Miracle-dz/UniFAR-FTUs huggingface dataset:
Is the 5-HT 1 D β Receptor Gene Implicated in the Pathogenesis of Obsessive-Compulsive Disorder ?

Objective: Obsessive-compulsive disorder (OCD) is a psychiatric condition for which strong evidence of a genetic component and serotonergic system involvement exists. Recent studies have shown that sumatriptan, a selective ligand of the serotonin (5-HT)1Dβ autoreceptor, modifies OCD symptoms. The aim of this study was to investigate the presence of linkage disequilibrium between the 5-HT1Dβ receptor gene, which has a variant caused by a silent G to C substitution at nucleotide 861 of the coding region, and OCD.
Penyebab Kelelahan Kerja pada Pekerja Mebel

Di industri modern, kelelahan kerja adalah fenomena kompleks yang disebabkan berbagai faktor. Penelitian ini bertujuan untuk mengetahui berbagai faktor yang memengaruhi kelelahan pada pekerja mebel. Penelitian dilaksanakan pada Februari – Maret 2013 di suatu perusahaan mebel di Kabupaten Jepara. Penelitian ini adalah dengan desain potong lintang melibatkan 70 orang responden. Kelelahan kerja diukur menggunakan reaction timer, stres kerja diukur menggunakan General Health Questionnaire-12. Monoton kerja, kerja lembur, motivasi, konflik kerja diukur dengan wawancara. Status gizi diukur dengan indeks massa tubuh (IMT). Rata-rata intensitas kebisingan atau Level Equivalent diukur dengan sound level meter, penerangan lokal diukur dengan lux meter, iklim kerja dengan questemp, dan beban kerja diukur dengan denyut nadi. Data diuji dengan kai kuadrat dan multivariat dianalisis dengan visual partial least square. Kelelahan kerja dipengaruhi oleh umur (nilai p = 0,018), monoton kerja (nilai p = 0,053), dan konflik kerja (nilai p = 0,019). Menurut analisis multivariat, kelelahan kerja dipengaruhi langsung oleh konflik kerja, stres kerja, lingkungan fisik, dan kapasitas kerja. Secara tidak langsung, kelelahan kerja dipengaruhi motivasi melalui stres kerja dan melalui beban kerja dan stres kerja, beban kerja melalui stres kerja dan melalui kapasitas kerja. Faktor yang memengaruhi kelelahan kerja adalah konflik kerja, lingkungan fisik tempat kerja, kapasitas kerja, dan stres kerja. In modern industries, fatigue is complex phenomenon caused by various factors. This study aimed to find out the factors related to fatigue case of furniture workers. This study was conducted in February - March 2013 at a furniture company in Jepara. Desaign of this study was cross-sectional method with 70 respondents. Fatigue was measured using reaction timer, General Health Questionnaire-12 was used to measure psychological distress. Monotony, overtime work, motivation and conflict was measured using questionnaire. BMI was used to measure nutrition status. Adaily noise Level equivalent was estimated using sound level meter; illumination was estimated using lux meter; heat stress was estimated using questemp and workload was estimated using heart rate. Data was analyzed using chisquare and multivariate was analyzed using visual partial least square program. Results of the research indicated that there was a relationship between age (p value = 0.018), monotonous (p value = 0.053), conflict at work (p value = 0.019) and fatigue. Multivariate analysis, which were conflict at work, stress of work, physical work environment and work capacity had a direct effect to the fatigue. Motivation had an indirect effect through stress at work and it had an indirect effect through the workload and stress at work. Physical workload had an indirect effect through stress at work to the fatigue and had an indirect effect through work capacity to the fatigue. The dominant factor related to fatigue is conflict at work, physical work environmental, work capacity and stress at work.
A pattern mining framework for inter-wafer abnormality analysis

This work presents three pattern mining methodologies for inter-wafer abnormality analysis. Given a large population of wafers, the first methodology identifies wafers with abnormal patterns based on a test or a group of tests. Given a wafer of interest, the second methodology searches for a test perspective that reveals the abnormality of the wafer. Given a particular pattern of interest, the third methodology implements a monitor to detect wafers containing similar patterns. This paper discusses key elements for implementing each of the methodologies and demonstrates their usefulness based on experiments applied to a high-quality SoC product line.
Modeling of the bacterial luciferase‐flavin mononucleotide complex combining flexible docking with structure‐activity data

Although the crystal structure of Vibrio harveyi luciferase has been elucidated, the binding sites for the flavin mononucleotide and fatty aldehyde substrates are still unknown. The determined location of the phosphate‐binding site close to Arg 107 on the α subunit of luciferase is supported here by point mutagenesis. This information, together with previous structure‐activity data for the length of the linker connecting the phosphate group to the isoalloxazine ring represent important characteristics of the luciferase‐bound conformation of the flavin mononucleotide. A model of the luciferase–flavin complex is developed here using flexible docking supplemented by these structural constraints. The location of the phosphate moiety was used as the anchor in a flexible docking procedure performed by conformation search by using the Monte Carlo minimization approach. The resulting databases of energy‐ranked feasible conformations of the luciferase complexes with flavin mononucleotide, ω‐phosphopentylflavin, ω‐phosphobutylflavin, and ω‐phosphopropylflavin were filtered according to the structure‐activity profile of these analogs. A unique model was sought not only on energetic criteria but also on the geometric requirement that the isoalloxazine ring of the active flavin analogs must assume a common orientation in the luciferase‐binding site, an orientation that is also inaccessible to the inactive flavin analog. The resulting model of the bacterial luciferase–flavin mononucleotide complex is consistent with the experimental data available in the literature. Specifically, the isoalloxazine ring of the flavin mononucleotide interacts with the Ala 74–Ala 75 cis‐peptide bond as well as with the Cys 106 side chain in the α subunit of luciferase. The model of the binary complex reveals a distinct cavity suitable for aldehyde binding adjacent to the isoalloxazine ring and flanked by other key residues (His 44 and Trp 250) implicated in the active site.
Impacts of Maternal Nutrition on Vascularity of Nutrient Transferring Tissues during Gestation and Lactation

As the demand for food increases with exponential growth in the world population, it is imperative that we understand how to make livestock production as efficient as possible in the face of decreasing available natural resources. Moreover, it is important that livestock are able to meet their metabolic demands and supply adequate nutrition to developing offspring both during pregnancy and lactation. Specific nutrient supplementation programs that are designed to offset deficiencies, enhance efficiency, and improve nutrient supply during pregnancy can alter tissue vascular responses, fetal growth, and postnatal offspring outcomes. This review outlines how vascularity in nutrient transferring tissues, namely the maternal gastrointestinal tract, the utero-placental tissue, and the mammary gland, respond to differing nutritional planes and other specific nutrient supplementation regimes.
Adaptive Spatiotemporal Receptive Field Estimation in the Visual Pathway

The encoding properties of the visual pathway are under constant control from mechanisms of adaptation and systems-level plasticity. In all but the most artificial experimental conditions, these mechanisms serve to continuously modulate the spatial and temporal receptive field (RF) dynamics. Conventional reverse-correlation techniques designed to capture spatiotemporal RF properties assume invariant stimulus-response relationships over experimental trials and are thus limited in their applicability to more natural experimental conditions. Presented here is an approach to tracking time-varying encoding dynamics in the early visual pathway based on adaptive estimation of the spatiotemporal RF in the time domain. Simulations and experimental data from the lateral geniculate nucleus reveal that subtle features of encoding properties can be captured by the adaptive approach that would otherwise be undetected. Capturing the role of dynamically varying encoding mechanisms is vital to our understanding of vision on the natural setting, where there is absence of a true steady state.
Results of the HMatch Ontology Matchmaker in OAEI 2006

In this paper, we discuss our experience in testing the HMatch matchmaking system by means of the tracks proposed in the ontology alignment evaluation initiative of 2006. HMatch is a system conceived for the goal of ontology matching in open and distributed systems. It is based on linguistic and structural matching techniques for the evaluation of affinity considering concept names and concept contexts. The paper discusses the results that have been obtained and the possible improvements of the matching techniques in ongoing and future work.
Using LSA and Noun Coordination Information to Improve the Recall and Precision of Automatic Hyponymy Extraction

In this paper we demonstrate methods of improving both the recall and the precision of automatic methods for extraction of hyponymy (IS_A) relations from free text. By applying latent semantic analysis (LSA) to filter extracted hyponymy relations we reduce the rate of error of our initial pattern-based hyponymy extraction by 30%, achieving precision of 58%. Applying a graph-based model of noun-noun similarity learned automatically from coordination patterns to previously extracted correct hyponymy relations, we achieve roughly a five-fold increase in the number of correct hyponymy relations extracted.
Parallel co-simulation of conventional and active networks

Discrete event simulations are widely used to study and analyze active and conventional networking architectures and protocols. Active networks must coexist and communicate with conventional networks to effectively utilize and extend the infrastructure of the Internet. Hence, large scale network simulations containing both conventional and active components should be conducted to study crucial scalability and performance issues. In this paper, a framework to enable parallel co-simulation of conventional and active networks is described. The framework integrates ANSE, a parallel active network simulation environment, with NS, a popular sequential network simulator. Object oriented techniques that completely insulate the application modules from the modifications have been employed for parallelizing NS in order to eliminate changes to the network models. This paper presents the design and implementation of the parallel co-simulation framework along with the results obtained from our co-simulation studies. Our studies indicate that parallel simulation techniques considerably reduce simulation times for even small sized network models.
Knowledge Extraction from Fuzzy Data for Estimating Consumer Behavior Models

For certain problems of casual modeling in marketing, the information is obtained by means of questionnaires. When these questionnaires include more than one item for each observable variable, the value of this variable can not be assigned a number, but a potentially scattered set of values. In this paper, we propose to represent the information contained in this set of values by means of a fuzzy number. A novel fuzzy statistics-based interpretation of the semantic of a fuzzy set will be used for this purpose, as we will consider that this fuzzy number is a nested family of confidence intervals for a central tendency measure of the value of the variable. A genetic learning algorithm, able to extract association fuzzy rules from this data, is also proposed. The accuracy of the model will be expressed by means of a fuzzy-valued function. We propose to jointly minimize this function and the complexity of the rule based model with multicriteria genetic algorithms, that in turn will depend on a fuzzy ranking-based ordering of individuals.
Collision-free curvature-bounded smooth path planning using composite Bezier curve based on Voronoi diagram

In this paper, we present an obstacle avoiding smooth path planning method based on Voronoi diagram and composite Bezier curve algorithm which obtains the curvature bounded path with small length. In our algorithm, a Voronoi diagram is constructed according to the global environment. The piecewise linear rough path in the Voronoi diagram which keeps away from the obstacles is obtained by performing Dijkstra's shortest path algorithm. Dynamic programming is employed to subdivide the nodes on the piecewise linear path into control point subsequences to generate a collision free composite Bezier curve which satisfies the curvature constraint and approaches minimal path length.
Temperature controller design for vapor compression refrigeration cycle systems

Air-conditioning systems have been extensively used in current society. As a vital part of air-conditioning systems, the vapor compressor refrigeration cycle (VCC) systems have attracted broad attention. In this study, a VCC temperature controller is developed according to the model predictive control (MPC) method. Firstly, a model identification approach is used to model the simplified temperature control system of VCC, then a MPC control strategy is developed to control the superheat degree and room temperature. An example is given to verify the effectiveness of the proposed approach.
Detection and Classification of Adult and Fetal ECG Using Recurrent Neural Networks, Embedded Volterra and Higher-Order Statistics

The fetal heart rate (FHR) is a useful tool in the assessment of the condition of the fetal before and during labour. Fetal Electrocardiography (FECG) (Sureau, 1996) uses noninvasive surface electrodes placed on the maternal abdomen is another tool for FHR recording (Sureau, 1996). The fetal signal is weak relative to the maternal signal and to the competing noise. Widrow et al. (Widrow et al., 1975) proposed an adaptive filtering and adaptive noise cancellation method to extract the FECG from the composite maternal ECG signal. Auto-correlation and cross correlation techniques (Van Bemmel, 1968) and spatial filtering techniques (Van Oosterom, 1986, and Bergveld and Meijier 1981) have been proposed. These methods require multiple maternal thoracic ECG signals. Other methods were proposed for the rejection of the disturbing maternal ECG signal (Sureau, 1996). The automated long-term evaluation of FECG is regarded as less robust than CTG. A failure rate of approximately 30% is quoted as an almost unanimous norm (Herbert et al., 1993). The advantage of FECG is that it can be implemented in small and relatively low-cost devices (Lin et al., 1997).
Effectiveness of Closure of Public Places with Time Delay in Disease Control

Summary A theoretical basis for the evaluation of the effciency of quarantine measure is developed in a SIR model with time delay. In this model, the effectiveness of the closure of public places such as schools in disease control, modeled as a high degree node in a social network, is evaluated by considering the effect of the time delay in the identification of the infected. In the context of the SIR model, the relation between the number of infectious individuals who are identified with time delay and then quarantined and those who are not identified and continue spreading the virus are investigated numerically. The social network for the simulation is modeled by a scale free network. Closure measures are applied to those infected nodes with high degrees. The effectiveness of the measure can be controlled by the present value of the critical degree KC: only those nodes with degree higher than KC will be quarantined. The cost CQ incurred for the closure measure is assumed to be proportional to the total links rendered inactive as a result of the measure, and generally decreases with KC, while the medical cost CQ incurred for virus spreading increases with KC. The total social cost (CM + CQ) will have a minimum at a critical KC, which depends on the ratio of medical cost coeffcient αM and closure cost coeffcient αQ. Our simulation results demonstrate a mathematical procedure to evaluate the effciency of quarantine measure. Although the numerical work is based on a scale free network, the procedure can be readily generalized and applied to a more realistic social network to determine the proper closure measure in future epidemics.
Hierarchical classification of G-Protein-Coupled Receptors with data-driven selection of attributes and classifiers

We address the important bioinformatics problem of predicting protein function from a protein's primary sequence. We consider the functional classification of G-Protein-Coupled Receptors (GPCRs), whose functions are specified in a class hierarchy. We tackle this task using a novel top-down hierarchical classification system where, for each node in the class hierarchy, the predictor attributes to be used in that node and the classifier to be applied to the selected attributes are chosen in a data-driven manner. Compared with a previous hierarchical classification system selecting classifiers only, our new system significantly reduced processing time without significantly sacrificing predictive accuracy.
A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition

In this paper, a human electrocardiogram (ECG) identification system based on ensemble empirical mode decomposition (EEMD) is designed. A robust preprocessing method comprising noise elimination, heartbeat normalization and quality measurement is proposed to eliminate the effects of noise and heart rate variability. The system is independent of the heart rate. The ECG signal is decomposed into a number of intrinsic mode functions (IMFs) and Welch spectral analysis is used to extract the significant heartbeat signal features. Principal component analysis is used reduce the dimensionality of the feature space, and the K-nearest neighbors (K-NN) method is applied as the classifier tool. The proposed human ECG identification system was tested on standard MIT-BIH ECG databases: the ST change database, the long-term ST database, and the PTB database. The system achieved an identification accuracy of 95% for 90 subjects, demonstrating the effectiveness of the proposed method in terms of accuracy and robustness.
Predicting Twitter User Demographics using Distant Supervision from Website Traffic Data

Understanding the demographics of users of online social networks has important applications for health, marketing, and public messaging. Whereas most prior approaches rely on a supervised learning approach, in which individual users are labeled with demographics for training, we instead create a distantly labeled dataset by collecting audience measurement data for 1,500 websites (e.g., 50% of visitors to gizmodo.com are estimated to have a bachelor's degree). We then fit a regression model to predict these demographics from information about the followers of each website on Twitter. Using patterns derived both from textual content and the social network of each user, our final model produces an average held-out correlation of . 77 across seven different variables (age, gender, education, ethnicity, income, parental status, and political preference). We then apply this model to classify individual Twitter users by ethnicity, gender, and political preference, finding performance that is surprisingly competitive with a fully supervised approach.
A DEAD Box RNA Helicase Is Critical for Pre-mRNA Splicing, Cold-Responsive Gene Regulation, and Cold Tolerance in Arabidopsis[C][W]

This article characterizes RCF1, a cold-inducible DEAD box RNA helicase that is important for pre-mRNA splicing of genes. RCF1 regulates the expression of cold-regulated genes and is vital for cold tolerance in plants. Cold stress resulting from chilling and freezing temperatures substantially reduces crop production worldwide. To identify genes critical for cold tolerance in plants, we screened Arabidopsis thaliana mutants for deregulated expression of a firefly luciferase reporter gene under the control of the C-REPEAT BINDING FACTOR2 (CBF2) promoter (CBF2:LUC). A regulator of CBF gene expression1 (rcf1-1) mutant that is hypersensitive to cold stress was chosen for in-depth characterization. RCF1 encodes a cold-inducible DEAD (Asp-Glu-Ala-Asp) box RNA helicase. Unlike a previously reported DEAD box RNA helicase (LOW EXPRESSION OF OSMOTICALLY RESPONSIVE GENES4 [LOS4]) that regulates mRNA export, RCF1 does not play a role in mRNA export. Instead, RCF1 functions to maintain proper splicing of pre-mRNAs; many cold-responsive genes are mis-spliced in rcf1-1 mutant plants under cold stress. Functional characterization of four genes (PSEUDO-RESPONSE REGULATOR5 [PRR5], SHAGGY-LIKE SERINE/THREONINE KINASE12 [SK12], MYB FAMILY TRANSCRIPTION FACTOR CIRCADIAN1 [CIR1], and SPFH/PHB DOMAIN-CONTAINING MEMBRANE-ASSOCIATED PROTEIN [SPFH]) that are mis-spliced in rcf1-1 revealed that these genes are cold-inducible positive (CIR1 and SPFH) and negative (PRR5 and SK12) regulators of cold-responsive genes and cold tolerance. Together, our results suggest that the cold-inducible RNA helicase RCF1 is essential for pre-mRNA splicing and is important for cold-responsive gene regulation and cold tolerance in plants.
Visibility of CT Early Ischemic Change Is Significantly Associated with Time from Stroke Onset to Baseline Scan beyond the First 3 Hours of Stroke Onset

Background and Purpose Non-contrast brain computed tomography (NCCT) remains the most common imaging modality employed to select patients for thrombolytic therapy in acute ischemic stroke. The current study used the Alberta Stroke Program Early CT Score (ASPECTS) to identify early ischemic changes on brain NCCT imaging with the aim to investigate whether a relationship exists between time from symptoms onset to NCCT with the presence of early ischaemic change quantified by ASPECTS. Methods We studied 1,329 ischemic stroke patients who had NCCT within 8 hours of stroke onset. Patients were assessed to see if they had any ASPECTS lesion and if the rate of patients with a lesion increased with time using logistic regression. Results 30% patients had an ASPECTS <10 within the first 3 hours from symptom onset. Within the first 3 hours, the odds for a CT change (ASPECTS <10) per minute of time was 1.00 with 95% confidence interval (CI) (0.99 to 1.00) (P=0.266). After 3 hours, there was a significant increase in odds of ASPECTS <10 with increasing time. The odds of being ASPECTS positive increased 1% (odds ratio=1.01) per 1 minute of time with 95% CI (1.00 to 1.01) (P=0.002). Conclusions We have identified that prior to first 3 hours of stroke there was no effect of time on odds of CT ischemic change; after the first 3 hours of stroke the odds increased with increasing time to CT scan. The occurrence of early ischemic change may be a marker of time from stroke onset rather than severity.
Consumer-based brand equity and purchase decision of Indian gold jewellery

Value of brand equity is proportional to the perceived risk from buying a product. When a consumer is attached with the purchase of a product emotionally or when the product is expensive, brand equity gains more significance. In the case of purchase of gold jewellery in the Indian conditions, the consumer adds more importance to the brand name and the brand equity attached to it. This study is unique in analysing the brand equity elements behind the purchase decision of Gold Plus gold jewellery with the help of predictive neural networks model. A study of the relative importance of the brand equity dimensions is not attempted in this study as there is rich literature on this subject. This paper identifies the significant brand equity elements which lead to the purchase decision of gold jewellery sold in India under the brand name of Gold Plus, a leading brand name in India.