Miracle-dz/UniFAR-FTUs huggingface dataset:
A Compact Computing Environment For A Windows PC Cluster Towards Seamless Molecular Dynamics Simulations

A Windows PC cluster is focused for its high availabilities and fruitful functions such as a well- tuned MPI library and a fully-equipped job scheduler. However, the software tools are complicated for users who are not familiar with the Windows system. They don't want to pay much time to learn about the sys- tem because what they want is getting calculated re- sults. Furthermore, there is not any tool to support visualization of calculated results. To support seam- less molecular dynamics simulations from computa- tions to visualization on a Windows cluster, a com- pact computing environment has been built by using Java. It provides hints for parallel computing and as- sists seamless job execution and its visualization. As a result, application users can proceed their compu- tations without deep understandings of the Windows cluster.
Towards the Automatic Creation of a Wordnet from a Term-Based Lexical Network

The work described here aims to create a wordnet automatically from a semantic network based on terms. So, a clustering procedure is ran over a synonymy network, in order to obtain synsets. Then, the term arguments of each relational triple are assigned to the latter, originating a wordnet. Experiments towards our goal are reported and their results validated.
A current-mode CMOS integrated microsystem for current spinning magnetic hall sensors

A magnetic Hall sensor working in the current-mode is presented. The proposed sensing device is composed by two Hall plates able to provide a differential current at the output nodes. The sensor, fabricated in a standard 0.18-μm CMOS technology, uses the spinning-current technique to compensate for the offset and obtains a sensitivity I<sub>Hall</sub>/(B⊥I<sub>bias</sub>) better than 0.02 T<sup>-1</sup> for magnetic fields ranging from 0 to 10 mT.
Optical Flow Estimation Using Discontinuity Conforming Filters

The discontinuities and the large image displacements pose some of the hardest problems in flow estimation. This paper uses a set of filters that change shape to avoid blending of the constraints across discontinuity boundaries. This is done by using an incompatibility measure of the constraints of neighbouring pixels. The algorithm is embedded in a coarse to fine multigrid scheme to address the problem of large displacements. We report results on real images which show that the algorithm works very well.
Gross Anatomical Features of the Gastrointestinal Tract (GIT) of Blue‐and‐Yellow Macaws (Ara ararauna) – Oesophagus to Cloaca

Morphological studies of the gastrointestinal tract of blue‐and‐yellow macaws (Ara ararauna) are scarce. In view of the paucity of information regarding the digestive tract of macaws, this study aims to describe the gross anatomical features (oesophagus to cloaca) as part of a broad study of the gastrointestinal tract (GIT) of these birds. Three animals (two males and one female) adult macaws were anatomically dissected from the oropharynx to the cloaca to expose the GIT. The oesophagus was identified as a muscle‐membranous tube continuous with the crop, which was intimately attached to the skin. The internal longitudinal folds of the cervical oesophagus were sparser cranial to the crop and less evident compared to the portion caudal to the crop. The duodenum began in the pylorus and was grey‐coloured exhibiting a large lumen. The jejunum was formed by loops in a spiral‐fashion model supported by mesojejunum. The ileum was also composed by small loops and was continuous with the colo‐rectum forming the large intestine, because the caeca were absent. The large intestine was short, median in position, suspended in the dorsal wall of the abdominal cavity by mesentery and ended in the cloaca. The GIT was similar to the basic patterns in birds, in general, and also presented new unreported morphological data that might be important when studying nutrition and health of the macaws.
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation

We present a discriminative nonparametric latent feature relational model (LFRM) for link prediction to automatically infer the dimensionality of latent features. Under the generic RegBayes (regularized Bayesian inference) framework, we handily incorporate the prediction loss with probabilistic inference of a Bayesian model; set distinct regularization parameters for different types of links to handle the imbalance issue in real networks; and unify the analysis of both the smooth logistic log-loss and the piecewise linear hinge loss. For the nonconjugate posterior inference, we present a simple Gibbs sampler via data augmentation, without making restricting assumptions as done in variational methods. We further develop an approximate sampler using stochastic gradient Langevin dynamics to handle large networks with hundreds of thousands of entities and millions of links, orders of magnitude larger than what existing LFRM models can process. Extensive studies on various real networks show promising performance.
Buffer-pool Aware Query Optimization

With the advent of 64-bit processors, large main memories are set to become very common. This in turn translates to larger buffer pool configurations in database servers. Query optimizers however, currently assume all data is disk resident while optimizing queries. This assumption will no longer be valid when buffer pools become 100’s of gigabytes in size. In this paper we examine how data presence in the buffer pool can affect the choice of query plans in an optimizer. We examine the possible benefits of buffer-pool aware query optimization and propose a generic architecture for implementing such an optimizer.
Crystal plasticity modeling of β phase deformation in Ti-6Al-4V

Ti-6Al-4V is an alloy of titanium that dominates titanium usage in applications ranging from mass-produced consumer goods to high-end aerospace parts. The material’s structure on a microscale is known to affect its mechanical properties but these effects are not fully understood. Specifically, this work will address the effects of low volume fraction intergranular β phase on Ti-6Al-4V’s mechanical response during the transition from elastic to plastic deformation. A crystal plasticity-based finite element model is used to fully resolve the deformation of the β phase for the first time. This high fidelity model captures mechanisms difficult to access via experiments or lower fidelity models. The results are used to assess lower fidelity modeling assumptions and identify phenomena that have ramifications for failure of the material.
A Self-Reference Watermarking Scheme Based on Wet Paper Coding

Fragile watermarking is applied to protect the integrity of the digital media. Current fragile watermarking schemes mainly provide the functionality of detecting and locating the tampered regions of an authorized image. The capability to recover the tampered regions has rarely been discussed in the literature. In fact, the recovery ability is an important issue while proving and maintaining the image integrity. For achieving these purposes, we first utilize the concept of self-reference to preserve the significant information of a protected image. Then we embed the information into the protected image using the technique of wet paper coding. According to experimental results, the new scheme is highly sensitive to detect and locate the tampered area. In particular, the results show that the quality of recovery image is satisfactory.
Oncolytic Viruses for Cancer Therapy: Overcoming the Obstacles

Targeted therapy of cancer using oncolytic viruses has generated much interest over the past few years in the light of the limited efficacy and side effects of standard cancer therapeutics for advanced disease. In 2006, the world witnessed the first government-approved oncolytic virus for the treatment of head and neck cancer. It has been known for many years that viruses have the ability to replicate in and lyse cancer cells. Although encouraging results have been demonstrated in vitro and in animal models, most oncolytic viruses have failed to impress in the clinical setting. The explanation is multifactorial, determined by the complex interactions between the tumor and its microenvironment, the virus, and the host immune response. This review focuses on discussion of the obstacles that oncolytic virotherapy faces and recent advances made to overcome them, with particular reference to adenoviruses.
Real-Time Fire and Smoke Detection for Open Space Surveillance

Artificial neural network is use for analyzing and training the sensed data which gathered by different channels. In this paper we use different combinations of techniques to detect smoke and flame detection algorithms in a video. The past sensed data cannot respond quickly and fire and smoke may not capture quickly. The region partitioning technique is proposed, which will increase the accuracy and also reduce test data so that rather than using a whole frame in a video it uses on part of that frame. The flame characteristics are used for normalization data we are processing. The use of neural network in combination with image processing can improve the accuracy and also help to predict the data. In improvement the wrong alarm problem is decreased. The double band method is use to detect fire. The region which we are analyzing for detecting fire and smoke is calculated directly so that it can reduce computational time.
Body Surface Detection of Delayed Depolarizations in Patients with Recurrent Ventricular Tachycardia and Left Ventricular Aneurysm

In eight patients with chronic ventricular tachycardia and left ventricular aneurysms, we detected delayed ECG wave forms after the QRS complex from the body surface using a high-resolution ECG recorder, amplification and signal averaging. Delayed wave-form activity (D wave) extended a mean of 70 msec beyond the termination of the QRS complex. This delayed activity frequently extended to the limit of the recording window, and may thus continue throughout much of diastole. Antiarrhythmic agents never abolished the delayed activity; however, it was abolished by aneurysmectomy in four patients. Ventricular tachycardia did not recur after surgery in the four patients during a mean follow-up of 1 year. The D wave was not found in eight control patients who had chronic recurrent ventricular tachycardia nor in 11 of 12 who had aneurysms alone. The surface D wave can be readily and reproducibly detected by high-resolution electrocardiography and appears to be specific for patients with left ventricular aneurysms who also have chronic recurrent ventricular tachycardia. This delayed wave-form activity has been noted during catheter and surgical endocardial and epicardial mapping. It may represent persistence of the cardiac impulse in islands of myocardium and may be a manifestation of the delayed and fractionated activity, noted by previous investigators.
Quantifying cellular and subcellular stretches in embryonic lung epithelia under peristalsis: where to look for mechanosensing

Peristalsis begins in the lung as soon as the smooth muscle (SM) forms, and persists until birth. As the prenatal lung is filled with liquid, SM action can, through lumen pressure, deform tissues far from the immediately adjacent tissues. Stretching of embryonic tissues has been shown to have potent morphogenetic effects. We hypothesize that these effects are at work in lung morphogenesis. In order to refine that broad hypothesis in a quantitative framework, we geometrically analyse cell shapes in an epithelial tissue, and individual cell deformations resulting from peristaltic waves that completely occlude the airway. Typical distortions can be very large, with opposite orientations in the stalk and tip regions. Apical distortions are always greater than basal distortions. We give a quantitative estimate of the relationship between length of occluded airway and the resulting tissue stretch in the distal tip. We refine our analysis of cell stresses and strains from peristalsis with a simple mechanical model of deformation of cells within an epithelium, which accounts for basic subcellular geometry and material properties. The model identifies likely stress concentrations near the nucleus and at the apical cell–cell junction. The surprisingly large strains of airway peristalsis may serve to rearrange cells and stimulate other mechanosensitive processes by repeatedly aligning cytoskeletal components and/or breaking and reforming lateral cell–cell adhesions. Stress concentrations between nuclei of adjacent cells may serve as a mechanical control mechanism guiding the alignment of nuclei as an epithelium matures.
Application of poly(trimethylene carbonate) and calcium phosphate composite biomaterials in oral and maxillofacial surgery

This thesis has been dedicated to explore the feasibilities of applying composite biomaterials to bone reconstruction in jawbones and skulls. The composite biomaterials used in our studies are composed of a polymer matrix and various calcium phosphate particles. The polymer matrix is made of a high-molecular-weight aliphatic polymer called poly(trimethylene carbonate)(PTMC) and it has taken different forms of membranes and disc-shaped porous scaffolds in different studies. The polymer of poly(trimethylene carbonate) possesses good mechanical properties for biomedical applications and can be degraded in vivo by enzymes via a surface erosion procedure. Thus, its good mechanical properties are maintained during degradation. The calcium phosphate particles used in our studies included β-tricalcium phosphate and biphasic calcium phosphate, a mixture of β-tricalcium phosphate and hydroxyapatite at a ratio of 20:80. β-tricalcium phosphate particles are known to conduct new bone formation in bone defects and biphasic calcium phosphate particles with micro pores have been shown to induce new bone formation. Although we did not find any positive effect of the composite materials on bone formation, the idea of incorporating calcium phosphate particles into PTMC matrices is promising. The optimal content of calcium phosphate particles in PTMC matrices needs to be determined to obtain composite materials which not only fill bone defects but also stimulate bone formation.
Crosstalk- and Process Variations-Aware High-Quality Tests for Small-Delay Defects

The population of small-delay defects (SDDs) in integrated circuits increases significantly as technology scales to 65 nm and below. Therefore, testing for SDDs is necessary to ensure the quality and reliability of high-performance integrated circuits fabricated with the latest technologies. Commercial timing-aware automatic test pattern generation (ATPG) tools have been developed for SDD detection. However, they only use static timing analysis reports in the form of standard delay format for path-length calculation and neglect important underlying causes, such as process variations, crosstalk, and power-supply noise, which can also induce small delays into the circuit and impact the timing of targeted paths. In this paper, we present an efficient pattern evaluation and selection procedure for screening SDDs that are caused by physical defects and by delays added to paths by process variations and crosstalk. In this procedure, the best patterns for SDDs are selected from a large repository test set. Experimental results demonstrate that our method sensitizes more LPs, detects more SDDs with a much smaller pattern count, and needs less CPU runtime compared with a commercial timing-aware ATPG tool.
Reducing energy and delay using efficient victim caches

In this paper, we investigate methods for improving the hit rates in the first level of memory hierarchy. Particularly, we propose victim cache structures to reduce the number of accesses to more power consuming structures such as level 2 caches. We compare the proposed victim cache techniques to increasing the associativity or the size of the level I data cache and show that the enhanced victim cache technique yield better energy-delay and energy-delay-area products. We also propose techniques that predict the hit/miss behavior of the victim cache accesses and bypass the victim cache when a miss can be determined quickly. We report simulation results obtained from SimpleScalar/ARM modeling a representative Network Processor architecture. The simulations show that the victim cache is able to reduce the energy consumption by as much as 17.6% (8.6% on average) while reducing the execution time by as much as 8.4% (3.7% on average) for a set of representative applications.
Effects of tomato powder or soy fiber addition and fat content on physicochemical properties of hot dogs

Tomato powder and soy fiber may provide health benefits by supplying dietary fiber and antioxidant compounds. The main objective of this study was to investigate the effects of dietary fiber additions (tomato powder 3%, tomato powder 5%, soy fiber 3% and soy fiber 5%) and fat content (10, 15 and 20%) on physical and chemical properties of beef hot dog. Tomato powder and soy fiber additions increased protein content and dietary fiber content in all cases (P < 0.05), and all dietary fiber additions provided a small degree of showed antioxidant activity in the order of (P < 0.05) 3% tomato powder >3% soy fiber> 5% tomato powder= 5% soy fiber. Tomato powder content had no effect on cooking loss (P > 0.05) but decreased water holding capacity (P < 0.05), whereas soy fiber decreased cooking loss and increased water holding capacity (P > 0.05). Increasing fat content generally resulted in increased cooking loss and water holding capacity (P < 0.05). However, interaction effects on cooking loss due to fiber addition were found in 10 and 20% fat levels (P < 0.05).
Healthy ageing in the Nun Study: definition and neuropathologic correlates.

BACKGROUND Although the concept of healthy ageing has stimulated considerable interest, no generally accepted definition has been developed nor has its biological basis been determined. OBJECTIVE To develop a definition of healthy ageing and investigate its association with longevity and neuropathology. METHODS Analyses were based on cognitive, physical, and post-mortem assessments from 1991 to 1998 in the Nun Study, a longitudinal study of ageing in participants 75+ years at baseline. We defined three mutually exclusive levels of healthy ageing (excellent, very good, and good) based on measures of global cognitive function, short-term memory, basic and instrumental activities of daily living, and self-rated function. Mortality analyses were based on 636 participants; neuropathologic analyses were restricted to 221 who had died and were autopsied. RESULTS Only 11% of those meeting criteria for the excellent level of healthy ageing at baseline subsequently died, compared with 24% for the very good, 39% for the good, and 60% for the remaining participants. Survival curves showed significantly greater longevity with higher levels of healthy ageing. The risk of not attaining healthy ageing, adjusted for age, increased two-fold in participants with brain infarcts alone, six-fold in those with Alzheimer neuropathology alone, and more than thirteen-fold in those with both brain infarcts and Alzheimer neuropathology. CONCLUSIONS The biological validity of our definition of healthy ageing is supported by its strong association with mortality and longevity. Avoiding Alzheimer and stroke neuropathology is critical to the maintenance of healthy ageing, and the presence of both pathologies dramatically decreases the likelihood of healthy ageing.
Health consequences of obesity

The recent epidemic of childhood obesity1 has raised concern because of the possible clinical and public health consequences.2,3 However, there remains a widespread perception among health professionals that childhood obesity is a largely cosmetic problem, with minor clinical effects. No systematic review has yet focused on the diverse array of possible consequences of childhood obesity, though older non-systematic reviews are available.4,5 In addition, no review to date has considered the vast body of evidence on the health impact of childhood obesity which has been published recently. The aim of the present review was therefore to provide a critically appraised, evidence based, summary of the consequences of childhood obesity in the short term (for the child) and longer term (in adulthood).
Song-induced ZENK gene expression in auditory pathways of songbird brain and its relation to the song control system

The ZENK gene encodes a zinc-finger-containing transcriptional regulator and can be rapidly activated in songbird brain by presentation of birdsong (Mello et al., 1992). Here we map the areas of the songbird forebrain that show this genomic response to birdsong, using in situ hybridization. After 30 min of song presentation ZENK mRNA levels reach a peak in the caudomedial telencephalon, in areas adjacent to or closely related with primary auditory structures. These areas include subfields of field L (L1 and L3), the caudomedial neostriatum (NCM), the caudomedial hyperstriatum ventrale (CMHV) anterior to field L, the caudal paleostriatum, and two field L targets, HVC shelf and RA cup. In contrast, ZENK induction is absent in some areas that show a response to song by other measures and where ZENK induction might have been expected. These include the direct thalamo- recipient field L subfield L2, and the nuclei of the circuit involved in the acquisition and production of learned song. These results demonstrate that ZENK induction following song presentation occurs only in a subset of areas physiologically activated by song, and draw attention to areas previously unsuspected as related to processing of complex auditory stimuli. Based on what is known about ZENK function in mammalian systems (Christy et al., 1989; Cole et al., 1989; Wisden et al., 1990), we speculate that areas revealed by ZENK induction might correspond to sites where critical neuronal modifications occur in response to birdsong presentation, possibly leading to the formation of song-related memories.
Difference networks and second-order difference networks

Deep convolution networks [1] showed extraordinary talents in computer vision in recent studies. However, how to train or optimize it is still difficult. In this paper, we introduce the Difference Network (DiffNet) and second-order Difference Network (soDiffNet), which propagated “salient difference features” with various identity shortcut connections. We embrace difference equations which combined current stack layers and input layers, rather than unreferenced functions. Furthermore, to utilize the high potential of identity shortcut connection, we introduced the second-order difference network unit to add depth of unit and therefore to the whole network. Notably, the difference network and the second-order network can be applied to diverse kinds of convolutional networks and significantly increase the performance over a variety of applications. In summary, our experiments on benchmark CIFAR-10, CIFAR-100, and CASIA-WebFace datasets investigated have shown that our network architecture has effectiveness and versatility in object classification and face recognition.