. In fact, we're infatuated with them.
LS — Have you ever bitten an Italian?
SGM — I sure haven't. I prefer things like sausage, garbonzo beans and fried peppers when it comes down to chomping down Italian.
LS — Well, maybe Chiellini tasted like those things you speak of.
SGM — Yeah sure. With some red gravy and sweet basil right?
LS — I only know of pizza.
SGM — A guy's shoulder isn't a pizza, you meathead.
LS — What is meathead?
SGM — That's you. Dead from the neck up. I've read where this is the third time you've bitten somebody in a match.
What? You think you're Marv Albert.
LS — I've heard of him. He bit somebody, right?
SGM — Yeah, his schimooza girlfriend during a sex romp. A boxer, who's known for not being on anybody's honor roll — Mike Tyson — once bit the ear of his opponent, Evander Holyfield.
This is personal with me Vampire Boy. You bit one of my countrymen. Eliminated the Italian team from this crazy tournament and left me with no legitimate reason to keep watching.
LS — Maybe I should say ... how do you say 'I'm sorry'?
SGM — Sorry won't cut it, you fanged piece of garbage.
Now they're giving you extra security.
LS — Yeah, it's cool. We now have guards, all the way around our hotel.
SGM — You're now infamous team takes on Colombia on Saturday. I hope the Colombians have smuggled some of their extra dope dealers into the lineup to take care of you.
Better yet, maybe you should be made to play with a Hannibal Lecter mask on.
LS — No. You don't understand Mr. Sam. This is not hockey.
SGM — Don't call me mister. I do understand. Maybe you were looking for endorsements. Like a Colgate commercial, or one for PolyGrip.
LS — Is endorsement like a suspension? My suspension is four months.
SGM — Four months? Listen here, Snagletooth. You should get a lifetime ban and have all of your teeth pulled out — with a pair of plyers.
LS — Lifetime ban? That's a long time not being able to bite somebody.
SGM — The punishment should actually fit the crime. Two minutes in a shark-infested pool located right in the center of Rome.
ESPN, ESPN2, Fox Sports, The Animal Channel ... even Shark Week could all telecast it.
We would call it Ciao, Baby. Or maybe, Chow, Baby.
Samuel G. Mustari covers sports for The Tribune. Reach him at (970) 392-4437 or follow him on Twitter @samuelmustari.


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Gloomy weather pushes eclipse fans away from North Queensland coast
- From: The Courier-Mail
- November 13, 2012
ECLIPSE chasers are heading west as weather reports predict the rare cosmic event will be visible in sunny conditions west of Mareeba.
Up to 60,000 tourists, NASA scientists and locals woke up in Cairns and Port Douglas today to gloomy forecasts of cloud and isolated light showers for tomorrow's two-hour spectacle.
Terry Cuttle, of the Astronomical Association of Queensland, said some eclipse chasers were moving inland in the hope of finding a clear view of one of the ``most spectacular events in nature''.
``But even if there is scattered cloud it will still make for a very dramatic effect down here on the coast,'' the astronomer told a large media pack in Palm Cove today.
Thousands are expected to line the beaches from Bloomfield in the north to Innisfail in the south to witness the two hours of partial eclipse either side with two-minutes of totality complete darkness as the moon blocks out the sun from 6.38am.
Up to 10,000 campers - including half a dozen Pagan couples who plan to marry under the celestial spectacle - at the Eclipse Festival near the remote Palmer River Roadhouse, two hours drive north of Cairns, are in prime viewing position.
Other well-heeled eclipse watchers have chartered light aircraft and helicopters to chase the sun and find a break in the clouds to get an unobscured look at the solar rarity.
For this total solar eclipse, the path of totality will be about 174km wide and will cover 14,500km over a three-hour period, mostly over the South Pacific ocean, except for when it tracks over the state's Top End.
Astronomy Magazine's Bob Berman, author of The Sun's Heartbeat, is in Cairns from the United States to live web-stream with the Slooh space camera.
He expects to see geysers of pink ``nuclear fire'' leaping from the edge of the sun when it is blocked by the moon.
``Nothing in nature can equal the sheer spectacle of a total solar eclipse, and this time the event is a dramatic sunrise apparition in the tropics, low over the ocean off the Great Barrier Reef.
``Occurring as it does within months of the expected Solar Max, the solar corona should take on a 'wound up' circular shape, with a high potential for tongues of pink nuclear fire leaping from the Sun's edge.''


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De Waart to fill in for ailing Chicago Symphony conductor
Milwaukee Symphony Orchestra music director Edo de Waart will fill in for ailing Chicago Symphony Orchestra music director Riccardo Muti at five subscription concerts this week and next week, the CSO has announced.
Muti has the flu, according to the CSO. »Read Full Article
Sunday brunch at Boerner ends until 2014; Pastiche in final week of lunch service
Brunch at Boerner: Bartolotta Catering has ended its Sunday buffet brunch at Boerner Botanical Gardens, 9400 Boerner Drive, Hales Corners.
The division of the Bartolotta Restaurant Group lost its catering contract with Milwaukee County for Boerner in May. The county instead awarded the contract, effective Jan. 1, to Zilli Hospitality, which offered a higher bid. »Read Full Blog Post


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11:00 am
Primal Grill with Steven Raichlen "Italian Fire" Since Roman times, the Italian focus-hearth-has made monumental contributions to the world of live fire cooking. A new addition to the Primal Grill equipment collection, an authentic Italian-style wood-burning oven, inspired this show's menu: two versions of Italy's iconic food, pizza, cooked on the floor of the oven but easily adapted to a conventional grill; wood oven-roasted sweet and sour duck; and monster bone-in pork chops glazed with a reduction of red wine, honey, and balsamic vinegar. Benissimo. D
11:30 am
Barbecue University with Steven Raichlen "Fire Away (Getting Started)" Raichlen fixes party-starting pass-arounds - pancetta-grilled diver scallop rumaki, summer sausage s'mores and Chinatown Ribs.G
12:00 pm
Great Conversations "Bill McKibben and Wendell Berry" Bill McKibben (environmental scholar, author of Deep Economy: The Wealth of Communities and the Durable Future) and Wendell Berry (honored writer, essayist, and cultural and economic critic). D
1:00 pm
French In Action "Encounters III" In the courtyard of the Sorbonne, Robert and Mireille have caught each other's eye. Meanwhile, on an upper floor, Jean-Pierre, the pick- up artist, reveals the tricks of his trade to a not-very appreciative audience.G
1:30 pm
French In Action "Getting Underway I" In the courtyard of the Sorbonne. Robert and Mireille finally meet. Just as they are getting to know each other, Mireille rushes off, leaving Robert to contemplate the spring day and write a postcard to his mother.G
2:00 pm
Unfinished Nation "Restless Society" Election of 1960. Kennedy's thousand days in office; his assassination. Johnson's succession: assault on poverty, Great Society. Battle for racial equality: expanding protests, urban violence, black power.G
2:30 pm
Unfinished Nation "A Nation Torn" Diversifying foreign policy. Confrontations with the Soviet Union. The agony of Viet Nam. The traumas of 1968: the Tet offensive, King and Kennedy assassinations, political turmoil.G
3:00 pm
Discovering Psychology - Updated Edition "The Behaving Brain" Investigates the structure and composition of the brain: how neurons function, how information is collected and transmitted, and how chemical reactions determine every thought, feeling, and action.G
3:30 pm
Discovering Psychology - Updated Edition "The Responsive Brain" Takes a closer look at how the brain, behavior and environment interact and how the brain's structure and functions are changed by stimulation from the social and physical context.G
4:00 pm
DragonflyTV "New York" Jenn and Emily, members of the Junior United States Luge Team, slip slide away at the New York Hall of Science playground, investigating gravity and then applying what they learn to maximize their timings on the icy tracks at Lake Placid. Stanley and Jessica go ape, checking out the Bronx Zoo's Congo Gorilla Forest to see how plants and animals coexist in the many layers of the African Rainforest. And find out what's not so natural about New York's Central Park-the most frequently visited urban park in the U.S. D
4:30 pm
Biz Kid$ "Have A Plan, Stan!" Explore the different elements of a business plan and see why it's crucial to develop a plan before you start your business. Meet a teen who opened a snow-cone shack, another who makes and sells candles, and a group who markets self-defense kits. D
5:00 pm
The Electric Company "Madame President" Lisa and Francine face off in the election for Book Club President. Can Lisa's campaign message win out over Francine's dirty politics?. D
5:30 pm
Cyberchase "Be Reasonable" Hacker returns to the Cybrary to wreak revenge on Ms. Fileshare and the kids. His crafty plan tricks the kids to try to rescue Ms. Fileshare, only to find themselves all trapped! If the CyberSquad doesn't escape in time, Hacker will steal the Cybrary's most valuable books - all about the most secret inner-workings of Motherboard!. D
6:00 pm
Knit & Crochet Today "Cables" Fear the cable no more. Our expert will show you how to make both knit and crochet cables to use in easy projects. Interview with knitwear designer Wenlan Chia. D
6:30 pm
Paint This with Jerry Yarnell "Turquoise River, Part 1" (18 x 24 Acrylic) In this opening segment, Jerry starts this popular painting by creating the backdrop using seven values of depth by layering with an impressionistic style. First using the Hake brush for the sky and then switching to a No. 10 bristle brush using vertical strokes to lay in the mountains, pine trees and rocks and focusing on transition blending to form soft edges. D
7:00 pm
Joanne Weir's Cooking Confidence "Journey to Italy" Joanne shares her memories of Italy with her student Barbra recreating some of the dishes form her travels. She starts with a simple salad of fig and prosciutto, then slowly adds just enough red wine for a faro risotto, and finally ends the meal with a dessert of strawberry, port, and black pepper. Recipes: Fig And Blueberry Salad With Creme Fraiche, Mint and Prosciutto di Parma, Farro Risotto with Red Wine and Grana Padano, Strawberry with Port and Black Pepper, and an Aperol Champagne Cocktail. D
7:30 pm
Martha Stewart's Cooking School "Pasta" Explore the art of making fresh pasta from scratch with Martha and her friend Michael White, chef, restaurateur and pasta specialist. Learn how to make the dough and then form it into strands by hand or with a pasta machine, and to hand-shape dough into shapes such as farfalle and tortelli. D
8:00 pm
This Old House "Essex 2012/13, Clam Flats & Lightning Rods" Kevin and Roger dig for clams, then finish up the barrier-free walk that leads to the house, using both granite and bluestone, but no steps. The standing-seam metal roof goes on, and Richard's creative ducting and plumbing will minimize the number of holes that need to go through it. A non-reactive lightning protection system is installed. D
8:30 pm
Rick Steves' Europe "London: Mod and Trad" Rick checks out the Millennium Bridge, banters with Beefeaters at the Tower of London and strolls trendy South Bank.G
9:00 pm
Travelscope "Mozambique, Africa" On Mozambique's Bazaruto Archipelago Kuta Katila means, "Roll your reed mat out on the sand, lay back and relax." Always ready to follow local customs, Joseph does exactly that at the Indigo Bay Island Resort and Spa on Bazaruto Island and at the Azura Resort on Benguerra Island. Joseph continues to practice the fine art of Kuta Katila on the sparkling beaches and in the turquoise waters of the Bazaruto Marine National Park. D
9:30 pm
Lidia's Italy In America "San Diego: Giant Squid, Milanese Style" Lidia shares her memories of San Diego with viewers and heads out to do some more fishing with Esca's Dave Pasternack. Joined by Del Posto's Mark Ladner, Lidia makes a Giant Squid Milanese, Stuffed Mushrooms, and Spinach Salad. D
10:00 pm
Cook's Country from America's Test Kitchen "Dixie Chicken" NULL
10:30 pm
Simply Ming "Jonathan Waxman & Oven-Roasting Vegetables" On this episode of SIMPLY MING, Ming demonstrates how one of the best ways to cook vegetables is to roast them because it concentrates their flavor. And for guest chef Jonathan Waxman, one of the godfathers of New American Cuisine, exalting great ingredients is what it's all about. Together, Ming and Jonathan, draw inspiration from mystery ingredients and the fantastic technique of oven roasting to create two delicious recipes: Spicy Oven-Roasted Chicken Breast with Baby Cauliflower and Potatoes and Macadamia Duck with Roasted Vegetables Waxman Style. D
11:00 pm
Primal Grill with Steven Raichlen "Italian Fire" Since Roman times, the Italian focus-hearth-has made monumental contributions to the world of live fire cooking. A new addition to the Primal Grill equipment collection, an authentic Italian-style wood-burning oven, inspired this show's menu: two versions of Italy's iconic food, pizza, cooked on the floor of the oven but easily adapted to a conventional grill; wood oven-roasted sweet and sour duck; and monster bone-in pork chops glazed with a reduction of red wine, honey, and balsamic vinegar. Benissimo. D
11:30 pm
Rick Steves' Europe "London: Mod and Trad" Rick checks out the Millennium Bridge, banters with Beefeaters at the Tower of London and strolls trendy South Bank.G


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John Bostic is an Actor/Singer and Computer Programmer who lives in Hammond Louisiana.
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Weldon Whiteaker
Mary Sawtelle
On the memorial for Mary Whiteaker Sawtelle #55660591 in the Grace Memorial Church Cemetery, Hammond, LA you have a photo of the Muncy family plot that you call Plot 32. From "files.usgwarchives.net" I find Mary Sawtelle buried in Lot 31 East, grave 6.
Weldon Whiteaker, gggg nephew
Added by
Weldon Whiteaker
on Aug 01, 2015 1:58 PM
Ellen Thompson
RE: Agnes Morris
This must not be the Agnes Morris for whom I'm searching. My Agnes never married; her maiden--& only last--name was Morris. She moved from north Ga. to Louisiana in the 1890s where she was a leader in education until her death in the 1930s.
I'm very sorry to have caused you extra work.
Ellen Thompson
Added by
Ellen Thompson
on Apr 25, 2015 6:33 AM
Ellen Thompson
Agnes Morris's grave in Louisiana
I did not see Agnes's marker in the photo that was posted. Did I just miss it? Did you perhaps load a different photo? I appreciate your help so much.
Ellen Thompson
Added by
Ellen Thompson
on Apr 24, 2015 2:53 PM
Family Grave Hunters
CJ Hess
I don't know if I told you thank you so much for going out and taking photos of my Uncle CJ's headstone. Yes my Aunt is still alive.
Thanks again so much
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Family Grave Hunters
on Apr 04, 2015 9:35 PM
Memorial photo for Robert Singleton
Hi, again. Thanks for all the photos I've rec'd from you in the past. Today, I had someone request that this particular one be removed - & I can't figure out how to delete it. She posted photos herself - with dates that match those of his - death in 1959 instead of 1944. Thanks! [page] http://www.findagrave.com/cgi-bin/fg.cgi?page=gr&GRid=59917754 - [photo] http://www.findagrave.com/cgi-bin/fg.cgi?page=pv&GRid=59917754&PIpi=84119685
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on Jan 05, 2015 7:52 PM
Donna D
Thank you so much for your help. I put this request out for a friend and she will be very happy to get this information.
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Donna D
on Dec 07, 2014 9:15 PM
Mitchell Sanders
Leon Ford III
John, Thanks for the photo and the quick response!
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Mitchell Sanders
on Aug 31, 2014 5:21 PM
Rhoni T
Robert Jack Price
wondering if you'd ever made a connection with Rex on Robert Jack Price? if so would you email me, I have a great grandfather that was his brother.
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Rhoni T
on Aug 28, 2014 5:09 PM
Infant Archie
Thank you for taking the picture.
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darren white
hey i need your help
my name is darren white and the person i was looking for is named greggory milton smith he was born september 15 1980 and passed on july 25 2005. the reason i am telling you this is because i would like to know his parents name, i have a feeling that this is one of my long lost relatives. all i need to know are his parents names if you can give me them, no numbers, or addresses or anything like that, i really need to know. my email is firstname.lastname@example.com
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With perfect W-shaped double bottom and good prospect for earnings, QNST is ready to make a leap.
ready to ?
1 minute to re-opening. With such a low float, I wonder how far this can drop.
$8.50 is where the "strong support" will be, but the results are so bad and the outlook to the future so bad, i think investors will be discounting this crap much lower. let's just say, there won't be any optimistic bounce and most will be getting outta dodge!
actually, obliteration comes to mind rather than soar
Soros just boght some DRIV..sure to buy more...BLIN also has content.


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- Main meeting room
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text:
CSU vs. New Mexico State
The Rams matched up with the New Mexico State Aggies in a dual meet at Moby Pool on Jan. 22, 2011.
At the 2010 Mountain West championships, led off the 200 Freestyle Relay team that earned fifth place, and also placed eighth in the 50 Freestyle, 25th in the 100 Back, 23rd in the 100 Freestyle, and seventh in the 400 Freestyle Relay, earning all-conference recognition...Scored 183.25 points on the season...A GPA of 3.063 earned her Mountain West academic all-conference honors.
Competed at the U.S. Open Swimming Championships at Seattle, Wash., in August, placing 32nd with a 26:51 in the 50 Freestyle...Clocked personal bests at the Mountain West Conference championships in the 50 Freestyle (22.90), 100 Freestyle (51.26) and 100 Backstroke (57.86)... Freestyle-leg of the 200 Medley Relay team (1:41.85), which broke a school record...Led off the 200 Freestyle Relay team that holds a school record (1:32.09)...Scored 458.75 points in the season...All-conference in the 200 Medley Relay and 50 Freestyle...A 3.00 GPA earned her academic all-conference honors...Named Most Improved in the Husker Invitational.
Swam as a true freshman for the University of Washington Huskies, before transferring home to Colorado State.
Highlands Ranch High School
Qualified for the U.S. nationals, lettering four years and serving as a team captain as a senior for the Falcons...Voted team MVP each of her last two seasons, as well as well as HRHS Female Student-Athlete of the Year in 2006-07...Won the 2007 state championship in both the 50 (23.77) and 100 freestyle (52.21)...As a junior, finished second in the 50 Free and third in the 100 Free at the Colorado state championships; additionally, contributed to a state championship on a 200 Medley Relay squad that swam the second-fastest time in Colorado high school annals...Also placed in the 50 Free as both a sophomore (ninth) and as a freshman (16th)...Swam for Highlands Ranch Aquatics and Matt Beck for seven years.
Born Sept. 5, 1989...Daughter of Diana Pinkley and Michael Dole...Has a sister, Tiffany...An apparel merchandising major...Full name is Samantha Jo Dole.
"This two-year all-conference swimmer can always be relied upon to get her hand on the wall first when it comes to the sprint freestyle."
-Coach John Mattos
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FORT COLLINS, Colo. – The Colorado State swimming & diving squad has added three more...
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COLLEGE STATION, Texas - The Colorado State Rams swimming & diving team took eighth at the 2016...
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text: The Second Time Around wiki last edited by NightFang3 on 10/18/14 04:50AM View full history April starts running Second Time Around. April inherited Second Time Around from her father when he died. After it came into daylight that Aprils boss Baxter Stockman was a madman and was imprisoned from his crimes against New York City, April stopped being computer scientist and started running Second Time Around. When the Shredder comes back in Teenage Mutant Ninja Turtles 9 (in story Silent Partner), the Turtles meet him in Second Time Around and battle him there. It is burned down after the battle with the rest of the building. April takes it very hard, because the building and shop were everything she had.


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$4.99Every fairy tale has a dark side...Elodie Rose has a secret. Any day, she'll become a wolf and succumb to the violence that's cursed her family for centuries. For seventeen years she's hidden who and what she is. But now someone knows the truth and is determined to exterminate her family line. Living on borrowed time in the midst of this dangerous game of hide and seek, the last thing Elodie needs
$3.99WARNING: Contains a sexy ex-marine, a stubborn, independent woman, and an incurably romantic BFF with matchmaking tendencies.Welcome back to Wishful, Mississppi, full of eccentric characters and southern charm, where author Kait Nolan delivers another heart-warming story of a strong, successful woman and the equally strong man who learns how to be her partner.Liam Montgomery is the last person who
$3.99A madcap modern marriage of convenience tale sure to leave fans begging for moreMaybe there hasn't been actual blood, other than a few paper cuts, but Myles has put plenty of sweat into his independent, local newspaper, and he's even willing to admit to a few manly tears. Certainly, the paper has been his mistress since he moved to the small town of Wishful, Mississippi, and he doesn't feel it's
$0.99Kait Nolan's Mirus series is set in a paranormal world unlike any you've visited before—inventive new mythology full of fast-paced action, dark dangers, sparkling magic, and sizzling, undeniable attraction.Cade Shepherd is on top of the world as this year's Ultimate Fighting Champion. He doesn't even remember his life as Gage Dempsey, a Shadow Walker with the ability to magically transport himself
$2.99Kait Nolan presents an engaging small town, second chance romance that will appeal to fans of Candis Terry's Sweet, Texas; Jill Shalvis' Lucky Harbor; and Ava Miles' Dare Valley. The best things happen while you're acting...The historic Madrigal theater is about to close its doors forever. A last ditch fund-raising effort, a production of White Christmas, is probably the only thing that could
$2.99Kait Nolan's Mirus series is set in a paranormal world unlike any you've visited before—inventive new mythology full of fast-paced action, dark dangers, sparkling magic, and sizzling, undeniable attraction.Trouble. That's what wolf-shifter Mick Guidry thinks when a beautiful woman appears in his New Orleans bar with a hurricane at her back. His first impression is confirmed when Sophie starts
Once Upon A Snow Day (Meet Cute Romance)Do you wanna build a snowman?Isabelle Lawson loves her job. Driven, dedicated, there's no room in her high-pressure life to look for love outside the pages of the books she edits. Can a fun-loving, handsome stranger change her mind?A novelette of approximately 10k words.Q: What makes the Meet Cute Romance series special?"Meet cute" is a term used to describe a situation in which a future romantic
Once Upon An Heirloom (Meet Cute Romance)A blind date on Valentine's Day. What could possibly go wrong?After being duped and robbed by a charming ex-boyfriend, Sylvie Noll is forced to go to a jewelry store to sell a beloved family heirloom or lose the business she's put everything into.Everett William Sperry, III is a hard-core do-gooder with a heart of gold and bank account to back him up. He impulsively buys Sylvie's hocked ring,
Once Upon A New Year's Eve (Meet Cute Romance)A second chance romance for anyone who ever fell in love with their brother's best friend.It should have been the perfect New Year's Eve date. But when Gemma Forester gets called to bail her older brother out of trouble, she comes face to face with some of her own. Aaron Hendricks never forgot his best friend's little sister, but ten years wasn't enough to prepare him for the woman she's become.
$3.99The road to redemption...Struggling single mom Corinne Dawson doesn't have time for fun. She's too busy making a new life for her son and trying to avoid being dragged down by the ghost of who she used to be. But when an accident knocks her boss out of a local dance competition fundraiser, she finds herself face-to-face with the worst mistake from her past.Attorney Tucker McGee has always seen
$3.99Kait Nolan's Mirus series is set in a paranormal world unlike any you've visited before—inventive new mythology full of fast-paced action, dark dangers, sparkling magic, and sizzling, undeniable attraction. A permanent injury in the line of duty effectively ended Ian Ryker's career as a Shadow Walker for the Council of Races. Being posted to a safe house in Washington, D.C. was one step short of
HELP! Food Allergies Coming To Dinner: The Pinch Hitter's Guide To Cooking Without Gluten or DairyYour boss is coming to dinner, and you just found out she's allergic to dairy.You love making food for the office, and a co-worker has gone gluten free.Your new sister-in-law is a celiac, and she's coming to the family reunion.You volunteered to bake for your son's class and just found out one of the kids has a milk allergy.You suspect that you might have a food allergy or sensitivity, and you