Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for Deep Phylogenetic Conservation of Exonic Splice-Related Constraints: Splice-Related Skews at Exonic Ends in the Brown Alga Ectocarpus Are Common and Resemble Those Seen in Humans

The control of RNA splicing is often modulated by exonic motifs near splice sites. Chief among these are exonic splice enhancers (ESEs). Well-described ESEs in mammals are purine rich and cause predictable skews in codon and amino acid usage toward exonic ends. Looking across species, those with relatively abundant intronic sequence are those with the more profound end of exon skews, indicative of exonization of splice site recognition. To date, the only intron-rich species that have been analyzed are mammals, precluding any conclusions about the likely ancestral condition. Here, we examine the patterns of codon and amino acid usage in the vicinity of exon–intron junctions in the brown alga Ectocarpus siliculosus, a species with abundant large introns, known SR proteins, and classical splice sites. We find that amino acids and codons preferred/avoided at both 3′ and 5′ ends in Ectocarpus, of which there are many, tend, on average, to also be preferred/avoided at the same exon ends in humans. Moreover, the preferences observed at the 5′ ends of exons are largely the same as those at the 3′ ends, a symmetry trend only previously observed in animals. We predict putative hexameric ESEs in Ectocarpus and show that these are purine rich and that there are many more of these identified as functional ESEs in humans than expected by chance. These results are consistent with deep phylogenetic conservation of SR protein binding motifs. Assuming codons preferred near boundaries are “splice optimal” codons, in Ectocarpus, unlike Drosophila, splice optimal and translationally optimal codons are not mutually exclusive. The exclusivity of translationally optimal and splice optimal codon sets is thus not universal.
Using static analysis data for performance modeling and prediction

In general, high performance computing applications have large codebases composed of various scientific algorithms which must be tuned to achieve optimal speed. Therefore, a programmer extracts pieces of code from large programs, as candidates for the performance tuning. Maximizing such code performance requires measurement, analysis, and optimization strategies, targeting hardware components. Furthermore, computer architecture improvement raises hardware co-design issues such as measuring detailed computer performance. Currently, code execution time is well measured, but it is much harder to break out the performance contributory details per hardware resource in order to predict a code performance. This paper presents the Ubenchface tool, a framework for performance prediction and knowledge discovery. Inversely to traditional measurement methods and modeling, the proposed tool considers static metrics to analyze and tune application performance. This framework is more informative than simple benchmarking, or microbenchmarking. It is useful for performance investigations in similarity and redundancy study concerning benchmark suites, predicting, understanding scaling, and tuning.
A new approach for HIV-1 protease cleavage site prediction combined with feature selection

Acquired immunodeficiency syndrome (AIDS) is a fatal disease which highly threatens the health of human being. Human immunodeficiency virus (HIV) is the pathogeny for this disease. Investigating HIV-1 protease cleavage sites can help researchers find or develop protease inhibitors which can restrain the replication of HIV-1, thus resisting AIDS. Feature selection is a new approach for solving the HIV-1 protease cleavage site prediction task and it’s a key point in our research. Comparing with the previous work, there are several advantages in our work. First, a filter method is used to eliminate the redundant features. Second, besides traditional orthogonal encoding (OE), two kinds of newly proposed features extracted by conducting principal component analysis (PCA) and non-linear Fisher transformation (NLF) on AAindex database are used. The two new features are proven to perform better than OE. Third, the data set used here is largely expanded to 1922 samples. Also to improve prediction performance, we conduct parameter optimization for SVM, thus the classifier can obtain better prediction capability. We also fuse the three kinds of features to make sure comprehensive feature representation and improve prediction performance. To effectively evaluate the prediction performance of our method, five parameters, which are much more than previous work, are used to conduct complete comparison. The experimental results of our method show that our method gain better performance than the state of art method. This means that the feature selection combined with feature fusion and classifier parameter optimization can effectively improve HIV-1 cleavage site prediction. Moreover, our work can provide useful help for HIV-1 protease inhibitor developing in the future.
Endurance Exercise as a Countermeasure for Aging

OBJECTIVE— We determined whether reduced insulin sensitivity, mitochondrial dysfunction, and other age-related dysfunctions are inevitable consequences of aging or secondary to physical inactivity. RESEARCH DESIGN AND METHODS— Insulin sensitivity was measured by hyperinsulinemic-euglycemic clamp and ATP production in mitochondria isolated from vastus lateralis biopsies of 42 healthy sedentary and endurance-trained young (18–30 years old) and older (59–76 years old) subjects. Expression of proteins involved in fuel metabolism was measured by mass spectrometry. Citrate synthase activity, mitochondrial DNA (mtDNA) abundance, and expression of nuclear-encoded transcription factors for mitochondrial biogenesis were measured. SIRT3, a mitochondrial sirtuin linked to lifespan-enhancing effects of caloric restriction, was measured by immunoblot. RESULTS— Insulin-induced glucose disposal and suppression of endogenous glucose production were higher in the trained young and older subjects, but no age effect was noted. Age-related decline in mitochondrial oxidative capacity was absent in endurance-trained individuals. Although endurance-trained individuals exhibited higher expression of mitochondrial proteins, mtDNA, and mitochondrial transcription factors, there were persisting effects of age. SIRT3 expression was lower with age in sedentary but equally elevated regardless of age in endurance-trained individuals. CONCLUSIONS— The results demonstrate that reduced insulin sensitivity is likely related to changes in adiposity and to physical inactivity rather than being an inevitable consequence of aging. The results also show that regular endurance exercise partly normalizes age-related mitochondrial dysfunction, although there are persisting effects of age on mtDNA abundance and expression of nuclear transcription factors and mitochondrial protein. Furthermore, exercise may promote longevity through pathways common to effects of caloric restriction.
The role of philosophical context in the development of theory: Towards methodological pluralism

The research strategy dictates the major direction of the research and constitutes one of the important decisions made by the researcher. However, researchers’ understanding on theory at the outset of the research guides the design of the research. The paper presents an overview of the involvement of theory within different research philosophies, approaches and methods. The relationship between data and theory is an issue that has been long debated. Moving from data to theory is commonly discussed in social constructionism with inductive approach and ideographic methods. However, within positivism philosophy with deductive approach and nomothetic methods, moving from theory to data is common. However, the growing concept of philosophical pluralism and methodological pluralism challenges the polarised views on philosophies and approaches, which suggests that methodologies are best used in complementary way.
Image processing and face detection analysis on face verification based on the age stages

The availability of computer systems has created a variety of automated applications in personal identification. From the various characteristics of biometrics, face recognition techniques mainly face verification has become an area of active research and the application are important in law enforcement because it can be done without involving the subject. However, the influence of age progression on face verification become a challenge to determine the similarity of image pairs from individual faces considering very limited of data base availability. This paper focuses on the development of image processing and face detection on face verification system by improving the image quality. The research use computer simulation, comparative studies, and analytical studies. The simulation of image processing using PhotoScape v3.5 software, while the verification using VeriLook 5.0/MegaMatcher VeriLook 4.0 Algorithm Demo. In the early step, database of face images are grouped by the age stages of education, then the simulation process includes the process of image processing, the enrolment process, and the verification process. The simulation results show the combination of image processing with contrast and sharpen increase the enrolment process by 17.14% with maximum success rate reaches 100%, where the entire 70-images training enrolled successfully. In verification process, the results of the combination increase the success rate of matching faces by 13.57%, where 96 image pairs successfully matched from a total of 140.
Boekbesprekingen van G.H.M. Evers, De economische waarde van werknemers, W.A.M. de Lange, Bouwstenen van de duurzame arbeidsorganisatie en R. Peccei, Human resource management and the search for the happy workplace

The analysis of the impact of human resource (HR) practices on employee well-being at work is an important yet relatively neglected area of inquiry within the field of human resource management (HRM). In this inaugural address, the main findings from ongoing research based on data from the 1998 British Workplace Employee Relations Survey (WERS98) are presented. These suggest that the HR practices that are adopted by organisations have a significant impact on the well-being of their workforces and that this impact tends, on the whole, to be more positive than negative. The effects, however, are more complex than is normally assumed in the literature. In particular, preliminary results indicate that the constellation of HR practices that help to maximise employee well-being (i.e. that make for happy workplaces), are not necessarily the same as those that make up the type of ‘High Performance Work Systems’ commonly identified in the literature. This has important theoretical, policy and ethical implications for the field of HRM. These are discussed along with important directions for future research.
Laparoscopic robotic total gastrectomy

Minimally invasive gastrectomy has become the standard of care in many centers in Asia but remains unpopular in Europe. The aim of this article is to present the technique of laparoscopic robot-assisted total gastrectomy. The presented case involved a 66-year-old female patient with an advanced gastric cancer on the lesser curvature of the stomach. The laparoscopic part of the procedure involved opening the lesser sac, mobilization of the greater curvature and transection of the duodenum. A robot was used for the D2 lymphadenectomy and creation of the anastomosis. In summary, we have found that during a total gastrectomy for advanced gastric cancer a successful oncological resection can be achieved using a minimally invasive approach. We have also found that by combining conventional laparoscopy with robotic assistance we could overcome the technical difficulties with regards to lymph node dissection and anastomosis.
Effect of superior–subordinate intergenerational conflict on job performance of new generation employees

We analyzed the influence of superior–subordinate intergenerational conflict on the job performance of 498 employees of Chinese enterprises born since 1980 (new generation employees). Results of a survey showed that the 3 dimensions of superior–subordinate intergenerational conflict, namely task conflict, relationship conflict, and procedural conflict, all had a significantly negative influence on the employees’ work engagement and job performance; work engagement exerted a significantly positive influence on job performance; work engagement played a partial mediating role in the relationship between both relationship conflict and procedural conflict and job performance, and fully mediated the relationship between task conflict and job performance; tolerance and confrontation in conflict resolution had a significantly moderating effect on the relationships between all 3 dimensions of superior–subordinate intergenerational conflict and work engagement; and coordination played a significant moderating role on the relationship between both task and procedural conflict and work engagement, but the role of coordination as a moderator in the relationship between relationship conflict and work engagement was nonsignificant. Theoretical contributions are discussed and options for practical guidance offered.
Mining the Heterogeneous Transformations between Data Sources to Aid Record Linkage

Heterogeneous transformations are translations between strings that are not characterized by a single function. E.g., nicknames, abbreviations and synonyms are heterogeneous transformations while edit distances are not. Such transformations are useful for information retrieval, information extraction and text understanding. They are especially useful in record linkage, where the problem is to determine whether two records refer to the same entity by examining the similarities between their fields. However, heterogeneous transformations are usually created manually and without assurance they will be useful. This paper presents a data mining approach to discover heterogeneous transformations between two data sets, without labeled training data, which can then be used to aid record linkage. In addition to simple transformations, our algorithm finds combinatorial transformations, such as synonyms and abbreviations together. Our experiments demonstrate that our approach can discover many types of specialized transformations, and we show that by exploiting these transformations we can improve record linkage accuracy. Our approach makes discovering and exploiting heterogeneous transformations more scalable and robust by lessening the domain and human dependencies.
The effects of exercise and two pre-exercise fluid amounts on cognition

Exercise is associated with elevated mood states and arousal. Observational studies support the claim that exercise can help individuals think more “clearly’ with reports of improved mood and feelings of psychological well-being following exercise. However, laboratory studies have produced equivocal results. The purpose of this study is to examine the effect of exercise intensity and two likely pre-exercise fluid amounts consumed by euhydrated athletes on cognitive performance. Fifteen college age students were randomly assigned to either a 150 ml or a 500 ml fluid condition on the first test day and received the other fluid condition on the second test day. Prior to exercise subjects completed baseline computerized cognitive tests then began a treadmill protocol of three 6 min stages at increasing intensity after which subjects completed cognitive tests. A second treadmill portion started at 7.5 mph for 2 min then speed was increased 0.5 mph every 30 s until voluntary exhaustion and final cognitive testing was completed. Our results demonstrate a facilitation of cognitive function in response to exercise with the exception of the match to sample cognitive test which showed lack of facilitation of cognition in the 500 ml condition at moderate exercise. Our research contributes to the growing field of exercise and its effects on cognition. Specifically working memory cognitive tests showed facilitation with exercise. These results may be applicable to a typical exercising population since our study included a common exercise mode (treadmill) at moderate and high intensities and likely fluid amounts.
Automatic Detection of Vulnerable Dynamic Component Loadings

Dynamic loading of software components (e.g., libraries or modules) is a widely used mechanism for improved system modularity and flexibility. In general, an operating system or a runtime environment resolves the loading of a specifically named component by searching for its first occurrence in a sequence of directories determined at runtime. Correct component resolution is critical for reliable and secure software execution, however, programming mistakes may lead to unintended or even malicious components to be resolved and loaded. In particular, dynamic loading can be hijacked by placing an arbitrary file with the specified name in a directory searched before resolving the target component. Although this issue has been known for quite some time, it was not considered serious because exploiting it requires access to the local file system on the vulnerable host. Recently such vulnerabilities started to receive considerable attention as their remote exploitation became realistic; it is now important to detect and fix these vulnerabilities. In this paper, we present the first automated technique to detect vulnerable and unsafe dynamic component loadings. We classify two types of unsafe dynamic loadings—resolution failure and resolution hijacking—and develop an effective dynamic program analysis to detect both types. A resolution failure happens when the target component cannot be located in any of the searched directories, while a resolution hijacking happens when there exist other directories searched before the directory containing the target component. Our analysis has two phases: 1) apply dynamic binary instrumentation to collect runtime information on component loading (online phase); and 2) analyze the collected information to detect vulnerable component loadings (offline phase). For evaluation, we implemented our technique to detect vulnerable and unsafe DLL loadings in popular Microsoft Windows software. Our results show that unsafe DLL loading is prevalent and can lead to serious security threats. Our tool detected more than 1,700 unsafe DLL loadings in 28 widely used software and discovered serious attack vectors for remote code execution. Microsoft has opened a Microsoft Security Response Center (MSRC) case on our reported issues and is working with us to develop necessary patches.
Evaluating the Self-Optimization Process of the Adaptive Memory Management Architecture Self-aware Memory

With the continuously increasing integration level, manycore processor systems are likely to be the coming system structure not only in HPC but also for desktop or mobile systems. Nowadays manycore processors like Tilera TILE, KALRAY MPPA or Intel SCC combine a rising number of cores in a tiled architecture and are mainly designed for high performance applications with focus on direct inter-core communication. The current architectures have limitations by central or sparse components like memory controllers, memory I/O or inflexible memory management. In the future highly dynamic workloads with multiple concurrently running applications, changing I/O characteristics and a not predictable memory usage have to be utilized on these manycore systems. Consequently the memory management has to become more flexible and distributed in nature and adaptive mechanisms and system structures are needed. With Self-aware Memory (SaM), a decentralized, scalable and autonomous self-optimizing memory architecture is developed. This adaptive memory management can achieve higher flexibility and an easy usage of memory. In this paper the concept of an ongoing decentralized self-optimization is introduced and the evaluation of its various parameters is presented. The results show that the overhead of the decentralized optimization process is amortized by the optimized runtime using the appropriate parameter settings.
Mining input sanitization patterns for predicting SQL injection and cross site scripting vulnerabilities

Static code attributes such as lines of code and cyclomatic complexity have been shown to be useful indicators of defects in software modules. As web applications adopt input sanitization routines to prevent web security risks, static code attributes that represent the characteristics of these routines may be useful for predicting web application vulnerabilities. In this paper, we classify various input sanitization methods into different types and propose a set of static code attributes that represent these types. Then we use data mining methods to predict SQL injection and cross site scripting vulnerabilities in web applications. Preliminary experiments show that our proposed attributes are important indicators of such vulnerabilities.
Long-Term Return Reversal: Evidence from International Market Indices

This paper documents evidence of reversals in the long-term returns of international equity markets. We use recent short-term performance to better select contrarian securities that appear ready to reverse. Our late-stage contrarian strategy consistently provides stronger evidence of long-term return reversal than does the traditional pure contrarian strategy when applied to developed and emerging market indices. Despite an absence of cross-sectional contrarian profits for developed markets in our post-1989 subsample, longitudinal analysis provides strong evidence of reversals during this period. Overall, our results suggest that the reversal of long-term returns may be stronger and more pervasive than is generally understood.
Identification of critical genes and gene interaction networks that mediate osteosarcoma metastasis to the lungs

Osteosarcoma (OS) is the most commonly diagnosed bone tumor in young adults under the age of 20. Metastasis is considered an important factor underlying cancer-associated morbidity and mortality, and, as a result, the survival rate of patients with metastatic OS is low. In spite of this, the mechanisms underlying metastasis in OS are currently not well understood. The present study compared gene expression levels between five non-metastatic and four metastatic OS tumor samples, using an Affymetrix microarray. A total of 282 genes were differentially expressed in the metastatic samples, as compared with the non-metastatic samples. Of these differentially expressed genes (DEGs), 212 were upregulated and 70 were downregulated. The following DEGs were associated with metastasis: Homeobox only protein; lysosomal-associated membrane protein-3; chemokine (C-C motif) ligand-18; carcinoembryonic antigen-related cell adhesion molecule-6; keratin-19; prostaglandin-endoperoxide synthase-2; clusterin; and nucleoside diphosphate kinase-1. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses were conducted, which identified 529 biological processes (P<0.01) and 10 KEGG pathways (P<0.05) that were significantly over-represented in the metastatic samples, as compared with the non-metastatic samples. Interaction networks for the DEGs were constructed using the corresponding GO terms and KEGG pathways, and these identified numerous genes that may contribute to OS metastasis. Among the enriched biological processes, four DEGs were consistently over-represented: Jun proto-oncogene, caveolin-1, nuclear factor-κB-inhibitor-α and integrin alpha-4; thus suggesting that they may have key roles in OS metastasis, and may be considered potential therapeutic targets in the treatment of patients with OS.