Miracle-dz/UniFAR-FTUs huggingface dataset:
Construction of null statistics in permutation-based multiple testing for multi-factorial microarray experiments

MOTIVATION The parametric F-test has been widely used in the analysis of factorial microarray experiments to assess treatment effects. However, the normality assumption is often untenable for microarray experiments with small replications. Therefore, permutation-based methods are called for help to assess the statistical significance. The distribution of the F-statistics across all the genes on the array can be regarded as a mixture distribution with a proportion of statistics generated from the null distribution of no differential gene expression whereas the other proportion of statistics generated from the alternative distribution of genes differentially expressed. This results in the fact that the permutation distribution of the F-statistics may not approximate well to the true null distribution of the F-statistics. Therefore, the construction of a proper null statistic to better approximate the null distribution of F-statistic is of great importance to the permutation-based multiple testing in microarray data analysis. RESULTS In this paper, we extend the ideas of constructing null statistics based on pairwise differences to neglect the treatment effects from the two-sample comparison problem to the multifactorial balanced or unbalanced microarray experiments. A null statistic based on a subpartition method is proposed and its distribution is employed to approximate the null distribution of the F-statistic. The proposed null statistic is able to accommodate unbalance in the design and is also corrected for the undue correlation between its numerator and denominator. In the simulation studies and real biological data analysis, the number of true positives and the false discovery rate (FDR) of the proposed null statistic are compared with those of the permutated version of the F-statistic. It has been shown that our proposed method has a better control of the FDRs and a higher power than the standard permutation method to detect differentially expressed genes because of the better approximated tail probabilities.
Small-scale curriculum changes for improving pre-service teachers’ preparation for Family-School Partnerships

Abstract Family-School Partnerships (FSP) are important for students’ academic achievements and social-emotional development. Therefore, pre-service teachers need to learn how to establish this. However, in teacher education programmes this topic is insufficiently addressed partially attributed to already overloaded programmes. This study reports on a small-scale curriculum change, aiming to foster pre-service teachers’ awareness of the importance of FSP, to broaden their concepts and support them in identifying learning goals for the future. An assignment to interview novice-teachers about FSP was followed by a class on this topic. Afterwards, pre-service teachers reported in written reflections that they had become aware of the importance of FSP, emphasising that FSP is more than just communication. However, their focus for further professionalisation remained on improving their communication skills. Though this small-scale curriculum change seems to be a small step forward to a better preparation on FSP, further improvements are necessary to promote a comprehensive view of FSP.
Immunotherapy of cancer with pressure modified cells.

Immunotherapy of human cancer has proven to be of limited clinical value thus far, largely because of its failure to overcome the multiple escape strategies deployed by tumor cells [1]. Renewed interest in cancer immunotherapy was stimulated in recent years by the identification of distinct tumor antigens that are capable of eliciting specific anti-tumor cytotoxic immune responses in vitro as well as in vivo. However, the availability of synthetic or purified tumor antigens may not in itself be sufficient to offer an improved therapeutic modality, since tumor antigens are numerous, metastatic tumor cells mutate frequently thereby altering their antigenic nature, and the immunogenic hierarchy of various tumor antigens is largely unknown [2]. The basic principles underlying tumor immunology that have evolved considerably over the past 40 years are straightforward:
Diversity and Homogeneity among Small Plasmids of Aeromonas salmonicida subsp. salmonicida Linked with Geographical Origin

Furunculosis, which is caused by Aeromonas salmonicida subsp. salmonicida, is a major salmonid disease in fish farms worldwide. Several plasmids found in this bacterium confer phenotypes such drug resistance and virulence. Small plasmids (pAsa1, pAsa2, pAsa3, and pAsal1) related to ColE1- and ColE2-type replicons are usually present in its normal plasmidome. In the present study, with the objective to investigate if these plasmids display particularities related to the origin of the isolates bearing them, a total of 153 isolates, including 78 new and 75 previously described, were analyzed for the presence of small plasmids by PCR and DNA restriction fragment profiling. A geographical dichotomy between Canadian and European isolates for their propensity to do not have pAsa3 or pAsal1 was found. In addition, the genotyping analysis led to the identification of two European isolates harboring an unusual pAsal1. An investigation by next-generation sequencing (NGS) of these two isolates shed light on two pAsal1 variants (pAsal1C and pAsal1D). As with pAsal1B, another pAsal1 variant previously described, these two new variants bore a second insertion sequence (ISAS5) in addition to the usual ISAS11. The characterization of these variants suggested that they could predominate over the wild-type pAsal1 in stressful conditions such as growth at temperatures of 25°C and above. To obtain a comprehensive portrait of the mutational pressure on small plasmids, 26 isolates whose DNA had been sequenced by NGS were investigated. pAsa3 and pAsal1 were more prone to mutations than pAsa1 and pAsa2, especially in the mobA gene, which encodes a relaxase and a primase. Lastly, the average copy number of each plasmid per cell was assessed using raw sequencing data. A clear trend with respect to the relative proportion per cell of each plasmid was identified. Our large-scale study revealed a geographical dichotomy in small plasmid repertoire in addition to a clear trend for pAsa3 and pAsal1 to be more frequently altered. Moreover, we present the discovery of two new variants of pAsal1: pAsal1C and pAsal1D.
Deazaneplanocin A Is a Promising Drug to Kill Multiple Myeloma Cells in Their Niche

Tumoral plasma cells has retained stemness features and in particular, a polycomb-silenced gene expression signature. Therefore, epigenetic therapy could be a mean to fight for multiple myeloma (MM), still an incurable pathology. Deazaneplanocin A (DZNep), a S-adenosyl-L-homocysteine hydrolase inhibitor, targets enhancer of zest homolog 2 (EZH2), a component of polycomb repressive complex 2 (PRC2) and is capable to induce the death of cancer cells. We show here that, in some MM cell lines, DZNep induced both caspase-dependent and -independent apoptosis. However, the induction of cell death was not mediated through its effect on EZH2 and the trimethylation on lysine 27 of histone H3 (H3K27me3). DZNep likely acted through non-epigenetic mechanisms in myeloma cells. In vivo, in xenograft models, and in vitro DZNep showed potent antimyeloma activity alone or in combination with bortezomib. These preclinical data let us to envisage new therapeutic strategies for myeloma.
On Krause's Multi-Agent Consensus Model With State-Dependent Connectivity

We study a model of opinion dynamics introduced by Krause: each agent has an opinion represented by a real number, and updates its opinion by averaging all agent opinions that differ from its own by less than one. We give a new proof of convergence into clusters of agents, with all agents in the same cluster holding the same opinion. We then introduce a particular notion of equilibrium stability and provide lower bounds on the inter-cluster distances at a stable equilibrium. To better understand the behavior of the system when the number of agents is large, we also introduce and study a variant involving a continuum of agents, obtaining partial convergence results and lower bounds on inter-cluster distances, under some mild assumptions.
An Energy-Efficient Mechanism for Self-Monitoring Sensor Web

A Sensor Web is a network of spatially distributed sensor platforms, which is especially well suited for environmental monitoring. Although sensor nodes of a Sensor Web are critical devices that perform the monitoring work, the low-cost implementation of sensor nodes poses that they are subject to failures and permanent damage. A life-condition monitoring mechanism for sensor nodes is therefore required to ensure the function of a Sensor Web. This paper studies this sensor-node monitoring problem in the domain where in-network sensor nodes are self-monitoring, i.e., the status of each sensor node is monitored by another node. To be energy-efficient, a mechanism for implementing self-monitoring Sensor Webs should minimize the energy required. We propose a formal formulation of this problem and show that it can be solved by finding a minimum spanning tree of the graph constructed by in-network nodes. We provide some distributed algorithms in solving this problem. Simulations are conducted to study the performance of these algorithms.
EVALUATING THE QUALITY OF ISLAMIC CIVILIZATION AND ASIAN CIVILIZATIONS EXAMINATION QUESTIONS

Assessment of learning involves determining whether the content and objectives of education have been mastered by administering quality tests. Thus, the quality of the test items used in evaluating students’ achievement should be a major area of concern in teaching and research in the field of education. This paper assesses the quality of Tamadun Islam dan Tamadun Asia (TITAS) or Islamic Civilization and Asian Civilizations Examination Questions by conducting item analysis. The developed one hundred (100) multiple choices questions were administered to N=36 degree students. The data obtained had been analyzed by conducting item analysis in order to determine the item difficulties, item discrimination indices and the distractors analysis. The finding of results indicates that, based on difficulty indices 18(18%) items were “problematic” or “faulty”, 66(66%) of the items have poor discriminating power. Similarly, the result of the distractor analysis showed 59(59%) of the distractors been flawed, having failed to meet the set minimum standards. Based on the findings it could be assumed that the test used has not been validated during the item development processes. It is recommended that, TITAS test items used in measuring students’ achievement should be made to pass through all the processes of standardization and validation by conducting item analysis to ensure its reliability as well as to minimize measurement errors.
Constrained texture mapping for polygonal meshes

Recently, time and effort have been devoted to automatic texture mapping. It is possible to study the parameterization function and to describe the texture mapping process in terms of a functional optimization problem. Several methods of this type have been proposed to minimize deformations. However, these existing methods suffer from several limitations. For instance, it is difficult to put details of the texture in correspondence with features of the model, since most of the existing methods can only constrain iso-parametric curves. We introduce in this paper a new optimization-based method for parameterizing polygonal meshes with minimum deformations, while enabling the user to interactively define and edit a set of constraints. Each user-defined constraint consists of a relation linking a 3D point picked on the surface and a 2D point of the texture. Moreover, the non-deformation criterion introduced here can act as an extrapolator, thus making it unnecessary to constrain the border of the surface, in contrast with classic methods. To minimize the criterion, a conjugate gradient algorithm is combined with a compressed representation of sparse matrices, making it possible to achieve a fast convergence.
Mechanisms of Resistance to Decitabine in the Myelodysplastic Syndrome

Purpose The DNA methylation inhibitor 5-aza-2′-deoxycytidine (DAC) is approved for the treatment of myelodysplastic syndromes (MDS), but resistance to DAC develops during treatment and mechanisms of resistance remain unknown. Therefore, we investigated mechanisms of primary and secondary resistance to DAC in MDS. Patients and Methods We performed Quantitative Real-Time PCR to examine expression of genes related to DAC metabolism prior to therapy in 32 responders and non-responders with MDS as well as 14 patients who achieved a complete remission and subsequently relapsed while on therapy (secondary resistance). We then performed quantitative methylation analyses by bisulfite pyrosequencing of 10 genes as well as Methylated CpG Island Amplification Microarray (MCAM) analysis of global methylation in secondary resistance. Results Most genes showed no differences by response, but the CDA/DCK ratio was 3 fold higher in non-responders than responders (P<.05), suggesting that this could be a mechanism of primary resistance. There were no significant differences at relapse in DAC metabolism genes, and no DCK mutations were detected. Global methylation measured by the LINE1 assay was lower at relapse than at diagnosis (P<.05). On average, the methylation of 10 genes was lower at relapse (16.1%) compared to diagnosis (18.1%) (P<.05). MCAM analysis showed decreased methylation of an average of 4.5% (range 0.6%–9.7%) of the genes at relapse. By contrast, new cytogenetic changes were found in 20% of patients. Conclusion Pharmacological mechanisms are involved in primary resistance to DAC, whereas hypomethylation does not prevent a relapse for patients with DAC treatment.
Attracting Comments: Digital Engagement Metrics on Facebook and Financial Performance

Many companies are now using social media such as Facebook for advertising and marketing purposes. To understand how using social media affects a company's business performance from a digital engagement perspective, this study examines how user comments on company Facebook posts influence company revenue. S&P 500 companies' revenue information in a five-year time span (from 2010 to 2015) is collected, and this information is matched to more than 24 million user comments directed at these companies' Facebook posts. The hypotheses are tested using static (fixed effects [FE] and random effects [RE]) as well as dynamic (generalized method of moments [GMM]) panel data analyses in econometric methods. The estimation results indicate that digital engagement volume, defined as the total number of Facebook comments a company received, has a significant and positive effect on revenue. In addition, digital engagement valence, defined as the average tone of Facebook comments directed toward a company, also has a significant and positive effect on revenue. Implications and directions for future research are discussed.
Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead

This paper is an update of a paper that five of us published in 1992. The areas of multiple criteria decision making (MCDM) and multiattribute utility theory (MAUT) continue to be active areas of management science research and application. This paper extends the history of these areas and discusses topics we believe to be important for the future of these fields.
Lyapunov exponent and criticality in the Hamiltonian mean field model

We investigate the dependence of the largest Lyapunov exponent (LLE) of an N-particle self-gravitating ring model at equilibrium with respect to the number of particles and its dependence on energy. This model has a continuous phase-transition from a ferromagnetic to homogeneous phase, and we numerically confirm with large scale simulations the existence of a critical exponent associated to the LLE, although at variance with the theoretical estimate. The existence of strong chaos in the magnetized state evidenced by a positive Lyapunov exponent is explained by the coupling of individual particle oscillations to the diffusive motion of the center of mass of the system and also results in a change of the scaling of the LLE with the number of particles. We also discuss thoroughly for the model the validity and limits of the approximations made by a geometrical model for their analytic estimate.
Mucosa-Associated Bacteria in the Human Gastrointestinal Tract Are Uniformly Distributed along the Colon and Differ from the Community Recovered from Feces

ABSTRACT The human gastrointestinal (GI) tract harbors a complex community of bacterial cells in the mucosa, lumen, and feces. Since most attention has been focused on bacteria present in feces, knowledge about the mucosa-associated bacterial communities in different parts of the colon is limited. In this study, the bacterial communities in feces and biopsy samples from the ascending, transverse, and descending colons of 10 individuals were analyzed by using a 16S rRNA approach. Flow cytometric analysis indicated that 105 to 106 bacteria were present in the biopsy samples. To visualize the diversity of the predominant and the Lactobacillus group community, denaturing gradient gel electrophoresis (DGGE) analysis of 16S rRNA gene amplicons was performed. DGGE analysis and similarity index comparisons demonstrated that the predominant mucosa-associated bacterial community was host specific and uniformly distributed along the colon but significantly different from the fecal community (P < 0.01). The Lactobacillus group-specific profiles were less complex than the profiles reflecting the predominant community. For 6 of the 10 individuals the community of Lactobacillus-like bacteria in the biopsy samples was similar to that in the feces. Amplicons having 99% sequence similarity to the 16S ribosomal DNA of Lactobacillus gasseri were detected in the biopsy samples of nine individuals. No significant differences were observed between healthy and diseased individuals. The observed host-specific DGGE profiles of the mucosa-associated bacterial community in the colon support the hypothesis that host-related factors are involved in the determination of the GI tract microbial community.
New Upper Bounds for the SAT / UNSAT Threshold for Shapes

Phase transitions not only occur in physics but also in many problems in computer science. Among the problems from computer science, there are many NP-complete ones. An especially important problem is the satisfiability problem, SAT, for Boolean formulas. When phase transitions of SAT problems are studied, the corresponding formulas are usually restricted to conjunctive normal form, i.e., the formula is a set of clauses. K-SAT is the problem, where all clauses consists of exactly K literals. When the density of clauses (i.e., the ratio between the number of clauses and the number of variables) is increased in random K-SAT problems, there is an abrupt change in the probability from being satisfiable to being unsatisfiable. Numerous experimental results are available, but the exact location of the phase transition is not known for the random KSAT problem with K > 2. There are only lower and upper bounds which are rigorously proven. In this thesis, we consider formulas with more structure, namely the model of fixed balanced shapes introduced by Navarro and Voronkov in 2005. They experimentally studied different shapes and provided first upper bounds for the critical value, i.e., the location where the phase transition occurs. These upper bounds were obtained by using the first moment method (FMM). We uniformly improve their upper bounds by a method which is based on locally maximal solutions. This method has been proposed by Creignou and Daudé in 2007. Since this method requires a sensitivity polynomial as an input, we show how such polynomials can be computed for shapes, and how the upper bounds are obtained. We discuss the limitations of the method by comparing the upper bounds computed with the FMM with the upper bounds computed by the new method for shapes with increasing size or depth.
Note on transformation to general curvilinear coordinates for Maxwell's curl equations

Arguments for H and B to be considered `axial', or pseudo vectors, are revisited. As a point against, we examine the complex-coordinate method for numerical grid truncation and mode loss analysis proved very successful in computational electrodynamics. This method is not compatible with convention that H and B are axial.
'Dinkies' and Housewives: The Regulation of Shopping Hours

The idea of deregulating shopping hours brings strong opposition from many groups in the society. Surprisingly, even many consumers oppose deregulation. This paper rationalizes this behavior by considering heterogeneous consumers who differ in their earnings abilities. If a majority of families has two income earners, long open hours become essential and the regulation of shopping hours tends to be eliminated. If most families are single income households, the regulation may be imposed in order to keep prices low. Taking the repercussions on the labor supply decision into account, multiple equilibria can be explained. Copyright 1997 by WWZ and Helbing & Lichtenhahn Verlag AG
Lifting-based rational wavelet design from a given signal

This paper proposes design of rational wavelet filterbank via lifting scheme. We introduce the concept of rate converters in lifting filters, while designing predict and update stages. This design approach to rational wavelet has all the advantages of lifting, including perfect reconstruction and the design being modular. In addition, both predict and update stage polynomials are obtained from a given signal making the proposed scheme a signal-matched wavelet design approach.
Interrelationships Among Self-Regulated Learning Processes: Toward a Dynamic Process-Based Model of Self-Regulated Learning

Self-regulation and learning are fundamentally dynamic phenomena that occur at the within-person level and unfold over time. However, the majority of the extant empirical research on self-regulated learning has been conducted at the between-person level, which can obscure the true nature of interrelationships among self-regulatory mechanisms. In the present study, we seek to advance a more nuanced view of the role of self-regulation in modern training and development by presenting a novel theoretical perspective that integrates cognitive, motivational, and behavioral mechanisms central to the literature on active learning with the more dynamic theoretical principles and mechanisms underlying stage-based cognitive models of skill acquisition. Hypotheses derived from this model were tested in a laboratory study with 305 participants who practiced a dynamic computer game involving strong cognitive and perceptual-motor demands. Bivariate cross-lagged latent growth models generally supported the proposed model, revealing systematic trends over the course of practice consistent with a series of iterative, bidirectional, and self-correcting reciprocal interrelationships among self-efficacy, metacognition, exploratory behavior, and practice performance. Collectively, these findings suggest that strong positive interrelationships among self-regulated learning variables at the between-person level may, in some cases, actually belie the true nature of their functional effects. Implications for theory and practice are discussed.