Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular characterization of the stress network in the human brain

The biological mechanisms underlying inter-individual differences in human stress reactivity remain poorly understood. We aimed to identify the molecular underpinning of neural stress sensitivity. Linking mRNA expression data from the Allen Human Brain Atlas to task-based fMRI revealed 201 differentially expressed genes in cortex-specific brain regions differentially activated by stress in individuals with low or high stress sensitivity. These genes are associated with stress-related psychiatric disorders (e.g. schizophrenia and anxiety) and include markers for specific neuronal populations (e.g. ADCYAP1, GABRB1, SSTR1, and TNFRSF12A), neurotransmitter receptors (e.g. GRIN3A, SSTR1, GABRB1, and HTR1E), and signaling factors that interact with the corticosteroid receptor and hypothalamic-pituitary-adrenal axis (e.g. ADCYAP1, IGSF11, and PKIA). Overall, the identified genes potentially underlie altered stress reactivity in individuals at risk for psychiatric disorders and play a role in mounting an adaptive stress response, making them potentially druggable targets for stress-related diseases.
A burst of genetic innovation in actin-related proteins (Arps) for testis-specific function in a Drosophila lineage

Many cytoskeletal proteins form the core of fundamental biological processes and are evolutionarily ancient. For example, the superfamily of actin-related proteins (Arps) specialized early in eukaryotic evolution for diverse cellular roles in the cytoplasm and the nucleus. Despite its strict conservation across eukaryotes, we find that the Arp superfamily has undergone dramatic lineage-specific diversification in Drosophila. Our phylogenomic analyses reveal four independent Arp gene duplications that originated in the common ancestor of the obscura group of Drosophila species and have been mostly preserved in this lineage. All four Arp paralogs have evolved under positive selection and are predominantly expressed in the male germline. We focus our analyses on the divergent Arp2D paralog, which arose via a retroduplication event from Arp2, a component of the 7-membered Arp2/3 complex that polymerizes branched actin networks. Computational modeling analyses suggest that Arp2D should be able to replace Arp2 in the Arp2/3 complex and bind daughter actin monomers, suggesting that Arp2D may augment Arp2’s functions in the male germline. We find that Arp2D is expressed during and following meiosis in the male germline, where it localizes to distinct locations such as actin cones–pecialized cytoskeletal structures that separate bundled spermatids into individual mature sperm. We hypothesize that this unprecedented burst of genetic innovation in cytoskeletal proteins may have been driven by the evolution of sperm heteromorphism in the obscura group of Drosophila.
Estimating convergence of Markov chain Monte Carlo simulations

An important research topic within Markov chain Monte Carlo (MCMC) methods is the estimation of convergence of a simulation. The simulation is divided in to two parts, pre- and post-convergence, where the pre-convergence part known as burn-in is discarded and the post-convergence part is used for inference. Recently, MCMC methods have become a popular way of analyzing phylogenetic models. As more and larger phylogenetic data sets are analyzed, there is a need for automated procedures estimating both convergence and sufficient run length of a simulation. Since MCMC methods are used in a variety of different research fields there are several different methods for evaluating the output of a run. In this thesis, we construct a diagnostic for estimating the burn-in of the chain. We then evaluate this diagnostic together with well known convergence diagnostics used in other fields on simulations performed on three different phylogenetic data sets. We also propose an algorithmic procedure for verifying convergence and sufficient run length of an MCMC-simulation.
Study about the inversion of radiative transfer for retrieving atmospheric parameters over the ocean using the Special Sensor Microwave/Imager (SSM/I) radiometer

A study about the maximum achievable unambiguity concerning the inversion of the relation between the 7 SSM/I-brightness temperatures at the top of the atmosphere (Tb-vectors) and the atmospheric parameters over sea surfaces is presented. As a result of these considerations a set of strongly nonlinear algorithms in matrix form for evaluating atmospheric parameters is elaborated. Applying these algorithms to a independent radiosonde data set it is shown, that they produce a clearly reduced RMS error compared with customary algorithms in closed formulation. Furthermore the reduction of the inversion ambiguity as a result of applying a certain knowledge of the atmospheric parameters is studied and quantified.
Static state estimation in electric power systems

A static state estimator is a collection of digital computer programs which convert telemetered data into a reliable estimate of the transmission network structure and state by accounting for 1) small random metering-communication errors; 2) uncertainties in system parameter values; 3) bad data due to transients and meter-communication failures; and 4) errors in the network structure due to faulty switch-circuit breaker status information. The overall state estimation process consists of four steps: 1) hypothesize mathematical structure; 2) estimate state vector; 3) detect bad data and/or structure errors; and identify bad data and/or structure errors. The problem is characterized by high dimensionality and the need for real-time solutions using limited computer time and storage. Various methods of solution are discussed and compared.
Computer-simulated Environment (VE) for training : challenge of efficacy evaluation

Computer-assisted instruction has been around for decades. There has been much speculation about the benefits of computer-mediated learning. Numerous applications have been developed in different domains incorporated with emerging technologies. In recently years, advanced technologies, such as Augmented Reality (AR) and Virtual Reality (VR), have received much attention in their potential of creating interactive learning experience for the users. However, related literature and empirical studies indicated that learning effects in computer-simulated environments or Virtual Environments (VEs) are not systematically tested. Furthermore, the performance and learning in computer-simulated learning environment need to be evaluated through more rigorous methods. This paper suggests that 1) the efficacy of VEs is subject to a close examination, not only in terms of how VE-based training systems are easy of use, but also in terms of how effective learning is; 2) evaluation of learning in computer simulated learning environments is required to be reconsidered in terms of theoretical basis and evaluation methodologies that are relevant to the measurement of training effectiveness in computer-simulated virtual learning environment. This paper explains on how learning can be assessed in VEs through the lens of training evaluation.
Nuclear Expression and DNA Binding Capacity of Receptor for Advanced Glycation End Products in Renal Tissue

The AGER gene encodes for a number of RAGE isoforms, with the membrane bound signal transduction and “decoy” circulating soluble RAGE being the best characterised. Here we demonstrate a novel nuclear isoform of RAGE in mice and human kidney cortex which by cell and size fractionation we determined to be approximately 37kda. This nuclear RAGE isoform is functional and binds to DNA sequences within the upstream 5’ promoter region of its own gene, AGER. This binding was shown to be abrogated by mutating the DNA consensus binding sequences during electromobility shift assay (EMSA) and was independent of NF-□B or AP-1 binding. Cotransfection of expression constructs encoding various RAGE isoforms along with AGER gene promoter reporter-plasmids identified that the most likely source of the nuclear isoform of RAGE was a cleavage product of the nt-RAGE isoform. In obese mice with impaired kidney function, there was increased binding of nuclear RAGE within the A. Region of ager gene promoter with corresponding increases in membrane bound RAGE in renal cells. These findings were reproduced in vitro using proximal tubule cells. Hence, we postulate that RAGE expression is in part, self-regulated by the binding of a nuclear RAGE isoform to the promoter of the AGER gene (encoding RAGE) in the kidney. We also suggest that this RAGE self-regulation is altered under pathological conditions and this may have implications for chronic kidney disease.
THE IMPACT OF COMPUTER ACTION GAMES ON THE COGNITIVE SYSTEM: A SHORT REVIEW

The aim of this review is showing the impact of playing computer action games on the cognitive processes- mostly on attention. Firstly, we described results from behavioral research indicating that the influence of playing computer games on attention, working memory, short-term memory or cognitive flexibility is not consistent. Secondly, results checking the impact of training connected with computer action games on event-related potentials (such as: N1, P1, P2, P3) are mentioned. Additionally, we present longitudinal studies carried out to investigate the persistence of computer action game training on cognitive abilities. Finally, we give some critical view of factors such as: playing experience, kind of game, participants' sex and motivation which can affect the result of mentioned studies.
Eastern Pacific migration strategies of pink-footed shearwaters Ardenna creatopus: implications for fisheries interactions and international conservation

The pink-footed shearwater Ardenna creatopus has a breeding range restricted to 3 central-Chilean islands and travels north in the eastern Pacific Ocean during the non-breeding period. Despite its Vulnerable IUCN status, the locations and relative importance of core nonbreeding areas and migratory pathways of the species are not well understood. During 5 years between 2006 and 2015, we tracked the movements of 42 after-hatch-year pink-footed shear waters in the non-breeding season using satellite tags. Tracked shearwaters exhibited 2 postbreeding-season migration strategies: 28% of individuals traveled 1600−2500 km north from their colonies to spend the entire non-breeding season off Peru, and 72% traveled 8000−11000 km north to waters off western North America (Baja California, Mexico, to southernmost Canada). Individuals that traveled to North America stopped in Peruvian waters on each leg of the migration, making this a migratory bottleneck. Core non-breeding-season areas included continental shelf and slope waters off Trujillo to Lima (Peru), central Baja California (Mexico), southern to central California (USA), and central Oregon (USA) to southern Vancouver Island (Canada). Of 12 national exclusive economic zones (EEZs) encountered north of their breeding range, birds primarily utilized the USA, Peru and Mexico, and to a lesser degree Chile, Canada, and Ecuador. Bycatch in fisheries was recently identified as a significant at-sea threat to pink-footed shear waters, and we found evidence of pink-footed shearwater bycatch in 6 EEZs encountered by tracked birds, although quantification of bycatch magnitude is variable and not all fisheries have been studied.
Presence of cucurbit viruses in Ankara and Antalya province and molecular characterization of coat protein gene of zucchini yellow mosaic virus turkish isolates

Cucurbits are widely grown vegetables in different provinces of Turkey. However their production is restricted by pests and pathogens including different plant viruses, among which Zucchini yellow mosaic virus (ZYMV) is particularly damaging. Infections by this virus during the early stages of plant development causes deformation of fruits and significant yield losses. During 2009-2014, 221 cucurbits samples were collected from fields and greenhouses from different provinces of Turkey. Serological testing was performed by double antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) for presence of Watermelon mosaic virus (WMV), ZYMV, Cucumber mosaic virus (CMV), Papaya ring spot virus (PRSV), cucumber green mottle mosaic virus (CGMMV) and Squash mosaic virus (SqMV). For molecular analaysis of ZYMV, full-length CP nucleotide sequences were obtained for 45 ZYMV isolates and compared with sequences from worldwide isolates available in databases. The CP coding regions of Turkish ZYMV were 837 nt long and encoded 279 amino acids (aa). Forty two isolates from different regions were classified in the molecular subgroup Al, the most frequent in the Mediterranean Basin, Europe and Africa. Three isolates collected from Antalya region were classified in subgroup A4 and showed 99 % sequence identity with isolates from the same subgroup that have emerged recently in France.
Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.
The Tandem Duplicator Phenotype Is a Prevalent Genome-Wide Cancer Configuration Driven by Distinct Gene Mutations

The tandem duplicator phenotype (TDP) is a genome-wide instability configuration primarily observed in breast, ovarian and endometrial carcinomas. Here, we stratify TDP tumors by classifying their tandem duplications (TDs) into three span intervals, with modal values of 11 Kb, 231 Kb, and 1.7 Mb. TDPs with prominent ~11 Kb TDs feature the conjoint loss of TP53 and BRCA1. TDPs with ~231 Kb and ~1.7 Mb TDs associate with CCNE1 pathway activation or CDK12 disruptions, in conjunction with TP53 mutations. We prove the driver role of TP53 and BRCA1 abrogation for TDP induction by generating short-span TDP mammary tumors in genetically modified mouse models harboring deleterious mutations in only these two genes. Lastly, heterogeneous combinations of mutations mediated by TDs are selected for and contribute to the oncogenic burden of TDP tumors.
A Proposed work on Adaptive resource provisioning for read intensive multi-tier applications in the cloud

With the growth of information technology, most important service is computing that meets every day needs of general community. Cloud computing is that type of computing model which uses computing resources for delivering information technology services over a network. A Service-Level Agreement (SLA) guarantees for specific quality attributes to the consumers of services such as response time, throughput etc. This paper proposed a system which addresses software configuration management. For example, we assume that the number of connections from each server in the Web server tier to the database tier is sufficient for the given workload. The proposed system also resolve problem for automatic detection and resolution of bottlenecks in a multi-tier Web application hosted on a cloud in order to provide surety of maximum response time requirements, in order to guarantees service level agreement i.e. response time. It also defines a method for identifying and retracting over provisioned resources in multi-tier cloud-hosted Web applications.
The good, the not good, and the not beautiful: On the non-obligatoriness of suppression following negation

Abstract The view that suppression of a concept within the scope of negation is not unconditional was originally introduced by Giora (2003, 2006; Giora and Fein 1999; Giora et al. 2007) via the retention hypothesis. Giora and her colleagues argue that negation does not necessarily suppress the concept within its scope. Instead, it often retains it for pragmatic considerations, both in the mind of the speaker and the addressee. The present study provides a quantitative corpus-based test for the retention hypothesis, that is the non-obligatoriness of suppression of negated concepts (also known as the negation as mitigation hypothesis, Giora 2003; Giora et al. 2005b), via a two-pronged method which combines corpus data and behavioral data. It focuses on the notion of polarity strength, which is a numerical value disclosing the degree of positivity or negativity associated with an adjective. A simple statistic which is introduced for the sake of this study – the Strength Index (SI) – naïvely assumes that canonical adjectives can be mitigated by replacing them with their negated antonyms, thus making it possible to attribute SI to them. SI is calculated for 8 canonical adjectival antonymous pairs of an emotive nature (such as good-bad). Depending on prior positive expectations, the retention hypothesis will gain support if the following results are obtained: Correlation between the SIs of unfavorable adjectives (e.g., bad) and behavioral data on the one hand, and the lack of correlation between the SIs of favorable adjectives (e.g., good) and behavioral data, on the other hand. Results attest to this correlation pattern, providing support for the retention hypothesis (see also Colston 1999).
Field Fungal Diversity in Freshly Harvested Maize

Maize is a major crop in China and maize production in Heilongjiang Province ranks No.1 in the country in annual maize production in the whole country. Maize is prone to invasion by fungi and mycotoxins produced by these fungi are proven to be serious threats to animals as well as human health. Through high through-put sequencing we detected the dominant phylum to be Ascomycota; Dothideomycetes, Sordariomycetes, Eurotiomycetes and Tremellomycetes, Saccharomycetes were the dominant classes; Hypocreales, Eurotiales, Capnodiales, Saccharomycetales, Tremellales, and Pleosporales were the main orders; Nectriaceae, Trichocomaceae, Cladosporiaceae, Debaryomycetaceae, Tremellaceae, and Pleosporaceae were major families; Gibberella, Cladosporium, Papiliotrema, Penicillium, Scheffersomyces, Talaromyces, and Epicoccum were the most abundant phylotypes at the genus level. Epicoccum_nigrum, Gibberella_zeae, Papiliotrema_flavescens, and Scheffersomyces_shehatae were the dominant fungal species. Great fungal diversity was observed in the maize samples harvested in the five major maize-growing regions in Heilongjiang Province. Maize-1 in Nenjiang County was observed to have the greatest fungal diversity and abundance among the five regions. Since some of the fungal species are mycotoxin producing, it is necessary to take precautions to ensure the maize is stored under safe conditions to prevent the occurrence of mycotoxins and the growth and reproduction of other fungi which results in deterioration in the quality of maize.
A Methodology for Applying Social Network Analysis Metrics on Biodiversity

This paper proposes a methodology for applying Social Network Analysis (SNA) metrics to biological interaction network studies in the Biodiversity Informatics domain, which may serve as a guide for this activity to other researchers. The methodology is formalized by means of Business Process Modeling Notation (BPMN) and structured in four steps: (i) mapping the data types and the interactions available; (ii) defining the key-questions to be answered and the analysis variables; (iii) choosing the SNA metrics appropriate to the context of the research; and (iv) performing the biological analysis with the support of SNA. As material resources, the SNA metrics were used, as well as a set of computational (such as R packages, Dieta, Pajek and Ucinet software) and statistical analysis (Exploratory Data Analysis and Multivariate Data Analysis) tools. The results show the benefits that providing a systematic method to guide the steps of one research can bring to a researcher - be it due to the support of the resources recommended, be it by the organization of the research activities. In addition, there is the possibility of applying this methodology to underexplored knowledge fields, such as Agrobiodiversity.