Miracle-dz/UniFAR-FTUs huggingface dataset:
LEAF OPTICAL RESPONSES TO LIGHT AND SOIL

Leaf optical parameters influence light availability at the cellular, leaf, and canopy scale of integration. While recent studies have focused on leaf optical responses to acute plant stress, the effects of changes in plant resources on leaf optics remain poorly characterized. We examined leaf optical and anatomical responses of five temperate deciduous tree species to moderate changes in nutrient and light availability. Spectral reflectance in the visible waveband generally increased at high light, but decreased with increased nutrient availability. Patterns of both spectral reflectance and absorptance were primarily determined by chlorophyll concentration although carotenoid concentration was also influential. While most anatomical features did not explain residual variation in reflectance, cuticle thickness was significantly related to reflectance at complementary angles compared to the angle of incidence. Absorptance did not change with light environment; however, absorption efficiency per unit biomass increased by approximately 40% under low light, due to reduced leaf mass per area. We conclude that changes in resource availability differentially influence leaf optical properties and that such changes are driven primarily by changes in pigment concentrations. The magnitude of leaf optical responses to moderate changes in resource availability was comparable to those of acute stress responses and varied among species.
Beyond Disciplinary Boundaries: Mapping Educational Science in the Discourse on Social Media

Social media has attracted considerable scholarly interest. Previous research has demonstrated the need for a more comprehensive overview of social media research across diverse disciplines. However, there is a lack of research that identifies the scope of social media integration across educational settings and how it relates to research in other academic disciplines. Harnessing the search terms of previous literature reviews, this study collected data on 80,267 articles from the Web of Science Core Collection database using search terms that were based on previous literature reviews. The data were analyzed using a combination of co-citation and bibliometric analyses via a mixed-methods approach. Our results show that there has been a constant increase in the number of publications concerned with social media, both as a transversal topic and within the educational sector. We are also able to show a range of topical domains in which the vast majority of research on social media is conducted. Our findings have practical implications for scholars and practitioners alike. Scholars can benefit from these types of analyses to identify authors and topic clusters that might otherwise have been unrecognized. Similarly, practitioners can benefit from this overview of the current “state-of-the-art” on social media.
Prediction of Genomic Breeding Values in a Commercial Pig Population

Prediction of genomic estimated breeding values (GEBVs) from dense, genome-wide single marker polymorphisms (SNPs) shows promise for more accurate prediction of a pig’s breeding value, particularly at a young age when selection decisions are often made. For traits related to female production there is only parental average breeding values with which to compare candidates for selection. An increase in the accuracy of a candidate’s estimated breeding value (EBV) will increase the rate of genetic gain, particularly for lowly heritable traits. Training populations of individuals with high accuracy EBVs in place of phenotypes have been used to estimate SNP effects (e.g. in dairy cattle; Van Raden et al. 2009) and calculate GEBVs with accuracy exceeding that of parent average. Pig populations generally lack sufficient numbers of animals with EBV accuracies approaching those in dairy training datasets (>0.85), but sampling individuals across generations with only moderately lower accuracies than in dairy cattle may yield GEBVs that are more predictive than EBVs. The objective of this work was to calculate GEBVs for two female reproduction traits in pigs and to evaluate the potential accuracy of these predictions through cross-validation.
Low-Latency Proactive Continuous Vision

Continuous vision is the cornerstone of a diverse range of intelligent applications found on emerging computing platforms such as autonomous machines and Augmented Reality glasses. A critical issue in today's continuous vision systems is their long end-to-end frame latency, which significantly impacts the system agility and user experience. We find that the long latency is fundamentally caused by the serialized execution model of today's continuous vision pipeline, whose key stages, including sensing, imaging, and vision computations, execute sequentially, leading to long frame latency. This paper seeks to reduce the end-to-end latency of continuous vision tasks. Our key idea is a new proactive vision execution model that breaks the sequential execution of the vision pipeline. Specifically, we propose to allow the pipeline front-end (sensing and imaging) to predict future frames; the pipeline back-end (vision algorithms) then predictively operates on the future frames to reduce frame latency. While the proactive execution model is generally applicable to any vision systems, we demonstrate its effectiveness using an implementation on resource-constrained mobile Systems-on-a-chips (SoC). Our system, PVF, incorporates two techniques to overcome key challenges that arise in deploying proactive vision in mobile systems: it enables multiple outstanding speculative frames by exploiting the hardware heterogeneities in mobile SoCs; it reduces the energy overhead of prediction by exploiting the error-resilient nature of vision algorithms. We show that PVF reduces the frame latency by up to 92% under the same energy.
Investigation of Antiviral Drugs with Direct Effect on RNA Polymerases and Simulation of Their Binding to SARS-CoV-2 (COVID-19) RNA-Dependent RNA Polymerase by Molecular Docking Method

Background: Following the outbreak of SARS-CoV (Severe Acute Respiratory Syndrome coronavirus) in 2002 and the outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012, we are facing the rapid spread of SARS-CoV-2 (COVID-19) in the world in 2019 Several outbreaks of the virus and its widespread prevalence have necessitated the design of drugs and vaccines in the shortest possible time This is not possible except by using bioinformatics tools In this study, the binding of drugs affecting RNA Polymerases to SARS-CoV-2 RNA-dependent RNA polymerase structure was simulated by molecular docking method Methods: The structure of drugs used to treat COVID-19 and their similar structures from the drugbank database received It was then subjected to molecular docking by AutoDock Vina software, and the structure with the most negative affinity was docked to reconsider its connection location Finally, the amino acids involved in binding were investigated by Discovery Studio software Results: In the test with in silico status, the Rifabutin had the best performance for SARS-CoV-2 RNA-dependent RNA polymerase binding, and the binding site identified for this drug was different from the binding site shown in the PDB database Conclusion: Further research on the Rifabutin could be the key to discovering new drugs for COVID-19 © 2020 This is an original open-access article distributed under the terms of the Creative Commons Attribution-noncommercial 4 0 International License which permits copy and redistribution of the material just in noncommercial usages with proper citation All rights reserved
Intensity-duration-frequency curves for the city of Ouagadougou: A tool for helping with the dimensioning of hydraulic structures

1. Intensity-duration-frequency (IDF) curves: what for? 1.1 Dimensioning of structures and design storm Hydraulic structures to manage rainwater runoff are based on control of flow routing via channels, overflow limitation by dikes or temporary storage of flows before surface discharge or infiltration into the soil. In both cases, the design of the structures is based on the definition of a design storm. Design storm is usually defined by a synthetic hyetograph that represents the intensity of the rain over a given period of time. A statistical frequency, most often expressed as a return period, is assigned to the design storm and depends on the targeted protection objectives (see Figure 1).
Artificial Intelligence Based Study on Analyzing of Habits and with History of Diseases of Patients for Prediction of Recurrence of Disease Due to COVID-19

A patient will visit physicians when he/she feels ill. This illness is not for COVID-19 but it is a general tendency of human being to visit doctor probably it can not be controlled by general drug. When a patient comes to a doctor, the doctor examines him/her after knowing his/her problem. The physician always asks him/her about some questions related to him/her daily life. For example, if a young male patient comes to a doctor with a symptom of fever and cough, the first question doctor asked him that he has a habit of smoking. Then doctor asks him whether this type of symptom appeared often to him previously or not. If the answers of both questions are yes, then the first one is habit and the second one is that he may suffering from some serious disease or a disease due to the weather. The aim of this paper is to consider habit of the patient as well as he/she has been affected by a critical disease. This information is used to build a model that will predict whether there is any possibility of his/her being affected by COVID-19. This research work contributes to tackle the pandemic situation occurred due to Corona Virus Infectious Disease, 2019 (Covid-19). Outbreak of this disease happens based on numerous factors such as past health records and habits of patients. Health records include diabetes tendency, cardiovascular disease existence, pregnancy, asthma, hypertension, pneumonia; chronic renal disease may contribute to this disease occurrence. Past lifestyles such as tobacco, alcohol consumption may be analyzed. A deep learning based framework is investigated to verify the relationship between past health records, habits of patients and covid-19 occurrence. A stacked Gated Recurrent Unit (GRU) based model is proposed in this paper that identifies whether a patient can be infected by this disease or not. The proposed predictive system is compared against existing benchmark Machine Learning classifiers such as Support Vector Machine (SVM) and Decision Tree (DT).
Morphological and molecular characterization of three new Parastenocarididae (Copepoda: Harpacticoida) from caves in Southern Italy

We describe three new parastenocaridid: Cottarellicaris sanctiangeli Bruno & Cottarelli sp. nov., Stammericaris vincentimariae Bruno & Cottarelli sp. nov. and Proserpinicars specincola Bruno & Cottarelli sp. nov., collected in the pools of five different caves located in Calabria (Southern Italy). We conducted a phylogenetic analysis based on the mitochondrial COI and ribosomal 18S sequences of C. sanctiangeli sp. nov. and S. vincentimariae sp. nov., and of four more species of Stammericaris and one Proserpinicaris available from literature. Based on the molecular study, the specimens of C. sanctiangeli sp. nov. are clearly separated from the species belonging to the closely-related genus Stammericaris . The morphological and molecular data indicate that the genera belonging to the two subfamilies Parastenocaridinae and Fontinalicaridinae form two monophyletic and distinct clades, thus supporting their status. We also provide insights on the genus Proserpinicaris based on morphological data only; in particular, the most important synapomorphic character of the genus, i.e., the taxonomic value of the hyaline structure inserted on the anterior surface of the male leg 4 basis, is discussed based on the development of the P4 endopod, as observed in the last copepodid stage of some species of this genus. Finally, we widen the biogeographic and ecological knowledge of the three genera.
Prevalence of Schistosomamansoni and S. haematobium in Snail Intermediate Hosts in Africa: A Systematic Review and Meta-analysis

Background. Schistosomiasis is caused by Schistosoma mansoni and S. haematobium in Africa. &ese schistosome parasites use freshwater snail intermediate hosts to complete their lifecycle. Varied prevalence rates of these parasites in the snail intermediate hosts were reported from several African countries, but there were no summarized data for policymakers. &erefore, this study was aimed to systematically summarize the prevalence and geographical distribution of S. mansoni and S. haematobium among freshwater snails in Africa.Methods. Literature search was carried out from PubMed, Science Direct, and Scopus which reported the prevalence of S. mansoni and S. haematobium among freshwater snails in Africa. &e pooled prevalence was determined using a random-effect model, while heterogeneities between studies were evaluated by I test. &e meta-analyses were conducted using Stata software, metan command. Results. A total of 273,643 snails were examined for the presence of S. mansoni and S. haematobium cercaria in the eligible studies. &e pooled prevalence of schistosome cercaria among freshwater snails was 5.5% (95% CI: 4.9–6.1%). &e pooled prevalence of S. mansoni and S. haematobium cercaria was 5.6% (95% CI: 4.9–6.3%) and 5.2% (95%CI: 4.6–5.7%), respectively. &e highest pooled prevalence was observed fromNigeria (19.0%; 95%CI: 12.7–25.3%), while the lowest prevalence was reported from Chad (0.05%; 95% CI: 0.03–0.13). Higher prevalence of schistosome cercaria was observed from Bulinus globosus (12.3%; 95% CI: 6.2–18.3%) followed by Biomphalaria sudanica (6.7%; 95%CI: 4.5–9.0%) and Biomphalaria pfeifferi (5.1%; 95% CI: 4.1–6.2%). &e pooled prevalence of schistosome cercaria obtained using PCR was 26.7% in contrast to 4.5% obtained by shedding cercariae. Conclusion. &is study revealed that nearly 6% of freshwater snails in Africa were infected by either S. haematobium or S. mansoni. &e high prevalence of schistosomes among freshwater snails highlights the importance of appropriate snail control strategies in Africa.
Measurement report: aerosol hygroscopic properties extended to 600 nm in the urban environment

Abstract. Submicron particles larger than 300 nm dominate the aerosol light extinction and mass concentration in the atmosphere. The water uptake ability of this size range greatly influences the particle mass, visibility degradation, and particle chemistry. However, most previous field measurements on aerosol hygroscopicity are limited within 350 nm. In this study, the size-resolved aerosol hygroscopic properties over an extended size range (50–600 nm) at 85 % relative humidity were investigated in Beijing winter from 27 November 2019 to 14 January 2020 using a humidity tandem differential mobility analyzer (HTDMA) instrument. The corresponding aerosol optical properties were also analyzed using the Mie scattering theory. Results show that the averaged probability distribution of growth factor (GF-PDF) is generally constituted by a more hygroscopic (MH) group and a less hygroscopic (LH) group (including hydrophobic). For the particles larger than 300 nm, there exists a large fraction of LH group particles, resulting in an unexpected low hygroscopicity. During the development of pollution, when particles are gradually aged and accumulated, the bulk hygroscopicity above 300 nm is enhanced significantly by the growth and expansion of the MH group. This result is supported by previous chemical composition analysis, and we give more direct and detailed evidence from the growth factor and mixing-state aspects. Our calculations indicate that the optical contribution of particles larger than 300 nm constitutes about two-thirds of the total aerosol extinction. The large hygroscopic variation in aerosols above 300 nm will influence the light degradation comparably with the increase in aerosol loading in low-visibility haze events. Our studies highlight that the hygroscopic properties above 300 nm are complex and vary greatly with different pollution stages. Therefore more field measurements and investigations need to be done in the future.
Effects of the Intervention “Reflective STRENGTH-Giving Dialogues” for Older Adults Living with Long-Term Pain: A Pilot Study

Background Long-term musculoskeletal pain is a major, often undertreated, disabling health problem among an increasing number of older adults. Reflective STRENGTH-giving dialogues (STRENGTH) may be a tool to support older adults living with long-term pain. The main aim of this pilot study was to investigate the immediate and longitudinal effect of the intervention STRENGTH on levels of pain, wellbeing, occurrence of depression symptoms, and sense of coherence (SOC) among community-dwelling older adults suffering from musculoskeletal pain compared to a control group. Methods The study was semiexperimental with an intervention group and a control group. The effect of a single STRENGTH intervention was reported on the Numeric Rating Scale (NRS) regarding pain and wellbeing. To evaluate the longitudinal effect of STRENGTH, using the Brief Pain Inventory-Short Form (BPI-SF), the Geriatric Depression Scale-20 (GDS-20), SOC-13 at baseline (T1), and six months after the intervention/no intervention (T2), a total of 30 older adults, aged 72 to 97 years (Mdn 86 years), were included consecutively and fulfilled the intervention series (n = 18) or untreated controls (n = 12). Results The intervention with STRENGTH decreases pain (NRS 6 Mdn versus NRS 4 Mdn, p < 0.001) and increases wellbeing (NRS 7 Mdn versus NRS 8 Mdn, p < 0.001). After a six-month study period with STRENGTH, no longitudinal effect difference was found compared to baseline. Compared to the control group, there was an increasing trend between decreased pain level and increased SOC level for STRENGTH intervention. Conclusions This pilot study supports STRENGTH's effect as a pain-alleviating model that provides a decrease in pain levels and an increase of wellbeing in older adults with long-term pain. STRENGTH dialogues could be a useful intervention to provide individually holistic care in older adults living with long-term pain.
Student-Led Adaptation of Improvement Science Learning During the COVID-19 Pandemic.

Introduction In response to the COVID-19 pandemic and the restriction of students participating in face-to-face instruction, two medical students rapidly adapted a preclinical curriculum that virtually teaches improvement science and equips learners with the knowledge to address patient needs. Methods Eight first-year medical students participating in a longitudinal patient navigation and health systems science program completed 15 interactive video sessions. After learning about the Model for Improvement and various quality improvement tools, students worked in teams of four to conduct several plan-do-study-act cycles. Postsession surveys captured student satisfaction, session feedback, and reflections about conducting improvement work. Two medical students then applied conventional content analysis to identify themes to describe the data. Results Student projects focused on addressing patients' health care and social resource needs through telephone and electronic interactions. Five themes were identified in the survey results: (1) learning by doing in the dynamic nature of improvement work; (2) enjoyment of virtual team-based learning; (3) project relevance to COVID-19; (4) utility of quality improvement tools; and (5) continuous curriculum improvement with student feedback. Conclusions In this student-led endeavor, we implemented a virtual improvement curriculum where first-year medical students apply improvement science knowledge to patient needs during the COVID-19 pandemic. Results demonstrate the feasibility of teaching improvement in a virtual setting where learning is action-based with project work being relevant to health care priorities. Our work provides a framework for others to continue teaching this integral component of medical education.
Anti-insect effect of Senna alata L. seed solvent extracts on Spodoptera litura Fab

Studies were carried out to determine the effect of Senna alata L. solvent seed extracts on third instar Spodoptera litura Fab. using leaf disc bioassay method. Seven different concentrations (5, 10, 20, 30, 50, 70 and 90 %) along with solvent control and absolute control were tested. The extracts showed diverse anti insect properties such as feeding deterrence, insecticidal and insects growth regulatory activity at different concentrations. Among the different solvent extracts of seed, the acetone extract showed maximum feeding deterrence activity of 95.22 per cent in higher concentration. When concentration increased the feeding deterrence was also found to be increased. In other solvent extracts, feeding deterrence was < 50 per cent. The maximum larval mortality (80%) was noticed in methanol extract. In ethyl acetate extract, maximum of 40 per cent larval malformation and 60 per cent pupal malformation were noticed. The experiment revealed that among various seed solvent extracts of S.alata tested against S. litura, the acetone extract of seed in higher concentration showed maximum feeding deterrence activity, the ethyl acetate extract of seed showed insect growth regulatory activity and methanol extract of seed showed insecticidal activity.
Development and validation of simple step protein precipitation 1 UHPLC-MS / MS methods for quantitation of temozolomide in patient 2 plasma samples 3 4

28 Temozolomide (TEMODALTM) (TMZ) is an antineoplastic agent that is primarily used 29 for the treatment of glioblastoma and anaplastic gliomas, two aggressive forms of brain 30 cancer. Due to the poor prognosis of brain tumour patients, there is an increasing body 31 of research into improving the stability and delivery of TMZ past the blood brain barrier 32 using carrier molecules. These require accurate determination of TMZ levels for 33
Genetic variability, heritability and genetic advance studies for quantitative and quality traits in basmati rice (Oryza sativa L.)

The present study was undertaken with an objective of estimation of genetic variability, heritability, genetic advance for yield components and quality parameters among thirty aromatic rice genotypes. The genotypes were evaluated in RBD and ANOVA results revealed the highly significant mean sum of squares among the genotypes for all the characters. PCV and GCV estimates were found high for almost all the traits of interest except for days to maturity, hulling percent and 100 kernel weight after cooking. High heritability was registered for all the traits except hulling percent, coupled with high genetic advance as percent of mean for all characters except days to maturity, 100 kernel weight after cooking and hulling percent, which indicates that these characters are largely controlled by additive gene action.
Tau and charm decays

A summary of recent precise results in tau and charm physics is presented. Topics include leptonic and hadronic tau decays, lepton flavour and lepton number violation, charm mixing and CP violation, leptonic and semileptonic charm decays, rare decays and spectroscopy. Résumé. Nous présentons une sélection de mesures précises et récentes des physiques du lepton τ et du quark charmé et leur interprétation. Nous examinons en particulier les désintégrations hadroniques et leptoniques du τ, les recherches de violation du nombre leptonique et du nombre leptonique par famille, le mélange des mésons neutres charmés et l’observation de la brisure de la symétrie C P , les désintégrations leptoniques et semileptoniques des hadrons charmés, leurs désintégrations rares et les récentes découvertes spectroscopiques.