Miracle-dz/UniFAR-FTUs huggingface dataset:
Significant Effect of Valproate Augmentation Therapy in Patients With Schizophrenia

AbstractValproate is an anticonvulsant, which is also widely used for treating psychiatric disorders. Some clinical trials have demonstrated benefits of valproate augmentation therapy in schizophrenia. Previous meta-analysis showed inconsistent findings because of limited literature at that time.The aim of this study is to update the newer published data by conducting a meta-analysis of clinical efficacy of valproate augmentation therapy in patients with schizophrenia or schizoaffective disorder.Data sources include electronic research through platform of PubMed.Study eligibility criteria, participants, and interventions were as follows: the inclusion criteria included articles discussing comparisons of the treatment effect in schizophrenic patients treated with antipsychotic augmented with valproate and antipsychotics with/without placebo; articles on clinical trials in humans. The exclusion criteria were case reports or series and nonclinical trials. We compared the effect between antipsychotic treatment with valproate augmentation and antipsychotic monotherapy.Data from clinical trials were pooled by random-effects model, and possible confounding variables were examined through meta-regression and subgroup analysis. Data from 11 articles including 889 patients were included into current meta-analysis.We found patients treated with antipsychotics with valproate augmentation showed significantly more improvement in total psychopathology than those treated with antipsychotics only (P = 0.02). Results from open trials, but not from randomized controlled trials (P = 0.20), showed significant improvement (P = 0.01). In addition, the significance only persisted in the studies conducted with a shorter treatment duration (P < 0.001) rather than longer treatment duration (P = 0.23). There is no difference in the dropout rate between valproate augmentation and antipsychotic treatment only (P = 0.14). We could not perform a detailed meta-analysis for every category of antipsychotics, long-term effect, and safety profiles of valproate augmentation therapy in maintenance treatment, safety in pregnant patients, and subtype of schizophrenia.Our meta-analysis highlights the significantly better treatment effect with valproate augmentation therapy in patients with schizophrenia or schizoaffective disorder, and provides important evidence for supporting the practice of valproate augmentation therapy in these patients.
Effects of mutant and antisense RNA of phospholamban on SR Ca(2+)-ATPase activity and cardiac myocyte contractility.

BACKGROUND The delayed cardiac relaxation in failing hearts has been attributed to a reduced activity of sarcoplasmic reticulum Ca(2+)-ATPase (SERCA2). Phospholamban (PLB) inhibits SERCA2 activity and is therefore a potential target to improve the cardiac performance in heart failure. METHODS AND RESULTS Mutants of PLB (Adv/mPLB) or antisense RNA of PLB (Adv/asPLB) was expressed in cardiac myocytes by recombinant adenovirus, and their effects on SERCA2 activity and myocyte contractility were studied. One mPLB, K3E/R14E, pentamerized with endogenous PLB in neonatal myocytes and resulted in a 45% increase in the affinity of SERCA2 for Ca(2+) and 27% faster diastolic Ca(2+) decline as determined by SR (45)Ca uptake assays and by indo 1-facilitated Ca(2+) transient measurement, respectively. Edge-detection analysis of adult myocyte contractility showed a 74% increase in fractional shortening, accompanied by 115% increase in velocity of relengthening and 25% decrease in time to half-maximal relengthening. In parallel, infection of neonatal cardiac myocytes by Adv/asPLB decreased the endogenous PLB level by 54%, which was associated with a 35% increase in Ca(2+) affinity of SERCA2 and 21% faster diastolic Ca(2+) decline. However, in adult cardiac myocytes, Adv/asPLB failed to significantly alter the endogenous PLB level, the SERCA2 activity, or most of the contractile parameters. CONCLUSIONS K3E/R14E is a dominant negative mutant of PLB that disrupts the structural integrity and function of the endogenous PLB and consequently enhances SERCA2 activity and myocyte contractility. In neonatal myocytes, the decrease in steady-state abundance of PLB by asPLB also leads to increased SERCA2 activity.
Invalidity of the Bootstrap and The M Out Of N Bootstrap for Confidence Interval Endpoints Defined by Moment Inequalities

This paper analyzes the finite-sample and asymptotic properties of several bootstrap and m out of n bootstrap methods for constructing confidence interval (CI) endpoints in models defined by moment inequalities. In particular, we consider using these methods directly to construct CI endpoints. By considering two very simple models, the paper shows that neither the bootstrap nor the m out of n bootstrap is valid in finite samples or in a uniform asymptotic sense in general when applied directly to construct CI endpoints. In contrast, other results in the literature show that other ways of applying the bootstrap, m out of n bootstrap, and subsampling do lead to uniformly asymptotically valid confidence sets in moment inequality models. Thus, the uniform asymptotic validity of resampling methods in moment inequality models depends on the way in which the resampling methods are employed.
Absolute magnitudes and kinematics of CP stars from Hipparcos data

The position in the HR diagram and the kinematic characteristics of different kinds of CP stars of the upper main sequence are obtained using the LM method (Luri et al., 1996). Most of the CP stars are main sequence stars occupying the whole width of the sequence. From a kinematic point of view, they belong to the young disk population (ages < 1.5 Gyr). It has also been found that, on kinematic grounds, the behaviour ofBootis stars is similar to the one observed for normal stars of the same spectral range. On the other hand, roAp and noAp stars show the same kinematic characteristics. The pe- culiar velocity distribution function has been decomposed into a sum of three dimensional gaussians and the presence of Pleiades, Sirius and Hyades moving groups has been clearly established. Finally, a small number of CP stars are found to be high-velocity objects.
Cohesion and Coalition Formation in the European Parliament: Roll-Call Votes and Twitter Activities

We study the cohesion within and the coalitions between political groups in the Eighth European Parliament (2014–2019) by analyzing two entirely different aspects of the behavior of the Members of the European Parliament (MEPs) in the policy-making processes. On one hand, we analyze their co-voting patterns and, on the other, their retweeting behavior. We make use of two diverse datasets in the analysis. The first one is the roll-call vote dataset, where cohesion is regarded as the tendency to co-vote within a group, and a coalition is formed when the members of several groups exhibit a high degree of co-voting agreement on a subject. The second dataset comes from Twitter; it captures the retweeting (i.e., endorsing) behavior of the MEPs and implies cohesion (retweets within the same group) and coalitions (retweets between groups) from a completely different perspective. We employ two different methodologies to analyze the cohesion and coalitions. The first one is based on Krippendorff’s Alpha reliability, used to measure the agreement between raters in data-analysis scenarios, and the second one is based on Exponential Random Graph Models, often used in social-network analysis. We give general insights into the cohesion of political groups in the European Parliament, explore whether coalitions are formed in the same way for different policy areas, and examine to what degree the retweeting behavior of MEPs corresponds to their co-voting patterns. A novel and interesting aspect of our work is the relationship between the co-voting and retweeting patterns.
The tissue-specific pathways regulating cell proliferation are inherited independently in somatic hybrid between thyroid and liver cells

Thyroid stimulating hormone (TSH) and insulin-like growth factors type 1 (IGF-I) regulate the proliferation and differentiation of cultured thyroid cells but not of cultured liver cells. We have examined the influence of TSH and IGF-I on the metabolic functions and proliferation of somatic hybrids obtained by fusing rat thyroid cells (FRTL5) with rat liver cells (BRL). While IGF-I is able to stimulate the proliferation of the hybrid cells (TxL) TSH fails to induce their growth. However, the hybrid TxL cells have surface TSH receptors with normal ligand characteristics. The addition of TSH to TxL cells led to typical enhancement of cAMP production and depolymerization of actin filaments. Yet, TSH failed to stimulate iodine uptake in the hybrid cells. Interestingly, iodine inhibited TxL proliferation induced by IGF- I but not by serum. It is concluded that the hybrid TxL cells inherited from the parental thyroid cells several important differentiated traits including mitogenic pathways induced and used by IGF-I, functional TSH receptors, and sensitivity to the inhibitory action of iodine.
Optimizing Winter Wheat Resilience to Climate Change in Rain Fed Crop Systems of Turkey and Iran

Erratic weather patterns associated with increased temperatures and decreasing rainfall pose unique challenges for wheat breeders playing a key part in the fight to ensure global food security. Within rain fed winter wheat areas of Turkey and Iran, unusual weather patterns may prevent attaining maximum potential increases in winter wheat genetic gains. This is primarily related to the fact that the yield ranking of tested genotypes may change from one year to the next. Changing weather patterns may interfere with the decisions breeders make about the ideotype(s) they should aim for during selection. To inform breeding decisions, this study aimed to optimize major traits by modeling different combinations of environments (locations and years) and by defining a probabilistic range of trait variations [phenology and plant height (PH)] that maximized grain yields (GYs; one wheat line with optimal heading and height is suggested for use as a testing line to aid selection calibration decisions). Research revealed that optimal phenology was highly related to the temperature and to rainfall at which winter wheat genotypes were exposed around heading time (20 days before and after heading). Specifically, later winter wheat genotypes were exposed to higher temperatures both before and after heading, increased rainfall at the vegetative stage, and reduced rainfall during grain filling compared to early genotypes. These variations in exposure to weather conditions resulted in shorter grain filling duration and lower GYs in long-duration genotypes. This research tested if diversity within species may increase resilience to erratic weather patterns. For the study, calculated production of a selection of five high yielding genotypes (if grown in five plots) was tested against monoculture (if only a single genotype grown in the same area) and revealed that a set of diverse genotypes with different phenologies and PHs was not beneficial. New strategies of progeny selection are discussed: narrow range of variation for phenology in families may facilitate the discovery and selection of new drought-resistant and avoidant wheat lines targeting specific locations.
A novel method for protein–protein interaction site prediction using phylogenetic substitution models

Protein–protein binding events mediate many critical biological functions in the cell. Typically, functionally important sites in proteins can be well identified by considering sequence conservation. However, protein–protein interaction sites exhibit higher sequence variation than other functional regions, such as catalytic sites of enzymes. Consequently, the mutational behavior leading to weak sequence conservation poses significant challenges to the protein–protein interaction site prediction. Here, we present a phylogenetic framework to capture critical sequence variations that favor the selection of residues essential for protein–protein binding. Through the comprehensive analysis of diverse protein families, we show that protein binding interfaces exhibit distinct amino acid substitution as compared with other surface residues. On the basis of this analysis, we have developed a novel method, BindML, which utilizes the substitution models to predict protein–protein binding sites of protein with unknown interacting partners. BindML estimates the likelihood that a phylogenetic tree of a local surface region in a query protein structure follows the substitution patterns of protein binding interface and nonbinding surfaces. BindML is shown to perform well compared to alternative methods for protein binding interface prediction. The methodology developed in this study is very versatile in the sense that it can be generally applied for predicting other types of functional sites, such as DNA, RNA, and membrane binding sites in proteins. Proteins 2012. © 2011 Wiley Periodicals, Inc.
Advanced sensor fault detection and isolation for electro-mechanical flight actuators

Moving towards the more electric aircraft to be able to replace mechanic, hydraulic and pneumatic components of an aircraft, the aircraft industry calls for new technologies able to support this trend. One of these technologies is the development of advanced electro-mechanical actuators for aircraft control surfaces. Step by step hydraulic actuators are replaced by their electro-mechanical alternatives featuring weight and cost savings. As hydraulic actuators are used for decades by the aircraft industry, they are augmented with advanced signal and model based fault detection and diagnosis systems able to monitor the actuator and initiate adaptations in case of failures. For electro-mechanical actuators such advanced monitoring systems are still in the initial stages. In this paper, fault detection and isolation filters are designed by applying advanced residual filter synthesis algorithms to be able to monitor the sensor of electro-mechanical actuators. This paves the way for possible adaptations in electro-mechanical actuator systems in case of failures.
Navigating the Tensions of Innovative Assessment and Pedagogy in Higher Education

Innovative practice in a classroom adds challenges and tensions to programs and institutional structures in higher education. With the recent emphasis on curricula reform, there is a great focus on assessment and pedagogical practices to support student learning. To illustrate the tensions arising from these efforts, we present four pedagogical and assessment innovation approaches using both Shulman’s (2005) Signature Pedagogies and Tatar’s (2007) Design Tensions frameworks. The four approaches include problem-based learning, game-based learning, case-based learning, and technology-enhanced learning. A narrative for each approach examines and addresses tensions using Shulman’s (2005) surface, deep and implicit structures. We argue that there is an interconnected complexity and conflicting visions among the micro- (e.g., classroom or practicum), meso- (e.g., program), and macro- (e.g., institution) levels. We acknowledge that dynamic tensions continually exist and needs to be thoughtfully navigated in support of innovative assessment and pedagogies in higher education. Dans l’enseignement superieur, les pratiques innovatrices en salle de classe ajoutent des defis et des tensions aux programmes et aux structures institutionnelles. Suite a l’importance accrue recemment attachee a la reforme des programmes d’etudes, l’accent est mis sur l’evaluation et les pratiques pedagogiques pour soutenir l’apprentissage des etudiants. Afin d’illustrer les tensions qui decoulent de ces efforts, nous presentons quatre approches de pedagogie et d’evaluation innovatrices qui font appel a la fois aux cadres de Shulman, Signature Pedagogies (2005), et a ceux de Tatar, Design Tensions (2007). Les quatre approches comprennent l’apprentissage par problemes, l’apprentissage fonde sur le jeu, l’apprentissage base sur des cas et l’apprentissage ameliore par les technologies. Chaque approche est examinee et traite des tensions qui en decoulent en faisant appel aux structures de surface, profondes et implicites de Shulman (2005). Nous soutenons qu’il existe une complexite inter-connectee et des visions conflictuelles aux niveaux micro (par ex. en salle de classe ou durant les stages), meso (par ex. dans les programmes) et macro (par ex. au niveau de l’etablissement). Nous reconnaissons que les tensions dynamiques existent de facon continue et doivent etre soigneusement examinees pour soutenir l’evaluation et les pedagogies innovatrices dans l’enseignement superieur.
Wavelet-based Indoor Object Recognition through Human Interaction

In this paper a preliminary work towards grounded robot concept learning through its vision system and human interaction is presented. With a lifelong learning server, introduced in previous work [7], the robot can learn to recognize instances of such concepts as “Person”, “Trash-can” and “Triangle sign” from the Haar wavelet transform of its vision space based on the instruction of a human teacher. Some experimental results and comparison with our previous work are also presented.
Network design for distributed model-based fault detection and isolation

This paper addresses the design of the communication network topology of a distributed diagnosis system in order to improve the fault detection and isolation performances. Specifically, a binary integer liner programming (BILP) formulation is proposed to find the optimal combination of edges of a graph that leads to the best communication network in views of the distributed diagnosis system. The presented method is based on structural models where diagnosis properties can be easily obtained. In addition, the method is successfully applied on a four tank system as an illustrative example.
RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem

For non-expert users, a textual query is the most popular and simple means for communicating with a retrieval or question answering system.However, there is a risk of receiving queries which do not match with the background knowledge.Query expansion and query rewriting are solutions for this problem but they are in danger of potentially yielding a large number of irrelevant words, which in turn negatively influences runtime as well as accuracy.In this paper, we propose a new method for automatic rewriting input queries on graph-structured RDF knowledge bases.We employ a Hidden Markov Model to determine the most suitable derived words from linguistic resources.We introduce the concept of triple-based co-occurrence for recognizing co-occurred words in RDF data.This model was bootstrapped with three statistical distributions.Our experimental study demonstrates the superiority of the proposed approach to the traditional n-gram model.
A practical clustering algorithm for static and dynamic information organization

We present and analyze the off-line star algorithm for clustering static information systems and the on-line star algo-rithm for clustering dynamic information systems. These algorithms organize a document collection into a number of clusters that is naturally induced by the collection via a computationally efficient cover by dense subgraphs. We further show a lower bound on the accuracy of the clusters produced by these algorithms as well as demonstrate that these algorithms are efficient (running times roughly linear in the size of the problem). Finally, we provide data from a number of experiments.
Blueprint for introducing innovation into wireless mobile networks

In the past couple of years we've seen quite a change in the wireless industry: Handsets have become mobile computers running user-contributed applications on (potentially) open operating systems. It seems we are on a path towards a more open ecosystem; one that has been previously closed and proprietary. The biggest winners are the users, who will have more choice among competing, innovative ideas. The same cannot be said for the wireless network infrastructure, which remains closed and (mostly) proprietary, and where innovation is bogged down by a glacial standards process. Yet as users, we are surrounded by abundant wireless capacity and multiple wireless networks (WiFi and cellular), with most of the capacity off-limits to us. It seems industry has little incentive to change, preferring to hold onto control as long as possible, keeping an inefficient and closed system in place. This paper is a "call to arms" to the research community to help move the network forward on a path to greater openness. We envision a world in which users can move freely between any wireless infrastructure, while providing payment to infrastructure owners, encouraging continued investment. We think the best path to get there is to separate the network service from the underlying physical infrastructure, and allow rapid innovation of network services, contributed by researchers, network operators, equipment vendors and third party developers. We propose to build and deploy an open - but backward compatible - wireless network infrastructure that can be easily deployed on college campuses worldwide. Through virtualization, we allow researchers to experiment with new network services directly in their production network.