Miracle-dz/UniFAR-FTUs huggingface dataset:
Local adaptation with high gene flow: temperature parameters drive adaptation to altitude in the common frog (Rana temporaria)

Both environmental and genetic influences can result in phenotypic variation. Quantifying the relative contributions of local adaptation and phenotypic plasticity to phenotypes is key to understanding the effect of environmental variation on populations. Identifying the selective pressures that drive divergence is an important, but often lacking, next step. High gene flow between high‐ and low‐altitude common frog (Rana temporaria) breeding sites has previously been demonstrated in Scotland. The aim of this study was to assess whether local adaptation occurs in the face of high gene flow and to identify potential environmental selection pressures that drive adaptation. Phenotypic variation in larval traits was quantified in R. temporaria from paired high‐ and low‐altitude sites using three common temperature treatments. Local adaptation was assessed using QST–FST analyses, and quantitative phenotypic divergence was related to environmental parameters using Mantel tests. Although evidence of local adaptation was found for all traits measured, only variation in larval period and growth rate was consistent with adaptation to altitude. Moreover, this was only evident in the three mountains with the highest high‐altitude sites. This variation was correlated with mean summer and winter temperatures, suggesting that temperature parameters are potentially strong selective pressures maintaining local adaptation, despite high gene flow.
Informative Labeling Schemes for the Least Common Ancestor Problem

We address the problem of labeling the nodes of a tree such that one can determine the identifier of the least common ancestor of any two nodes by looking only at their labels. This problem has application in routing and in distributed computing in peer-to-peer networks. A labeling scheme using Θ(log n)-bit labels has been presented by Peleg. By engineering this scheme and a new one due to the authors, we obtain a variety of data structures with the same asymptotic performances. We conduct a thorough experimental evaluation of all these data structures. Our results clearly show which variants achieve the best performances in terms of space usage, construction time, and query time. Effective representations of large, geographically dispersed communication networks should allow the users to efficiently retrieve information about the network in a distributed and localized way. Labeling schemes provide an answer to this problem by assigning labels to the network nodes in such a way that queries can be computed alone from the labels of the involved nodes, without any extra information source. The primary goal of a labeling scheme is to minimize the maximum label length, while keeping queries fast. Adjacency labeling schemes were first introduced by Breuer and Folkman in [5, 6], and further studied in [11]. The interest in informative labeling schemes, however, was revived only more recently, after Peleg showed the feasibility of the design of efficient labeling schemes capturing distance information [15]. Since then, upper and lower bounds for labeling schemes have been proved on a variety of graph families (including weighted trees, bounded arboricity graphs, intersection-based and cdecomposable graphs) and for a large variety of queries, including distance [2, 8, 10], tree ancestry [1, 3], flow and connectivity [13]. In spite of a large body of theoretical works, to the best of our knowledge only few experimental investigations of the efficiency of informative labeling schemes have been addressed in the literature [8, 12]. In our work [7] we focus on labeling schemes for answering least common ancestor queries in trees. Labeling schemes for least common ancestors are mainly useful in routing messages on tree networks: the ability to compute the identifier of the least common ancestor of any two nodes u and v turns out to be useful when a message has to be sent from u to v in the network, because the message has to go through lca(u, v). Other applications are related to query processing in XML search engines and distributed computing in peer-to-peer networks (see, e.g., [3, 4, 12]). In [16], Peleg has proved that for the class of n-node trees there exists a labeling scheme for least common ancestors using Θ(log n)-bit labels, which is also shown to be asymptotically optimal. We finally remark that, when node levels are known, it is trivial to compute the distance between any two nodes given their lca. Therefore, all the data structures considered in this work can be easily exploited to answer distance queries.
A medium‐scale assay for enhancer validation in amniotes

Enhancers are key elements to control gene expression in time and space and thus orchestrate gene function during development, homeostasis, and disease. Whole genome approaches and bioinformatic predictions have generated a tremendous pool of potential enhancers, however their spatiotemporal activity often remains to be validated in vivo. Despite recent progress in developing high throughput strategies for enhancer evaluation, these remain mainly restricted to invertebrates and in vitro cell culture.
Ontario Healthcare Coverage Eligibility Among New Permanent Residents: A Scoping Review

ABSTRACT New permanent residents to Ontario can experience difficulties accessing health services due to the 3-month residency requirement for provincial healthcare coverage. This scoping literature review, which included peer-reviewed articles and gray literature from 1993–2013, examined the effects of the 3-month waiting period on the health of new permanent residents to Ontario, public health, and the health-care system. At the individual level, issues of affordability, pre-existing conditions, and quality of care were prominent throughout the literature. At a systems level, the policy was found to constrain various health-care settings, pose a risk to public health, and compound health-care system costs.
Distribution and Diversity of Archaea Corresponding to the Limnological Cycle of a Hypersaline Stratified Lake (Solar Lake, Sinai, Egypt)

ABSTRACT The vertical and seasonal distribution and diversity of archaeal sequences was investigated in a hypersaline, stratified, monomictic lake, Solar Lake, Sinai, Egypt, during the limnological development of stratification and mixing. Archaeal sequences were studied via phylogenetic analysis of 16S rDNA sequences as well as denaturing gradient gel electrophoresis analysis. The 165 clones studied were grouped into four phylogenetically different clusters. Most of the clones isolated from both the aerobic epilimnion and the sulfide-rich hypolimnion were defined as cluster I, belonging to theHalobacteriaceae family. The three additional clusters were all isolated from the anaerobic hypolimnion. Cluster II is phylogenetically located between the generaMethanobacterium and Methanococcus. Clusters III and IV relate to two previously documented groups of uncultured euryarchaeota, remotely related to the genusThermoplasma. No crenarchaeota were found in the water column of the Solar Lake. The archaeal community in the Solar Lake under both stratified and mixed conditions was dominated by halobacteria in salinities higher than 10%. During stratification, additional clusters, some of which may possibly relate to uncultured halophilic methanogens, were found in the sulfide- and methane-rich hypolimnion.
Effective Fault Handling Algorithm for Load Balancing Using Ant Colony Optimization in Cloud Computing

Cloud computing is an emerging technology in distributed computing. It is a collection of interconnected virtual machines as to facilitate pay per use model as per the demand and requirement of the user. The primary aim of cloud computing is to provide efficient access to remote and geographically distributed resources without losing the property of reliability. In order to make these virtual machines hassle free, a distribution of work load (Load balancing) is done properly. Since in cloud computing the processing is done on remote computers hence there are more chances of errors, due to the undetermined latency and lose control over computing node. So it is very necessary to maintain the reliability of remote computers. That is why it is mandatory to create a fault tolerant infrastructure for cloud computing. This paper focuses on to balance the load of entire system while trying to maintain the reliability of the system by creating it as a fault tolerant system. Our objective is to study the existing ACO’s and to develop an effective fault tolerant system using ant colony optimization. Paper describes an algorithm in order to make the system more reliable and fault tolerant.
Transcriptional Repression of the Rat Osteocalcin Gene by δEF1

Intron I of the rat osteocalcin gene contains silencer elements that suppress osteocalcin-reporter fusion gene transcription. The consensus sequence for the transcription factor δEF1 is homologous to two pyrimidine-rich repeats in intron 1 that contribute to silencing of osteocalcin-reporter fusion genes. To assess if overexpression of δEF1 augments transcriptional repression by these sequences, the intron 1 sequences (wtS) were placed upstream to the native rat osteocalcin promoter fused to a luciferase reporter gene (-306-OCluc). Coexpression of the wtS-(-306-OCluc) fusion gene with δEF1 decreased luciferase activity 30% relative to cotransfection with empty vector. Repression was abolished by point mutations in the putative δEF1 motifs, mS-(-306-OCluc). To determine whether δEF1 binds to these DNA sequences, gel retardation assays were performed using oligonucleotides containing the putative osteocalcin δEF1 motifs and a classical δEF1 motif, as radiolabeled probes. A comigrating DNA-protein complex ge.
Constraints-based stoichiometric analysis of hypoxic stress on steroidogenesis in fathead minnows, Pimephales promelas

SUMMARY In this study, an in silico genome-scale metabolic model of steroidogenesis was used to investigate the effects of hypoxic stress on steroid hormone productions in fish. Adult female fathead minnows (Pimephales promelas) were exposed to hypoxia for 7 days with fish sub-sampled on days 1, 3 and 7 of exposure. At each time point, selected steroid enzyme gene expressions and steroid hormone productions were quantified in ovaries. Fold changes in steroid enzyme gene expressions were used to qualitatively scale transcript enzyme reaction constraints (akin to the range of an enzyme’s catalytic activity) in the in silico model. Subsequently, in silico predicted steroid hormone productions were qualitatively compared with experimental results. Key findings were as follows. (1) In silico gene deletion analysis identified highly conserved ‘essential’ genes required for steroid hormone productions. These agreed well (75%) with literature-published genes downregulated in vertebrates (fish and mammal) exposed to hypoxia. (2) Quantification of steroid hormones produced ex vivo from ovaries showed a significant reduction for 17β-estradiol and 17α,20β-dihydroxypregnenone production after 24 h (day 1) of exposure. This lowered 17β-estradiol production was concomitant with downregulation of cyp19a1a gene expression in ovaries. In silico predictions showed agreement with experimentation by predicting effects on estrogen (17β-estradiol and estrone) production. (3) Stochastic sampling of in silico reactions indicated that cholesterol uptake and catalysis to pregnenolone along with estrogen methyltransferase and glucuronidation reactions were also impacted by hypoxia. Taken together, this in silico analysis introduces a powerful model for pathway analysis that can lend insights on the effects of various stressor scenarios on metabolic functions.
Extracting Topic Maps from Web browsing histories

In this paper, we propose a method of clustering to extract Topic Map from the Web browsing history. The our method is based on the traditional agglomerative clustering with the constraint of the Web structure and the weight of link relation. Topic Map shows 2Dvisualized overview graph of the Web browsing history, and the relations between the topics that are gathered by a user and extracted from the pages around the history pages. Using the Web browsing history, we experimentally evaluate the extracted Topic Maps.
Probability-Based Incremental Association Rule Discovery Algorithm

In dynamic databases, new transactions are appended as time advances. This may introduce new association rules and some existing association rules would become invalid. Thus, the maintenance of association rules for dynamic databases is an important problem. In this paper, probability-based incremental association rule discovery algorithm is proposed to deal with this problem. The proposed algorithm uses the principle of Bernoulli trials to find expected frequent itemsets. This can reduce a number of times to scan an original database. This paper also proposes a new updating and pruning algorithm that guarantee to find all frequent itemsets of an updated database efficiently. The simulation results show that the proposed algorithm has a good performance.
Tin Whisker formation - results, test methods and countermeasures

Electroplated tin layers as used as lead-free solderable f~sh on the terminations of semiconductor devices are known to form whiskers. These whiskers are monoclystals of tin and grow within weeks to years with a diameter of some microns up to a length of several hundreds of microns or even millimetres. Thus they can cause shorts and the failure of a whole electronic circuit. This paper shows that these whiskers grow under the force of compressive stress in the layer, which is usually developed by the growth of an irregular intermetallic layer at the substrate / plating interface. We show that none of the actually known test methods can accelerate whisker growth or that growth rates can be correlated to ambient conditions. However, we show the effectivity of barrier layers to prevent whisker growth and propose a test method to judge on the whisker safety by extrapolation of the initial growth rate within the first weeks after electroplating.
A five-wave HLL Riemann solver for relativistic MHD

We present a five-wave Riemann solver for the equations of ideal relativistic magnetohydrodynamics. Our solver can be regarded as a relativistic extension of the five-wave HLLD Riemann solver initially developed by Miyoshi and Kusano for the equations of ideal MHD. The solution to the Riemann problem is approximated by a five wave pattern, comprised of two outermost fast shocks, two rotational discontinuities and a contact surface in the middle. The proposed scheme is considerably more elaborate than in the classical case since the normal velocity is no longer constant across the rotational modes. Still, proper closure to the Rankine-Hugoniot jump conditions can be attained by solving a nonlinear scalar equation in the total pressure variable which, for the chosen configuration, has to be constant over the whole Riemann fan. The accuracy of the new Riemann solver is validated against one dimensional tests and multidimensional applications. It is shown that our new solver considerably improves over the popular HLL solver or the recently proposed HLLC schemes.
Clinical Applications of the Photopic Negative Response to Optic Nerve and Retinal Diseases

The photopic negative response (PhNR) in response to a brief flash is a negative-going wave following the b-wave of the cone electroretinogram (ERG) that is driven by retinal ganglion cells (RGCs). The function of RGCs is objectively evaluated by analysing the PhNR. We reviewed articles regarding clinical use of the PhNR. The PhNR was well correlated with the visual sensitivity obtained by standard automated perimetry and morphometric parameters of the inner retina and optic nerve head in optic nerve and retinal diseases. Moreover, combining the PhNR with focal or multifocal ERG techniques enables the objective assessment of local function of RGCs. The PhNR is therefore likely to become established as an objective functional test for optic nerve and retinal diseases involving RGC injury.
A Novel Algorithm for Line Clipping

A new algorithm for clipping a line segment in two dimension against a rectangular window is presented in this paper . The algorithm are different to the others of line clipping algorithms . This algorithm use the affine transformations(Shearing transformations) to transform the line segment and the window ,which make the process of clipping the line segment very simple and avoid solving the equations set to get the points of intersections which are made by the line segment and the window . comparing to some classical algorithms , the algorithm of this paper are faster for the speeds of clipping the line segment and more efficiency for the calculations.
Sentiment Analysis: A Survey of Current Researchand Techniques

Opinions and reviews on products and services are expressed in the Web through blogs, feedback forms; it is essential to develop methods to automatically classify and gauge them to identify the underlying sentiment about the product. Analyzing the polarity of sentiment expressed in data is Opinion Mining (OM). It is a system that identifies and classifies opinion/sentiment as represented in electronic text. Economic and marketing researches depend heavily on accurate method to predict sentiments of opinions extracted from internet and predict online customer’s preferences. OM has many steps, and techniques for each step. This study ensures an overall survey about OM related to product reviews, and classification algorithms used for sentiment classification.
Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition

In order to overcome the limitation of traditional nonnegative factorization algorithms, the paper presents a generalized discriminant orthogonal non-negative tensor factorization algorithm. At first, the algorithm takes the orthogonal constraint into account to ensure the nonnegativity of the low-dimensional features. Furthermore, the discriminant constraint is imposed on low-dimensional weights to strengthen the discriminant capability of the low-dimensional features. The experiments on facial expression recognition have demonstrated that the algorithm is superior to other non-negative factorization algorithms.
Characterization of Serine Proteinase Expression in Agaricus bisporus and Coprinopsis cinerea by Using Green Fluorescent Protein and the A. bisporus SPR1 Promoter

ABSTRACT The Agaricus bisporus serine proteinase 1 (SPR1) appears to be significant in both mycelial nutrition and senescence of the fruiting body. We report on the construction of an SPR promoter::green fluorescent protein (GFP) fusion cassette, pGreen_hph1_SPR_GFP, for the investigation of temporal and developmental expression of SPR1 in homobasidiomycetes and to determine how expression is linked to physiological and environmental stimuli. Monitoring of A. bisporus pGreen_hph1_SPR_GFP transformants on media rich in ammonia or containing different nitrogen sources demonstrated that SPR1 is produced in response to available nitrogen. In A. bisporus fruiting bodies, GFP activity was localized to the stipe of postharvest senescing sporophores. pGreen_hph1_SPR_GFP was also transformed into the model basidiomycete Coprinopsis cinerea. Endogenous C. cinerea proteinase activity was profiled during liquid culture and fruiting body development. Maximum activity was observed in the mature cap, while activity dropped during autolysis. Analysis of the C. cinerea genome revealed seven genes showing significant homology to the A. bisporus SPR1 and SPR2 genes. These genes contain the aspartic acid, histidine, and serine residues common to serine proteinases. Analysis of the promoter regions revealed at least one CreA and several AreA regulatory motifs in all sequences. Fruiting was induced in C. cinerea dikaryons, and fluorescence was determined in different developmental stages. GFP expression was observed throughout the life cycle, demonstrating that serine proteinase can be active in all stages of C. cinerea fruiting body development. Serine proteinase expression (GFP fluorescence) was most concentrated during development of young tissue, which may be indicative of high protein turnover during cell differentiation.
Distributed Channel Assignment Algorithm for 802.11 Networks

We consider a WLAN network, which consists in a set of 802.11 access points (APs) in infrastructure mode. The problem to be solved consists in assigning a channel to each AP such that the total effective throughput is maximized. The solution proposed in this paper uses a distributed algorithm to solve this problem. One software agent manages one AP and is able to communicate with its neighbors in order to optimize the global effective throughput. Simulation experiments with different topologies have given very good results, even with very dense and large networks. Furthermore, comparison with optimal solutions on small networks has shown that the performance of the algorithm described in this paper is very close to optimality. Our solution is independent from service providers and can be applied to all 802.11 WLAN networks
Differential sensitivity of medium‐ and large‐sized striatal neurons to NMDA but not kainate receptor activation in the rat

Infrared videomicroscopy and differential interference contrast optics were used to identify medium‐ and large‐sized neurons in striatal slices from young rats. Whole‐cell patch‐clamp recordings were obtained to compare membrane currents evoked by application of N‐methyl‐d‐aspartate (NMDA) and kainate. Inward currents and current densities induced by NMDA were significantly smaller in large‐ than in medium‐sized striatal neurons. The negative slope conductance for NMDA currents was greater in medium‐ than in large‐sized neurons and more depolarization was required to remove the Mg2+ blockade. In contrast, currents induced by kainate were significantly greater in large‐sized neurons whilst current densities were approximately equal in both cell types. Spontaneous excitatory postsynaptic currents occurred frequently in medium‐sized neurons but were relatively infrequent in large‐sized neurons. Excitatory postsynaptic currents evoked by electrical stimulation were smaller in large‐ than in medium‐sized neurons. A final set of experiments assessed a functional consequence of the differential sensitivity of medium‐ and large‐sized neurons to NMDA. Cell swelling was used to examine changes in somatic area in both neuronal types after prolonged application of NMDA or kainate. NMDA produced a time‐dependent increase in somatic area in medium‐sized neurons whilst it produced only minimal changes in large interneurons. In contrast, application of kainate produced significant swelling in both medium‐ and large‐sized cells. We hypothesize that reduced sensitivity to NMDA may be due to variations in receptor subunit composition and/or the relative density of receptors in the two cell types. These findings help define the conditions that put neurons at risk for excitotoxic damage in neurological disorders.
Processing of synchronously sampled AC signals in presence of interharmonics and subharmonics

The paper discusses the problem of estimating the value of the active power of the AC signal in the presence of subharmonics and interharmonics. The analysis makes use of the most general model of the voltage and current signal, i.e. the most complex spectral content that can be expected to appear in practice. A simulation of the suggested procedure has been done as well, as a final confirmation of the possibility to have accurate processing by using the synchronized sampling technique, even in the presence of subharmonics and interharmonics.