Miracle-dz/UniFAR-FTUs huggingface dataset:
Kokkos implementation of Albany: a performance-portable finite element application.

Modern HPC applications need to be run on many different platforms and performance portability has become a critical issue: parallel code needs to be executed correctly and performant despite variation in the architecture, operating system and software libraries. The numerical solution of partial differential equations using the finite element method is one of the key applications of high performance computing. This poster presents a performance portable implementation of the the finite element assembly in the Albany code, based on Kokkos programming model from Trilinos. Evaluation experiments show good performance results for a single implementation across three multicore/manycore architectures: NVIDIA GPUs, Multicore CPUs, Intel Xeon Phi.
Contextual cueing based on specific and categorical properties of the environment

During the analysis of a visual scene, top-down processing is constantly directing the subject's attention to the zones of interest in the scene. The contextual cueing paradigm developed by Chun and Jiang (1998) shows how contextual regularities can facilitate the search for a particular element via implicit learning mechanisms. The study presented here reports three experiments that used this paradigm. Experiment 1 showed that regularities in the specific elements of the context can act as cues to the location of the target. Experiments 2 and 3 explored a novel aspect of contextual regularities, namely semantic regularities based on the categorization of contextual elements. Contextual cueing effects were obtained when semantic-category membership of the context predicted the target location. Moreover, in all three experiments, contextual cueing effects were obtained implicitly. The results suggest that in target-detection tasks, implicit learning can be based not only on the specific constituents of the context, but also on the semantic categories of those constituents, depending on their predictive power.
Apoptotic Index and Mib-1 Antibody Expression in Premalignant and Malignant Lesions of Uterine Cervix

Introduction: Cervical cancers are the second most frequent type of female cancer, responsible for about 5% of cancer deaths in females worldwide. Recently, parameters of cell proliferation and cell death have emerged as important diagnostic and prognostic tools. Aims: The aim was to evaluate the role of Apoptotic Index and Ki-67 as proliferation marker in premalignant and malignant lesions of uterine cervix. Materials and Methods: The study included 179 patients of cervical dysplasias and malignancy. Evaluation of Apoptotic Index (using light microscopy) was performed on hematoxylin and eosin-stained sections. Ki-67 (MIB-1 antibody) expression was both graded as well as Labelling Index was calculated. Statistical evaluation was carried out using the Student t test (p<0.05). Results: There was increase in mean Apoptotic Index with increasing grade of dysplasia and difference in mean values between CIN-I and CIN-II; CIN-I and CIN-III were found to be statistically significant. Also Apoptotic Index increased from well differentiated Squamous Cell Carcinoma (SCC) to poorly differentiated SCC. There was increase in mean Labelling Index with increasing grade of dysplasia and when the p value amongst these groups was statistically significant. Labelling Index was maximum in Poorly Differentiated SCC and minimum in Moderatly Differentiated SCC and p value amongst these groups was found to be statistically significant. Conclusion: Both Apoptotic Index and Ki-67 expression could be used as a biomarkers in the evaluation of the proliferative activity and progressive potential of dysplastic and neoplastic changes.
Emotions Emerge from More Basic Psychological Ingredients: A Modern Psychological Constructionist Model

Over a century ago, William James outlined the first psychological constructionist model of emotion, arguing that emotions are phenomena constructed of more basic psychological parts. In this article, I outline a modern psychological constructionist model of emotion. I first explore the history of psychological construction to demonstrate that psychological constructionist models have historically emerged in an attempt to explain variability in emotion that cannot be accounted for by other approaches. I next discuss the modern psychological constructionist model of emotion that I take in my own research, outlining its hypotheses, existing empirical support, and areas of future research. I conclude by arguing that psychological constructionist models can help scientists better understand the human mind.
SPTF: A Scalable Probabilistic Tensor Factorization Model for Semantic-Aware Behavior Prediction

With the rapid rise of various e-commerce and social network platforms, users are generating large amounts of heterogeneous behavior data, such as purchasehistory, adding-to-favorite, adding-to-cart and click activities, and this kind of user behavior data is usually binary, only reflecting a user's action or inaction (i.e., implicit feedback data). Tensor factorization is a promising means of modeling heterogeneous user behaviors by distinguishing different behavior types. However, ambiguity arises in the interpretation of the unobserved user behavior records that mix both real negative examples and potential positive examples. Existing tensor factorization models either ignore unobserved examples or treat all of them as negative examples, leading to either poor prediction performance or huge computation cost. In addition, the distribution of positive examples w.r. t. behavior types is heavily skewed. Existing tensor factorization models would bias towards the type of behaviors with a large number of positive examples. In this paper, we propose a scalable probabilistic tensor factorization model (SPTF) for heterogeneous behavior data and develop a novel negative sampling technique to optimize SPTF by leveraging both observed and unobserved examples with much lower computational costs and higher modeling accuracy. To overcome the issue of the heavy skewness of the behavior data distribution, we propose a novel adaptive ranking-based positive sampling approach to speed up the model convergence and improve the prediction accuracy for sparse behavior types. Our proposed model optimization techniques enable SPTF to be scalable to large-scale behavior datasets. Extensive experiments have been conducted on a large-scale e-commerce dataset, and the experimental results show the superiority of our proposed SPTF model in terms of prediction accuracy and scalability.
Apparent seasonal cycle in isotopic discrimination of carbon in the atmosphere and biosphere due to vapor pressure deficit

We explore seasonal variability in isotopic fractionation by analyzing observational data from the atmosphere and the biosphere, as well as simulated data from a global model. Using simulated values of atmospheric CO2 and its carbon isotopic composition, we evaluated different methods for specifying background concentrations when calculating the isotopic signature of source CO2 (δs) to the atmosphere. Based on this evaluation, we determined that free troposphere measurements should be used when available as a background reference when calculating δs from boundary layer observations. We then estimate the seasonal distribution of δs from monthly climatologies derived from several atmospheric sampling sites. This approach yields significant seasonal variations in δs with more enriched values during the summer months that exceed the uncertainty of δs estimated for any given month. Intra‐annual measurements of δ13C in the cellulose of Pinus taeda growing in the southeastern U.S. also reveal seasonal isotopic variations that are consistent in phase but not necessarily amplitude with atmospherically derived estimates of δs. Coherent seasonal patterns in δs inferred from the atmosphere and observed in the biosphere were not consistent with the seasonal isotopic discrimination simulated by a commonly used biosphere model. However, δs seasonality consistent with observations from the atmosphere and biosphere was retrieved with a revised biosphere model when stomatal conductance, and thus isotopic discrimination, was allowed to vary in response to vapor pressure deficit rather than relative humidity. Therefore, in regions where vapor pressure deficit and relative humidity are positively covariant over the growth season, such as the sub‐tropics, different stomatal conductance models may yield very different estimates of CO2 and H2O exchange between the biosphere and atmosphere.
Using concept mapping for maintainability assessments

Many important phenomena within software engineering are difficult to define and measure. One example is software maintainability, which has been the subject of considerable research and is believed to be a critical determinant of total software costs. We propose using concept mapping, a well-grounded method used in social research, to operationalize the concept of software maintainability according to a given goal and perspective in a concrete setting. We apply this method to describe four systems that were developed as part of an industrial multiple-case study. The outcome is a conceptual map that displays an arrangement of maintainability constructs, their interrelations, and corresponding measures. Our experience is that concept mapping (1) provides a structured way of combining static code analysis and expert judgment; (2) helps in the tailoring of the choice of measures to a particular system context; and (3) supports the mapping between software measures and aspects of software maintainability. As such, it constitutes a useful addition to existing frameworks for evaluating quality, such as ISO/IEC 9126 and GQM, and tools for static measurement of software code. Overall, concept mapping provides a systematic, structured, and repeatable method for developing constructs and measures, not only of maintainability, but also of software engineering phenomena in general.
USING ENCRYPTION AND TRUSTED THIRD PARTIES TO ENABLE DATA ANONYMITY IN THE FLOCKS ARCHITECTURE : A PRIVACY ENHANCING TECHNOLOGY

In recent years, the right of the privacy of the employee and the right of a company to monitor Web traffic through its own network has been heatedly debated. Flocks is a Privacy Enhancing Technology (PET) used within an organization to balance both the need for Web usage anonymity by employees and the need for administrators to trace misusers of the World Wide Web. Flocks operate by establishing a number of Web proxies, which randomly forward requests to each other (or to the destination Web server). User anonymity is preserved as no single proxy can determine the sender of the message. The current Flocks technology has several shortcomings. One problem is that the communication between the Flock proxies is unencrypted, and thus an administrator of any proxy can read the Web request in plaintext. These logs can compile a huge dossier of information which can be used for illicit purposes against the employee and without the employee’s consent. The aim of the paper is to investigate the use of cryptographic techniques to secure data anonymity while maintaining similar levels of connection anonymity of Crowds and Flocks. We introduce external trusted third parties in addition to the encrypted Flocks system to provide data anonymity for the Flocks architecture. We analyse the new Flocks architecture against various attacks from a threat model. The resulting improved Flocks technology will improve the anonymity of Web users in an organisation.
Peristaltic Flow in a non-Uniform Channel with Heat and Mass Transfer

The combined effect of heat and mass transfer on the peristaltic flow of fourth grade fluid in a non-uniform channel has been investigated. Flow analysis has been carried out in the presence of an induced magnetic field. The governing flow equations have been transformed in a wave frame. The arising equations have been solved for the stream function, pressure gradient, temperature, concentration, magnetic force function, induced magnetic field and current density. The role of embedded parameters is displayed and discussed.
Transgenic Arabidopsis thaliana containing increased levels of ATP and sucrose is more susceptible to Pseudomonas syringae

Disease resistance exerts a fitness cost on plants, presumably due to the extra consumption of energy and carbon. In this study, we examined whether transgenic Arabidopsis thaliana with increased levels of ATP and sucrose is more resistant or susceptible to pathogen infection. Lines of A. thaliana over-expressing purple acid phosphatase 2 (AtPAP2) (OE lines) contain increased levels of ATP and sucrose, with improved growth rate and seed production. Compared to wild type (WT) and pap2 lines, the OE lines were more susceptible to several Pseudomonas syringae pv. tomato (Pst) strains carrying AvrRpm1, AvrRpt2 AvrRps4, AvrPtoB, HrcC and WT strain DC3000. The increased susceptibility of the OE lines to Pst strains cannot solely be attributed to the suppressed expression of R-genes but must also be attributed to the suppression of downstream signaling components, such as MOS2, EDS1 and EDS5. Before infection, the levels of salicylic acid (SA) and jasmonic acid (JA) precursor OPDA were similar in the leaves of OE, pap2 and WT plants, whereas the levels of JA and its derivative JA-Ile were significantly lower in the leaves of OE lines and higher in the pap2 line. The expression of JA marker defense gene PDF1.2 was up-regulated in the OE lines compared to the WT prior to Pst DC3000 infection, but its expression was lower in the OE lines after infection. In summary, high fitness Arabidopsis thaliana exhibited altered JA metabolism and broad suppression of R-genes and downstream genes as well as a higher susceptibility to Pst infections.
Production and use of antibodies for the detection of Taura syndrome virus in penaeid shrimp

Monoclonal (MAb) and polyclonal (PAb) ant ibod~es were produced agalnst the penaeld shnmp virus, Taura syndrome virus (TSV), ~sola ted from naturally infected Penaeus vannamel from farms in Ecuador, Hawall and Texas The PAbs produced in both chickens and mice were capable of detecting TSV In the hernolymph of shnmp duiiny the acute phase ot ~nfection by a n irnmunoblot assay The MAbs were produced using BALB/cByJ mouse spleen cells fused with non-iinmunoglobulinsecreting SP2/0-Ag-14 mouse n~yeloma cells Three MAbs of different immunoglobul~n lsotypes (IgGy I K IgGy 2 b ~ and IgGy 3 ~ ) were compared in an lmrnunoblot assay to deterrmne their r e a c t ~ v ~ t y o hemolymph from TSV-infected shnmp during the acute and chronlc phases of ~nfection and their crossleactivity if any w ~ t h other shrlmp viruses Western blots of purified TSV were used to compare the specificities of the 3 MAbs for the stluctural protelns of the vlrus The MAbs were used to inonitor a laboratory-lnduced TSV infection In juvenile P vannaniel, and they were capable of detecting the virus in the hemolymph of both acute and chromc phase samples The results with chronlc phase hemolymph samples were vanable and indicated the need to develop an lmmunoassay in which the virus In a sample is captured by one antlbody and then detected w ~ t h a second an t~body The availabil~ty of MAbs with different speclfic~ties for TSV viral proteins and the ability to produce PAbs in chickens w l l make it possible to develop a sensitive captuie assay for rapid detection of the virus In f ~ e l d situations
STRENGTH TRAINING METHODS AND THE WORK OF ARTHUR JONES

This paper reviews research evidence relating to the strength training advice offered by Arthur Jones, founder and retired Chairman of Nautilus Sports/Medical Industries and MedX Corporation. Jones advocated that those interested in improving their muscular size, strength, power and/or endurance should perform one set of each exercise to muscular failure (volitional fatigue), train each muscle group no more than once (or, in some cases, twice) per week, perform each exercise in a slow, controlled manner and perform a moderate number of repetitions (for most people, ~8-12). This advice is very different to the strength training guidelines offered by the National Strength and Conditioning Association, the American College of Sports Medicine and most exercise physiology textbooks. However, in contrast to the lack of scientific support for most of the recommendations made by such bodies and in such books, Jones’ training advice is strongly supported by the peer-reviewed scientific literature, a statement that has recently been supported by a review of American College of Sports Medicine resistance training guidelines. Therefore, we strongly recommend Jones’ methods to athletes and coaches, as they are time-efficient and optimally efficacious, and note that, given his considerable contribution to the field of strength training, academic recognition of this contribution is long overdue.
Dynamic Local Models for Online Recommendation

With the explosion of the volume of user-generated data, designing online recommender systems that learn from data streams has become essential. These systems rely on incremental learning that continuously update models as new observations arrive and they should be able to adapt to drifts in real-time. User preferences evolve over time and tracking their evolution is not an easy task. In addition to the low number of observations available per user, the preferences change at different moments and in different ways for each individual. In this paper, we propose a novel approach based on local models to address this problem. Local models are known for their ability to capture diverse preferences among user subsets. Our approach automatically detects the drift of preferences that leads a user to adopt a behavior closer to the users of another subset, and adjusts the models accordingly. Our experiments on real world datasets show promising results and prove the effectiveness of using local models to adapt to changes in user preferences.
Scholarly texts flavoured with conversational features : A corpus-based study of Hungarian EFL learners

This paper deals with the use of corpus linguistics to promote better academic writing. To explore Hungarian undergraduate EFL learners’ awareness of academic vocabulary register conventions a learner corpus was compiled, and particular vocabulary items were then compared with the academic and spoken subcorpora of the BNC to establish similarities or differences with native academic writing or spoken language by counting frequency of use. The results largely confirm and coincide with previous (multicultural) research results, which demonstrate a considerable amount of stylistically inappropriate, colloquial lexical features in undergraduates’ academic writing.
Mizan: a system for dynamic load balancing in large-scale graph processing

Pregel [23] was recently introduced as a scalable graph mining system that can provide significant performance improvements over traditional MapReduce implementations. Existing implementations focus primarily on graph partitioning as a preprocessing step to balance computation across compute nodes. In this paper, we examine the runtime characteristics of a Pregel system. We show that graph partitioning alone is insufficient for minimizing end-to-end computation. Especially where data is very large or the runtime behavior of the algorithm is unknown, an adaptive approach is needed. To this end, we introduce Mizan, a Pregel system that achieves efficient load balancing to better adapt to changes in computing needs. Unlike known implementations of Pregel, Mizan does not assume any a priori knowledge of the structure of the graph or behavior of the algorithm. Instead, it monitors the runtime characteristics of the system. Mizan then performs efficient fine-grained vertex migration to balance computation and communication. We have fully implemented Mizan; using extensive evaluation we show that---especially for highly-dynamic workloads---Mizan provides up to 84% improvement over techniques leveraging static graph pre-partitioning.
Reliability Estimation Process

The design space of integrated circuits grows due to the need of fault recognition and error compensation. To meet reliability requirements, several reliability increasing methods have to be evaluated. We present a reliability estimation process which allows estimating the resulting reliability of a modified circuit without the need of synthesis. For further speed up, synthesis results after choosing a reliability increasing methods are analyzed. The process is applied to a case study which proves applicability.
Carotid Artery Wall Imaging: Perspective and Guidelines from the ASNR Vessel Wall Imaging Study Group and Expert Consensus Recommendations of the American Society of Neuroradiology

SUMMARY: Identification of carotid artery atherosclerosis is conventionally based on measurements of luminal stenosis and surface irregularities using in vivo imaging techniques including sonography, CT and MR angiography, and digital subtraction angiography. However, histopathologic studies demonstrate considerable differences between plaques with identical degrees of stenosis and indicate that certain plaque features are associated with increased risk for ischemic events. The ability to look beyond the lumen using highly developed vessel wall imaging methods to identify plaque vulnerable to disruption has prompted an active debate as to whether a paradigm shift is needed to move away from relying on measurements of luminal stenosis for gauging the risk of ischemic injury. Further evaluation in randomized clinical trials will help to better define the exact role of plaque imaging in clinical decision-making. However, current carotid vessel wall imaging techniques can be informative. The goal of this article is to present the perspective of the ASNR Vessel Wall Imaging Study Group as it relates to the current status of arterial wall imaging in carotid artery disease.
Finding Diego: A Bilingual Student Integrates School, Language, and Identity

ABSTRACT This article presents a mixed-methods case study of Diego, a bilingual teen who completed public school in Florida. During adolescence, Diego negotiated multiple identities: successful student, Mexican American, bilingual, and typical U.S. teenager. Diego provided interviews and bilingual (English/Spanish) writing (narrative/expository) in 2008 (at age 12, Grade 6) and in 2012 (at age 16, Grade 10). A qualitative analysis of his interviews and a quantitative linguistic analysis of his writing reveal central elements of Diego’s language development as related to academic English and identity. Educational implications for working with bilingual adolescents are discussed.
Performance Optimization Problem in Speculative Prefetching

Speculative prefetching has been proposed to improve the response time of network access. Previous studies in speculative prefetching focus on building and evaluating access models for the purpose of access prediction. This paper investigates a complementary area which has been largely ignored, that of performance modeling. We analyze the performance of a prefetcher that has uncertain knowledge about future accesses. Our performance metric is the improvement in access time, for which we derive a formula in terms of resource parameters (time available and time required for prefetching) and speculative parameters (probabilities for next access). We develop a prefetch algorithm to maximize the improvement in access time. The algorithm is based on finding the best solution to a stretch knapsack problem, using theoretically proven apparatus to reduce the search space. An integration between speculative prefetching and caching is also investigated.