Miracle-dz/UniFAR-FTUs huggingface dataset:
ASSESSMENT OF ANTIMICROBIAL AND ANTIOXIDANT ACTIVITIES OF A SPECIES OF ASPERGILLUS: AN ENDOPHYTIC FUNGUS OF SCHIMA WALLICHII (DC.) KORTH. LEAVES

Objective: The main goals of this study were to check the antimicrobial and antioxidant potentials of an endophytic fungal strain isolated from the leaves of Schima wallichii (DC.) Korth. Methods: The antibacterial and antifungal activities of the isolated fungal endophyte Visva-Bharati endophyte fungal (VBEF2) were checked by disc diffusion and agar well diffusion methods, respectively, against six pathogenic bacteria and four pathogenic fungi. The minimum inhibitory concentration (MIC) values and the mode of action of VBEF2 against Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli were determined following colony-forming units (CFU) counting method. Antioxidant activity of the isolate was studied following 2, 2-diphenyl-2- picrilhydrazyl (DPPH) reduction assay. Results: The cell-free supernatants (CFS) of VBEF2 exhibited excellent antibacterial activity against all the bacteria used. The ethyl acetate extract of the endophyte was found to have the MIC of 50 μg/ml and 150 μg/ml against S. aureus and E. coli , respectively. It showed bactericidal mode of action against both of them. The CFS of the strain VBEF2 also showed excellent activities against two animal and two plant pathogenic fungi by producing zones of inhibition in the range of 10-20 mm. In the DPPH scavenging antioxidant assay, the ethyl acetate extract of VBEF2 was found with a low IC50 value of 19.01 μg/ml. The strain VBEF2 was identified as a species of Aspergillus based on its colony morphology and structural features observed under a compound light microscope. Conclusion: The strain VBEF2 can be implemented in various fields of pharmaceutical industry as it showed multidimensional beneficial attributes such as excellent antimicrobial and antioxidant activity.
TReaDS: Tandem Repeats Discovery Service

Motivation Tandem Repeats (TRs) are multiple duplications of substrings in the DNA that occur contiguously and may involve mutations, such as substitutions, insertions, and deletions. Not only TRs are privileged targets in activities such as fingerprinting or tracing the evolution of populations, but they have also been linked to several diseases, disorders and addictive behaviors. Even though the depth of the research on TRs has been boosted by the availability of efficient non-trivial algorithms for finding TRs (even when mutations occur with non-negligible probability), comparative studies report significant differences among the sets of TRs that can be detected by using different tools and show how critical it is the choice of the input parameters. Thus, biologists could highly benefit from a tool that gives them the possibility of simultaneously querying multiple systems and getting a global, comparative and synthetic view of the results, with the same effort one would exert in using just one of the systems. Here we present TReaDS, the Tandem Repeats Discovery Service, which allows the user to: simultaneously run different algorithms on the same data set; manually choose for each algorithm a different parameter settings, or express her/his request in a simple and concise way (exact or approximate, short or long TRs), delegating to TReaDS the burden of choosing the right choice of parameters for all the systems; and get back a report that can be also downloaded for further, off-line, investigations. To the best of our knowledge TReaDS is the first meta search engine for tandem repeats and there is no similar and comparable system freely available.
The application of computational biology to study structure, function, interactions and evolution of DNA and RNA methyltransferases

Nowadays there are plenty of Computational Biology programs which are available to study various properties of proteins, like their structure, function, interactions with other proteins or evolution. In this work we have applied these tools to study RNA and DNA methyltransferases. Investigation of the DNA recognition by M.EcoRV aided with a homology model and sequence alignment shed light on the evolutionary pathways leading to change in sequence specificity of this protein, as well as on the mechanism and temporal order of events leading to the DNA recognition and methylation. Dnmt2 is an enzyme which looks like an authentic DNA methyltransferase but methylates tRNA molecules. This enzyme was studied using multiple sequence alignment and phylogenetic analysis as starting point. Our data clearly show that it follows the catalytic mechanism of m5C DNA MTases to methylate RNA. This represents the first example of such an enzyme. A homology model of the Dnmt3a catalytic domain, allowed us to study the function of its conserved residues and to interpret the experimental results. In addition, we have created a novel method to investigate protein-protein interaction sites, called "Absence of Interference" approach. We have employed this method to study the Dnmt3a/Dnmt3L complex. We have also contributed to the repository of bioinformatic programs, by creating new tools which are helpful to interpret and present experimental data. The Prima software is able to calculate conservation scores generated by the "Absence of Interference" method and map them onto protein models. DistriDist can analyze the distribution of pairwise distances between the query occurrences in a provided longer sequence, which can be helpful to identify the regions of the genome that can play a role in epigenetic regulation. BDPC was designed to analyze, present and compare the results from the bisulfite genomic sequencing projects, a laborious task which before had to be done manually.
Effective approaches to combining lexical and syntactical information for code summarization

Natural language summaries of source codes are important during software development and maintenance. Recently, deep learning based models have achieved good performance on the task of automatic code summarization, which encode token sequence or abstract syntax tree (AST) of code with neural networks. However, there has been little work on the efficient combination of lexical and syntactical information of code for better summarization quality. In this paper, we propose two general and effective approaches to leveraging both types of information: a convolutional neural network that aims to better extract vector representation of AST node for downstream models; and a Switch Network that learns an adaptive weight vector to combine different code representations for summary generation. We integrate these approaches into a comprehensive code summarization model, which includes a sequential encoder for token sequence of code and a tree based encoder for its AST. We evaluate our model on a large Java dataset. The experimental results show that our model outperforms several state‐of‐the‐art models on various metrics, and the proposed approaches contribute a lot to the improvements.
Effect of organic sources of chromium supplementation with low levels of protein on the growth performance and rumen fermentation profile of growing steers.

The aim of this study was to evaluate organic sources of chromium and the level of inclusion of these sources on the growth performance and rumen fermentation of Nellore Angus crossbred steers with low protein diets. Forty-eight crossbreed Red Angus Nellore, with body weight of approximately 200 ±14 kg and 10 months old, were used. Twelve animals were cannulated in the rumen to evaluate the dry matter degradability of Tifton-85 hay and ruminal fermentation profile. A randomized block design was applied, with a 3x4 factorial arrangement. Animals were distributed among the twelve diets, in which the three chromium sources were used. The chromium sources used were: 1hrome sulfate, 2chromium yeast, 3-chromium methionine, with four levels of inclusion 0, 1, 2 and 4 mg / animal / day. An effect for chromium sources and levels for dry matter intake was observed, as well as the effect of source and levels of inclusion of chromium and their interaction in the diets. For the concentrations of propionate, chromium source was important, with the highest percentage obtained for chromium yeast. Diets with low levels of crude protein are recommended for the growth of non-stressed crossbred Nellore Angus, with the additional use of chromium yeast or chromium methionine at the dose of 2 mg / animal / day.
Redescription and Phylogenetic Assessment of ‘Prognathodon’ Stadtmani: Implications for Globidensini Monophyly and Character Homology in Mosasaurinae

ABSTRACT Prognathodon stadtmani was discovered in the Campanian portion of the Upper Cretaceous Mancos Shale in western Colorado in 1975. Following its original description almost two decades ago, more material of the holotype was prepared. Those new elements include a quadrate, often considered one of the most critical bones for understanding mosasaur systematics, portions of the skull roof, posterior mandible, and braincase. Prognathodon stadtmani exhibits a suite of features that include both derived character states observed in later mosasaurines and primitive features present in earlier members of the clade, such as Clidastes. Although the quadrate resembles those of Prognathodon and Globidens in some respects, it lacks fusion between the suprastapedial process and ascending tympanic rim observed in those taxa. I ran a series of phylogenetic analyses using parsimony and Bayesian inference to understand the relationships of this taxon. Regardless of character selection or methodology, ‘Prognathodon’ stadtmani was not found to be monophyletic with the rest of the genus Prognathodon. Depending on method, it was recovered as the sister taxon to the rest of Globidensini, the sister taxon to Mosasaurini + Globidens, or an early diverging mosasaurine outside of both Globidensini and Mosasaurini. Owing to these results, I assign the type to a new genus, Gnathomortis, gen. nov., yielding the species Gnathomortis stadtmani, comb. nov. Furthermore, the rest of the genus Prognathodon and the clade Globidensini more broadly were not consistently recovered as monophyletic. Many characters of the quadrate and the dentition that typically united those clades are optimized as homoplastic based on my resulting topologies.
Cats and dogs cross the line : domestic breeds follow Rensch ’ s rule , their wild relatives do not

синдром доместикации, обнаруженный Чарльзом дарвином, показывает, что доместицированные виды приобрели ряд новых морфологических, физиологических и поведенческих характеристик, которых не было у их диких предков. Поскольку размер тела и половой диморфизм по размеру тела (ПдрТ) являются важнейшими видовыми характеристиками, влияющими почти на все аспекты жизни животных, мы изучили влияние доместикации на эти два показателя у домашних собак и кошек в сравнении с их сородичами: собачьими и кошачьими, а также проанализировали применимость правила ренша для обоих домашних видов. в анализ были включены данные по максимальной высоте в холке у 89 пород собак и максимальной массе тела у 64 пород собак и 37 пород кошек. Кроме того, использованы данные по массе тела 36 диких видов собачьих и 36 видов кошачьих, полученные в ходе более ранних исследований. результаты показали, что значения массы тела и их диапазон у домашних собак значительно превышают эти показатели у представителей семейства canidae в целом, в то время как соответствующие показатели ПдрТ у них схожи. У домашних кошек диапазон значений массы тела укладывается в диапазон значений, характерных для их видов-предшественников, но при этом существенно сужен, тогда как значения соответствующих показателей ПдрТ сравнимы. регрессии, полученные как стандартным методом главных осей (rMa), так и методом наименьших квадратов (olS), показали, что у домашних видов размеры тела самок и самцов подчиняются правилу ренша, а у их диких сородичей – нет. данные результаты обсуждаются в свете существующих знаний о доместикации видов Canis familiaris и Felis catus.
Construction of high‐density genetic linkage map and mapping quantitative trait loci (QTL) for flowering time in autotetraploid alfalfa (Medicago sativa L.) using genotyping by sequencing

Flowering time is an important agronomic trait of alfalfa (Medicago sativa L.). Managing flowering time can produce economic benefits for farmers. To understand the genetic basis of this trait, quantitative trait loci (QTL) mapping was conducted in a full‐sib population that consisted of 392 individuals segregating based on flowering time. High density linkage maps were constructed using single nucleotide polymorphism (SNP) markers generated by genotyping‐by‐sequencing (GBS). The linkage maps contained 3,818 SNP markers on 64 linkage groups in two parents. The average marker density was 4.33 cM for Parent 1 (P1) and 1.47 cM for Parent 2 (P2). Phenotypic data for flowering time was collected for three years at one location. Twenty‐eight QTLs were identified associated with flowering time. Eleven QTLs explained more than 10% of the phenotypic variation. Among them, five main effect QTLs located on linkage group (LG) 7D of P1 and five main effect QTLs located on LG 6D of P2 were identified. Three QTLs were co‐located with other QTLs. The identified linked markers to QTLs could be used for marker‐assisted selection in breeding programs to develop new alfalfa varieties to modulate flowering time.
Solar panel failure detection by infrared UAS digital photogrammetry: a case study

Infrared thermal photogrammetry is an attractive solution for the diagnosis of photovoltaic systems. Traditional systems often require high-end drones and expensive cameras, but more recently, low-cost thermal sensors on board of small-scale drone platforms suitable for digital photogrammetry have emerged as a promising approach. Nevertheless, studies evaluating its effectiveness can barely be found in the literature. Unlike many works in the literature that analyze individual images, through digital photogrammetry it is also possible to create orthomosaics of complete installations or high-resolution maps of segments that cannot be visualized and analyzed properly with single images. In this work, a photogrammetric thermal analysis methodology with a small-scale drone and a thermal camera is presented and a case of study is analyzed. To validate and quantitatively scale the results, functional tests on the panels were performed and temperature measurements with a thermocouple on the panels were carried out. The results from both single images and orthomosaics confirm that it is possible to obtain qualitative and quantitative information to detect failures in solar panel installations with a low-cost thermal sensor on board of small-scale drone platforms. These results may be useful for defining surveillance and maintenance procedures with low-cost equipment in photovoltaic installations, which can help for early detection of failures, operation with higher efficiency and to achieve longer lifetimes of the panels.
Principles for the buffering of genetic variation.

Most genetic research has used inbred organisms and has not explored the complexity of natural genetic variation present in outbred populations. The translation of genotype to phenotype is complicated by gene interactions observed as epistasis, canalization, robustness, or buffering. Analysis of double mutations in inbred experimental organisms suggests some principles for gene interaction that may apply to natural variation as well. The buffering of variation in one gene is most often due to a small number of other genes that function in the same biochemical process. However, buffering can also result from genes functioning in processes extrinsic to that of the primary gene.
Biosorption Potential of the Microchlorophyte Chlorella vulgaris for Some Pesticides

Nowadays, pollution of either surface or ground water with pesticides is considered as one of the greatest challenges facing Humanity and being a national consideration in Egypt. Agricultural activities are the point source of pesticides that polluting water bodies. The present study investigated the potentiality of Chlorella vulgaris for bioremoval of pesticides mixture of 0.1 mg/mL for each component (Atrazine, Molinate, Simazine, Isoproturon, Propanil, Carbofuran, Dimethoate, Pendimethalin, Metoalcholar, Pyriproxin) either as free cells or immobilized in alginate. Two main experiments were conducted including short- term study having 60 min contact time using fresh free and lyophilized cells and other long-term study having five days incubation period using free and immobilized cells. In the short-term study, the presence of living cells led to bioremoval percentage ranged from 86 to 89 and the lyophilized algal biomass achieved bioremoval ranged from 96% to 99%. In long-term study, the presence of growing algae resulted in pesticides bioremoval ranged from 87% to 96.5%. The main mechanism behind the removal of pesticides in water phase is proposed to be biosorption onto the algal cells. This conclusion is based on the short duration required for removal to occur. The obtained results encourage using microalgae in bioremediation of pesticides polluted water.
A DEVS-based pivotal modeling formalism and its verification and validation framework

System verification is an ever-lasting system engineering challenge. The increasing complexity in system simulation requires some level of expertise in handling the idioms of logic and discrete mathematics to correctly drive a full verification process. It is recognized that visual modeling can help to fill the knowledge gap between system experts and analysis experts. However, such an approach has been used on the one hand to specify the behavior of complex systems, and on the other hand to specify complex requirement properties, but not simultaneously. This paper proposes a framework that is unique in supporting a full system verification process based on the graphical modeling of both the system of interest and the requirements to be checked. Patterns are defined to transform the resulting models to formal specifications that a model checker can manipulate. A real-time crossing system is used to illustrate the proposed framework.
Hawking radiation of regular Hayward black hole surrounded by quintessence

We investigate Hawking radiation of regular Hayward black hole surrounded by quintessence. Using the null geodesic method, we derive the expression of the emission rate and deduce the expression of the Boltzmann factor of the black hole. The expression of the change of entropy is also derived using the first law of black hole thermodynamics. The results show that the Boltzmann factor increases when increasing the density of quintessence a or the correction term due to the quantum effects β respectively; showing that the black hole radiates at slower rate. Moreover, the increase of the quantum effects accentuates the decreasing of the change of Bekenstein-Hawking entropy of black hole.
Climate, snowmelt dynamics and atmospheric deposition interact to control dissolved organic carbon export from a northern forest stream over 26 years

Increasing concentrations of dissolved organic carbon (DOC) have been identified in many freshwater systems over the last three decades. Studies have generally nominated atmospheric deposition as the key driver of this trend, with changes in climatic factors also contributing. However, there is still much uncertainty concerning net effects of these drivers on DOC concentrations and export dynamics. Changes in climate and climate mediated snowfall dynamics in northern latitudes have not been widely considered as causal factors of changes in long-term DOC trends, despite their disproportionate role in annual DOC export. We leveraged long-term datasets (1988–2013) from a first-order forested tributary of Lake Superior to understand causal factors of changes in DOC concentrations and exports from the watershed, by simultaneously evaluating atmospheric deposition, temperature, snowmelt timing, and runoff. We observed increases in DOC concentrations of approximately 0.14 mg C l−1 yr−1 (mean = 8.12 mg C l−1) that were related with declines in sulfate deposition (0.03 mg SO42− l−1 yr−1). Path analysis revealed that DOC exports were driven by runoff related to snowmelt, with peak snow water equivalences generally being lower and less variable in the 21st century, compared with the 1980s and 1990s. Mean temperatures were negatively related (direct effects) to maximum snow water equivalences (−0.71), and in turn had negative effects on DOC concentrations (−0.58), the timing of maximum discharge (−0.89) and DOC exports (indirect effect, −0.41). Based on these trends, any future changes in climate that lessen the dominance of snowmelt on annual runoff dynamics—including an earlier peak discharge—would decrease annual DOC export in snowmelt dominated systems. Together, these findings further illustrate complex interactions between climate and atmospheric deposition in carbon cycle processes, and highlight the importance of long-term monitoring efforts for understanding the consequences of a changing climate.
The Increasing Risk of Vector-Borne Diseases: Mapping the Effects of Climate Change and Human Population Density on Future Aedes aegypti Habitats

The Aedes aegypti mosquito is the vector for four infectious diseases of global concern – Yellow Fever, Dengue, Chikungunya, and Zikavirus. Previous attempts to model the expansion of the vector habitat due to global climate change have rarely included characteristics related to the human populations on which this mosquito is dependent. The purpose of this research was to determine whether the inclusion of human population density improves model performance while creating risk maps that can be used to determine where humans are most likely to be exposed to the vector in the future. The resulting model demonstrated that the inclusion of human population density improves the predictive power for A. aegypti and should be considered during model development. Maps produced by the model were also suitable for identifying regions where human populations are most likely to experience increased risk. Finally, two areas at risk of expansion were highlighted as a case study in pairing risk mapping with evidence-based intervention strategies to identify sites that would benefit from mosquito-control efforts. In this case, a low-cost program of insecticide-treated covers for water storage containers would likely work well in both Minas Gerais, Brazil and Northwestern Province, Zambia to mitigate mosquito risk. This research demonstrates that human population characteristic not only improve model fit but also increase the extent to which risk maps are actionable by aiding in targeting interventions.
Using Le Bissonnais method to study the stability of soil aggregates in plantations and its influence mechanism

ABSTRACT To evaluate the influence of different plantations on the stability of soil aggregates, we selected 5 typical plantations in south subtropical region: Pinus massoniana (PM), Cunninghamia lanceolata (CL), Eucalyptus urophylla×E. grandis (EU), Mytilaria laosensis (ML) and Castanopsis hystrix (CM). Soil aggregate stability was determined by the Le Bissonnais method and included three disruptive treatments. FW caused the greatest damage to the soil aggregate structure, after which the soil aggregates were mainly 0.2–0.5 mm in size. The MWD and GMD values of the three treatments were basically the same, i.e., WS > SW > FW, and gradually decreased with increasing soil depth. Compared to the plantations, the natural forest had higher MWD and GMD but lower RSI and RMI. Among the 5 plantation types, the SOM of the EU was lowest in five soil layers. SOM, Fe and Al had significantly positive correlations with MWD but negative correlations with Mn (p < 0.05), which indicated that SOM, Fe and Al were involved in the formation of macroaggregates and increased the stability of soil aggregates. Reasonable forest management measures will contribute to the formation of soil aggregates and the improvement of soil quality.