Miracle-dz/UniFAR-FTUs huggingface dataset:
Revision of the nonequilibrium thermal dissociation and stringent washing approaches for identification of mixed nucleic acid targets by microarrays

Microarray experiments typically involve washing steps that remove hybridized nonspecific targets with the purpose of improving the signal-to-noise ratio. The quality of washing ultimately affects downstream analysis of the microarray and interpretation. The paucity of fundamental studies directed towards understanding the dissociation of mixed targets from microarrays makes the development of meaningful washing/dissociation protocols difficult. To fill the void, we examined activation energies and preexponential coefficients of 47 perfect match (PM) and double-mismatch (MM) duplex pairs to discover that there was no statistical difference between the kinetics of the PM and MM duplexes. Based on these findings, we evaluated the nonequilibrium thermal dissociation (NTD) approach, which has been used to identify specific microbial targets in mixed target samples. We found that the major premises for various washing protocols and the NTD approach might be seriously compromised because: (i) nonspecific duplexes do not always dissociate before specific ones, and (ii) the relationship between dissociation rates of the PM and MM duplexes depends on temperature and duplex sequence. Specifically for the NTD, we show that previously suggested use of reference curves, indices of curves and temperature ramps lead to erroneous conclusions.
Altered Modular Organization of Functional Connectivity Networks in Cirrhotic Patients without Overt Hepatic Encephalopathy

Minimal hepatic encephalopathy (MHE) is associated with changes in functional connectivity. To investigate the patterns of modular changes of the functional connectivity in the progression of MHE, resting-state functional magnetic resonance imaging was acquired in 24 MHE patients, 31 cirrhotic patients without minimal hepatic encephalopathy (non-HE), and 38 healthy controls. Newman's metric, the modularity Q value, was maximized and compared in three groups. Topological roles with the progression of MHE were illustrated by intra- and intermodular connectivity changes. Results showed that the Q value of MHE patients was significantly lower than that of controls (P < 0.01) rather than that of non-HE patients (P > 0.05), which was correlated with neuropsychological test scores rather than the ammonia level and Child-Pugh score. Less intrasubcortical connections and more isolated subcortical modules were found with the progression of MHE. The non-HE patients had the same numbers of connect nodes as controls and had more hubs compared with MHE patients and healthy controls. Our findings supported that both intra- and intermodular connectivity, especially those related to subcortical regions, were continuously impaired in cirrhotic patients. The adjustments of hubs and connector nodes in non-HE patients could be a compensation for the decreased modularity in their functional connectivity networks.
Disorders of phospholipid metabolism: an emerging class of mitochondrial disease due to defects in nuclear genes

The human nuclear and mitochondrial genomes co-exist within each cell. While the mitochondrial genome encodes for a limited number of proteins, transfer RNAs, and ribosomal RNAs, the vast majority of mitochondrial proteins are encoded in the nuclear genome. Of the multitude of mitochondrial disorders known to date, only a fifth are maternally inherited. The recent characterization of the mitochondrial proteome therefore serves as an important step toward delineating the nosology of a large spectrum of phenotypically heterogeneous diseases. Following the identification of the first nuclear gene defect to underlie a mitochondrial disorder, a plenitude of genetic variants that provoke mitochondrial pathophysiology have been molecularly elucidated and classified into six categories that impact: (1) oxidative phosphorylation (subunits and assembly factors); (2) mitochondrial DNA maintenance and expression; (3) mitochondrial protein import and assembly; (4) mitochondrial quality control (chaperones and proteases); (5) iron–sulfur cluster homeostasis; and (6) mitochondrial dynamics (fission and fusion). Here, we propose that an additional class of genetic variant be included in the classification schema to acknowledge the role of genetic defects in phospholipid biosynthesis, remodeling, and metabolism in mitochondrial pathophysiology. This seventh class includes a small but notable group of nuclear-encoded proteins whose dysfunction impacts normal mitochondrial phospholipid metabolism. The resulting human disorders present with a diverse array of pathologic consequences that reflect the variety of functions that phospholipids have in mitochondria and highlight the important role of proper membrane homeostasis in mitochondrial biology.
Spontaneous facial micro-expression detection based on deep learning

Facial micro-expression refers to split-second muscle changes in the face, indicating that a person is either consciously or unconsciously suppressing their true emotions. Although these expressions are constantly occurring on people faces, they were easily ignored by people with the eye blinking. That is to say, most people don't notice them and it is the true representation of people emotions and mental health. Accordingly, both of psychologists and computer scientists (in the fields of computer vision and machine learning in particular) pay attention to it owing to their promising applications in various fields (e.g. Mental clinical diagnosis and therapy, affective computing). However, detecting micro-expression is still difficult task. Here, we proposed a novel approach based on deep multi-task learning method with the HOOF(Histograms of oriented optical flow) feature for micro-expression detection. We investigated a deep multi-task learning method for facial landmark localization and split the facial area into regions of interest(ROIS). Faical micro-expression are generated by the movement of facial muscles, so we combined robust optical flow approach with the HOOF feature for evaluating the direction of movement of facial muscles. Through some experiments on CASME spontaneous micro-expression database, we can demonstrate our proposal method can achieve good performance for detecting micro-expression.
Assessing the Role of Contingency Awareness in Attitudinal Conditioning with Implications for Advertising Research

The authors investigate a basic mechanism for shaping attitudes that has largely been ignored by empirical researchers in the marketing discipline. Two experiments are reported in which traditional Pavlovian procedures are merged with a view of conditioning that encourages theorizing about attendant cognitive processes. The data indicate that contingency learning or awareness may be a requirement for successful attitudinal conditioning. Contingency awareness entails conscious recognition of the relational pattern between the conditioned and unconditioned stimuli used in a conditioning procedure. In experiment 1, the conditioning procedure affected the evaluative judgments of subjects who were classified (post hoc) as contingency aware. In experiment 2, instructions that promoted contingency learning as part of the procedure again influenced participants’ attitude judgments. Implications are offered for theory development and for constructing advertisements to foster attitudinal conditioning. Specific suggestions for further research on how one might structure television commercials to foster contingency learning also are presented.
Narrative social psychology

Social psychologists argue that people’s past weighs on their present (e.g. Liu and Hilton, 2005). The present chapter intends to show that language, particularly narrative language is an extremely useful device so as to trace the impact of past experiences on current psychological conditions. We will first review some basic tenets of narrative psychology. In the next section, we will contrast the social cognitive approach to language with that of the narrative approach emphasizing that whereas social cognition conceives language as mediator of social perception, narrative psychology in general and narrative social psychology in particular are interested in linguistic expressions of individual and group identity. We will also demonstrate that current studies on group based emotions (intergroup emotions, e.g. Smith (1993), or collective emotions, e.g. Doosje et al., 1998) can also be placed in the framework of narrative-linguistic analysis. A contrast between the universalistic social cognitive approach to self and self-categorization and the more relativistic stance of the narrative social psychology to narratively constructed personal identity and historically constructed group identity will also be discussed.The forthcoming section will outline the concepts and methods we have developed for studying quantitatively the processes and states of personal and group identity. Finally, an application of the analytic devices to the Hungarian national identity with particular respect to the elaboration of historical traumas will be presented.
The impact of language models and loss functions on repair disfluency detection

Unrehearsed spoken language often contains disfluencies. In order to correctly interpret a spoken utterance, any such disfluencies must be identified and removed or otherwise dealt with. Operating on transcripts of speech which contain disfluencies, we study the effect of language model and loss function on the performance of a linear reranker that rescores the 25-best output of a noisy-channel model. We show that language models trained on large amounts of non-speech data improve performance more than a language model trained on a more modest amount of speech data, and that optimising f-score rather than log loss improves disfluency detection performance. Our approach uses a log-linear reranker, operating on the top n analyses of a noisy channel model. We use large language models, introduce new features into this reranker and examine different optimisation strategies. We obtain a disfluency detection f-scores of 0.838 which improves upon the current state-of-the-art.
Building a grid-point cloud-semantic map based on graph for the navigation of intelligent wheelchair

The automatic navigation of the intelligent wheelchair is a major challenge for its applications. Most previous researches mainly focus on 2D navigation of intelligent wheelchair, which loses many useful environment information. This paper proposed a novel Grid-Point Cloud-Semantic Multi-layered Map based on graph optimization for intelligent wheelchair navigation. For mapping, the 2D grid map is at the bottom, the 3D point cloud map is on the grid map and the semantic markers are labelled in them. The semantic markers combine the name and coordinate value of object marker together. For navigation, the wheelchair uses the grid map for localization and path planning, uses the point cloud map for feature extraction and obstacle avoidance, and uses the semantic markers for human-robot vocal interaction. A number of experiments are carried out in real environments to verify its feasibility.
Remote networking technology for IoT: Cloud-based access for AllJoyn-enabled devices

The Internet of Things (IoT) represents a vision of a future communication between users, systems, and daily objects performing sensing and actuating capabilities with the goal to bring unprecedented convenience and economical benefits. Today, a wide variety of developed solutions for IoT can be seen through the all industry fields. Each of the developed systems is based on the proprietary SW implementation unable (in most cases) to share collected data with others. Trying to offer common communication platform for IoT, AllSeen Alliance introduced Alljoyn framework - interoperable platform for devices (sensors, actuators, etc.) and applications to communicate among themselves regardless of brands, transport technologies, and operating systems. In this paper, we discuss an application for remote management of light systems built as an extension of Alljoyn Framework - developed application is independent on communication technologies (e.g., ZigBee or WiFi). Besides provided communication independence, the presented framework can run on both major SoC architectures ARM and MIPS. To this end, we believe that our application (available as open source on GitHub) can serve as building block in future IoT / Smart home implementations.
A Constrained Least Squares Approach to Interactive Mesh Deformation

In this paper, we propose a constrained least squares approach for stably computing Laplacian deformation with strict positional constraints. In the existing work on Laplacian deformation, strict positional constraints are described using large values of least squares weights, which often cause numerical problems when Laplacians are described using cotangent weights. In our method, we describe strict positional constraints as hard constraints. We solve the combination of hard and soft constraints by constructing a typical least squares matrix form using QR decomposition. In addition, our method can manage shape deformation under over-constraints, such as redundant and conflicting constraints. Our framework achieves excellent performance for interactive deformation of mesh models
Identification of causal pattern using opinion analysis in Indonesian medical texts

Medical text extraction has become needs for researcher and society to generate factual knowledge about disease diagnosis. Disease diagnosis information is usually related to causality, symptom, and disease. Today, source of information about causality, symptom, and disease are able to be obtained from print and electronic media. The research focused on experiment and analytic related to identification of health information which is related with causality. Causality is a sentence explains about cause and effect. Some of extraction patterns to identify causality sentence have been done by researcher to generate discourse marker. However, discourse marker cannot be found in every sentence which obtains cause and effect meaning. Therefore, this research suggests a new approach to identify a correlation of causality sentences using analytical opinion pattern. Positive sentences (+) can represent an explanation of cause sentence, whereas negative sentences (-) can represent an explanation of sentence effect. Classification method that is used to identify opinion sentences is Lexicon, Naïve Bayes and SVM with 230 amount of training. The experiment using 3 chronological scenarios generate an average result as follows: Lexicon propose generates 50,14; 50,87; 49,71 while Naïve Bayes method generates 42,32; 43,33; 45,07 and SVM method generates 97,68; 97,97; 95,19. Recall measurement generates 50% from 10 sentences random.
Combined rasagiline and antidepressant use in Parkinson disease in the ADAGIO study: effects on nonmotor symptoms and tolerability.

IMPORTANCE Depression, cognitive impairment, and other nonmotor symptoms (NMSs) are common early in Parkinson disease (PD) and may be in part due to disease-related dopamine deficiency. Many patients with PD are treated with antidepressants for NMSs, and the effect of the combination of PD medications that enhance dopamine neurotransmission and antidepressants on NMSs has not been studied. We report the effects of the addition of a monoamine oxidase B inhibitor, rasagiline, to antidepressant treatment in PD. OBJECTIVE To evaluate the effect of rasagiline on depression, cognition, and other PD NMSs in patients taking an antidepressant in the Attenuation of Disease Progression With Azilect Given Once Daily (ADAGIO) study. DESIGN, SETTING, AND PARTICIPANTS The ADAGIO study was a double-blind, placebo-controlled, delayed-start trial of rasagiline in de novo PD. In this exploratory post hoc analysis, we analyzed patients taking an antidepressant during the 36-week phase 1 period, in which patients were randomized to rasagiline (1 or 2 mg/d) or placebo. MAIN OUTCOMES AND MEASURES We evaluated the change in NMSs in patients taking an antidepressant and rasagiline compared with those taking placebo. The NMSs were assessed by Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale Nonmotor Experiences of Daily Living, the original Unified Parkinson's Disease Rating Scale, and the Parkinson Fatigue Scale. RESULTS A total of 191 of the 1174 patients (16.3%) were treated with antidepressants during phase 1 and provided efficacy data. Depression and cognition scores revealed significantly less worsening in the rasagiline group compared with the placebo group (differences in Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale item-adjusted means [SEs], -0.19 [0.10], P = .048, and -0.20 [0.05], P < .001, respectively). Parkinson Fatigue Scale (mean [SE] difference, -0.42 [0.09], P < .001) and daytime sleepiness (mean [SE] difference, -0.24 [0.09], P = .006) scores also revealed significantly less worsening in the rasagiline group compared with placebo. There was a nonsignificant trend toward less worsening in apathy and no significant between-group differences in anxiety or sleep. The effect on depression remained significant after controlling for improvement in motor symptoms (mean [SE] difference, -0.23 [0.09], P = .009). There were no serious adverse events in the combined rasagiline-antidepressant group suggestive of serotonin syndrome. CONCLUSIONS AND RELEVANCE The combination of rasagiline and antidepressants in patients with de novo PD is associated with reduced worsening of a range of NMSs in preliminary analyses. Adverse effects appear uncommon with this combination. These findings suggest a role for dopamine-enhancing therapies in NMSs in early PD and encourage further study and confirmation. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00256204.
Genetic Variants Contributing to Colistin Cytotoxicity: Identification of TGIF1 and HOXD10 Using a Population Genomics Approach

Colistin sulfate (polymixin E) is an antibiotic prescribed with increasing frequency for severe Gram-negative bacterial infections. As nephrotoxicity is a common side effect, the discovery of pharmacogenomic markers associated with toxicity would benefit the utility of this drug. Our objective was to identify genetic markers of colistin cytotoxicity that were also associated with expression of key proteins using an unbiased, whole genome approach and further evaluate the functional significance in renal cell lines. To this end, we employed International HapMap lymphoblastoid cell lines (LCLs) of Yoruban ancestry with known genetic information to perform a genome-wide association study (GWAS) with cellular sensitivity to colistin. Further association studies revealed that single nucleotide polymorphisms (SNPs) associated with gene expression and protein expression were significantly enriched in SNPs associated with cytotoxicity (p ≤ 0.001 for gene and p = 0.015 for protein expression). The most highly associated SNP, chr18:3417240 (p = 6.49 × 10−8), was nominally a cis-expression quantitative trait locus (eQTL) of the gene TGIF1 (transforming growth factor β (TGFβ)-induced factor-1; p = 0.021) and was associated with expression of the protein HOXD10 (homeobox protein D10; p = 7.17 × 10−5). To demonstrate functional relevance in a murine colistin nephrotoxicity model, HOXD10 immunohistochemistry revealed upregulated protein expression independent of mRNA expression in response to colistin administration. Knockdown of TGIF1 resulted in decreased protein expression of HOXD10 and increased resistance to colistin cytotoxicity. Furthermore, knockdown of HOXD10 in renal cells also resulted in increased resistance to colistin cytotoxicity, supporting the physiological relevance of the initial genomic associations.
Development, Theoretical Framework, and Lessons Learned From Implementation of a School-Based Influenza Vaccination Intervention

The Advisory Committee on Immunization Practices (ACIP) recently recommended that all children 6 months to 18 years old be vaccinated annually against influenza. School-based influenza vaccination interventions may potentially increase influenza vaccination rates among hard-to-reach populations, particularly rural adolescents. This article describes the theoretical framework, intervention development, and lessons learned from 1st-year implementation of a multicomponent intervention aimed to promote influenza vaccine acceptance among multiethnic (predominantly African American) adolescents attending middle and high school in rural Georgia. Adolescents, parents, and school administrators were active participants in the development and implementation of the intervention. The educational intervention, which consisted of a brochure and a school skit/ presentation, was guided by constructs from the Health Belief Model and social norms. Process evaluation results indicated that our intervention development methods were successful in creating a low-cost, theory-based educational intervention that garnered community investment and met the cultural relevance and literacy needs of our target audience. To our knowledge, this study is the first to extensively engage middle- and high-school students and parents in the design and implementation of key educational components of a theory-based influenza vaccination intervention.
Social Network Analysis of 50 Years of International Collaboration in the Research of Educational Technology

The definition of the field of educational technology has evolved over 50 years. New inventions and economic globalization increasingly facilitate people’s communication for exchange of ideas and collaboration. This work attempts to describe international research collaboration in educational technology for the past 50 years. This article intends to offer an objective and quantitative description through social network analysis. The structure and evolutionary model for the international collaboration network in educational technology is proposed. Economic and geographical factors related to collaboration are analyzed, and the relationship between the number of author origins of ^an article and the times cited of the article received is discussed.