gebhart/patrepeval huggingface dataset:
Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques (2017)

Software security vulnerabilities are one of the critical issues in the realm of computer security. Due to their potential high severity impacts, many different approaches have been proposed in the past decades to mitigate the damages of software vulnerabilities. Machine-learning and data-mining techniques are also among the many approaches to address this issue. In this article, we provide an extensive review of the many different works in the field of software vulnerability analysis and discovery that utilize machine-learning and data-mining techniques. We review different categories of works in this domain, discuss both advantages and shortcomings, and point out challenges and some uncharted territories in the field.
The power of prediction with social media (2013)

Purpose ‐ Social media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians ‐ among others ‐ new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently, little is known about their overall potential, limitations and general applicability to different domains. Therefore, better understanding the predictive power and limitations of social media is of utmost importance. Design/methodology/approach ‐ Different types of forecasting models and their adaptation to the special circumstances of social media are analyzed and the most representative research conducted up to date is surveyed. Presentations of current research on techniques, methods, and empirical studies aimed at the prediction of future or current events from social media data are provided. Findings ‐ A taxonomy of prediction models is introduced, along with their relative advantages and the particular scenarios where they have been applied to. The main areas of prediction that have attracted research so far are described, and the main contributions made by the papers in this special issue are summarized. Finally, it is argued that statistical models seem to be the most fruitful approach to apply to make predictions from social media data. Originality/value ‐ This special issue raises important questions to be addressed in the field of social media-based prediction and forecasting, fills some gaps in current research, and outlines future lines of work.
Draft Genome Sequence of Bacillus atrophaeus UCMB-5137, a Plant Growth-Promoting Rhizobacterium (2013)

Bacillus atrophaeus UCMB-5137 shows an extraordinary activity in root colonization and plant and crop protection. Its draft genome sequence comprises 21 contigs of 4.11 Mb, harboring 4,167 coding sequences (CDS). The genome carries several genes encoding antimicrobial lipopeptides and polyketides. Multiple horizontally acquired genes of possible importance for plant colonization were also found.
The Role of Shigella spp., Enteroinvasive Escherichia coli, and Other Enteropathogens as Causes of Childhood Dysentery in Thailand (1986)

Shigella spp. were isolated from 44%, Pleisomonas shigelloides from 22%, Campylobacter spp. from 16%, and Salmonella spp. from 10% of 200 Thai children with mucoid or bloody diarrhea. Enteroinvasive Escherichia coli (EIEC) was identified by examining isolates of E. coli for plasmids larger than 120 megadaltons (MDa), by identifying E. coli with a virulence marker antigen in an ELISA, and by performing DNA hybridization with a 17-kilobase (kb) EcoRI digestion fragment of plasmid pWR100 (a 140-MDa plasmid of Shigella flexneri 5). Sixty-four isolates of EIEC from 10 (5%) of the children were identified by these methods and confirmed by the Sereny test. All isolates of EIEC fermented lactose, and isolates of EIEC from seven children belonged to recognized serotypes of EIEC (O28ac:H- and O29:H-), whereas isolates of EIEC from three children were untypable. Examination of DNA from the total fecal growth with the 17-kb probe identified 9 of 10 children from whom EIEC were isolated and 2 of 102 children from whom EIEC or Shigella spp. were not isolated. Detection of EIEC by ELISA and DNA hybridization are important advances in defining the etiology of dysentery.
Shape and reflectance from an image sequence generated using extended sources (2003)

The authors present a method for determining the shapes of surfaces whose reflectance properties may vary from Lambertian to specular, without prior knowledge of the relative strengths of the Lambertian and specular components of reflection. The object surface is illuminated using extended light sources and is viewed from a single direction. Surface illumination using extended sources makes it possible to ensure the detection of both Lambertian and specular reflections. Multiple source directions are used to obtain an image sequence of the object. An extraction algorithm uses the set of image intensity values measured at each surface point to compute orientation as well as relative strengths of the Lambertian and specular reflection components. The proposed method is called photometric sampling, as it uses samples of photometric function that relates image intensity to surface orientation, reflectance, and light source characteristics. Experiments were conducted on Lambertian surfaces, specular surfaces, and hybrid surfaces, whose reflectance models are composed of both Lambertian and specular components. The results show high accuracy in measured orientations and estimated reflectance parameters.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Risk Assessment (2005)

Abstract The “risk” of a potentially dangerous hazard may be measured either by the probability of its occurrence (perhaps per unit time or unit of exposure), or by combining this with a measure of its severity. Risk assessment may involve estimation of these quantities, evaluation of their significance for individuals and communities, the extent to which individuals may differ in their perceptions of risks, and the measures taken by individuals and communities to reduce the impact of risks. These aspects are considered in turn.
Indices of cardiovascular function derived from peripheral pulse wave analysis using radial applanation tonometry: a measurement repeatability study (2007)

Pulse wave analysis (PWA) using applanation tonometry is a non-invasive technique for assessing cardiovascular function. It produces three important indices: ejection duration index (ED%), augmentation index adjusted for heart rate (AIX@75), and subendocardial viability ratio (SEVR%). The aim of this study was to assess within- and between-observer repeatability of these measurements. After resting supine for 15 minutes, 20 ambulant patients (16 male) in sinus rhythm underwent four PWA measurements on a single occasion. Two nurses (A & B) independently and alternately undertook PWA measurements using the same equipment (Omron HEM-757; SphygmoCor with Millar hand-held tonometer) blind to the other nurse's PWA measurements. Within- and between-observer differences were analysed using the Bland-Altman ;limits of agreement' approach (mean difference +/- 2 standard deviations, 2SD). Mean age was 56 (blood pressure, BP 136/79; pulse rate 64). BP/PWA measurements remained stable during assessment. Based on the average of two PWA measurements the mean +/- 2SD between-observer difference in ED% was 0.3 +/- 2.0; AIX@75 1.0 +/- 3.9; and SEVR% 1.7 +/- 14.2. Based on a single PWA measurement the between-observer difference was ED% 0.3 +/- 3.3; AIX@75 1.7 +/- 6.9; and SEVR% 0.6 +/- 22.6. Within-observer differences for nurse-A were ED% 0.0 +/- 5.4; AIX@75 1.5 +/- 7.0; and SEVR% 1.7 +/- 39.0 (nurse-B: 0.1 +/- 3.8; 0.1 +/- 8.0; and 0.6 +/- 23.3, respectively). PWA demonstrates high levels of repeatability even when used by relatively inexperienced staff and has the potential to be included in the routine cardiovascular assessment of ambulant patients.
Application of Tatian"s method to slanted-edge MTF measurement (2005)

The ISO 12233 method for the measurement of the spatial frequency response (SFR) of digital still cameras and scanners is based on the analysis of slanted-edge image features. The procedure applies a form of edge-gradient analysis to an estimated edge-spread function. As with all measurement, image noise can introduce bias error and variation into the resulting camera SFR and modulation transfer function, (MTF). It is often pointed out that applying a derivative filter to the estimated edge-spread function, as is done in the ISO method, amplifies this image noise. To reduce the influence of noise on the measurement, data averaging and fitting have been proposed. One method for edge-gradient analysis, reported by Tatian, avoids the above discrete derivative step. The MTF is expressed as a trigonometric series, whose elements are estimated from the measured edge-spread function. We describe the application of this method as an intermediate step in the ISO procedure. The method was benchmarked for both synthetic edges and captured test images. Results indicate good agreement between the two estimates for low-noise image data. For higher noise levels, however, Tatian's method is found to be susceptible to the selection (cropping) of the input data array. For the conditions tested, we found no clear advantage of this method over the current ISO procedure. For other applications, the slanted-edge analysis provides a front end to Tatian's method, and others, based on parametric modeling or statistical fitting.
Sequence-Aware Factorization Machines for Temporal Predictive Analytics (2020)

In various web applications like targeted advertising and recommender systems, the available categorical features (e.g., product type) are often of great importance but sparse. As a widely adopted solution, models based on Factorization Machines (FMs) are capable of modelling high-order interactions among features for effective sparse predictive analytics. As the volume of web-scale data grows exponentially over time, sparse predictive analytics inevitably involves dynamic and sequential features. However, existing FM-based models assume no temporal orders in the data, and are unable to capture the sequential dependencies or patterns within the dynamic features, impeding the performance and adaptivity of these methods. Hence, in this paper, we propose a novel Sequence-Aware Factorization Machine (SeqFM) for temporal predictive analytics, which models feature interactions by fully investigating the effect of sequential dependencies. As static features (e.g., user gender) and dynamic features (e.g., user interacted items) express different semantics, we innovatively devise a multi-view self-attention scheme that separately models the effect of static features, dynamic features and the mutual interactions between static and dynamic features in three different views. In SeqFM, we further map the learned representations of feature interactions to the desired output with a shared residual network. To showcase the versatility and generalizability of SeqFM, we test SeqFM in three popular application scenarios for FM-based models, namely ranking, classification and regression tasks. Extensive experimental results on six large-scale datasets demonstrate the superior effectiveness and efficiency of SeqFM.
Autonomic Provisioning of Backend Databases in Dynamic Content Web Servers (2006)

In autonomic provisioning, a resource manager allocates resources to an application, on-demand, e.g., during load spikes. Modelling-based approaches have proved very successful for provisioning the web and application server tiers in dynamic content servers. On the other hand, accurately modelling the behavior of the back-end database server tier is a daunting task. Hence, automated provisioning of database replicas has received comparatively less attention. This paper introduces a novel pro-active scheme based on the classic K-nearest-neighbors (KNN) machine learning approach for adding database replicas to application allocations in dynamic content web server clusters. Our KNN algorithm uses lightweight monitoring of essential system and application metrics in order to decide how many databases it should allocate to a given workload. Our pro-active algorithm also incorporates awareness of system stabilization periods after adaptation in order to improve prediction accuracy and avoid system oscillations. We compare this pro-active self-configuring scheme for scaling the database tier with a reactive scheme. Our experiments using the industry-standard TPC-W e-commerce benchmark demonstrate that the pro-active scheme is effective in reducing both the frequency and peak level of SLA violations compared to the reactive scheme. Furthermore, by augmenting the pro-active approach with awareness and tracking of system stabilization periods induced by adaptation in our replicated system, we effectively avoid oscillations in resource allocation.
Chemicals from Synthesis Gas: Catalytic Reactions of CO and H2 (1983)

1. Introduction to Petrochemicals.- 2. Mechanistic Principles.- 3. Hydrocarbon Synthesis.- 4. Olefin Hydroformylation.- 5. Olefin Carbonylation and Related Reactions.- 6. Methanol and Formaldehyde.- 7. Methanol Carbonylation and Related Chemistry.- 8. Nitrogen-Containing Systems.- 9. Direct Conversion of Syn Gas to Oxygenates.- 10. Summary - Directions for the Future.
Preface Vol. 6, No. 2, 2016 (2016)

This section contains the general information about the current volume of the journal viz. message from editor, brief introduction about authors of content in current volume, testimonial and motivational messages received by editor, and other covering/packaging content of the journal.
Face detection using gradient vector flow (2004)

Face detection is an important research area having wide applications in man-machine interface, visual surveillance and face recognition. We have proposed an algorithm for face detection using Gradient Vector Flow in gray level images which overcomes the problem for localization and initialization. The algorithm has been tested on various face databases and the result shows an accuracy of 97% with invariance to pose and orientation.
Synthesis of D‐(‐)‐[1,7‐<sup>13</sup>C<sub>2</sub>]shikimic acid (1992)

Abstract The chemical synthesis of 99% enriched D(‐)‐[1,7‐ 13 C 2 ]shikimic acid from [1,2‐ 13 C 2 ]acetate in 25% overall yield is described. A two‐carbon phosphonate synthon was prepared from [1,2‐ 13 C 2 ]acetate and used in the shikimate synthesis of Fleet and coworkers.
Static and Evolving Norovirus Genotypes: Implications for Epidemiology and Immunity (2017)

Noroviruses are major pathogens associated with acute gastroenteritis worldwide. Their RNA genomes are diverse, with two major genogroups (GI and GII) comprised of at least 28 genotypes associated with human disease. To elucidate mechanisms underlying norovirus diversity and evolution, we used a large-scale genomics approach to analyze human norovirus sequences. Comparison of over 2000 nearly full-length ORF2 sequences representing most of the known GI and GII genotypes infecting humans showed a limited number (≤5) of distinct intra-genotypic variants within each genotype, with the exception of GII.4. The non-GII.4 genotypes were comprised of one or more intra-genotypic variants, with each variant containing strains that differed by only a few residues over several decades (remaining "static") and that have co-circulated with no clear epidemiologic pattern. In contrast, the GII.4 genotype presented the largest number of variants (>10) that have evolved over time with a clear pattern of periodic variant replacement. To expand our understanding of these two patterns of diversification ("static" versus "evolving"), we analyzed using NGS the nearly full-length norovirus genome in healthy individuals infected with GII.4, GII.6 or GII.17 viruses in different outbreak settings. The GII.4 viruses accumulated mutations rapidly within and between hosts, while the GII.6 and GII.17 viruses remained relatively stable, consistent with their diversification patterns. Further analysis of genetic relationships and natural history patterns identified groupings of certain genotypes into larger related clusters designated here as "immunotypes". We propose that "immunotypes" and their evolutionary patterns influence the prevalence of a particular norovirus genotype in the human population.
Major O‐glycosylated sialoglycoproteins of human hematopoietic cells: Differentiation antigens with poorly understood functions (1988)

All human hematopoietic cells seem to contain a major, heavily O-glycosylated sialoglycoprotein. Glycophorin A is specific for the erythroid lineage of cells, and leukocytes have a major sialoglycoprotein, also called leukosialin or sialophorin. Cell differentiation results in patterns of O-glycosylation in these proteins, which reflect the stage of differentiation within a cell lineage as well as lineage specificity. The altered carbohydrate compositions may influence the interactions of the cells with external ligands. Healthy individuals lacking glycophorin A in their red cells are known, whereas a deficiency of the leukocyte sialoglycoprotein may result in immunological disease. Although little is known about the physiological functions of these proteins, they form interesting models for studies on regulation of glycosylation, biosynthesis of O-glycosylated glycoproteins, and function of cell surface receptors.
Assessment of Tip Shape Effect on Rotor Aerodynamic Performance in Hover (2015)

In the present study, an unstructured mixed mesh flow solver was used to conduct a numerical prediction of the aerodynamic performance of the S-76 rotor in hover. For the present mixed mesh methodology, the near-body flow domain was modeled by using body-fitted prismatic/tetrahedral cells while Cartesian mesh cells were filled in the off-body region. A high-order accurate weighted essentially non-oscillatory (WENO) scheme was employed to better resolve the flow characteristics in the off-body flow region. An overset mesh technique was adopted to transfer the flow variables between the two different mesh regions, and computations were carried out for three different blade configurations including swept-taper, rectangular, and swept-taper-anhedral tip shapes. The results of the simulation were compared against experimental data, and the computations were also made to investigate the effect of the blade tip Mach number. The detailed flow characteristics were also examined, including the tip-vortex trajectory, vortex core size, and first-passing tip vortex position that depended on the tip shape.
Friction and Wear of Hemiarthroplasty Biomaterials in Reciprocating Sliding Contact With Articular Cartilage (2011)

Friction and wear of four common orthopaedic biomaterials, alumina (Al2O3), cobalt-chromium (CoCr), stainless steel (SS), and crosslinked ultra-high-molecular-weight polyethylene (UHMWPE), sliding against bovine articular cartilage explants were investigated by reciprocating sliding, nanoscale friction and roughness measurements, protein wear assays, and histology. Under the experimental conditions of the present study, CoCr yielded the largest increase in cartilage friction coefficient, largest amount of protein loss, and greatest change in nanoscale friction after sliding against cartilage. UHMWPE showed the lowest cartilage friction coefficient, least amount of protein loss, and insignificant changes in nanoscale friction after sliding. Although the results are specific to the testing protocol and surface roughness of the examined biomaterials, they indicate that CoCr tends to accelerate wear of cartilage, whereas the UHMWPE shows the best performance against cartilage. This study also shows that the surface characteristics of all biomaterials must be further improved to achieve the low friction coefficient of the cartilage/cartilage interface.
Hover Pad (2014)

Handheld displays enable flexible spatial exploration of information spaces -- users can physically navigate through three-dimensional space to access information at specific locations. Having users constantly hold the display, however, has several limitations: (1) inaccuracies due to natural hand tremors; (2) fatigue over time; and (3) limited exploration within arm's reach. We investigate autonomous, self-actuated displays that can freely move and hold their position and orientation in space without users having to hold them at all times. We illustrate various stages of such a display's autonomy ranging from manual to fully autonomous, which -- depending on the tasks -- facilitate the interaction. Further, we discuss possible motion control mechanisms for these displays and present several interaction techniques enabled by such displays. Our Hover Pad toolkit enables exploring five degrees of freedom of self-actuated and autonomous displays and the developed control and interaction techniques. We illustrate the utility of our toolkit with five prototype applications, such as a volumetric medical data explorer.
Surveillance of Medical Device–Related Hazards and Adverse Events in Hospitalized Patients (2004)

More intensive surveillance methods yielded higher rates of medical device problems than found with traditional voluntary reporting, with little overlap between methods. Several detection methods had low efficiency in detecting AMDEs. The high rate of AMDEs suggests that AMDEs are an important patient safety issue, but additional research is necessary to identify optimal AMDE detection strategies.
Psychosocial Determinants of Childhood and Adolescent Obesity (2008)

The purpose of this article was to identify psychosocial determinants of childhood and adolescent obesity. Some of the determinants were considered non-modifiable such as genetics, sex, age, and race. The risk of developing obesity started early on in life, with high birth weight, rapid growth in infancy, maternal smoking during pregnancy, and lack of breastfeeding indicated as positive predictors. Family food environment and dietary behaviors were considered modifiable determinants and included: consumption of unhealthy foods, portion sizes, snacking, and number of family meals. Physical activity was also considered a protective factor against the development of obesity, with overweight children significantly less active than those who were non-overweight. Recommendations for successful interventions and future research were discussed.
In‐Vehicle AR‐HUD System to Provide Driving‐Safety Information (2013)

Augmented reality (AR) is currently being applied actively to commercial products, and various types of intelligent AR systems combining both the Global Positioning System and computer‐vision technologies are being developed and commercialized. This paper suggests an in‐vehicle head‐up display (HUD) system that is combined with AR technology. The proposed system recognizes driving‐safety information and offers it to the driver. Unlike existing HUD systems, the system displays information registered to the driver's view and is developed for the robust recognition of obstacles under bad weather conditions. The system is composed of four modules: a ground obstacle detection module, an object decision module, an object recognition module, and a display module. The recognition ratio of the driving‐safety information obtained by the proposed AR‐HUD system is about 73%, and the system has a recognition speed of about 15 fps for both vehicles and pedestrians.