Miracle-dz/UniFAR-FTUs huggingface dataset:
The impacts of climate change on the reproductive success of migratory fish

Article history: Received 24 August 2015 Received in revised form 10 November 2015 Accepted 15 November 2015 Available online 18 November 2015 Climate change and urbanisation of watercourses affect water temperatures and current flow velocities in river systems on a global scale. This represents a particularly critical issue for migratory fish species with complex life histories that use rivers to reproduce. Salmonids aremigratory keystone species that provide substantial economical value to ecosystems and human societies. Consequently, a comprehensive understanding of the effects of environmental stressors on their reproductive success is critical in order to ensure their continued abundance during future climatic change. Salmonids are capital breeders, relying entirely on endogenous energy stores to fuel return migration to their natal spawning sites and reproduction upon arrival. Metabolic rates and cost of transport en-route increase with temperature and at extreme temperatures, swimming is increasingly fuelled anaerobically, resulting in an oxygen debt and reduced capacity to recover from exhaustive exercise. Thermally challenged salmonids also produce less viable gametes, which themselves are affected by water temperature after release. Passage through hydrological barriers and temperature changes both affect energy expenditure. As a result, important energetic tradeoffs emerge between extra energy used duringmigration and that available for other facets of the reproductive cycle, such as reproductive competition and gamete production. However, studies identifying these tradeoffs are extremely sparse. This review focuses on the specific locomotor responses of salmonids to thermal and hydrological challenges, identifying gaps in our knowledge and highlighting the potential implications for key aspects of their reproduction. © 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Advanced software programs for the analysis of genetic diversity in livestock genomics: a mini review

ABSTRACT The analysis of genetic diversity is very essential to understand the evolution and adaptability of livestock species to different environmental conditions. Genetic variation is the raw material for selection and foundation for breed improvement programmes. The use of high throughput molecular marker technologies, advanced statistical and software tools have revolutionized the precision of animal genetic diversity analysis in a large number of populations with limited time and resources. SNP genotyping is one of the best methods to study genetic variation due to its abundance in livestock species, stability and cost-effectiveness. In this review, some of the most popularly used diversity analysis software programs in livestock genomics are discussed briefly. Microsatellite-based software such as Genepop, Fstat, Genetix, TFPGA, Stackpack, Arlequin and other multipurpose software such as PLINK, PowerMarker, TASSEL, BEAGLE, R software packages (GenABEL, SNPassoc, snpstats, SNP relate), Gemma, SNP Express, SVS, etc. can be utilized for diversity analysis.
Microbial genomes retrieved from High Arctic lake sediments encode for adaptation to cold and oligotrophic environments

The Arctic is currently warming at an unprecedented rate, which may affect environmental constraints on the freshwater microbial communities found there. Yet, our knowledge of the community structure and functional potential of High Arctic freshwater microbes remains poor, even though they play key roles in nutrient cycling and other ecosystem services. Here, using high-throughput metagenomic sequencing and genome assembly, we show that sediment microbial communities in the High Arctic’s largest lake by volume, Lake Hazen, are phylogenetically diverse, ranging from Proteobacteria, Verrucomicrobia, Planctomycetes, to members of the newly discovered Candidate Phyla Radiation (CPR) groups. These genomes displayed a high prevalence of pathways involved in lipid chemistry, and a low prevalence of nutrient uptake pathways, which might represent adaptations to the specific, cold (~3.5°C) and extremely oligotrophic conditions in Lake Hazen. Despite these potential adaptations, it is unclear how ongoing environmental changes will affect microbial communities, the makeup of their genomic idiosyncrasies, as well as the possible implications at higher trophic levels.
A Point of Two Mode-Session Logs Based Web User Interest Prediction System From Web Search Engine

— Information prediction from web search is a hands-off process based on user interest. By differently user may think based on the knowledge or relevant search things, but web mining tasks are complex to understanding the user behaviour and knowledge to retrieve the right things to the user. To propose a new intent interest prediction for improving the efficiency, we propose a session timing preference based two mode user interest prediction methods called semantic log pre-fetch clustering (SLCPC) algorithm and personalized feed ranking (FPR) algorithm to deduce a set of related categories for each user query based on the retrieval history of the user session, i.e. different contents have to be placed for different users according to the user relevant search profiles spending time on interested logs. Two modes analyse behaviours like time of visit, navigation URL, weblogs, and user actions on the webpage. SLPC predicts web log data of the user and also identifies the implicit behaviours performed by the user. The identified information is used to identify the user interest and seeds are generated by logging page. So the user doesn't wait for long more time to search our interesting factor frequently. The web users are clusters based on the feed ranking interest which is used continues searches. Our proposed system improves the accuracy of personalized user search compared to an existing approach.
Widespread phenotypic hypervariation in the enigmatic anchialine shrimp Barbouria cubensis (Decapoda: Barbouriidae).

Classification and evolutionary relationships among anchialine shrimp from the family Barbouriidae Christoffersen, 1987, has long been a topic of debate amongst crustacean taxonomists. To date, no study has examined morphological or molecular variation among populations of these enigmatic shrimp. The present study documents and analyzes patterns of widespread morphological variation within populations of Barbouria cubensis von Martens, 1872, from anchialine pools on three Bahamian islands. Such extensive morphological variation confounds identification using classic taxonomical methods. Phenotypic variation is by no means a new topic, but studies of decapods are typically limited to isolated individuals or few morphological characters. Moreover, past studies of B. cubensis do not report extensive morphological variation, however we find that upwards of 90% of individuals are affected. Anomalous phenotypes are described in 54 morphological characters with no detectable pattern associated with geographic distribution. The term phenotypic hypervariation (PhyV) is used to describe morphological variation that greatly deviates from any previous taxonomic descriptions. Analysis of partial sequences of the 16S and COI mitochondrial genes confirm the identity of morphologically variable specimens as B. cubensis without population structure across the tropical western Atlantic. A test for cryptic diversity within B. cubensis suggests PhyV is not correlated with cryptic diversity. Morphological variation at this scale likely depends on recent changes either to their environment or genetic diversity.
Drp1-mediated mitochondrial fission regulates calcium and F-actin dynamics during wound healing

Mitochondria adapt to cellular needs by changes in morphology through fusion and fission events, referred to as mitochondrial dynamics. Mitochondrial function and morphology are intimately connected and the dysregulation of mitochondrial dynamics is linked to several human diseases. In this work, we investigated the role of mitochondrial dynamics in wound healing in the Drosophila embryonic epidermis. Mutants for mitochondrial fusion and fission proteins fail to close their wounds, indicating that the regulation of mitochondrial dynamics is required for wound healing. By live-imaging, we found that loss of function of the mitochondrial fission protein Dynamin-related protein 1 (Drp1) compromises the increase of cytosolic and mitochondrial calcium upon wounding and leads to F-actin defects at the wound edge, culminating in wound healing impairment. Our results highlight a new role for mitochondrial dynamics in the regulation of calcium and F-actin during epithelial repair. Summary We show that mitochondrial dynamics proteins are required for epithelial repair. In particular, Drp1 loss-of-function leads to defects in the dynamics of cytosolic and mitochondrial calcium and F-actin upon wounding.
Information Extraction from Text through Sequence Labelling

The way information is represented in natural language text is highly inconsistent, which makes it extremely complicated and practically impossible to explicitly tell a computer in which all ways a particular information can be represented in natural language texts, and enable it to read and understand it. The system presented here tries to bridge this gap by automatically extracting information from English text in web pages and representing them in a structured format so that it can be analysed efficiently. In order to implement the system, the task of information extraction is modelled as a sequence labelling one. It mainly uses the machine learning technique called Conditional Random Fields (CRF) to train the model and to tag the text. Further statistical and rule based techniques are also employed wherever appropriate to obtain the feature set. The system exhibits a precision of 91% and a recall of 77% that guaranties the validity of extraction techniques employed.
Cellules myéloïdes et microARNs dans l'arthrite juvénile

L'arthrite juvenile idiopathique (AJI) est un groupe heterogene de rhumatismes inflammatoires chroniques affectant les enfants de moins de 16 ans. Cette atteinte inflammatoire d'origine inconnue est caracterisee par une arthrite persistant plus de 6 semaines en l'absence de traitements. Afin de mettre en evidence des mecanismes impliques dans la physiopathologie de l'AJI, une inclusion de patients atteints d'une autre forme d'arthrite juvenile, a savoir l'arthrite septique, a ete effectuee. En parallele, des etudes comparatives entre le sang peripherique (SP) et le liquide synovial (LS) des patients atteints d'AJI ont ete realisees afin de rechercher des mecanismes specifiques aux perturbations articulaires. Un interet particulier a ete porte sur les sous-populations de monocytes et de cellules dendritiques (DCs) ainsi que les profils d'expression des microARNs (miARNs) dans le sang peripherique et le LS des patients. Ces differents marqueurs biologiques ont ete choisis car ils jouent un role majeur a la fois dans la regulation de l'inflammation et la pathogenese des maladies inflammatoires. L'analyse de l'expression des miARNs par une approche de sequencage a haut debit suivie d'une validation par RT-qPCR a mis en evidence des miARNs deregules de facon specifique dans l'AJI par rapport a l'AS. De plus, la caracterisation phenotypique des sous-populations de cellyles myeloides a montre une accumulation et une activation cellulaire propre a l'AJI. Dans l'ensemble, ce projet m'a permis d'identifier differents acteurs cellulaires et moleculaires pouvant etre impliques dans la physiopathologie de l'AJI.
When water interacts with temperature: Ecological and evolutionary implications of thermo‐hydroregulation in terrestrial ectotherms

Abstract The regulation of body temperature (thermoregulation) and of water balance (defined here as hydroregulation) are key processes underlying ecological and evolutionary responses to climate fluctuations in wild animal populations. In terrestrial (or semiterrestrial) ectotherms, thermoregulation and hydroregulation closely interact and combined temperature and water constraints should directly influence individual performances. Although comparative physiologists traditionally investigate jointly water and temperature regulation, the ecological and evolutionary implications of these coupled processes have so far mostly been studied independently. Here, we revisit the concept of thermo‐hydroregulation to address the functional integration of body temperature and water balance regulation in terrestrial ectotherms. We demonstrate how thermo‐hydroregulation provides a framework to investigate functional adaptations to joint environmental variation in temperature and water availability, and potential physiological and/or behavioral conflicts between thermoregulation and hydroregulation. We extend the classical cost–benefit model of thermoregulation in ectotherms to highlight the adaptive evolution of optimal thermo‐hydroregulation strategies. Critical gaps in the parameterization of this conceptual optimality model and guidelines for future empirical research are discussed. We show that studies of thermo‐hydroregulation refine our mechanistic understanding of physiological and behavioral plasticity, and of the fundamental niche of the species. This is illustrated with relevant and recent examples of space use and dispersal, resource‐based trade‐offs, and life‐history tactics in insects, amphibians, and nonavian reptiles.
La pyrolyse Rock-Eval et ses applications. Première partie.

Concue pour repondre aux besoins de l'exploration petroliere, la methode de pyrolyse Rock-Eval est maintenant largement utilisee. Elle fournit, en effet, et d'une facon rapide, differentes informations sur le contenu organique des roches, telles que le potentiel petrolier des series rencontrees, la nature des kerogenes, leur etat de maturation. En ce qui concerne le materiel, deux nouvelles versions ont ete mises au point a l'Institut Francais du Petrole (IFP) depuis l'apparition en 1977 des premiers appareils Rock-Eval : un Rock-Eval II completement automatise grâce a un microprocesseur et dote, en option, d'un module de dosage du carbone organique; un Rock-Eval III (Oil Show Analyzer) qui se distingue du precedent par le fait qu'il analyse separement le gaz et l'huile et qu'il effectue le dosage du carbone organique a la place du pic S3. En ce qui concerne l'interpretation de la methode, l'experience acquise tant par les applications aux bassins sedimentaires que par les etudes experimentales menees en laboratoire a permis de mieux connaitre les parametres utilises (pics S1, S2, S3, temperature de pyrolyse Tmax) a travers leurs variations et, de la, de mieux discerner les limites d'application de la methode. En ce qui concerne l'application de la methode, la representation verticale des resultats sous forme de logs geochimiques conduit a une interpretation a la fois efficace et pratique. Des abaques et des diagrammes de reference permettent de caracteriser les roches meres (potentiels petroliers, types de matiere organique, degre d'evolution, alterations. . . ) ainsi que les phenomenes de migration. L'etablissement de cartes geochimiques a l'echelle du bassin devient alors possible. Enfin la methode est sortie du domaine de l'exploration petroliere proprement dite pour trouver des applications a l'etude des charbons, des roches bitumineuses, des sediments recents et meme aux techniques du raffinage et de la recuperation secondaire des bruts.
International Journal of Engineering

Feature selection for various applications has been carried out for many years in many different research areas. However, there is a trade-off between finding feature subsets with minimum length and increasing the classification accuracy. In this paper, a filter-wrapper feature selection approach based on fuzzy-rough gain ratio is proposed to tackle this problem. As a search strategy, a modified Ant Colony Optimization (ACO) algorithm is applied on filter phase. ACO has been approved to be a suitable solution in many difficult problems with graph search space such as feature selection. Choosing minimal data reductions among the subsets of features with first and second maximum accuracies is the main contribution of this work. To verify the efficiency of our approach, experiments are performed on 10 well-known UCI data sets. Analysis of the experimental results demonstrates that the proposed approach is able to satisfy two conflicting constraints of feature selection, increasing the classification accuracy as well as decreasing the length of the reduced subsets of features. doi : 10.5829/ije.2017. 30.09c. 05
IMPACT OF A WARMED ENVIRONMENT, SPIKE MORPHOLOGY AND GENOTYPE ON FHB LEVELS IN A SOFT RED WINTER WHEAT MAPPING POPULATION

OF DISSERTATION IMPACT OF A WARMED ENVIRONMENT, SPIKE MORPHOLOGY AND GENOTYPE ON FHB LEVELS IN A SOFT RED WINTER WHEAT MAPPING POPULATION Fusarium head blight (FHB) is a serious disease of wheat (Triticum aestivum) and other small grains; disease severity is affected by temperature and rainfall. This research comprised three studies: an artificially warmed experiment during 2016-2017, a morphology study and an FHB resistance screening study in 2015-2016, using approximately 250 wheat cultivars and breeding lines from programs in the eastern US. The location was the University of Kentucky Spindletop Research Farm in Lexington, KY. Higher levels of Fusarium damaged kernels and the toxin deoxynivalenol (DON) were observed in the warmed treatment compared to the control, and plant development was accelerated. In the FHB resistance screen, significant (p<0.05) genotype differences for all traits were observed. A GWAS identified 16 SNPs associated with resistance and susceptibility, ranging from -2.14 to 4.01%. Three DON-associated SNPs reduced toxin levels by 3.2, 2.1, and 1.5 ppm. In the morphology study, negative correlations were observed among morphological and disease traits. Small effect SNPs were identified for all morphological traits, which might be useful in genomic selection; traits like spike length, spikelet number and inclination could be used in phenotyping. Response to warming indicates that existing resistance sources may be less effective in a warming climate.
Synthesis, in vitro evaluation of cytotoxicity and radiosensitizer activity of novel 2-(2, 4-dinitrobenzylidene) cyclohexanone derivatives against the radioresistant HT29 cell line under aerobic condition

Introduction: Bifunctional radiosensitizer agents in which nitroaromatic moieties are attached through a linker to antineoplastic moieties have demonstrated higher cytotoxicity and radiosensitizer effects than the corresponding counterparts. This study was conducted to investigate the cytotoxicity and radiosensitizer activities of 2, 4-dinitrobenzene as a radiosensitizer moiety which connected to α, β unsaturated aryl ketones against the radioresistant human HT29 colon cancer cells. Methods: A series of bifunctional radiosensitizer derivatives that are composed of electron-affinic 2, 4-dinitrophenyl moiety and thiol reactive unsaturated conjugated ketones were prepared. The designed compounds were synthesized by the reaction of the corresponding 2, 4-dinitrobenzaldehyde, cyclohexanone and different aryl aldehydes. The cytotoxicity and radiosensitizer activity of the tested compounds were examined against HT29 colon cancer cells under aerobic condition. The IC50 value of the tested compounds and percent of survival cells were analyzed by the MTT assay. The clonogenic assay was used to assess the cell viability following treatment with the tested compounds with or without the combination of radiation. Results:This approach demonstrated that the tested compounds at the concentrations utilized have little or no cytotoxicity towards the radioresistant HT29 cell line but have great cytotoxicity and radiosensitizer activity when combined with irradiation. Conclusion: The novel bifunctional unsaturated conjugated aryl ketones which are thiol alkylators found to exhibit radiosensitivity activity. Consequently, these new developed compounds should be evaluated further to assess their potential efficacy with radiotherapy to combat malignancies in a pre-clinical animal model.
Calculation of narrower confidence intervals for tree mortality rates when we know nothing but the location of the death/survival events

Abstract Many ecological applications, like the study of mortality rates, require the estimation of proportions and confidence intervals for them. The traditional way of doing this applies the binomial distribution, which describes the outcome of a series of Bernoulli trials. This distribution assumes that observations are independent and the probability of success is the same for all the individual observations. Both assumptions are obviously false in many cases. I show how to apply bootstrap and the Poisson binomial distribution (a generalization of the binomial distribution) to the estimation of proportions. Any information at the individual level would result in better (narrower) confidence intervals around the estimation of proportions. As a case study, I applied this method to the calculation of mortality rates in a forest plot of tropical trees in Lambir Hills National Park, Malaysia. I calculated central estimates and 95% confidence intervals for species‐level mortality rates for 1,007 tree species. I used a very simple model of spatial dependence in survival to estimate individual‐level risk of mortality. The results obtained by accounting for heterogeneity in individual‐level risk of mortality were comparable to those obtained with the binomial distribution in terms of central estimates, but the precision increased in virtually all cases, with an average reduction in the width of the confidence interval of ~20%. Spatial information allows the estimation of individual‐level probabilities of survival, and this increases the precision in the estimates of mortality rates. The general method described here, with modifications, could be applied to reduce uncertainty in the estimation of proportions related to any spatially structured phenomenon with two possible outcomes. More sophisticated approaches can yield better estimates of individual‐level mortality and thus narrower confidence intervals.
Discriminative Gene Selection Employing Linear Regression Model

Microarray datasets enables the analysis of expression of thousands of genes across hundreds of samples. Usually classifiers do not perform well for large number of features (genes) as is the case of microarray datasets. That is why a small number of informative and discriminative features are always desirable for efficient classification. Many existing feature selection approaches have been proposed which attempts sample classification based on the analysis of gene expression values. In this paper a linear regression based feature selection algorithm for two class microarray datasets has been developed which divides the training dataset into two subtypes based on the class information. Using one of the classes as the base condition, a linear regression based model is developed. Using this regression model the divergence of each gene across the two classes are calculated and thus genes with higher divergence values are selected as important features from the second subtype of the training data. The classification performance of the proposed approach is evaluated with SVM, Random Forest and AdaBoost classifiers. Results show that the proposed approach provides better accuracy values compared to other existing approaches i.e. ReliefF, CFS, decision tree based attribute selector and attribute selection using correlation analysis.