Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated whole transcriptome and DNA methylation analysis identifies gene networks specific to late-onset Alzheimer's disease.

Previous transcriptome studies observed disrupted cellular processes in late-onset Alzheimer's disease (LOAD), yet it is unclear whether these changes are specific to LOAD, or are common to general neurodegeneration. In this study, we address this question by examining transcription in LOAD and comparing it to cognitively normal controls and a cohort of "disease controls. " Differential transcription was examined using RNA-seq, which allows for the examination of protein coding genes, non-coding RNAs, and splicing. Significant transcription differences specific to LOAD were observed in five genes: C10orf105, DIO2, a lincRNA, RARRES3, and WIF1. These findings were replicated in two independent publicly available microarray data sets. Network analyses, performed on 2,504 genes with moderate transcription differences in LOAD, reveal that these genes aggregate into seven networks. Two networks involved in myelination and innate immune response specifically correlated to LOAD. FRMD4B and ST18, hub genes within the myelination network, were previously implicated in LOAD. Of the five significant genes, WIF1 and RARRES3 are directly implicated in the myelination process; the other three genes are located within the network. LOAD specific changes in DNA methylation were located throughout the genome and substantial changes in methylation were identified within the myelination network. Splicing differences specific to LOAD were observed across the genome and were decreased in all seven networks. DNA methylation had reduced influence on transcription within LOAD in the myelination network when compared to both controls. These results hint at the molecular underpinnings of LOAD and indicate several key processes, genes, and networks specific to the disease.
Multiperspective stereo matching and volumetric reconstruction

Stereo matching and volumetric reconstruction are the most explored 3D scene recovery techniques in computer vision. Many existing approaches assume perspective input images and use the epipolar constraint to reduce the search space and improve the accuracy. In this paper we present a novel framework that uses multi-perspective cameras for stereo matching and volumetric reconstruction. Our approach first decomposes a multi-perspective camera into piecewise primitive General Linear Cameras or GLCs [32]. A pair of GLCs in general do not satisfy the epipolar constraint. However, they still form a nearly stereo pair. We develop a new Graph-Cut-based algorithm to account for the slight vertical parallax using the GLC ray geometry. We show that the recovered pseudo disparity map conveys important depth cues analogous to perspective stereo matching. To more accurately reconstruct a 3D scene, we develop a new multi-perspective volumetric reconstruction method. We discretize the scene into voxels and apply the GLC back-projections to map the voxel onto each input multi-perspective camera. Finally, we apply the graph-cut algorithm to optimize the 3D embedded voxel graph. We demonstrate our algorithms on both synthetic and real multi-perspective cameras. Experimental results show that our methods are robust and reliable.
Mediating Effect of Academic Self-Efficacy on the Relationship between Academic Stress and Academic Burnout in Chinese Adolescents

The current study investigated how academic stress, academic burnout, and academic self-efficacy relate to each other; in addition, this study examined the mediating effects of academic self-efficacy on the relationship between academic stress and academic burnout of Chinese adolescents. A total of 412 students attending third-grade from two different middle schools (ninth-grade in the United States) located in Jiading District of Shanghai participated in the final analysis. By using structural equation modeling (SEM) and the maximum likelihood estimation procedures of AMOS 20.0, the latent variable measurement models were confirmed. The results and conclusions of this study are summarized as follows. A positive correlation between academic stress and academic burnout was soundly supported by this study. Meanwhile, both academic stress and academic burnout indicated negative correlations with academic self-efficacy. The modeling indicated that academic self-efficacy has a partial mediating process and a direct effect on the relationship between academic stress and academic burnout. Thus, academic stress and academic burnout were significantly weaker when academic self-efficacy was higher. In the field of education and curriculum, these results are applicable for restructuring or developing Chinese middle school curriculum utilizing useful methods for adolescents to develop their academic self-efficacy.
Microsurgical Treatment of Meningiomas in the Torcular Herophili Region

AbstractThe Torcular Herophili region of the brain is anatomically complex, and surgery in this area requires much skill and care. Retrospective analysis on 35 cases of meningiomas in the Torcular Herophili region treated by microsurgery and confirmed by pathology. Tumor resection range was evaluated using the Simpson grading criteria. Postoperative complications and tumor recurrence were evaluated. Patients were followed up. The Karnofsky performance status was used to evaluate neurologic functions. Magnetic resonance venography (MRV) and magnetic resonance imaging (MRI) revealed the extent of disease in all patients. Simpson level I excision was done in 27 patients, level II in 5 patients, and level IV in 3 patients. Gamma knife treatment after surgery was performed in 3 patients. Symptoms of increased intracranial pressure were relieved after surgery. No patient died, and no patient suffered from any relevant operative complications and disabilities. Pathology reported typical meningioma (World Health Organization [WHO] level I) in 32 patients, and atypical meningioma (WHO level II) in 3 patients. Thirty-two patients were followed up for 0.5 to 5 years: 1 patient relapsed 2 years after operation (Simpson level IV excision), and 2 patients relapsed 3 years after operation (one Simpson level I and one level II). These results indicated that MRV should be performed to confirm the exact relationship between the tumor and venous sinus. The operative approach should be planned according to the MRI results, and the venous sinus should be preserved. Gamma knife might be a beneficial auxiliary treatment of meningioma in the Torcular Herophili region.
Agriculture sur pentes au Vietnam : une nécessité pour la sécurité alimentaire et un risque pour la durabilité du système agricole

Tandis que les zones de montagne moins peuplees apportent les ressources en eau qui permettent aux plaines de prosperer, les habitants des zones montagneuses continuent a souffrir de pauvrete, de faibles productivites agricoles accompagnees de degradation environnementale. Une solution a ce paradigme semble etre la mobilisation mutuelle de toutes parties prenantes via des mecanismes incitatifs de type PES (Payment for Environmental Services). L'idee est de relier politiques agricoles et strategies individuelles dans une meme action repondant aux contraintes physiques, economiques et culturelles des milieux physiques et humains en meme temps qu'aux contraintes institutionnelles pour une bonne gouvernance. Un meilleur lien entre terres de pente et plaines devrait garantir un usage durable des terres de pente sans risque pour les plaines.
GenToS: Use of Orthologous Gene Information to Prioritize Signals from Human GWAS

Genome-wide association studies (GWAS) evaluate associations between genetic variants and a trait or disease of interest free of prior biological hypotheses. GWAS require stringent correction for multiple testing, with genome-wide significance typically defined as association p-value <5*10−8. This study presents a new tool that uses external information about genes to prioritize SNP associations (GenToS). For a given list of candidate genes, GenToS calculates an appropriate statistical significance threshold and then searches for trait-associated variants in summary statistics from human GWAS. It thereby allows for identifying trait-associated genetic variants that do not meet genome-wide significance. The program additionally tests for enrichment of significant candidate gene associations in the human GWAS data compared to the number expected by chance. As proof of principle, this report used external information from a comprehensive resource of genetically manipulated and systematically phenotyped mice. Based on selected murine phenotypes for which human GWAS data for corresponding traits were publicly available, several candidate gene input lists were derived. Using GenToS for the investigation of candidate genes underlying murine skeletal phenotypes in data from a large human discovery GWAS meta-analysis of bone mineral density resulted in the identification of significantly associated variants in 29 genes. Index variants in 28 of these loci were subsequently replicated in an independent GWAS replication step, highlighting that they are true positive associations. One signal, COL11A1, has not been discovered through GWAS so far and represents a novel human candidate gene for altered bone mineral density. The number of observed genes that contained significant SNP associations in human GWAS based on murine candidate gene input lists was much greater than the number expected by chance across several complex human traits (enrichment p-value as low as 10−10). GenToS can be used with any candidate gene list, any GWAS summary file, runs on a desktop computer and is freely available.
Practical experiments in parsing using Tree Adjoining Grammars

We present an implementation of a chart-based head-corner parsing algorithm for lexicalized Tree Adjoining Grammars. We report on some practical experiments where we parse sentences from the Wall Street Journal using this parser. In these experiments the parser is run without any statistical pruning; it produces all valid parses for each sentence in the form of a shared derivation forest. The parser uses a large Treebank Grammar with tree templates with about lexicalized trees. The results suggest that the observed complexity of parsing for LTAG is dominated by factors other than sentence length. 1. Motivation The particular experiments that we report on in this paper were chosen to discover certain facts about LTAG parsing in a practical setting. Specifically, we wanted to discover the importance of the worst-case results for LTAG parsing in practice. Let us take Schabes’ Earleystyle TAG parsing algorithm (Schabes, 1994) which is the usual candidate for a practical LTAG parser. The parsing time complexity of
Information systems as social structures

Organizations are changing at an ever-faster pace, as they try tokeep up with globalization and the information revolution.Unfortunately, information systems technologies do not supportsystem evolution well, making information systems a roadblock toorganizational change. We propose to view information systems associal structures and define methodologies which develop and evolveseamlessly an information system within its operationalenvironment. To this end, this paper proposes an ontology forinformation systems that is inspired by social and organizationalstructures. The ontology adopts components of the i*organizational modeling framework, which is founded on the notionsof actor, goal and social dependency. Socialpatterns, drawn from research on cooperative and distributedarchitectures, offer a more macroscopic level of social structuredescription. Finally, the proposed ontology includes organizationalstyles inspired from organization theory. These are used not onlyto model the overall organizational context of an informationsystem, but also its architecture. Social patterns andorganizational styles are defined in terms of configurations ofi* concepts. The research has been conducted in the contextof the Troposproject.
Empowering End Users to Confine Their Own Applications: The Results of a Usability Study Comparing SELinux, AppArmor, and FBAC-LSM

Protecting end users from security threats is an extremely difficult, but increasingly critical, problem. Traditional security models that focused on separating users from each other have proven ineffective in an environment of widespread software vulnerabilities and rampant malware. However, alternative approaches that provide more finely grained security generally require greater expertise than typical end users can reasonably be expected to have, and consequently have had limited success. The functionality-based application confinement (FBAC) model is designed to allow end users with limited expertise to assign applications hierarchical and parameterised policy abstractions based upon the functionalities each program is intended to perform. To validate the feasibility of this approach and assess the usability of existing mechanisms, a usability study was conducted comparing an implementation of the FBAC model with the widely used Linux-based SELinux and AppArmor security schemes. The results showed that the functionality-based mechanism enabled end users to effectively control the privileges of their applications with far greater success than widely used alternatives. In particular, policies created using FBAC were more likely to be enforced and exhibited significantly lower risk exposure, while not interfering with the ability of the application to perform its intended task. In addition to the success of the functionality-based approach, the usability study also highlighted a number of limitations and problems with existing mechanisms. These results indicate that a functionality-based approach has significant potential in terms of enabling end users with limited expertise to defend themselves against insecure and malicious software.
Non-relevance feedback document retrieval

This paper reports a new document retrieval method using nonrelevant documents. From a large data set of documents, we need to find documents that relate to human interesting in as few iterations of human testing or checking as possible. In each iteration a comparatively small batch of documents is evaluated for relating to the human interesting. We applied active learning techniques based on support vector machine for evaluating successive batches, which is called relevance feedback. Our proposed approach has been very useful for document retrieval with relevance feedback experimentally. The relevance feedback needs a set of relevant and nonrelevant documents to work usefully. However, the initial retrieved documents, which are displayed to a user, sometimes don't include relevant documents. In order to solve this problem, we propose a new feedback method using information of nonrelevant documents only. We named this method "nonrelevance feedback document retrieval". The nonrelevance feedback document retrieval is based on one-class support vector machine. Our experimental results show that this method can retrieve relevant documents using information of nonrelevant documents only.
The International Dimension of the Antitrust Practice in Poland, Hungary and the Czech Republic

This paper analyses how the competition authorities in the Czech republic, Poland and Hungary (CPH) have dealt with the interface between trade and competition in their actual practice. The following findings emerge (i) there has not been any significant conflict in the allocation of jurisdiction between CPH on the one hand and the EU on the other hand. This may however be due to a lack of integration between these countries. (ii) the definition of the relevant geographic market suffers from significant shortcomings in each country under review with a general bias in favour of narrow market definition. Problems are most severe in the Czech republic. (iii) Anti-trust agencies in all three countries have attempted to advocate competition in the formulation of trade policy. Developments regarding the independence of the agencies is however mixed. There are some worrying signs that the Polish agency has become less independent whereas the Hungarian agency has probably become even more independent (iv) anti-trust agencies in all three countries could indeed be pursuing objectives of industrial policy in the exercise of merger control towards foreign firms. The situation is most severe in Poland where the suspicion arises that profitable market positions have been auctioned off to foreign buyers in exchange for commitments which are unrelated to the competitive situation.
Towards ground truth in geometric textures

Two-dimensional geometric texture synthesis is the geometric analogue of raster-based texture synthesis. An absence of conventional evaluation procedures in recent synthesis attempts demands an inquiry into the visual significance of synthesized results. In this paper, we report on two psychophysical experiments that explore how people understand notions of similarity in geometric textures. We present perceptual metrics and human texture generation features that are crucial for future researchers when developing and assessing the success of their algorithms.
The Munich 2011 CHiME Challenge Contribution: NMF-BLSTM Speech Enhancement and Recognition for Reverberated Multisource Environments

We present the Munich contribution to the PASCAL ‘CHiME’ Speech Separation and Recognition Challenge: Our approach combines source separation by supervised convolutive non-negative matrix factorisation (NMF) with our tandem recogniser that augments acoustic features by word predictions of a Long Short-Term Memory recurrent neural network in a multi-stream Hidden Markov Model. The performance of our source separation approach is demonstrated in a sequence of gradually refined speech recognisers. While NMF drastically improves performance for all investigated recognisers, best results are obtained with the multi-stream approach along with a novel adaptation technique for noise dictionaries in supervised NMF. On thefinal Challenge test set, the proposed system delivers an average keyword recognition accuracy of 87.86% across SNRs ranging from -6 to 9dB, reducing the error rate from 44% to 12% compared to the Challenge baseline. Index Terms: Non-Negative Matrix Factorisation, Tandem Speech Recognition
Inclusive education policy in the Hong Kong primary music classroom

ABSTRACT An education reform policy and inclusive education policy have been implemented in Hong Kong for over a decade. As more students with special educational needs have entered the mainstream education system under these policies, Hong Kong's primary music classrooms offer a site where three policies interact—the education reform policy entitled “Learning to Learn,” the policy of inclusive education, and the undeclared “policy” of making savings in the government budget. This article seeks to explore the results of the interaction of these three policies. A qualitative study was carried out to investigate the views of Hong Kong primary school music teachers on the policy of inclusion in relation to music teaching. Insufficient support in inclusive learning in “non-core” subjects, such as music, is evidenced.
Adaptive testing with equated number-correct scoring

A constrained CAT algorithm is presented that automatically equates the number-correct scores on adaptive tests. The algorithm can be used to equate number-correct scores across different administrations of the same adaptive test as well as to an external reference test. The constraints are derived from a set of conditions on item response functions that guarantees the observed number-correct score distributions on two test forms to be identical (van der Linden & Luecht, 1998). An item pool from the Law School Admission Test is used to compare the results of the algorithm with those for traditional observed-score equating of ability estimates to number-correct scores as well as the transformation to predicted number-correct scores through the test characteristic function. The effects of the constraints on the statistical properties of the ability estimator are examined.
Neural Correlates of Racial Ingroup Bias in Observing Computer-Animated Social Encounters

Despite evidence for the role of group membership in the neural correlates of social cognition, the mechanisms associated with processing non-verbal behaviors displayed by racially ingroup vs. outgroup members remain unclear. Here, 20 Caucasian participants underwent fMRI recording while observing social encounters with ingroup and outgroup characters displaying dynamic and static non-verbal behaviors. Dynamic behaviors included approach and avoidance behaviors, preceded or not by a handshake; both dynamic and static behaviors were followed by participants’ ratings. Behaviorally, participants showed bias toward their ingroup members, demonstrated by faster/slower reaction times for evaluating ingroup static/approach behaviors, respectively. At the neural level, despite overall similar responses in the action observation network to ingroup and outgroup encounters, the medial prefrontal cortex showed dissociable activation, possibly reflecting spontaneous processing of ingroup static behaviors and positive evaluations of ingroup approach behaviors. The anterior cingulate and superior frontal cortices also showed sensitivity to race, reflected in coordinated and reduced activation for observing ingroup static behaviors. Finally, the posterior superior temporal sulcus showed uniquely increased activity to observing ingroup handshakes. These findings shed light on the mechanisms of racial ingroup bias in observing social encounters, and have implications for understanding factors related to successful interactions with individuals from diverse backgrounds.
Effects of Additional Yoga, Meditation and Homework: A Randomized Controlled Trial Evaluating Sleep Problems with a University Student Sample

Aims: To investigate the effects of a theory-based treatment (active control condition) addressing social-cognitive constructs on healthy lifestyle behaviors, and whether additional effects would occur if additional practical exercises with yoga, meditation, and homework to improve self-regulatory strategies (intervention condition) were added. Study Design: Pilot study. Place and Duration: An international university in Germany, four weeks. Methodology: 23 undergraduate students were allocated either to an active control group (sessions addressing social-cognitive constructs, with no yoga, meditation, or homework) or an intervention group (sessions addressing social-cognitive constructs, with additional practical exercise in yoga and meditation, and homework to increase self-regulation). Students participated in weekly sessions over four weeks. All study participants improved in their self-regulatory skills (pros, subjective norm, self-efficacy, goal setting and cons). Effects on sleep problems transpired as an interaction of time and treatment group Original Research Article British Journal of Education, Society & Behavioural Science, 4(12): 1687-1702, 2014 1688 (Eta2=.13). The intervention increased self-regulatory strategies more than the active control treatment (Eta2=.17). Conclusion: Results highlight the importance of exercising yoga and meditation, and providing additional material to enhance self-regulatory strategies. By doing so, sleep problems in students can be reduced.