Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Expression of Two Distinct Functional Isoforms of Melanopsin (Opn4) in the Mammalian Retina

Melanopsin is the photopigment that confers photosensitivity to a subset of retinal ganglion cells (pRGCs) that regulate many non-image-forming tasks such as the detection of light for circadian entrainment. Recent studies have begun to subdivide the pRGCs on the basis of morphology and function, but the origin of these differences is not yet fully understood. Here we report the identification of two isoforms of melanopsin from the mouse Opn4 locus, a previously described long isoform (Opn4L) and a novel short isoform (Opn4S) that more closely resembles the sequence and structure of rat and human melanopsins. Both isoforms, Opn4L and Opn4S, are expressed in the ganglion cell layer of the retina, traffic to the plasma membrane and form a functional photopigment in vitro. Quantitative PCR revealed that Opn4S is 40 times more abundant than Opn4L. The two variants encode predicted proteins of 521 and 466 aa and only differ in the length of their C-terminal tails. Antibodies raised to isoform-specific epitopes identified two discrete populations of melanopsin-expressing RGCs, those that coexpress Opn4L and Opn4S and those that express Opn4L only. Recent evidence suggests that pRGCs show a range of anatomical subtypes, which may reflect the functional diversity reported for mouse Opn4-mediated light responses. The distinct isoforms of Opn4 described in this study provide a potential molecular basis for generating this diversity, and it seems likely that their differential expression plays a role in generating the variety of pRGC light responses found in the mammalian retina.
Principal Instructional Leadership, Teacher Self-Efficacy, and Teacher Professional Learning in China: Testing a Mediated-Effects Model

Background: Empirical evidence increasingly suggests that leadership which motivates, supports, and sustains the professional learning of teachers has a knock-on effect for both student learning and school improvement. The current study was conducted in China, where the workplace learning of teachers is embedded in a strong tradition of school-based, teacher learning practices such as the Master Teacher–Apprentice Bond and Teacher Research Groups. Purpose: The study investigated a mediated-effects model of principal instructional leadership and teacher learning. The model proposed principal time management skills and self-efficacy as antecedents of instructional leadership and teacher self-efficacy as a mediator of principal instructional leadership effects on the professional learning of teachers. Method: Survey data were collected from 3,414 teachers and 186 principals in 186 middle schools in Qingdao, China. Confirmatory factor analysis, structural equation modeling, and bootstrapping were used to analyze the multisource data. Results: The research confirmed a partial mediation model whereby principal instructional leadership evidenced moderate direct and indirect effects on teacher professional learning. Principal time management and self-efficacy exercised small effects on principal instructional leadership. Implications: The research adds to a growing body of research that affirms a positive relationship between principal leadership and teacher professional learning and emphasizes the importance of self-efficacy in shaping educator practice. The authors suggest the timeliness for scholars to undertake systematic reviews of this literature on leadership and teacher professional learning, and offer recommendations for school leadership practice.
Theoretical accuracy analysis of indoor visible light communication positioning system based on time-of-arrival

In this paper, an improved channel model and estimation for positioning in indoor environments using the visible light is presented. For positioning, the specific propagation and indoor channel model for visible light is used and a time-of-arrival (TOA) based distance estimations are proposed for two cases of known and unknown transmitter and receiver vertical distance. Based on this model and also assuming perfect synchronization between transmitter and receiver, the Cramer-Rao lower bound (CRLB) is computed as the theoretical limits on the performance and accuracy of any unbiased estimator. Unlike the radio frequency (RF) channel, the visible light communication (VLC) channel depends on the distance between the transmitter and receiver. Calculations show that proposed channel model and positioning result to more accurate distance estimate compared to their counterparts and the corresponding CRLB is almost 100 times lower than what was previously supposed.
Genome-wide localization of exosome components to active promoters and chromatin insulators in Drosophila

Chromatin insulators are functionally conserved DNA–protein complexes situated throughout the genome that organize independent transcriptional domains. Previous work implicated RNA as an important cofactor in chromatin insulator activity, although the precise mechanisms are not yet understood. Here we identify the exosome, the highly conserved major cellular 3′ to 5′ RNA degradation machinery, as a physical interactor of CP190-dependent chromatin insulator complexes in Drosophila. Genome-wide profiling of exosome by ChIP-seq in two different embryonic cell lines reveals extensive and specific overlap with the CP190, BEAF-32 and CTCF insulator proteins. Colocalization occurs mainly at promoters but also boundary elements such as Mcp, Fab-8, scs and scs′, which overlaps with a promoter. Surprisingly, exosome associates primarily with promoters but not gene bodies of active genes, arguing against simple cotranscriptional recruitment to RNA substrates. Similar to insulator proteins, exosome is also significantly enriched at divergently transcribed promoters. Directed ChIP of exosome in cell lines depleted of insulator proteins shows that CTCF is required specifically for exosome association at Mcp and Fab-8 but not other sites, suggesting that alternate mechanisms must also contribute to exosome chromatin recruitment. Taken together, our results reveal a novel positive relationship between exosome and chromatin insulators throughout the genome.
Représentativité dans le choix des acteurs en recherche participative: cas de l'introduction de variétés hybrides de maïs Chinoises au Bénin

Le present article vise a verifier Ex-post la pertinence de choix des acteurs au regard du contexte et des resultats d'evaluation perceptive obtenus. L'evaluation perceptive en cause ici porte autant sur les phases vegetatives, de recolte et de transformation de quatre varietes hybrides de mais chinoises. L'effort de recherche a essentiellement consiste a voir l'action collective des acteurs comme un systeme d’action concret (SAC), celui dans lequel les jeux sont plus ou moins integres et articules les uns aux autres. Apres avoir pris en compte la caracterisation socioeconomique des acteurs et l’adoption ou non d’une variete de mais introduite, la modelisation a l’aide d’une regression logistique binaire revele la pertinence des aptitudes associatives d'un cote, et l'experience de l'autre. La performance liee au genre est revelee a travers un ratio hommes-femmes relativement en faveur des femmes. Un biais spatial attendu est mis en exergue et est logiquement exprime a travers les acteurs, alors que le biais lie au genre a disparu face aux appartenances socioprofessionnelles. La representativite dans le choix des acteurs est requise afin d'assurer une evaluation objective de l'adoption varietale. Mots-cles: Adoption, Mais chinois, Choix des acteurs, Representativite, Evaluation perceptive, Benin English Title: Actors' representativeness in the participatory research : case study of the introduction of Chinese hybrid maize varieties in Benin English Abstract This paper aims at Ex-post analyzing the relevance of the choice of actors with respect to the context and the findings from the resulting perceptive evaluation. Perceptive evaluation refers to vegetative, harvest and processing phases of Chinese hybrid maize varieties. That is why actors should be representative of most socio-professional categories of farm workers. It is of a great importance that gender bias does not hinder the process of collective action. Such an endeavor is based on considering "Collective Action" as "Concrete Action System", system that relies on integrated and articulated games. After taking into account the socioeconomic characterization of actors and the adoption of a new variety of maize, modeling on the basis of binary logistic regression provides insights on the relevance of associative skills as well as actors' knowledge. There is representativeness with respect to the ratio male-female, which is relatively in favor of female. Spatial bias is stressed and is logically expressed through actors' perception on various sites, while gender bias does not exist in the face of socio-professional classes. Representativeness should be taken into account in the choice of actors in order to ensure objective evaluation of varietal adoption. Keywords: Adoption, Chinese maize, Choice of actors, Representativeness, Perceptive evaluation, Benin
Modeling Uncertainties In Robot Motions

Dealing with uncertainty is one of the major problems in robotics and one of the main obstacles to populating the world with robots that do something useful. This paper offers a new method for modeling uncertainties that exist in & robotic system, bosed on stochaatic differential equations. The benefit of using such a model is that we axe then able to capture in a analytic mathemgtical structure three key points underlying robot motion: I) the ability to properly express uncertainty within the motion descriptions, 2) the dynamic, changing nature of the task and its constraints, and 3) the idea of establishing a success probability or difficulty index for a taak. This paper is an expansion of these ideas, describing the models used and some initial experimental results for two robotic tasks: planning a velocity profile under force and time constraints, and a simple peg-in-hole task. With respect to the dynsmic nature of robotic motion tasks, the model of the environment uncert~dnty that we propose here is "dynamic" rather than "static~; the amount of knowledge about the environment is Mlowed to change as the robot moves. These results suggest that computetional models traditionMly found in the ~lower~ levels in robot systems may have application in the %pper ~ planning levels as well.
When They Come in Crowds: Charity Appeals and Moral Fatigue

Abstract The present research examined the effect of exposure to multiple charity appeals on a range of variables that are strongly predictive of moral behavior in two lab experiments. Using videos (Experiment 1; N = 75) and posters (Experiment 2, N = 62) from charitable organizations, the present findings demonstrate that exposure to multiple charity appeals (but not few charity appeals or exposure to multiple commercials) lead to moral fatigue, expressed in a breakdown of empathic accuracy, moral regard, and prosocial intent. Implications of this finding are discussed.
MPI-ClustDB: A fast String Matching Strategy Utilizing Parallel Computing

ClustDB is a tool for the identification of perfect matches in large sets of sequences. It is faster and can handle at least 8 times more data than VMATCH, the most memory efficient exact program currently available. Still ClustDB needs about four hours to compare all Human ESTs. We therefore present a distributed and parallel implementation of ClustDB to reduce the execution time. It uses a message-passing library called MPI and runs on distributed workstation clusters with significant runtime savings. MPI-ClustDB is written in ANSI C and freely available on request from the authors.
Connecting Peptide Physicochemical and Antimicrobial Properties by a Rational Prediction Model

The increasing rate in antibiotic-resistant bacterial strains has become an imperative health issue. Thus, pharmaceutical industries have focussed their efforts to find new potent, non-toxic compounds to treat bacterial infections. Antimicrobial peptides (AMPs) are promising candidates in the fight against antibiotic-resistant pathogens due to their low toxicity, broad range of activity and unspecific mechanism of action. In this context, bioinformatics' strategies can inspire the design of new peptide leads with enhanced activity. Here, we describe an artificial neural network approach, based on the AMP's physicochemical characteristics, that is able not only to identify active peptides but also to assess its antimicrobial potency. The physicochemical properties considered are directly derived from the peptide sequence and comprise a complete set of parameters that accurately describe AMPs. Most interesting, the results obtained dovetail with a model for the AMP's mechanism of action that takes into account new concepts such as peptide aggregation. Moreover, this classification system displays high accuracy and is well correlated with the experimentally reported data. All together, these results suggest that the physicochemical properties of AMPs determine its action. In addition, we conclude that sequence derived parameters are enough to characterize antimicrobial peptides.
Indoor localization techniques using wireless network and artificial neural network

This research focuses on improving indoor localization using wireless network and artificial neural network (ANN). This involves strategic study on wireless signal behavior and propagation inside buildings, suitable propagation model to simulate indoor propagation and evaluations on different localization methods such as distance based, direction based, time based and signature based. It has been identified that indoor signal propagation impairments are severe, non-linear and custom to a specific indoor location. To accommodate these impairments, an ANN is proposed to provide a viable solution for indoor location prediction as it learns the location specific parameters during training, and then performs positioning based on the trained data, while being robust to severe and non-linear propagation effects. The versatility of ANN allows different setup and optimization possibilities to affect location prediction capabilities. This research identified the best feedforward backpropagation neural network configuration for the generated simulation data and introduced a new optimization method. Indoor-specific received signal strength data were developed with the Lee’s in-building model according to a custom indoor layout. Simulation work was done to test localization performance with different feedforward backpropagation neural network setups with the generated received signal strength data as input. A data preparation method that converts the received signal strength raw data into average, median, min and max values prior to be fed into the neural network process was carried out. The method managed to increase location prediction performance using feedforward neural network with two hidden layers trained with Bayesian Regularization algorithm producing root mean squared error of 0.0821m, which is 50% better in comparison to existing research work. Additional tests conducted with six different relevant scenarios verified the scheme for localization performance robustness. In conclusion, the research has improved the performance of indoor localization using wireless network and ANN.
Capturing the Essence of Benchmarks : A New Approach to Benchmark Synthesis

In the nineteen-eighties, synthetic workloads such as Whetstone and Dhrystone fell out of favor as benchmarks of computer performance as they became less and less representative of the performance of continuouslyevolving applications and language features. Hand-coded synthetic benchmarks are difficult to develop and maintain, and they are subject to compiler optimizations that often eliminate code meant to make a significant contribution to performance. We present a new automatic benchmark synthesis methodology to address these problems. By focusing on major workload characteristics, we are able to create (synthesize) representative programs with significantly reduced runtimes. Given any application, we are able to characterize it and generate a synthetic version of the application with approximately the same instruction stream characteristics. We synthesize representative versions of the SPEC95, SPEC2000, and TPC-C benchmarks, compile and execute them and obtain an average IPC within 3.9%, 2.4% and 6.4%, respectively, of the average IPC of the original benchmarks with remarkably similar instruction mix and cache access characteristics, dispatch window occupancies, and dependency characteristics in most cases. Also, the changes in IPC due to design changes are found to be proportional to the changes in IPC in the original applications. At the same time, the synthetic benchmarks execute more than three orders of magnitude faster than the original applications.
Renewable Energy-Aware Information-Centric Networking

The ICT industry today is placed as one of the major consumers of energy, where recent reports have also shown that the industry is a major contributor to global carbon emissions. While renewable energy-aware data centers have been proposed, these solutions have certain limitations. The primary limitation is due to the design of data centers which focus on large-size facilities located in selected locations. This paper addresses this problem, by utilizing in-network caching with each router having storage and being powered by renewable energy sources (wind and solar). Besides placing contents closer to end users, utilizing in-network caching could potentially increase probability of capturing renewable energy in diverse geographical locations. Our proposed solution is dual- layered: on the first layer a distributed gradient-based routing protocol is used to discover the paths along routers that are powered by the highest renewable energy, and on the second layer, a caching mechanism will pull the contents from the data centre and place them on routers of the paths that are discovered by our routing protocol. Through our experiments on a testbed utilizing real meteorological data, our proposed solution has demonstrated increased quantity of renewable energy consumption, while reducing the workload on the data centers.
Finding falls in ambulatory care clinical documents using statistical text mining

OBJECTIVE To determine how well statistical text mining (STM) models can identify falls within clinical text associated with an ambulatory encounter. MATERIALS AND METHODS 2241 patients were selected with a fall-related ICD-9-CM E-code or matched injury diagnosis code while being treated as an outpatient at one of four sites within the Veterans Health Administration. All clinical documents within a 48-h window of the recorded E-code or injury diagnosis code for each patient were obtained (n=26 010; 611 distinct document titles) and annotated for falls. Logistic regression, support vector machine, and cost-sensitive support vector machine (SVM-cost) models were trained on a stratified sample of 70% of documents from one location (dataset Atrain) and then applied to the remaining unseen documents (datasets Atest-D). RESULTS All three STM models obtained area under the receiver operating characteristic curve (AUC) scores above 0.950 on the four test datasets (Atest-D). The SVM-cost model obtained the highest AUC scores, ranging from 0.953 to 0.978. The SVM-cost model also achieved F-measure values ranging from 0.745 to 0.853, sensitivity from 0.890 to 0.931, and specificity from 0.877 to 0.944. DISCUSSION The STM models performed well across a large heterogeneous collection of document titles. In addition, the models also generalized across other sites, including a traditionally bilingual site that had distinctly different grammatical patterns. CONCLUSIONS The results of this study suggest STM-based models have the potential to improve surveillance of falls. Furthermore, the encouraging evidence shown here that STM is a robust technique for mining clinical documents bodes well for other surveillance-related topics.
Genotype Distribution and Molecular Epidemiology of Hepatitis C Virus in Hubei, Central China

Background Little is known about the molecular epidemiology of hepatitis C virus (HCV) infection in Central China. Methodology/Principal Findings A total of 570 patients from Hubei Province in central China were enrolled. These patients were tested positive for HCV antibody prior to blood transfusion. Among them, 177 were characterized by partial NS5B and/or Core-E1 sequences and classified into five subtypes: 1b, 83.0% (147/177); 2a, 13.0% (23/177); 3b, 2.3% (4/177); 6a, 1.1% (2/177); 3a, 0.6% (1/177). Analysis of genotype-associated risk factors revealed that paid blood donation and transfusion before 1997 were strongly associated with subtypes 1b and 2a, while some subtype 2a cases were also found in individuals with high risk sexual behaviors; subtypes 3b, 6a, and 3a were detected only in intravenous drug users. Phylogeographic analyses based on the coalescent datasets demonstrated that 1b, 2a, 3b, and 6a were locally epidemic in Hubei Province. Among them, subtype 1b Hubei strains may have served as the origins of this subtype in China, and 2a and 3b Hubei strains may have descended from the northwest and southwest of China, respectively, while 6a Hubei strains may have been imported from the central south and southwest. Conclusion/Significance The results suggest that the migration patterns of HCV in Hubei are complex and variable among different subtypes. Implementation of mandatory HCV screening before donation has significantly decreased the incidence of transfusion-associated HCV infection since 1997. More attention should be paid to intravenous drug use and unsafe sexual contact, which may have become new risk factors for HCV infection in Hubei Province.
An Optimized Two-Safe Approach to Maintaining Remote Backup Systems

In a remote backup system, transaction processing takes place at the primary and the log records generated at the primary are propagated to the remote backup which uses them to reconstruct a recent state of the database at the primary. In the event of a primary failure, the backup system takes over transaction processing without causing users to observe a breach in service. Existing remote backup algorithms can be classi ed as either 2-safe or 1-safe based on whether or not the commitment of the transaction at the primary is synchronized with the propagation of its log records to the backup. Both approaches have limitations. While 1-safe approaches o er higher primary system throughput and lower transaction response time, unlike 2-safe approaches, they do not guarantee persistence of transactions during backup takeover. In this paper, we present an optimized 2-safe approach to maintaining remote backup systems that combines the desirable features of both 1-safe and 2-safe approaches { high throughput (similar to 1-safe) without risking the loss of transactions (similar to 2-safe). Algorithms are developed for multiple processor primary and backup system environments.