Miracle-dz/UniFAR-FTUs huggingface dataset:
Methylytransferase Activity of Dengue RNA virus by Using Purified Protein

Dengue disease (DENV) is the purpose behind dengue fever. It is a mosquito-borne single positive-stranded RNA contamination of the family Flaviviridae; sort Flavivirus. Dengue illness is a mosquito-borne making or re-rising pathogen. Its positive sense RNA genome has a top at the 5'- end and no poly(A) tail at the 3'- end. The viral RNA encodes a single polyprotein, C-M-E-NS1-NS2A-NS2B-NS3-NS4A-NS4B-NS5. The polyprotein is prepared into three auxiliary proteins (C, M, and E) and seven nonstructural (NS) proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B, NS5). NS3 and NS5 are multifunctional chemicals performing different undertakings in the viral life cycle. The N-terminal area of NS5 has unmistakable GTP and S-adenosylmethionine (SAM) restricting locales. The job of GTP restricting site is trapped in the guanylyltransferase (GTase) movement of NS5. We depict the development of the MTase space of NS5 in an E. coli articulation vector and conditions for enzymatic activity of N7-and 2'O-methyltransferase exercises that yield the last sort I 5'- topped RNA.
FAST FINDING THE CLUSTERS OF ARBITRARY SHAPES

In this paper, we give the FFCAS (Fast Finding the Clusters of Arbitrary Shapes) algorithm to find the clusters of arbitrary shapes fast. At first, we distribute each data object into atomic clusters, small e-neighbors of objects. Then, we find out all core atomic clusters, the atomic clusters with high density. By eliminating all redundant atomic clusters in a cluster, we only use boundary to represent a cluster, so the space required for clustering is reduced greatly and can be stored in main memory. Furthermore, since e is small, we can describe clusters in arbitrary shapes. FFCAS scans database only once and the worst time complexity is O(n log n), where n is the number of the objects in database. Our experiments demonstrate that the run time of FFCAS is linear with the objects number in database and it can find the clusters of arbitrary shapes. It is not sensible to outliers, and it is also efficient to large and high dimension database.
Applying Cognitive Load Theory Principles to Library Instructional Guidance

ABSTRACT If the goal of library instructional guidance is to provide students with the knowledge needed to acquire new skills in order to accomplish their learning objectives, then it is prudent to consider factors that impact learning. Cognitive load theory addresses several of these factors and is applicable to a wide-range of instructional devices used by librarians, particularly during research guide design, multimedia development, and database administration. This article will provide academic librarians with an overview of cognitive load theory and strategies for minimizing distractions while maximizing the student's learning potential.
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test

Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifications and drug intervention can prevent diabetes, therefore, an early identification of high risk individuals is important to design targeted prevention strategies. In this paper, we present an automatic tool that uses machine learning techniques to predict the development of type 2 diabetes mellitus (T2DM). Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). We trained and validated the models using the OGTT and demographic data of 1,492 healthy individuals collected during the San Antonio Heart Study. This study collected plasma glucose and insulin concentrations before glucose intake and at three time-points thereafter (30, 60 and 120 min). Furthermore, personal information such as age, ethnicity and body-mass index was also a part of the dataset. Using 11 oral glucose tolerance test (OGTT) measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using Minimum Redundancy Maximum Relevance feature selection algorithm. All possible combinations of the 10 best ranked features were used to generate SVM based prediction models. This research shows that an individual’s plasma glucose levels, and the information derived therefrom have the strongest predictive performance for the future development of T2DM. Significantly, insulin and demographic features do not provide additional performance improvement for diabetes prediction. The results of this work identify the parsimonious clinical data needed to be collected for an efficient prediction of T2DM. Our approach shows an average accuracy of 96.80 % and a sensitivity of 80.09 % obtained on a holdout set.
Interacción de factores ambientales y enemigos naturales con poblaciones de Aulacaspis tubercularis Newstead en Nayarit, México

El objetivo de este estudio fue conocer la dinámica poblacional de la escama blanca del mango, Aulacaspis tubercularis Newstead a diferentes temperaturas y determinar las relaciones que existen entre factores de clima y enemigos naturales con las poblaciones de la escama. El estudio se realizó en 2013-2014 en siete hurtos de mango (Manguifera indica L.) del cultivar Ataulfo, situados en lugares con diferentes temperaturas en San Blas, Nayarit. En cada huerto se registró quincenalmente las poblaciones de escama blanca y de sus depredadores insectiles. Se realizaron análisis de varianza para comparar las poblaciones entre fechas de muestreo y localidades, también se obtuvieron correlaciones entre temperatura, precipitación pluvial y el complejo de depredadores con las poblaciones de la plaga. Los niveles poblacionales más altos de la escama blanca del mango se registraron durante el periodo con temperaturas más altas y sin precipitación pluvial (abril-junio); en contraste, durante el periodo con precipitación pluvial, la población en todos los huertos fue escasa o nula. Se determinó correlación positiva de la temperatura con la población de la escama blanca del mango, de tal manera que el aumento de la temperatura durante el año favoreció el incremento de las poblaciones de la plaga. En contraste, la precipitación pluvial impactó negativamente a la plaga al reducir drásticamente la densidad de sus poblaciones. Finalmente, el aumento de las poblaciones de la escama favoreció el incremento de la densidad poblacional del complejo de depredadores de la plaga.
Deep Tweets: from Entity Linking to Sentiment Analysis

The huge amount of information streaming from online social networking is increasingly attracting the interest of researchers on sentiment analysis on micro-blogging platforms. We provide an overview on the open challenges of sentiment analysis on Italian tweets. We discuss methodological issues as well as new directions for investigation with particular focus on sentiment analysis of tweets containing figurative language and entity-based sentiment analysis of micro-posts.
Effect of fruit size, parental trees origin and trial conditions on the growth characteristics of European chestnut seedlings.

BOLVANSKÝ, M. , UŽÍK, M. 2011. Effect of fruit size, parental trees origin and trial conditions on the growth characteristics of European chestnut seedlings. Folia oecol. , 38: 146–155. In the spring of 2005, a field trial was established in forest nursery Hladomer, near community Lovce, Slovakia with the aim to find out an effect of different origin of fruits on growth characteristics of seedlings. Fruits were collected from twelve half-sib families of European chestnut, grown at an experimental plot in Horné Lefantovce. All studied families originated from old trees grown at four different localities of Slovakia (three half-sib families per locality) and exhibited above-average growth characteristics among all of 120 progenies grown at the experimental plot. Variability of growth characteristics (stem height and stem diameter) of both oneand two-yearold seedlings was significantly affected by their origin (locality of parental tree and half-sib family derived from these trees) and by different nut size used in three trial replications. In three of four studied origins, non significant differences in stem height of one-year-old seedlings between second and third replications changed to significant ones in two-year-old seedlings. These differences were assigned to different light and soil conditions on two trial blocks caused by partial shading of first and second trial blocks. Between weight of fruits and studied growth characteristics either low correlations (for data of individual fruits) or medium strong correlations (data grouped by fruit groups of different weight) were observed. Correlation between stem height means of families and stem height means of one-year-old and/or two-year-old seedlings derived from these progenies was only medium strong (r = 0.52 and 0.54) however similar inter-generation in stem diameter was very low and nonsignificant.
Early seedling establishment of Picea abies in small forest gaps in the Swiss Alps

Early seedling establishment of Picea abies (L.) Karst. in small forest gaps was studied in drier, subalpine P. abies ecosystems in the Swiss Alps. Study sites were on steep south and north slopes. Average gap size was 15 m x 20 m on the south slope and 15 m x 70 m on the north slope. Sowing trials established on different microsites were observed for 2 or 3 years. Direct sunlight was assessed with hemispherical photography. Emergence was better on the north slope than on the south slope. On the south slope, emergence was higher on the mineral soil than on the organic layer and was negatively associated with direct sunlight, especially during the noon period. On both slopes, drought due to rainfall interception at the gap edge negatively affected emergence. The limiting factor for survival and growth on the south slope was drought (on the organic layer), whereas on the north slope lack of direct radiation and pathogenic fungi developing in the snowpack were limiting. The early regeneration niche on the so.
Long‐term experiment manipulating community assembly results in favorable restoration outcomes for invaded prairies

Invasive species are a common problem in restoration projects. Manipulating soil fertility and species arrival order has the potential to lower their abundance and achieve higher abundances of seeded native species. In a 7‐year experiment in Missouri, United States, we tested how nutrient addition and the timing of arrival of the invasive legume Lespedeza cuneata and seeded native prairie grass and forb species influenced overall community composition. Treatments that involved early arrival of seeded forb and grass species and late arrival of L. cuneata were most successful at creating community structure that fulfilled our restoration goals, displaying high abundance of seeded native forb species, low abundances of L. cuneata, and non‐native species. There were few treatment interactions, with the exception that timing seeded native forbs and timing of L. cuneata arrival interactively influenced the abundance of seeded native forbs. This suggests that the individual treatments are supporting the restoration goals, such as creating a community with low abundance of L. cuneate or high abundance of native seeded species, without restricting each other. This study demonstrates the importance of priority effects in disturbed habitats prone to invasion, the lasting effects of initial seeding on long‐term community composition, and the potential for fertilization to positively benefit restoration of degraded grasslands.
Long term trend of an endangered bat species in north-western Italy

Thirty three maternity roosts of Rhinolophus hipposideros were monitored from 2000 to 2018 in an area of north-western Italy, between the Piedmont (13 roosts) and Liguria regions (20 roosts), and data were analysed through a TRIM statistic to calculate a robust estimation of reproductive population trends. Throughout the 19-years-long monitoring period, a total of 5135 Rhinolophus hipposideros were counted in maternity roost, with a mean of 273 (SD = 198.1) per year (mean Piedmont = 73, SD = 85.9; mean Liguria = 200, SD = 164.6). The population analysis model shows a significant overall gradient of 1.047, which corresponds to an average annual increase of 4.7 % over the period considered. The analysis suggests that in the study area, the reproductive population of Rhinolophus hipposideros monitored in the maternity roost has increased throughout the period from 2000-2018, with large increases after 2010 and different trends occurring in the two regions considered, including a significant moderate increase in Liguria and a stable trend in Piedmont. The results agreed with the recently observed trends in other European countries for this species.
Spatiotemporal expression pattern of alpha, beta, and gamma genes during BoHV-5 infection

Bovine herpesvirus 5 is an alphaherpesvirus that causes nonsuppurative meningoencephalitis in cattle. This disease occurs naturally in either outbreaks or isolated cases, and exhibits low morbidity and high lethality. Although previous studies elucidated crucial aspects involved in the pathogenesis of the disease, there is a paucity of information regarding the molecular events contributing to infection and replication of BoHV-5. The objective of the present study was to determine the in vitro gene expression pattern of BoHV-5 (e.g., alpha, beta, and gamma genes) and host cells genes (GAPDH and 18S) over time utilizing different quantities of inoculated virus. Three BoHV-5 genes (bICP0, UL9, US4) and one structural bovine cell gene had their expression accessed by real-time PCR. While the expression of BoHV-5 genes increased during the course of infection, GAPDH gene expression decreased in the host cells, evidencing the effect of viral infection on the expression of bovine cell genes. The 18S ribosomal RNA (rRNA) gene was constitutively expressed throughout BoHV-5 infection. Our data clearly demonstrates that GAPDH gene should not be used as a reference gene in studies of BoHV-5 infection because it was influenced by viral infection. However, 18S rRNA was constitutively expressed and, therefore, is recommended for normalization of BoHV-5 infection studies in bovine cells. The expression of viral genes transcripts was not altered by increasing number of viral particles added to the culture. All viral genes included here demonstrated the same expression pattern over time and there was no difference in the expression of viral genes among the various time points. Our data show important differences comparing to classical studies regarding herpesvirus alpha, beta, and gamma genes expression. More research is necessary to improve our understanding about the BoHV-5 biology during infection. Studies employing next-generation sequencing (i.e., RNA-seq), using both in vitro and in vivo models, would be the next logical step to grasp the virus and host cell’s transcriptome changes over the course of infection.
Translation of Word Vectors by Exploiting Translatable Context Pairs

While vector-based representations of word meanings (word vectors) have been widely used in a variety of natural language processing applications, they are not meant for capturing the similarity between words in different languages. This prevents using word vectors in multilingual-applications such as cross-lingual information retrieval and machine translation. To solve this problem, we propose a method that learns a cross-lingual projection of word representations from one language into another. Our method utilizes translatable context pairs obtained from a bilingual dictionary and surface similarity as bonus terms of the objective function. In the experiments, we evaluated the effectiveness of the proposed method in four languages, Japanese, Chinese, English and Spanish. Experiments shows that our method outperformed existing methods without any additional supervisions.
Trusted computing base using virtualization platform

Virtualization was introduced to increase the security of embedded devices while avoiding the shortcomings caused by the hardware-based approach such as poor flexibility,high complexity and high production cost of equipments.Virtualization platform SmartVP offers a secure system environment by the software-based approach.SmartVP partitions the computing resources on the ARM processor into two parallel sets,one for standard real-time operating system T-Kernel and the other for general-purpose operating system Linux.The trusted computing base of SmartVP is constructed by protecting the code and data of the software on T-Kernel,as well as by implementing the fundamental security services and interfaces.Both performance benchmark and applications show that SmartVP improves the security of embedded devices and reduces the implementing risk together with developing time and cost.
Genome-wide analysis reveals a switch in the translational program upon oocyte meiotic resumption

During oocyte maturation, changes in gene expression depend exclusively on translation and degradation of maternal mRNAs rather than transcription. Execution of this translation program is essential for assembling the molecular machinery required for meiotic progression, fertilization, and embryo development. With the present study, we used a RiboTag/RNA-Seq approach to explore the timing of maternal mRNA translation in quiescent oocytes as well as in oocytes progressing through the first meiotic division. This genome-wide analysis reveals a global switch in maternal mRNA translation coinciding with oocyte re-entry into the meiotic cell cycle. Messenger RNAs whose translation is highly active in quiescent oocytes invariably become repressed during meiotic re-entry, whereas transcripts repressed in quiescent oocytes become activated. Experimentally, we have defined the exact timing of the switch, the repressive function of CPE elements, and identified a novel role for CPEB1 in maintaining constitutive translation of a large group of maternal mRNAs during maturation.
Insights into the Diversity of Secondary Metabolites of Planktothrix Using a Biphasic Approach Combining Global Genomics and Metabolomics

Cyanobacteria are an ancient lineage of slow-growing photosynthetic bacteria and a prolific source of natural products with diverse chemical structures and potent biological activities and toxicities. The chemical identification of these compounds remains a major bottleneck. Strategies that can prioritize the most prolific strains and novel compounds are of great interest. Here, we combine chemical analysis and genomics to investigate the chemodiversity of secondary metabolites based on their pattern of distribution within some cyanobacteria. Planktothrix being a cyanobacterial genus known to form blooms worldwide and to produce a broad spectrum of toxins and other bioactive compounds, we applied this combined approach on four closely related strains of Planktothrix. The chemical diversity of the metabolites produced by the four strains was evaluated using an untargeted metabolomics strategy with high-resolution LC–MS. Metabolite profiles were correlated with the potential of metabolite production identified by genomics for the different strains. Although, the Planktothrix strains present a global similarity in terms of a biosynthetic cluster gene for microcystin, aeruginosin, and prenylagaramide for example, we found remarkable strain-specific chemodiversity. Only few of the chemical features were common to the four studied strains. Additionally, the MS/MS data were analyzed using Global Natural Products Social Molecular Networking (GNPS) to identify molecular families of the same biosynthetic origin. In conclusion, we depict an efficient, integrative strategy for elucidating the chemical diversity of a given genus and link the data obtained from analytical chemistry to biosynthetic genes of cyanobacteria.
QoS and Energy-Aware Routing for Wireless Sensor Networks

Wireless sensor networks represent a new paradigm in wireless technology, drawing significant attention and research from diverse fields of engineering. Many new applications are emerging and the rapid deployment of such networks is underway with busy researchers and engineers creating and optimizing WSN technology all around the world (Culler, 2003). The vision of many researchers is to create sensor-rich ubiquitous computing and smart environments through planned or ad-hoc deployment of thousands of sensor nodes, each with a short-range wireless communications channel, and capable of detecting ambient conditions, such as temperature, movement, sound, light, or the presence of certain objects. ABSTrACT
Genetic mapping of shnE.3.2 in Drosophila melanogaster

Genetic mapping of shn in Drosophila melanogaster Kayla Bieser1, Jamie Siders Sanford2, Ken Saville3, Katherine F. Arreola1, Zachary T. Ayres2, David Basulto1, Serena Benito1, Christopher J. Breen3, Julian A. Brix1, Nicole Brown1, Krissa K. Burton2, Taree M. Chadwick1, Matthew Chen3, Katherine Chu1, Beverly L. Corbett1, Zerick Dill3, Meghan A. Faughender1, Ashlynn D. Hickey2, Joshua S. Julia2, Shannon S. Kelty2, Brigette B. K. Kobs3, Bryce A. Krason1, Brian Lam1, Colin L. McCullough2, Bryanna R. McEwen2, Julian L. McKenzie2, Kayla R. McQuinn3, Chloe M. Moritz2, Kristina E. Myers2, Elizabeth M. Naugle2, Ashley M. Nutter2, Danielle Q. O’Conke2, Megan T. O’Grondik2, Kriya B. Patel2, Sydney M. Rudowski3, Emma N. Sberna2, Gunner M. Stall3, Tad L. Steiner2, Eda Tanriverdi2, Natalia Torres Patarroyo1, Virginia L. Traster1, Leo P. Tsai1, Andrew J. Valenti2, Mariela M. Villegas1, Samantha M. Voors2, Kierra K. Watson2, Megan E. Wright2, and Jacob D. Kagey4# #corresponding author 1. Department of Physical and Life Sciences, Nevada State College 2. Department of Biological and Allied Health Sciences, Ohio Northern University 3. Department of Biology, Albion College 4. Biology Department, University of Detroit Mercy
Model order reduction for left ventricular mechanics via congruency training

Computational models of the cardiovascular system and heart function are currently being investigated as analytic tools to assist medical practice and clinical trials. Recent technological advances allow for finite element models of heart ventricles and atria to be customized to medical images and to assimilate electrical and hemodynamic measurements. Optimizing model parameters to physiological data is, however, challenging due to the computational complexity of finite element models. Metaheuristic algorithms and other optimization strategies typically require sampling hundreds of points in the model parameter space before converging to optimal solutions. Similarly, resolving uncertainty of model outputs to input assumptions is difficult for finite element models due to their computational cost. In this paper, we present a novel, multifidelity strategy for model order reduction of 3-D finite element models of ventricular mechanics. Our approach is centered around well established findings on the similarity between contraction of an isolated muscle and the whole ventricle. Specifically, we demonstrate that simple linear transformations between sarcomere strain (tension) and ventricular volume (pressure) are sufficient to reproduce global pressure-volume outputs of 3-D finite element models even by a reduced model with just a single myocyte unit. We further develop a procedure for congruency training of a surrogate low-order model from multi-scale finite elements, and we construct an example of parameter optimization based on medical images. We discuss how the presented approach might be employed to process large datasets of medical images as well as databases of echocardiographic reports, paving the way towards application of heart mechanics models in the clinical practice.