Miracle-dz/UniFAR-FTUs huggingface dataset:
New Covariance-Based Feature Extraction Methods for Classification and Prediction of High-Dimensional Data

Sofolahan, Mopelola A. Ph.D., Purdue University, December 2013. New CovarianceBased Feature Extraction Methods for Classification and Prediction of High-Dimensional Data. Major Professor: Okan Ersoy. When analyzing high dimensional data sets, it is often necessary to implement feature extraction methods in order to capture relevant discriminating information useful for the purposes of classification and prediction. The relevant information can typically be represented in lower-dimensional feature spaces, and a widely used approach for this is the principal component analysis (PCA) method. PCA efficiently compresses information into lower dimensions; however, studies indicate that it is not optimal for feature extraction especially when dealing with classification problems. Furthermore, for high-dimensional data having limited observations, as is typically the case with remote sensing data and nonstationary data such as financial data, covariance matrix estimation becomes unreliable, and this adversely affects the representation of data in the PCA domain. In this thesis, we first introduce a new feature extraction method called summed component analysis (SCA), which makes use of the structure of eigenvectors of the common covariance matrix to generate new features as sums of certain original features. Secondly, we present a variation of SCA, known as class summed component analysis (CSCA). CSCA takes advantage of the relative ease of computing the class covariance matrices and uses them to determine data transformations. Since the new features consist of simple sums of the original features, we are able to gain a conceptual meaning of the new representation of the data which is appealing for man-machine interface. We evaluate these methods on data sets with varying sample sizes and on financial time series, and are able to show improved classification and prediction accuracies.
A decidable timeout-based extension of linear temporal logic

We develop a timeout extension of propositional linear temporal logic (which we call ToLTL) to specify timing properties of timeout-based models of real-time systems. A timeout is used to model the execution of an action marking the end of a delay. With a view to expressing such timeout constraints, ToLTL uses a dynamic variable to abstract the timeout behaviour in addition to a variable which captures the global clock and some static timing variables which record time instances when discrete events occur. We propose a corresponding timeout tableau for satisfiability checking of the ToLTL formulas. Further we prove that the validity checking for such an extended logic remains PSPACE-complete. Under discrete time semantics, with bounded timeout increments, the model-checking problem which verifies if a ToLTL-formula holds in a timeout Kripke structure is also shown to be PSPACE complete. We further prove that ToLTL, when interpreted over discrete time, can be embedded in the monadic second-order logic with time and timeout and show an expressive completeness result for ToLTL. However, when ToLTL is interpreted over dense time without non-zenoness, the resulting logic becomes -complete (i.e., highly undecidable).
Intel OpenMP C++/Fortran Compiler for Hyper-Threading Technology: Implementation and Performance

In the never-ending quest for higher performance, CPUs become faster and faster. Processor resources, however, are generally underutilized by many applications. Intel’s Hyper-Threading Technology is developed to resolve this issue. This new technology allows a single processor to manage data as if it were two processors by executing data instructions from different threads in parallel rather than serially. Processors enabled with Hyper-Threading Technology can greatly imp rove the performance of applications with a high degree of parallelism. However, the potential gain is only obtained if an application is multithreaded, by either manual, automatic, or semiautomatic parallelization techniques. This paper presents the compiler techniques of OpenMP pragmaand directive-guided parallelization developed for the highperformance Intel C++/Fortran compiler. We also present a performance evaluation of a set of benchmarks and applications.
Reproductive traits of the symbiotic pea crab Austinotheres angelicus (Crustacea, Pinnotheridae) living in Saccostrea palmula (Bivalvia, Ostreidae), Pacific coast of Costa Rica

Abstract Pea crabs of the family Pinnotheridae exhibit a symbiotic life style and live associated with a variety of different marine organisms, especially bivalves. Despite the fact that pea crabs can cause serious problems in bivalve aquaculture, the available information about the ecology of these crabs from Central America is extremely limited. Therefore, the present study aimed to describe different reproductive features of the pinnotherid crab Austinotheres angelicus associated with the oyster Saccostrea palmula in the Golfo de Nicoya, Pacific coast of Costa Rica. Monthly sampling was conducted from April to December 2012. Average carapace width (CW) of the 47 analyzed ovigerous females was 7.62 mm. The species produced on average 2677 ± 1754 recently -extruded embryos with an average volume of 0.020 ± 0.003 mm3; embryo volume increased during embryogenesis by 21%, but did not vary significantly between developmental stages. Brood mass volume varied greatly (between 11.7 and 236.7 mm3), and increased significantly with female CW. Females invested on average 76.7% (minimum: 21.7%; maximum: 162.8%) of their body weight in brood production, which confirms a substantially higher energy allocation for embryo production in pinnotherid crabs compared to free-living decapods.
Homozygosity Mapping and Whole Exome Sequencing Reveal a Novel Homozygous COL18A1 Mutation Causing Knobloch Syndrome

The aim of this study was to identify the genetic basis of a chorioretinal dystrophy with high myopia of unknown origin in a child of a consanguineous marriage. The proband and ten family members of Iranian ancestry participated in this study. Linkage analysis was carried out with DNA samples of the proband and her parents by using the Human SNP Array 6.0. Whole exome sequencing (WES) was performed with the patients’ DNA. Specific sequence alterations within the homozygous regions identified by whole exome sequencing were verified by Sanger sequencing. Upon genetic analysis, a novel homozygous frameshift mutation was found in exon 42 of the COL18A1 gene in the patient. Both parents were heterozygous for this sequence variation. Mutations in COL18A1 are known to cause Knobloch syndrome (KS). Retrospective analysis of clinical records of the patient revealed surgical removal of a meningocele present at birth. The clinical features shown by our patient were typical of KS with the exception of chorioretinal degeneration which is a rare manifestation. This is the first case of KS reported in a family of Iranian ancestry. We identified a novel disease-causing (deletion) mutation in the COL18A1 gene leading to a frameshift and premature stop codon in the last exon. The mutation was not present in SNP databases and was also not found in 192 control individuals. Its localization within the endostatin domain implicates a functional relevance of endostatin in KS. A combined approach of linkage analysis and WES led to a rapid identification of the disease-causing mutation even though the clinical description was not completely clear at the beginning.
Hiring Stars and Their Colleagues: Exploration and Exploitation in Professional Service Firms

This paper examines exploration and exploitation in professional service firms by focusing on the individuals who carry out the exploration and exploitation activities. Specifically, we examine the performance of star security analysts who join new firms in exploration versus exploitation roles. We find that stars hired to explore (initiate new activities) experience a short-and long-term performance decline; by contrast, stars who join new firms to exploit (reinforce existing activities) suffer only a short-term drop in performance. Stars hired in exploration roles can preserve some of their performance by moving with a group of colleagues from the originating firm. Investors view the hiring of a star analyst as value-destroying for the hiring firm regardless of whether the firm is hiring to exploit or explore, but the negative reactions are economically more extreme for exploration hires. These findings indicate that, even at the individual level, probabilities of success in exploration activities are lower than in exploitation activities, thereby reinforcing the tendency toward exploitation.
Differences of Urinary Arsenic Metabolites and Methylation Capacity between Individuals with and without Skin Lesions in Inner Mongolia, Northern China

Incomplete arsenic (As) methylation has been considered a risk factor of As-related diseases. This study aimed to examine the difference of urinary As metabolites and the methylation capacity between subjects with and without skin lesions. Urinary inorganic arsenic (iAs), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) were analyzed. The percentage of each As species (iAs%, MMA%, and DMA%), the primary methylation index (PMI) and secondary methylation index (SMI) were calculated. The results showed that subjects with skin lesions have higher levels of urinary iAs (99.08 vs. 70.63 μg/g Cr, p = 0.006) and MMA (69.34 vs. 42.85 μg/g Cr, p = 0.016) than subjects without skin lesions after adjustment for several confounders. Significant differences of urianry MMA% (15.49 vs. 12.11, p = 0.036) and SMI (0.74 vs. 0.81, p = 0.025) were found between the two groups. The findings of the present study suggest that subjects with skin lesions may have a lower As methylation capacity than subjects without skin lesions.
MoViMash: online mobile video mashup

With the proliferation of mobile video cameras, it is becoming easier for users to capture videos of live performances and socially share them with friends and public. As an attendee of such live performances typically has limited mobility, each video camera is able to capture only from a range of restricted viewing angles and distance, producing a rather monotonous video clip. At such performances, however, multiple video clips can be captured by different users, likely from different angles and distances. These videos can be combined to produce a more interesting and representative mashup of the live performances for broadcasting and sharing. The earlier works select video shots merely based on the quality of currently available videos. In real video editing process, however, recent selection history plays an important role in choosing future shots. In this work, we present MoViMash, a framework for automatic online video mashup that makes smooth shot transitions to cover the performance from diverse perspectives. Shot transition and shot length distributions are learned from professionally edited videos. Further, we introduce view quality assessment in the framework to filter out shaky, occluded, and tilted videos. To the best of our knowledge, this is the first attempt to incorporate history-based diversity measurement, state-based video editing rules, and view quality in automated video mashup generations. Experimental results have been provided to demonstrate the effectiveness of MoViMash framework.
From ‘motivational climate’ to ‘motivational atmosphere’: A review of research examining the social and environmental influences on athlete motivation in sport

This chapter is intended to provide a comprehensive review of the various theories of social and environmental factors that influence athletes’ motivation in sport. In order to achieve this, a short historical review is conducted of the various ways in which motivation has been studied over the past 100 years, culminating in the ‘social-cognitive’ approach that undergirds several of the current theories of motivation in sport. As an outcome of this brief review, the conceptualisation and measurement of motivation are discussed, with a focus on the manner in which motivation may be influenced by key social agents in sport, such as coaches, parents and peers. This discussion leads to a review of Deci & Ryan’s (2000) self-determination theory (SDT), which specifies that environments and contexts which support basic psychological needs (competence, relatedness and autonomy) will produce higher quality motivation than environments which frustrate of exacerbate these needs. The research establishing the ways in which key social agents can support these basic needs is then reviewed, and the review depicts a situation wherein SDT has precipitated a way of studying the socio-environmental influences on motivation that has become quite piecemeal and fragmented. Following this, the motivational climate approach (Ames, 1992) specified in achievement-goals theory (AGT – Nicholls, 1989) is also reviewed. This section reveals a body of research which is highly consistent in its methodology and findings. The following two sections reflect recent debates regarding the nature of achievement goals and the way they are conceptualised (e.g., approach-avoidance goals and social goals), and the implications of this for motivational climate research are discussed. This leads to a section reviewing the current issues and concerns in the study of social and environmental influences on athlete motivation. Finally, future research directions and ideas are proposed to facilitate, precipitate and guide further research into the social and environmental influences on athlete motivation in sport. Recent studies that have attempted to address these issues are reviewed and their contribution is assessed.
On-line time domain reflectometry measurements of temperature variations of an XLPE power cable

In this paper an on-line time domain reflectometry system and a four-days measurements sequence are presented. Detected pulse velocity variations are attributed to temperature variations of the cable caused by a load cycling. The changes in the pulse velocity are verified by propagation constant measurements of a power cable at different temperatures in 300 kHz-500 MHz frequency range. Also an influence of temperature dependent semiconducting screens and XLPE insulation to the changes in the cable's capacitance is investigated.
ADAM10 Releases a Soluble Form of the GPNMB/Osteoactivin Extracellular Domain with Angiogenic Properties

Background Glycoprotein non-metastatic melanoma protein B (GPNMB)/Osteoactivin (OA) is a transmembrane protein expressed in approximately 40–75% of breast cancers. GPNMB/OA promotes the migration, invasion and metastasis of breast cancer cells; it is commonly expressed in basal/triple-negative breast tumors and is associated with shorter recurrence-free and overall survival times in patients with breast cancer. Thus, GPNMB/OA represents an attractive target for therapeutic intervention in breast cancer; however, little is known about the functions of GPNMB/OA within the primary tumor microenvironment. Methodology/Principal Findings We have employed mouse and human breast cancer cells to investigate the effects of GPNMB/OA on tumor growth and angiogenesis. GPNMB/OA-expressing tumors display elevated endothelial recruitment and reduced apoptosis when compared to vector control-derived tumors. Primary human breast cancers characterized by high vascular density also display elevated levels of GPNMB/OA when compared to those with low vascular density. Using immunoblot and ELISA assays, we demonstrate the GPNMB/OA ectodomain is shed from the surface of breast cancer cells. Transient siRNA-mediated knockdown studies of known sheddases identified ADAM10 as the protease responsible for GPNMB/OA processing. Finally, we demonstrate that the shed extracellular domain (ECD) of GPNMB/OA can promote endothelial migration in vitro. Conclusions/Significance GPNMB/OA expression promotes tumor growth, which is associated with enhanced endothelial recruitment. We identify ADAM10 as a sheddase capable of releasing the GPNMB/OA ectodomain from the surface of breast cancer cells, which induces endothelial cell migration. Thus, ectodomain shedding may serve as a novel mechanism by which GPNMB/OA promotes angiogenesis in breast cancer.
Active vision of a heavy material handling agricultural robot using robust control: a case study for initial cost problem

We propose a new active vision of a heavy material handling agricultural robot emphasizing the initial cost. A key point is a new combination of a structure system and a control system, not only one of the two. First, a camera configuration with only one camera is proposed to achieve lower initial cost. This configuration requires more robustness. Second, in order to realize the vision, a robust control system is designed in the presence of uncertainty and constraint. Finally, the validity is confirmed by experiments in an actual open field. The camera configuration can not work well without the designed controllers. That is, the robust controllers reduce the initial cost.
Interstitial Inflammatory Lesions of the Pulmonary Allograft: A Retrospective Analysis of 2697 Transbronchial Biopsies

Background. Parenchymal and bronchial inflammatory and fibrotic lesions other than acute cellular rejection (ACR) and lymphocytic bronchiolitis are prevalent; however, the context in which they appear is unknown, and often no specific treatment is instigated. Objectives. To describe the prevalence, incidence and possible associations between commonly identified inflammatory and fibrotic lesions in the pulmonary allograft. Methods. Retrospective chart review of all transbronchial biopsies performed within the first 2 years of 299 lung-transplanted patients in the period 1996 to 2006. Results. A total of 2697 biopsies were evaluated corresponding to a mean of 6±2 (median 8) completed schedules per patient. Diffuse alveolar damage (DAD) was the second most common histological finding within the first 2 weeks after transplantation. The peak prevalence of bronchiolitis obliterans organizing pneumonia (BOOP) and interstitial pneumonitis occurred at 4 to 6 weeks, and 6 to 12 weeks, respectively. There was a steady increase in the cumulative proportion of patients with fibrosis and bronchiolitis obliterans, at each successive scheduled surveillance time point beyond 3 months posttransplantation. The strongest histological correlations were between ACR and lymphocytic bronchiolitis (OR 5.1, P<0.0001) or interstitial fibrosis (OR 3.2, P<0.0001). Patients with interstitial pneumonitis and pulmonary hemosiderosis were also more likely to demonstrate the finding of interstitial fibrosis (OR 3.0 and 3.7, P<0.0001, respectively). Acute cellular rejection was not associated with DAD, and patients with lymphocytic bronchiolitis were not more likely to demonstrate features of organizing pneumonia (DAD or BOOP). Conclusions. Histologic findings of ACR, lymphocytic bronchiolitis, BOOP, and interstitial pneumonitis were directly associated with the development of interstitial fibrosis and bronchiolitis obliterans.
Efficient Self-Evolving Evolutionary Learning for Neurofuzzy Inference Systems

This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA is that it is based on evolutionary algorithms that can determine the number of fuzzy rules and adjust the NFIS parameters. The SEELA consists of structure learning and parameter learning. The structure learning attempts to determine the number of fuzzy rules. A subgroup symbiotic evolution is adopted to yield several variable fuzzy systems, and an elite-based structure strategy is adopted to find a suitable number of fuzzy rules for solving a problem. The parameter learning is to adjust parameters of the NFIS. It is a hybrid evolutionary algorithm of cooperative particle swarm optimization (CPSO) and cultural algorithm, called cultural CPSO (CCPSO). The CCPSO, which uses cooperative behavior among multiple swarms, can increase the global search capacity using the belief space. Experimental results demonstrate that the proposed method performs well in predicting time series and solving nonlinear control problems.
Genotype to Phenotype Maps: Multiple Input Abiotic Signals Combine to Produce Growth Effects via Attenuating Signaling Interactions in Maize

The complexity of allele interactions constrains crop improvement and the prediction of disease susceptibility. Additive allele effects are the foundation for selection in animal and plant breeding, and complex genetic and environmental interactions contribute to inefficient detection of desirable loci. Manipulation and modeling of other sources of variation, such as environmental variables, have the potential to improve our prediction of phenotype from genotype. As an example of our approach to analysis of the network linking environmental input to alleles, we mapped the genetic architecture of single and combined abiotic stress responses in two maize mapping populations and compared the observed genetic architecture patterns to simple theoretical predictions. Comparisons of single and combined stress effects on growth and biomass traits exhibit patterns of allele effects that suggest attenuating interactions among physiological signaling steps in drought and ultraviolet radiation stress responses. The presence of attenuating interactions implies that shared QTL found in sets of environments could be used to group environment types and identify underlying environmental similarities, and that patterns of stress-dependent genetic architecture should be studied as a way to prioritize prebreeding populations. A better understanding of whole-plant interactor pathways and genetic architecture of multiple-input environmental signaling has the potential to improve the prediction of genomic value in plant breeding and crop modeling.
Regulation and Distrust

In a cross-section of countries, government regulation is strongly negatively correlated with social capital. We document this correlation, and present a model explaining it. In the model, distrust creates public demand for regulation, while regulation in turn discourages social capital accumulation, leading to multiple equilibria. A key implication of the model is that individuals in low trust countries want more government intervention even though the government is corrupt. We test this and other implications of the model using country- and individual-level data on social capital and beliefs about government’s role, as well as on changes in beliefs and in trust during the transition from socialism.
Early Word Recognition and Later Language Skills

Recent behavioral and electrophysiological evidence has highlighted the long-term importance for language skills of an early ability to recognize words in continuous speech. We here present further tests of this long-term link in the form of follow-up studies conducted with two (separate) groups of infants who had earlier participated in speech segmentation tasks. Each study extends prior follow-up tests: Study 1 by using a novel follow-up measure that taps into online processing, Study 2 by assessing language performance relationships over a longer time span than previously tested. Results of Study 1 show that brain correlates of speech segmentation ability at 10 months are positively related to 16-month-olds’ target fixations in a looking-while-listening task. Results of Study 2 show that infant speech segmentation ability no longer directly predicts language profiles at the age of five. However, a meta-analysis across our results and those of similar studies (Study 3) reveals that age at follow-up does not moderate effect size. Together, the results suggest that infants’ ability to recognize words in speech certainly benefits early vocabulary development; further observed relationships of later language skills to early word recognition may be consequent upon this vocabulary size effect.