Miracle-dz/UniFAR-FTUs huggingface dataset:
Some Good NewS About RumiNAtioN: tASk-FocuSed thiNkiNG AFteR FAiluRe FAcilitAteS PeRFoRmANce imPRovemeNt

Is there an adaptive side to rumination? We tested whether rumination that is focused on correcting past mistakes and active goal achievement could produce positive outcomes; this is in contrast to rumination that focuses on the implications of failure (i.e., state rumination) and task-irrelevant rumination. In all studies, participants received failure feedback on an initial task. A second task similar to the first provided an opportunity for improvement. Studies 1 and 2 manipulated type of ruminative thought such that it was action-focused, state-focused, or task-irrelevant. Action-focused rumination led to performance improvement relative to the other two conditions. Experiment 3 allowed participants to ruminate naturalistically. The more that participants' rumination contained action-focused thoughts, the more their performance improved. Hence, rumination can yield benefits if it focuses on correcting errors and goal attainment.
Towards an Unsupervised Method for Network Anomaly Detection in Large Datasets

In this paper, we present an effective tree based subspace clustering technique (TreeCLUSS) for finding clusters in network intrusion data and for detecting known as well as unknown attacks without using any labelled traffic or signatures or training. To establish its effectiveness in finding the appropriate number of clusters, we perform a cluster stability analysis. We also introduce an effective cluster labelling technique (CLUSSLab) to label each cluster based on the stable cluster set obtained from TreeCLUSS. CLUSSLab is a multi-objective technique that employs an ensemble approach for labelling each stable cluster generated by TreeCLUSS to achieve high detection rate. We also introduce an effective unsupervised feature clustering technique to identify the dominating feature set from each cluster. We evaluate the performance of both TreeCLUSS and CLUSSLab using several real world intrusion datasets to identify known as well as unknown attacks and find that results are excellent.
Genetic Determination of Colles' Fracture and Differential Bone Mass in Women With and Without Colles' Fracture

Osteoporotic fractures (OFs) are a major public health problem. Direct evidence of the importance and, particularly, the magnitude of genetic determination of OF per se is essentially nonexistent. Colles' fractures (CFs) are a common type of OF. In a metropolitan white female population in the midwestern United States, we found significant genetic determination of CF. The prevalence (K) of CF is, respectively, 11.8% (±SE 0.7%) in 2471 proband women aged 65.55 years (0.21), 4.4% (0.3%) in 3803 sisters of the probands, and 14.6% (0.7%) in their mothers. The recurrence risk (K0), the probability that a woman will suffer CF if her mother has suffered CF is 0.155 (0.017). The recurrence risk (Ks), the probability that a sister of a proband woman will suffer CF given that her proband sister has suffered CF is 0.084 (0.012). The relative risk λ (the ratio of the recurrence risk to K), which measures the degree of genetic determination of complex diseases such as CF, is 1.312 (0.145; λ0) for a woman with an affected mother and 1.885 (0.276; λs) for a woman with an affected sister. A λ‐value significantly greater than 1.0 indicates genetic determination of CF. The terms λ0 and λs are related to the genetic variances of CF. These parameters translate into a significant and moderately high heritability (0.254 [0.118]) for CF. These parameters were estimated by a maximum likelihood method that we developed, which provides a general tool for characterizing genetic determination of complex diseases. In addition, we found that women without CF had significantly higher bone mass (adjusted for important covariates such as age, weight, etc.) than women with CF.
A New Architecture for Reduction of Energy Consumption of Home Appliances

This paper presents the recent results achieved by AIM consortium (AIM, 2008) in developing and demonstrating a new information and communication technologies (ICT) architecture for modelling, virtualising and managing the energy consumption of home appliances. The architecture aims at fostering a harmonised technological frame for profiling and optimizing the energy consumption patterns of home appliances. The intention is to offer users a number of standalone- and operator-based residential services that will allow them to manage efficiently the energy consumed in households. To make these services possible the frame adopts a generalised method for household appliances management, which is based on an accurate modelling of operational modes of appliances and the ability of the home network to switch on or off some of their internal functions without limiting their control just to the active or stand-by states. As a pilot application, the appliances being considered for the first implementation of the architecture are: white goods, e.g. refrigerators, ovens, washing machines, dryers; audiovisual equipment, e.g. TVs, DVDs, Set-top-Boxes; and home communication devices, e.g. wireless routers, DECT phones, residential gateways, modems. The requirements defined for the architecture concern mainly usability aspects of power management functions, integration with the home network and service deployment. The final result provided by the project is a system with enhanced home network architecture, incorporating services for home appliances energy consumption monitoring and management and using a generic technology. The two major challenges are energy saving and the architecture's long-term sustainability.
Image denoising via group sparse eigenvectors of Graph Laplacian

In this paper, a group sparse model using Eigenvectors of the Graph Laplacian (EGL) is proposed for image denoising. Unlike the heuristic setting for each image and for each noise deviation in the traditional denoising method via the EGL, in our group-sparse-based method, the used eigenvectors are adaptively selected with the error control. Sequentially, a modified group orthogonal matching pursuit algorithm is developed to efficiently solve the optimal problem in this group sparse model. The experiments show that our method can achieve a better performance than some well-developed denoising methods, especially in the noise of large deviations and in the SSIM measure.
Probabilistic Latent Prosody Analysis for Robust Speaker Verification

In this investigation, two probabilistic latent semantic analyses (PLSA)-based approaches are proposed for use in speaker verification systems to reduce the number of parameters required by prosodic speaker models to (1) estimate reliably speakers' bi-gram models and to (2) reduce the amount of required training and test data. The basic concept is to (1) adopt PLSA to smooth the underlying n-gram-based prosodic speaker models, and to (2) use PLSA to find a compact latent prosody space to represent efficiently the constellation of speakers. The proposed approaches are evaluated on the standard single-speaker detection task of the 2001 NIST Speaker Recognition Evaluation Corpus, where only one 2 minute training enrollment speech and 30 s test speech on average are available. Experimental results demonstrated that the proposed approach can reduce the required number of bi-gram parameters from 112 to 88 and 63 per speaker and improve the EERs of MAP-GMM and GMM+T-norm from 12.4% and 9.5% to 10.4% and 8.4%, respectively, and finally to 8.1% after fusing all systems
Students’ Experiences, Learning Outcomes and Satisfaction in e-Learning

This study was aimed to examine whether students’ experiences in e-learning are related to learning outcomes and satisfaction. Three learning experiences, which are course design, interaction with the instructor and interaction with peer students were identified as the predictors of learning outcomes and satisfaction. Self-administered questionnaire was adopted. The paper questionnaires were distributed to students at a university in Malaysia. In total, 670 valid responses were obtained. Exploratory factor analysis was performed to confirm the underlying factor structure for the observed variables. Regression analyses indicated that course design, interaction with the instructor and interaction with peer students are positively related to the learning outcomes and satisfaction. Among all learning experiences, interaction with peer students make the strongest contributions to learning outcomes and satisfaction. This study demonstrates the importance for University administrators and instructors to design e-learning course to optimal students’ experiences to enhance their learning outcomes and satisfaction.
On the thresholds of generalized LDPC convolutional codes based on protographs

A threshold analysis of terminated generalized LDPC convolutional codes (GLDPC CCs) is presented for the binary erasure channel. Different ensembles of protograph-based GLDPC CCs are considered, including braided block codes (BBCs). It is shown that the terminated PG-GLDPC CCs have better thresholds than their block code counterparts. Surprisingly, our numerical analysis suggests that for large termination factors the belief propagation decoding thresholds of PG-GLDPC CCs coincide with the ML decoding thresholds of the corresponding PG-GLDPC block codes.
On the existence of compositional barrier certificates

This paper provides a necessary and sufficient condition for the compositional verification of a continuous system with additively separable barrier functions. The compositional safety verification enables the verification of an interconnection of subsystems. The idea behind the compositional analysis is to allow the verification of systems with a high dimension, by the verification of multiple lower dimensional subproblems. In the compositional safety analysis, a particular structure is imposed on the barrier certificate, restricting the applicability of the method. We show an example of a system that cannot be verified using the compositional method, but can be verified using a centralized method. This example highlights how not to decompose systems, and should be used to guide the decomposition of a system into appropriate subsystems. Finally, we provide a second condition for the compositional safety analysis that enables the verification of the counterexample, by imposing a less restrictive structure of the barrier function. This shows that the counterexample can be solved with a compositional method, but at an increased computational complexity.
Interpersonal trust and team performance: a QuantItatIve study

The relationship between two variables in a team - interpersonal trust and team performance – was examined. Working teams (N-26) comprising 181 persons (84 female, 97 male) of several organisations participated in this study. It was predicted that higher level of interpersonal trust among team members will lead to high team performance while lower interpersonal trust will lead a team to poor team performance resulting in a positive correlation between the given two variables. Pearson product-moment correlation (Pearson’s r) method was used. Interpersonal trust among team members had a significant positive effect on overall team performance. This study suggested that working teams in organisations can achieve their goal more easily if team members are high in interpersonal trust compared to teams who lack it.
Genome sequencing-assisted identification and the first functional validation of N-acyl-homoserine-lactone synthases from the Sphingomonadaceae family

Background Members of the genus Novosphingobium have been isolated from a variety of environmental niches. Although genomics analyses have suggested the presence of genes associated with quorum sensing signal production e.g., the N-acyl-homoserine lactone (AHL) synthase (luxI) homologs in various Novosphingobium species, to date, no luxI homologs have been experimentally validated. Methods In this study, we report the draft genome of the N-(AHL)-producing bacterium Novosphingobium subterraneum DSM 12447 and validate the functions of predicted luxI homologs from the bacterium through inducible heterologous expression in Agrobacterium tumefaciens strain NTL4. We developed a two-dimensional thin layer chromatography bioassay and used LC-ESI MS/MS analyses to separate, detect and identify the AHL signals produced by the N. subterraneum DSM 12447 strain. Results Three predicted luxI homologs were annotated to the locus tags NJ75_2841 (NovINsub1), NJ75_2498 (NovINsub2), and NJ75_4146 (NovINsub3). Inducible heterologous expression of each luxI homologs followed by LC-ESI MS/MS and two-dimensional reverse phase thin layer chromatography bioassays followed by bioluminescent ccd camera imaging indicate that the three LuxI homologs are able to produce a variety of medium-length AHL compounds. New insights into the LuxI phylogeny was also gleemed as inferred by Bayesian inference. Discussion This study significantly adds to our current understanding of quorum sensing in the genus Novosphingobium and provide the framework for future characterization of the phylogenetically interesting LuxI homologs from members of the genus Novosphingobium and more generally the family Sphingomonadaceae.
On a Generic Shape Complementarity Score

Motivation. The ability to quantify shape complementarity (i.e., a measure for the ‘goodness of fit’) of geometric interfaces appears fundamental to applications as diverse as mechanical design and manufacturing automation, robot motion planning and navigation, protein docking and rational drug design, and in the broad scientific arena whenever the behavior/function of a system is dependent on proper geometric alignment (i.e., interfaceability) of the constituents. However, the current challenge lies in the lack of a generic mathematical formulation that applies to objects of arbitrary shape, and obtaining a general measure of interfaceability without simplifying assumptions on the shape domain remains an open problem. In spite of the substantial amount of research on ad-hoc measures of shape complementarity for protein complexes (i.e., finite arrangements of spherical atoms) reviewed in [5, 8], the problem is scarcely studied for objects of arbitrarily complex surface features [1]. Here we propose a novel formulation and computational framework for objects of arbitrary shape in the Euclidean 3−space, potentially extensible to higher dimensions, built on a generalization of the ideas that are in use in the most recent protein docking systems [2, 4].
Impaired NFKBIE gene function decreases cellular uptake of methotrexate by down-regulating SLC19A1 expression in a human rheumatoid arthritis cell line

Abstract Objective: A non-synonymous single nucleotide polymorphism (nsSNP, rs2233434, Val194Ala) in the NFKBIE (nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, epsilon) gene is known to be a rheumatoid arthritis (RA) susceptibility polymorphism in the Japanese RA population and could be closely associated with nuclear factor kappaB (NF-κB) activity. Inflammation caused by RA is sometimes associated with changes in expression levels of MTX (methotrexate) pathway-related genes. It is of interest to examine whether the NFKBIE gene had any influences on the mode of MTX action. Methods: Both knockdown of NFKBIE gene expression and overexpression of wild-type NFKBIE and Val194Ala mutation were performed. A transfected human RA synovial cell line was cultured and then gene expressions in the MTX pathway were measured. In addition, we measured the uptake and efflux of MTX derivatives under the NFKBIE knockdown condition. Results: Knockdown of NFKBIE reduced the mRNA for SLC19A1, a main MTX membrane transporter, and the intracellular accumulations of MTX derivatives. Moreover, our experiments also confirmed that overexpression of Val194Ala mutant NFKBIE decreased the SLC19A1 mRNA when compared to that of wild-type NFKBIE. Conclusions: We suggest that the impairment of NFKBIE gene function can reduce the uptake of MTX into cells, suggesting that the gene is an important factor for the RA outcome.
Cooperative Regions For Coded Cooperation Over Time-Varying Fading Channels

The performance analysis of coded cooperation has been mainly focused on two extreme cases of channel variability, i.e. the block-fading (BF) and the fast-fading (FF) model. In more practical propagation environments the fading correlation across time depends on the level of user mobility. This paper analyzes the effects of time-selective fading on the performance of coded cooperation by providing an analytical framework for the error rate evaluation as a function of the mobility degree of the mobile station (MS) and of the quality of the inter-MS channel. The purpose is to evaluate the conditions on the propagation settings where the additional exploitation of spatial diversity (when time-diversity is available) provided by cooperative transmission is able to enhance substantially the performance of the non-cooperative transmission. We show that coded cooperation can outperform the non-cooperative (coded and bit-interleaved) transmission only up to a certain degree of mobility. The cooperative region is defined as the collection of mobility settings for which coded cooperation can be regarded as a competitive strategy compared to non-cooperative transmission. Contrary to what has been previously shown for BF channels, we demonstrate that the inter-MS channel quality plays a key role in the definition of the cooperative region.
Re-structuring, Re-labeling, and Re-aligning for Syntax-Based Machine Translation

This article shows that the structure of bilingual material from standard parsing and alignment tools is not optimal for training syntax-based statistical machine translation (SMT) systems. We present three modifications to the MT training data to improve the accuracy of a state-of-the-art syntax MT system: re-structuring changes the syntactic structure of training parse trees to enable reuse of substructures; re-labeling alters bracket labels to enrich rule application context; and re-aligning unifies word alignment across sentences to remove bad word alignments and refine good ones. Better structures, labels, and word alignments are learned by the EM algorithm. We show that each individual technique leads to improvement as measured by BLEU, and we also show that the greatest improvement is achieved by combining them. We report an overall 1.48 BLEU improvement on the NIST08 evaluation set over a strong baseline in Chinese/English translation.
Effects of Chrysin-PLGA-PEG Nanoparticles on Proliferation and Gene Expression of miRNAs in Gastric Cancer Cell Line

Background Recently, Chrysin, as a flavone, has revealed cancer chemo-preventive activity. The present experiment utilized the PLGA-PEG-chrysin complex, and free chrysin, to evaluation of the expression of miR-22, miR-34a and miR-126 in human gastric cell line. Objectives The purpose of this study was to examine whether nano encapsulating chrysin improves the anti-cancer effect of free chrysin on AGS human gastric cell line. Methods Properties of the chrysin encapsulated in PLGA-PEG nanoparticles were investigated by SEM, H NMR, and FTIR. The assessment of cytotoxicity on the growth of the human gastric cell line was carried out through MTT assay. After treating the cells with a prearranged amount of pure and encapsulated chrysin, RNA was extracted and the expressions of miR-22, miR-34a and miR-126 were measured by using real-time PCR. Results With regard to the amount of the chrysin loaded in PLGA-PEG nanoparticles, IC50 value was significantly decreased in nanocapsulatedchrysin, in comparison with free chrysin. This finding has been proved through the further increase of miR-22, miR-34a and miR-126 gene expression of nanocapsulatedchrysin, in comparison with free chrysin. Conclusions In this study, we revealed that the PLGA-PEG-chrysin is more effective than free chrysin in inhibiting the growth of human gastric cell line.
Image Preprocess Head Detection Body Detection Signage Detection Signage Detection Signage Recognition

—Signage plays an important role in wayfinding and navigation to assist blind people accessing unfamiliar environments. In this paper, we present a novel camera-based approach to automatically detect and recognize restroom signage. Our method can handle symbolic signs, text, or both. For symbolic signage, we first employ shape detection to extract the attended areas which contain restroom signage. Then, local features are extracted from the attended areas to search for possible signage based on Scale-Invariant Feature Transform (SIFT) descriptor. Third, symbolic signage is detected and recognized as the regions with the SIFT matching scores larger than a threshold. For signage with text, a robust text extraction method is developed to detect the text regions, which are then binarized and recognized by off-the-shelf optical character recognition (OCR) software. The recognition results are then transformed into speech for blind users. Experiments show that the proposed method can handle multiple signage detection. Evaluation results on our collected restroom signage dataset demonstrate the effectiveness and efficiency of the proposed method.
Group Sparse Non-negative Matrix Factorization for Multi-Manifold Learning

Many observable data sets such as images, videos and speech can be modeled by a mixture of manifolds which are the result of multiple factors (latent variables). In this paper, we propose a novel algorithm to learn multiple linear manifolds for face recognition, called Group Sparse Non-negative Matrix Factorization (GSNMF). Via the group sparsity constraint imposed on the column vectors of the coefficient matrix, we obtain multiple linear manifolds each of them belongs to a particular class. For a test image, we represent it as a linear combination of the learned multiple linear manifolds, and then the representation is naturally group sparse: only the coefficients corresponding to the same class are nonzero. We conduct extensive experiments to verify the proposed algorithm using the ORL database, the Yale database and the Extended Yale B database. Our evaluation shows that GSNMF achieves accurate recognition on face images with varying illuminations and expressions.
Identification of Mycobacterium tuberculosis CTL epitopes restricted by HLA-A*0201 in HHD mice.

BACKGROUND CD8 T cells are thought to play an important role in protective immunity to tuberculosis. The major histocompatibility complex class I subtype HLA-A*0201 is one of the most prevalent class I alleles, with a frequency of over 30% in most populations. HLA-A*0201 transgenic, H-2D(b)/mouse beta2-microglobulin double-knockout mice (HHD) which express human HLA-A*0201 but no mouse class 1, was shown to provide a powerful model for studying induction of HLA-A*0201-restricted immune responses in vivo. METHODS HHD mice were immunized with plasmid DNA encoding MPB51 by using a gene gun, and IFN-gamma production from the immune spleen cells was analyzed in response to a synthetic overlapping peptide library covering the mature MPB51 sequence. catatonic T lymphocytes (CTL) activity was measured using cytotoxicity assay and the three-color flowcytometry was used to reveal IFN-gamma-producing immune spleen cells. RESULTS Our findings were shown that only one peptide, p51-70, appeared to stimulate the immune splenocytes to produce IFN-gamma. Flow cytometric analysis with intracellular IFN-gamma and the T-cell phenotype revealed that the p51-70 peptide contains an immunodominant CD8+ T-cell epitope. Further analysis with computer-assisted algorithms permitted identification of a T-cell nona mer epitope, p54-62. Finally, we proved that the p54-62/HLA-A*0201 complex is strongly recognized by HLA class I-restricted CD8+ MPB5 1-specific CTL cells. CONCLUSION These results suggest that vaccination with MPB51 gene elicited MPB51-specific CTL. In addition, the P54-62 epitope thus represent potential subunit component for the design of vaccines against tuberculosis.