Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting University Students’ Academic Success Using Different Tree Classifiers And Ensemble Approaches To Suggest Suitable Program

: One of the most important issues in succeeding the academic life is to assign students to the right college program when they arrive to the end of the basic education stage. Data mining is one of the best alternative solution to find patterns and to provide a suitable program which enhance the student survival in their college life. This research experimented different tree classification algorithms and supplemented by ensemble approach to suggest the best classifier model based on predictive accuracy performance. The result reveals a very interesting prediction that the average grade in math is a very important predictor for programs like Mathematics and Engineering. For non-engineering program, the average grade in English is the dominant predicting variable. However, this study produce a conflating result which reveals that average grade in English is not a significant predictor on the program that offer English as a major subject (AB English Language) instead general grade average is the predicting variable. In the case of IT, the average grade in TLE and Science is an important predicting variable. The result of evaluation in the final stage of the model construction process reveals that bagging + j-48 tree classifier obtained highest accuracy as compared with other tree classifiers and forest tree classifier obtained the highest value in dropout precision and graduated recall. The experimental result also reveals that combining these tree learning algorithms using ensemble approach has minimal increase in classification performance.
Reproductive biology and pollination of two species of Byrsonima Kunth in a Cerrado fragment in Central Brazil

The flowers of Byrsonima basiloba A. Juss. and Byrsonima intermedia A. Juss. show diurnal anthesis. The stigma receptivity extends for up to three days after anthesis. The pollen is white and powdery, and the viability for B. basiloba pollen is 96.2%, while for B. intermedia , it is 92.9%. In the reproductive system treatments, B. basiloba had 28.9% fruit production in natural conditions and 3.4% in xenogamy. Conversely, B. intermedia had the highest fruit production for xenogamy (36.8%), followed by natural pollination (13.8%). The female bees of the genus Epicharis were the most likely bee genus to collect pollen and oil during the period observed. The bees of the genus Augochloropsis collected only pollen, and Paratetrapedia aff. testacea Smith collected oil in flower buds during the pre-anthesis phase.
Oscillation criteria for a class of nonlinear discrete fractional order equations with damping term

Abstract The aim in this work is to investigate oscillation criteria for a class of nonlinear discrete fractional order equations with damping term of the form Δa(t)Δr(t)gΔαx(t)β+p(t)Δr(t)gΔαx(t)β+F(t,G(t))=0,t∈Nt0. $$\begin{array}{} \displaystyle \Delta\left[a(t)\left[\Delta\left(r(t)g\left(\Delta^\alpha x(t)\right)\right)\right]^\beta\right]+p(t)\left[\Delta\left(r(t)g\left(\Delta^\alpha x(t)\right)\right)\right]^\beta+F(t,G(t))=0, t\in N_{t_0}. \end{array}$$ In the above equation α (0 < α ≤ 1) is the fractional order, G(t)=∑s=t0t−1+αt−s−1(−α)x(s) $\begin{array}{} \displaystyle G(t)=\sum\limits_{s=t_0}^{t-1+\alpha}\left(t-s-1\right)^{(-\alpha)}x(s) \end{array}$ and Δα is the difference operator of the Riemann-Liouville (R-L) derivative of order α. We establish some new sufficient conditions for the oscillation of fractional order difference equations with damping term based on a Riccati transformation technique and some inequalities. We provide numerical examples to illustrate the validity of the theoretical results.
Systems of Co-Creation Artistic reflection

Abstract This article is an artistic reflection of a research project called Please Switch On Your Mobile Phones (PSOYMP) that took place in three venues in Wales in 2014. The aim of PSOYMP was to develop new tools for audience interaction with on-stage dance, with the intention of developing new audiences. The project utilised an action research model to create a flexible choreographic and digital hybrid system that enabled the audience to collaborate in real time with the creative team–a choreographer, five dancers, a digital artist and a technologist–using mobile phones and tablets. The project resulted in the creation of an hour-long performance event. This was developed through three stages that included a week-long residency in each stage and a public performance event with a feedback session at the end of each residency. The final event was streamed live via YouTube and a web-based application, which allowed the online audience to participate in the event and to collaborate with the creative team in a similar way to the in-house audience. This article focusses on the creative process and discusses the nature and the development of the collaboration between the creative team and the audience.
A real-time, transient kinetic study of Drosophila melanogaster Dicer-2 elucidates mechanism of termini-dependent cleavage of dsRNA

Drosophila melanogaster Dicer-2 (dmDcr-2) differentially processes dsRNA with blunt or 2 nucleotide 3’-overhanging termini. We investigated the transient kinetic mechanism of these reactions using a rapid reaction stopped-flow technique and time-resolved fluorescence spectroscopy. We found that ATP binding to dmDcr-2’s helicase domain impacts the kinetics of dsRNA binding and dissociation in a termini-dependent manner, emphasizing the termini-dependent discrimination of dsRNA on a biologically-relevant time-scale. ATP-hydrolysis mediates local unwinding of dsRNA, and directional translocation on unwound single-stranded RNA, which is concurrent with a slow rewinding prior to dsRNA cleavage. Time-resolved fluorescence anisotropy reveals a nucleotide-dependent change in conformational dynamics of the helicase and Platform•PAZ domains in the nanosecond timescale that is correlated with termini-dependent dsRNA cleavage. Our study delineates kinetic events and transient intermediates for a Dicer-catalyzed reaction, thus establishing a framework for understanding other Dicers and how accessory factors modulate the reaction.
Brazilin Removes Toxic alpha-Synuclein and Seeding Competent Assemblies from Parkinson Brain by Altering Conformational Equilibrium

Alpha-synuclein (α-syn) fibrils, a major constituent of the neurotoxic Lewy Bodies in Parkinson’s disease, form via nucleation dependent polymerization and can replicate by a seeding mechanism. Brazilin, a small molecule derived from red cedarwood trees in Brazil, has been shown to inhibit the fibrillogenesis of amyloid-beta (Aβ) and α-syn, prompting our inquiry in its mechanism of action. Here we test the effects of Brazilin on both seeded and unseeded α-syn fibril formation and show that the natural polyphenol inhibits fibrillogenesis of α-syn by a unique mechanism that is distinct from other polyphenols and is also distinct from its effect on Aβ. Brazilin preserves the natively unfolded state of α-syn by stabilizing the compact conformation of the α-syn monomer over the aggregation-competent extended conformation. Molecular docking of Brazilin shows the molecule to interact both with unfolded α-syn monomers and with the cross-β sheet structure of α-syn fibrils. Brazilin eliminates seeding competence of α-syn assemblies from Parkinson’s disease patient brain tissue, and treatment of pre-formed fibril assemblies with Brazilin significantly reduces their toxicity in primary neurons. Our findings suggest that Brazilin has substantial potential as a neuroprotective and therapeutic agent for Parkinson’s Disease. Highlights - The natural polyphenol Brazilin binds to monomeric, oligomeric and fibrillar α-syn - Brazilin shifts the equilibrium away from aggregation-competent monomer conformations - Brazilin inactivates seeding-competent α-syn isolated from Parkinson patients’ brains - Brazilin detoxifies α-syn aggregation intermediates and stabilizes mature amyloid fibrils Graphical Abstract
PyEcoLib: a python library for simulating E. coli stochastic size dynamics

Recent studies describe bacterial division as a jump process triggered when it reaches a fixed number of stochastic discrete events at a rate depending on the cell-size. This theoretical approach enabled the computation of stochastic cell-size transient dynamics with arbitrary precision, with the possibility of being coupled to other continuous processes as gene expression. Here we synthesize most of this theory in the tool PyEcoLib, a python-based library to estimate bacterial cell size stochastic dynamics including continuous growth and division events. In this library, we include examples predicting statistical properties seen in experiments.
Dynamics of brain function in chronic pain patients assessed by microstate analysis of resting-state electroencephalography

Chronic pain is a highly prevalent and severely disabling disease, which is associated with substantial changes of brain function. Such changes have mostly been observed when analyzing static measures of brain activity during the resting-state. However, brain activity varies over time and it is increasingly recognized that the temporal dynamics of brain activity provide behaviorally relevant information in different neuropsychiatric disorders. Here, we therefore investigated whether the temporal dynamics of brain function are altered in chronic pain. To this end, we applied microstate analysis to eyes-open and eyes-closed resting-state electroencephalography (EEG) data of 101 patients suffering from chronic pain and 88 age- and gender-matched healthy controls. Microstate analysis describes EEG activity as a sequence of a limited number of topographies termed microstates, which remain stable for tens of milliseconds. Our results revealed that sequences of 5 microstates, labelled with the letters A to E, described resting-state brain activity in both groups and conditions. Bayesian analysis of the temporal characteristics of microstates revealed that microstate D has a less predominant role in patients than in healthy participants. This difference was consistently found in eyes-open and eyes-closed EEG recordings. No evidence for differences in other microstates was found. As microstate D has been previously related to attentional networks and functions, abnormalities of microstate D might relate to dysfunctional attentional processes in chronic pain. These findings add to the understanding of the pathophysiology of chronic pain and might eventually contribute to the development of an EEG-based biomarker of chronic pain.
Th2 Cytokine Modulates Herpesvirus Reactivation in a Cell Type-Specific Manner

Herpesviruses establish lifelong quiescent infections in specific cells in the body and reactivate to produce infectious virus only when precise signals induce them to do so. The signals that induce herpesvirus reactivation are often studied only in one particular cell type infected with the virus. ABSTRACT Gammaherpesviruses such as Epstein-Barr virus (EBV), Kaposi’s sarcoma-associated virus (KSHV), and murine gammaherpesvirus 68 (MHV68) establish latent infection in B cells, macrophages, and nonlymphoid cells and can induce both lymphoid and nonlymphoid cancers. Research on these viruses has relied heavily on immortalized B cell and endothelial cell lines. Therefore, we know very little about the cell type-specific regulation of virus infection. We have previously shown that treatment of MHV68-infected macrophages with the cytokine interleukin-4 (IL-4) or challenge of MHV68-infected mice with an IL-4-inducing parasite leads to virus reactivation. However, we do not know if all latent reservoirs of the virus, including B cells, reactivate the virus in response to IL-4. Here, we used an in vivo approach to address the question of whether all latently infected cell types reactivate MHV68 in response to a particular stimulus. We found that IL-4 receptor expression on macrophages was required for IL-4 to induce virus reactivation but that it was dispensable on B cells. We further demonstrated that the transcription factor STAT6, which is downstream of the IL-4 receptor and binds the virus gene 50 N4/N5 promoter in macrophages, did not bind to the virus gene 50 N4/N5 promoter in B cells. These data suggest that stimuli that promote herpesvirus reactivation may affect latent virus only in particular cell types but not in others. IMPORTANCE Herpesviruses establish lifelong quiescent infections in specific cells in the body and reactivate to produce infectious virus only when precise signals induce them to do so. The signals that induce herpesvirus reactivation are often studied only in one particular cell type infected with the virus. However, herpesviruses establish latency in multiple cell types in their hosts. Using murine gammaherpesvirus 68 (MHV68) and conditional knockout mice, we examined the cell type specificity of a particular reactivation signal, interleukin-4 (IL-4). We found that IL-4 induced herpesvirus reactivation only from macrophages but not from B cells. This work indicates that regulation of virus latency and reactivation is cell type specific. This has important implications for therapies aimed at either promoting or inhibiting reactivation for the control or elimination of chronic viral infections.
Existence and Hyers-Ulam stability results for a class of fractional order delay differential equations with non-instantaneous impulses

Abstract In this paper, we mainly consider the existence and Hyers-Ulam stability of solutions for a class of fractional differential equations involving time-varying delays and non-instantaneous impulses. By the Krasnoselskii’s fixed point theorem, we present the new constructive existence results for the addressed equation. In addition, we deduce that the equations have Hyers-Ulam stable solutions by utilizing generalized Grönwall’s inequality. Some results in this literature are new and improve some early conclusions.
Novel taxa of Acidobacteriota involved in seafloor sulfur cycling

Acidobacteriota are widespread and often abundant in marine sediments, yet their metabolic and ecological properties are poorly understood. Here, we examined metabolisms and distributions of Acidobacteriota in marine sediments of Svalbard by functional predictions from metagenome-assembled genomes (MAGs), amplicon sequencing of 16S rRNA and dissimilatory sulfite reductase (dsrB) genes and transcripts, and gene expression analyses of tetrathionate-amended microcosms. Acidobacteriota were the second most abundant dsrB-harboring (averaging 13%) phylum after Desulfobacterota in Svalbard sediments, and represented 4% of dsrB transcripts on average. We propose two new Acidobacteriota genera, Candidatus Sulfomarinibacter (class Thermoanaerobaculia, ‘sub-division 23’) and Ca. Polarisedimenticola (‘sub-division 22’), with distinct genetic properties that may explain their distributions in biogeochemically distinct fjord sediments. Ca. Sulfomarinibacter encodes flexible respiratory routes, with potential for oxygen, nitrous oxide, metal-oxide, tetrathionate, sulfur and sulfite/sulfate respiration, and possibly sulfur disproportionation. Potential nutrients and energy include cellulose, proteins, cyanophycin, hydrogen and acetate. A Ca. Polarisedimenticola MAG encodes enzymes to degrade proteins, and to reduce oxygen, nitrate, sulfur/polysulfide and metal-oxides. 16S rRNA gene and transcript profiling showed Ca. Sulfomarinibacter members were relatively abundant and transcriptionally active in sulfidic fjord sediments, while Ca. Polarisedimenticola members were more relatively abundant in metal-rich fjord sediments. Overall, we reveal various physiological features of uncultured marine Acidobacteriota that indicate fundamental roles in seafloor biogeochemical cycling.
Carbon for nutrient exchange between the lycophyte, Lycopodiella inundata and Mucoromycotina ‘fine root endophytes’ is unresponsive to high atmospheric CO2 concentration

Background and Aims Non-vascular plants associating with arbuscular mycorrhizal (AMF) and Mucoromycotina ‘fine root endophyte’ (MFRE) fungi derive greater benefits from their fungal associates under higher atmospheric [CO2] than ambient, however nothing is known about how changes in [CO2] affects MFRE function in vascular plants. Methods We measured movement of phosphorus (P), nitrogen (N) and carbon (C) between the lycophyte, Lycopodiella inundata and Mucoromycotina fine root endophyte fungi using 33P-orthophosphate, 15N-ammonium chloride and 14CO2 isotope tracers under ambient and elevated atmospheric [CO2] concentrations of 440 and 800 ppm, respectively. Key Results Transfer of 33P and 15N from MFRE to plant were unaffected by changes in [CO2]. There was a slight increase in C transfer from plant to MFRE under elevated [CO2]. Conclusions Our results demonstrate that the exchange of C-for-nutrients between a vascular plant and Mucoromycotina FRE is largely unaffected by changes in atmospheric [CO2]. Unravelling the role of MFRE in host plant nutrition and potential C-for-N trade changes between symbionts under varying abiotic conditions is imperative to further our understanding of the past, present and future roles of diverse plant-fungal symbioses in global ecosystems.
Evolutionary history of cotranscriptional editing in the paramyxoviral phosphoprotein gene

The phosphoprotein gene of the paramyxoviruses encodes multiple protein products. The P, V, and W proteins are generated by transcriptional slippage. This process results in the insertion of non-templated guanosine nucleosides into the mRNA at a conserved edit site. The P protein is an essential component of the viral RNA polymerase, and is encoded by a direct copy of the gene in the majority of paramyxoviruses. However, in some cases the non-essential V protein is encoded by default and guanosines must be inserted into the mRNA in order to encode P. The number of guanosines inserted can be described by a probability distribution which varies between viruses. In this article we review the nature of these distributions, which can be inferred from mRNA sequencing data, and reconstruct the evolutionary history of cotranscriptional editing in the paramyxovirus family. Our model suggests that, throughout known history of the family, the system has switched from a P default to a V default mode four times; complete loss of the editing system has occurred twice, the canonical zinc finger domain of the V protein has been deleted or heavily mutated a further two times, and the W protein has independently evolved a novel function three times. Finally, we review the physical mechanisms of cotranscriptional editing via slippage of the viral RNA polymerase.
Deep Learning with Data Transformation and Factor Analysis for Student Performance Prediction

Student performance prediction is one of the most concerning issues in the field of education and training, especially educational data mining. The prediction supports students to select courses and design appropriate study plans for themselves. Moreover, student performance prediction enables lecturers as well as educational managers to indicate what students should be monitored and supported to complete their programs with the best results. These supports can reduce formal warnings and expulsions from universities due to students’ poor performance. This study proposes a method to predict student performance using various deep learning techniques. Also, we analyze and present several techniques for data pre-processing (e.g., Quantile Transforms and MinMax Scaler) before fetching them into well-known deep learning models such as Long Short Term Memory (LSTM) and Convolutional Neural Networks (CNN) to do prediction tasks. Experiments are built on 16 datasets related to numerous different majors with appropriately four million samples collected from the student information system of a Vietnamese multidisciplinary university. Results show that the proposed method provides good prediction results, especially when using data transformation. The results are feasible for applying to practical cases.
A Review On Suitable Execution Environment For Executing Parallel Workloads With Mapreduce And Spark

: The high volume of networked computers, workstations, LANs has prompted users to move from a simple end user computing to a complex distributed computing environment. This transition is not just networking the computers, but also involves improvement of performance when used to solve various computational problems. Sequential and parallel execution has its significance on enhancing the performance of a system. Hence when a computational intensive problem solved by a different approach and configuration, it may lead to either performance enhancement or degradation. Therefore, to improve the efficiency, an appropriate method needs to be adopted. This paper discusses to find a suitable method for a problem by examining several approaches and configurations for its execution. Hadoop MapReduce and Apache Spark open source frameworks are used to conduct our experiments and results are analysed.
Prediction Of Hashtags For Images – A Survey

: Hashtags are one of the regular patterns in web-based life locales. They are commonly utilized with writings or pictures via web-based networking media. Choosing or thinking about a reasonable hashtag for a picture is an unwieldy procedure. ML helps in making this procedure simpler. In this paper different techniques for anticipating hashtags for pictures utilizing ML have been looked at.
Terracotta Temples of Birbhum : An Ethno ‐ archaeological

The terracotta temples of Birbhum are one of the unparalleled cultural heritages of the country. Present paper speaks about the aesthetic values of these monuments. In addition, present work has tried to bridge a temporal gap between past and present social cognition as reflected in the making of these monuments of Birbhum. The paper shows past life‐ways carried remarkable influence and inspiration to the artists and architects of studied monuments. Ethno‐archaeological parallels can be witnessed in modern day rural Birbhum as discussed in present paper.