Miracle-dz/UniFAR-FTUs huggingface dataset:
Reforming Motivation: How the structure of instruction affects students’ learning experiences

Over the past decade, several US school and instructional reforms have sought ways to counter trends of mediocrity in education. These reforms are grounded in structural motivation theories which postulate that students' learning experiences are optimised when instruction is authentic, challenging, demands skills, and allows for student autonomy. This study set out to investigate empirically the effects of these four structural characteristics of instruction on students' learning experiences. Using a unique methodological design, the current investigation measures students' learning experiences with a confirmatory factor analysis. The four factors which emerged are next predicted with a series of structural variables. The results show that high quality learning experiences are indeed authentic, allow choice, and demand student skills. Boring and alienated experiences are produced when these instructional characteristics are absent. The findings suggest that the structures of instruction that disaffect students are overwhelmingly represented in students' daily school life; those that spark their hearts are not frequent enough to motivate students. They also imply that students do not have a general tendency to be emotionally depressed in school; rather, they perceive their experiences to be highly influenced by specific structural characteristics of instruction.
True Random Number Generation by Variability of Resistive Switching in Oxide-Based Devices

Scalable, low-power random number generator (RNG) blocks are essential for encryption in today's communication systems. To allow for true RNG, a system must display an inherently-random physical phenomenon, such as the timing of individual fluctuations in random telegraph noise or the random trapping/detrapping phenomena in dielectrics. In this work, a true RNG based on set variability in a resistive switching memory (RRAM) is demonstrated. The RNG relies on a single RRAM device, which is repeatedly programmed at a constant voltage close to the nominal set voltage. Due to the statistical variability of the set voltage, set transition takes place only in 50% of the applied pulses, thus resulting in a bimodal distribution of resistance. The bimodal distribution of analog resistance is finally converted into a 0/1 distribution of output voltage values through digital regeneration with a CMOS inverter.
Significant Advancements in Technology to Improve Instruction for all Students

Sharing thoughts on what represents significant advancements involving the education of persons for whom typical instruction is not effective seems simple enough. You think about the work you are engaged in and reflect on how you came to do what you are doing. If you have a record of being persistent in your work, then that becomes the context for your perceptions of significant advancements. While limited as a strategy for framing a vision for the future, the views of an individual do have potential when combined with the perspective of others. Emerging technologies in the realm of instructional change brought about by the Internet provide the framework for the choice of significant advancements, discussed in this article, to improve instruction for all students including students with disabilities. They include the impact of technologies that allow for measuring physiological and motivational responses of online learners that enhance the personalization of online instruction, the impact of wireless computing in contributing to how ubiquitous computing influences learning environments for all learners, and the increased capacity offered by technology to increase sensitivity to variability among online learners and to stimulate research in the important area of inquiry.
Myeloid-derived suppressor cells

While conventional anticancer therapies, including surgical resection, radiotherapy, and/or chemotherapy, are relatively efficient at eliminating primary tumors, these treatment modalities are largely ineffective against metastases. At least in part, this reflects the rather inefficient delivery of conventional anticancer agents to metastatic lesions. We have recently demonstrated that myeloid-derived suppressor cells (MDSCs) can be used as cellular missiles to selectively deliver a radioisotope-coupled attenuated variant of Listeria monocytogenes to both primary and metastatic neoplastic lesions in mice with pancreatic cancer. This novel immunotherapeutic intervention robustly inhibited tumor growth while promoting a dramatic decrease in the number of metastases.
An improved spray and wait algorithm based on RVNS in Delay Tolerant Mobile Sensor Networks

Due to the limited resources of DTMSN (Delay Tolerant Mobile Sensor Networks), network congestion becomes a critical problem to resolve. Traditional congestion control methods where the number of copies is restricted to limit data packet forwarding cannot adapt to constantly changing network environment because of fixed number of copies. Fortunately, this problem can be solved through a real-time algorithm by modifying data packet forwarding conditions. However, one of the major challenges of this algorithm is detecting characteristics of the network environment accurately and efficiently. In this paper, an optimized routing algorithm, RVNS (Reduced Variable Neighborhood Search)-based Spray and Wait (SW) is proposed. In this algorithm, nodes will transmit and store the counter record of each other when they meet, based on which, RVNS is introduced to calculate a real-time threshold for the forwarding condition to control packet delivery. Simulation results show that the proposed algorithm increases delivery probability and dramatically reduces the overhead ratio. In some extreme cases, this algorithm can reach an extremely low overhead ratio (ten times lower than that of SW), meaning that the proposed algorithm suits challenged networks well.
The Lethal Effect of a Benzamide Derivative, 3-Methoxybenzamide, Can Be Suppressed by Mutations within a Cell Division Gene, ftsZ, in Bacillus subtilis

ABSTRACT 3-Methoxybenzamide (3-MBA), which is known to be an inhibitor of ADP-ribosyltransferase, inhibits cell division in Bacillus subtilis, leading to filamentation and eventually lysis of cells. Our genetic analysis of 3-MBA-resistant mutants indicated that the primary target of the drug is the cell division system involving FtsZ function during both vegetative growth and sporulation.
Risk Management of Residential Mortgage in China Using Date Mining A Case Study

This paper investigates the risk management for residential mortgage in China. The paper finds out that the Chinese commercial banks have to take all the risks of residential mortgages. By examining a causal model of China’s mortgage market, the paper reveals that with relatively tight financial regulations by Chinese central bank, commercial banks have to solely depend on the credit system to screen out potential default loan applicants. Therefore, it is urgent for commercial banks to build an effective screening system to reduce the risk introduced by loan defaults. The paper reports an analytic study based on a real dataset of 641,988 observations provided by a Chinese commercial bank. The outcomes suggest that the classification model is effective for credit scoring with the data collected at China, and, however, the quality of the data needs to be improved for more precise default risk management.
Improving Perceived Control in Homeless Men by increasing Computer Literacy

Abstract The purpose of this study was to determine whether a six-week computer literacy course would benefit a group of fourteen men participating in a residency program at a local homeless shelter. We hypothesized that computer literacy would increase self-esteem, perceived social support and control while decreasing depression. Measures of self-esteem, non-clinical depression, perceived social support, and perceived control were administered before and after the program. Results indicated that computer literacy increases perceived control. Perceptions of self-esteem also increased before and after the program.
Differences in Neuroretinal Function between Adult Males and Females

Purpose To determine whether neuroretinal function differs in healthy adult males and females younger and older than 50 years. Methods This study included one eye from each of 50 normal subjects (29 females and 21 males). Neuroretinal function was assessed using first-order P1 implicit times (ITs) and N1-P1 amplitudes (AMPs) obtained from photopic multifocal electroretinograms. To assess local differences, retinal maps of local IT and (separately) AMP averages were constructed for each subject group. To examine global differences, each subject’s 103 ITs and (separately) AMPs were also averaged to create whole-eye averages. Subsequently, retinal maps and whole-eye averages of one subject group were compared with those of another. Results In subjects younger than 50 years, neuroretinal function differed significantly between the males and females: local ITs were significantly shorter at 83 of 103 tested retinal locations, and whole-eye IT averages were shorter (p = 0.015) in the females compared with the males. In contrast, no analysis indicated that the males and females older than 50 years were significantly different. A subanalysis showed that the females who reported a hysterectomy (n = 5) had the longest whole-eye ITs of all subject groups (p ⩽ 0.0013). In the females who did not report a hysterectomy, neuroretinal function was worse in the females older than 50 years compared with the females younger than 50 years: local ITs were significantly longer at 62 of 103 retinal locations tested, and whole-eye IT averages tended to be greater (p = 0.04). Conversely, ITs were not statistically different between the younger and older males. N1-P1 amplitudes did not differ between the sexes. Conclusions Multifocal electroretinogram IT differs between males and females, depending on the age group and hysterectomy status.
MacSHAPA and the enterprise of exploratory sequential data analysis (ESDA)

This paper discusses some of the problems associated with observational data analysis for complex domains, and introduces the term "exploratory sequential data analysis" (ESDA) to describe the different kinds of observational data analysis currently being performed in many areas of the behavioral and social sciences. The development and functionality of a software tool? MacSHAPA? for certain kinds of ESDA is described. MacSHAPA is designed to bring investigators into closer contact with their data and to help them achieve greater research productivity and quality. MacSHAPA allows investigators to see their data in various ways, to enter it, edit it and encode it, and to carry out statistical analyses and make reports. MacSHAPA's relation to other ESDA software tools is indicated throughout the paper.
Clinically Relevant Mutant DNA Gyrase Alters Supercoiling, Changes the Transcriptome, and Confers Multidrug Resistance

ABSTRACT Bacterial DNA is maintained in a supercoiled state controlled by the action of topoisomerases. Alterations in supercoiling affect fundamental cellular processes, including transcription. Here, we show that substitution at position 87 of GyrA of Salmonella influences sensitivity to antibiotics, including nonquinolone drugs, alters global supercoiling, and results in an altered transcriptome with increased expression of stress response pathways. Decreased susceptibility to multiple antibiotics seen with a GyrA Asp87Gly mutant was not a result of increased efflux activity or reduced reactive-oxygen production. These data show that a frequently observed and clinically relevant substitution within GyrA results in altered expression of numerous genes, including those important in bacterial survival of stress, suggesting that GyrA mutants may have a selective advantage under specific conditions. Our findings help contextualize the high rate of quinolone resistance in pathogenic strains of bacteria and may partly explain why such mutant strains are evolutionarily successful. IMPORTANCE Fluoroquinolones are a powerful group of antibiotics that target bacterial enzymes involved in helping bacteria maintain the conformation of their chromosome. Mutations in the target enzymes allow bacteria to become resistant to these antibiotics, and fluoroquinolone resistance is common. We show here that these mutations also provide protection against a broad range of other antimicrobials by triggering a defensive stress response in the cell. This work suggests that fluoroquinolone resistance mutations may be beneficial under a range of conditions. Fluoroquinolones are a powerful group of antibiotics that target bacterial enzymes involved in helping bacteria maintain the conformation of their chromosome. Mutations in the target enzymes allow bacteria to become resistant to these antibiotics, and fluoroquinolone resistance is common. We show here that these mutations also provide protection against a broad range of other antimicrobials by triggering a defensive stress response in the cell. This work suggests that fluoroquinolone resistance mutations may be beneficial under a range of conditions.
Scaling up Group Closeness Maximization

Closeness is a widely-used centrality measure in social network analysis. For a node it indicates the inverse average shortest-path distance to the other nodes of the network. While the identification of the k nodes with highest closeness received significant attention, many applications are actually interested in finding a group of nodes that is central as a whole. For this problem, only recently a greedy algorithm with approximation ratio (1-1/e) has been proposed [Chen et al., ADC 2016]. Since this algorithm's running time is still expensive for large networks, a heuristic without approximation guarantee has also been proposed in the same paper. In the present paper we develop new techniques to speed up the greedy algorithm without losing its theoretical guarantee. Compared to a straightforward implementation, our approach is orders of magnitude faster and, compared to the heuristic proposed by Chen et al., we always find a solution with better quality in a comparable running time in our experiments. Our method Greedy++ allows us to approximate the group with maximum closeness on networks with up to hundreds of millions of edges in minutes or at most a few hours. To have the same theoretical guarantee, the greedy approach by [Chen et al., ADC 2016] would take several days already on networks with hundreds of thousands of edges. In a comparison with the optimum, our experiments show that the solution found by Greedy++ is actually much better than the theoretical guarantee. Over all tested networks, the empirical approximation ratio is never lower than 0.97. Finally, we study for the first time the correlation between the top-k nodes with highest individual closeness and an approximation of the most central group in large networks. Our results show that the overlap between the two is relatively small, which indicates empirically the need to distinguish between the two problems.
Genome‐wide association studies: quality control and population‐based measures

Genome‐wide association studies, using hundreds of thousands of single‐nucleotide polymorphism (SNP) markers, have become a standard approach for identifying disease susceptibility genes. The change in the technology poses substantial computational and statistical challenges that have been addressed in the quality control, imputation, and population‐based measure groups of the Genetic Analysis Workshop 16. The computational challenges pertain to efficient memory management and computational speed of the statistical procedures, and we discuss an approach for efficient SNP storage. Accuracy and computational speed is relevant for genotype calling, and the results from a comparison of three calling algorithms are discussed. The first statistical challenge is related to statistical quality control, and we discuss two novel quality control procedures. These low‐level analyses have an effect on subsequent preparatory steps for high‐level analyses, e.g., the quality of genotype imputation approaches. After the conduct of a genome‐wide association study with successful replication and/or validation, measures of diagnostic accuracy, including the area under the curve, are investigated. The area under the curve can be constructed from summary data in some situations. Finally, we discuss how the population‐attributable risk of a genetic variant that is only measured in a reference data set can be determined. Genet. Epidemiol. 33 (Suppl. 1):S45–S50, 2009. © 2009 Wiley‐Liss, Inc.
Understanding, modelling and managing longevity risk: key issues and main challenges

This article investigates the latest developments in longevity-risk modelling, and explores the key risk management challenges for both the financial and insurance industries. The article discusses key definitions that are crucial for the enhancement of the way longevity risk is understood, providing a global view of the practical issues for longevity-linked insurance and pension products that have evolved concurrently with the steady increase in life expectancy since s. In addition, the article frames the recent and forthcoming developments that are expected to action industry-wide changes as more effective regulation, designed to better assess and efficiently manage inherited risks, is adopted. Simultaneously, the evolution of longevity is intensifying the need for capital markets to be used to manage and transfer the risk through what are known as Insurance-Linked Securities (ILS). Thus, the article will examine the emerging scenarios, and will finally highlight some important potential developments for longevity-risk management from a financial perspective with reference to the most relevant modelling and pricing practices in the banking industry.
Identification and pathogenicity of Botiyosphaeria species associated with grapevine decline in Western Australia

Botryosphaeria species have recently gained importance as pathogens of grapevines worldwide. A survey was conducted of 16 vineyards in three grape-growing regions in Western Australia to determine if Botryosphaeria species were playing a role in grapevine decline. B. australis, B. rhodina, B. obtusa and B. stevensii were isolated from grapevines exhibiting symptoms of decline, and identified based on morphological characteristics and ITS sequence data. These species have all been isolated from grapevines elsewhere in the world. Regional differences between Botryosphaeria species were apparent. B. rhodina was isolated only from the Swan Districts region. B. australis was present in the Margaret River and Pemberton/Manjimup regions, but was never isolated from the Swan Districts region. B. obtusa was isolated from all regions, but most prominently from Manjimup, and B. stevensii was isolated only once from Manjimup. A pathogenicity trial found B. australis, B. rhodina and B. stevensii to be pathogenic to grapevines, whereas B. obtusa did not produce any lesions on the cuttings. In Western Australia, B. australis appears to be the predominant pathogenic Botryosphaeria sp. The role of other species of Botryosphaeria and the interaction between species requires further study.
Process Research in Strategy Formation: Theory, Methodology and Relevance

This paper develops a view of the strategy formation process, drawing on a review of contributions that are based on a process approach, and more specifically the work of Henry Mintzberg, Andrew Pettigrew and Andrew Van de Ven. This view is meant to provide a way to bridge the content–process gap in strategic management by addressing the aspects of process theory and process methodology. Structuration is found to provide a useful theoretical basis for strategy formation research. Process methodology is found to be about discovering valid generative mechanisms that explain regular patterns in event sequences. Strategy formation research can then be made relevant for management practice by providing insight with regard to generative mechanisms and associated process trajectories of continuity and change, to allow for judgements on the favourability of the course of the process as well as the necessity to intervene or to let the process run its course.
Estimation of Non-Idealities in Sigma-Delta Modulators for Test and Correction Using Unscented Kalman Filters

In this paper, an enhanced unscented Kalman filter is used for the estimation of non-idealities in sigma-delta modulators. As sigma-delta modulator based analog-to-digital converters are known to be prone to performance degradation from many circuit non-idealities, testing and selection of the manufactured chips as well as post-correction procedures are required to ensure a reliable performance. In contrast to most state-of-the art techniques, the proposed estimator is capable of simultaneously tracking a large set of non-ideal parameters with high accuracy and in a very short offline time within the range of microseconds. Three possible implementations are proposed and it is shown how the technique is used to perform an in situ non-ideality estimation and subsequent calibration of a manufactured chip, bringing the modulator back into its designed performance range. It is further demonstrated that the estimator can reliably detect the non-idealities over a wide range when intentionally degrading the performance of the chip by manually sweeping its trimming parameters. The presented hardware measurement results prove that the proposed technique is practically applicable to the test and/or calibration of sigma-delta data converters.
Detection of Molecular Paths Associated with Insulitis and Type 1 Diabetes in Non-Obese Diabetic Mouse

Recent clinical evidence suggests important role of lipid and amino acid metabolism in early pre-autoimmune stages of type 1 diabetes pathogenesis. We study the molecular paths associated with the incidence of insulitis and type 1 diabetes in the Non-Obese Diabetic (NOD) mouse model using available gene expression data from the pancreatic tissue from young pre-diabetic mice. We apply a graph-theoretic approach by using a modified color coding algorithm to detect optimal molecular paths associated with specific phenotypes in an integrated biological network encompassing heterogeneous interaction data types. In agreement with our recent clinical findings, we identified a path downregulated in early insulitis involving dihydroxyacetone phosphate acyltransferase (DHAPAT), a key regulator of ether phospholipid synthesis. The pathway involving serine/threonine-protein phosphatase (PP2A), an upstream regulator of lipid metabolism and insulin secretion, was found upregulated in early insulitis. Our findings provide further evidence for an important role of lipid metabolism in early stages of type 1 diabetes pathogenesis, as well as suggest that such dysregulation of lipids and related increased oxidative stress can be tracked to beta cells.