Miracle-dz/UniFAR-FTUs huggingface dataset:
Pre‐dispersal seed predation and pollen limitation constrain population growth across the geographic distribution of Astragalus utahensis

A central focus of ecology is to understand the conditions under which biotic interactions affect species’ abundance and distribution. Classic and recent studies have shown that biotic interactions can strongly impact local or regional patterns of species abundance, but two fundamental questions remain largely unaddressed for non‐competitive biotic interactions. First, do the effects of these interactions on population performance change predictably with environmental context? Second, to what extent do population‐scale effects contribute to limiting species’ geographic distributions? To address these questions, we experimentally assessed the extent to which pollen limitation and insect seed predators affected the fecundity and projected population growth rate (λ) of the native forb Astragalus utahensis. We studied populations at the centre and northern edge of the latitudinal range of A. utahensis that occur across a gradient in abiotic harshness characterized primarily by declining mean annual precipitation. Supplementing pollen and suppressing pre‐dispersal seed predators increased seed production similarly within A. utahensis populations at the centre and northern edge of the range. Integral projection population models revealed that relaxing these checks on seed production tended to increase λ in most populations, regardless of their location within the range. Synthesis. Our results suggest that pollen limitation and insect herbivores limit population growth in A. utahensis similarly across the centre‐to‐north portion of its latitudinal distribution. However, because A. utahensis population growth barely reaches the level of replacement at the northern range edge, the reduction in λ resulting from these interactions may contribute to limiting expansion at the northern edge of A. utahensis’ latitudinal range.
Comparison and suitability of genotype by environment analysis methods for yield-related traits of pearl millet

Pearl millet ( Pennisetum glaucum (L.) R. Br. ) is an important food security and income crop for households living in semi-arid zones in Uganda. However, the genotype by environment interaction, in addition to the several methods used for its assessment, complicates selection of varieties adapted to such semi-arid areas. The objective of this study, therefore, was to compare common methods used to assess stability and adaptability of improved genotypes. Seventy six genotypes were planted in four environments in an alpha experimental design with two replications. Results showed that genotype by environment interactions were significant at p<0.05 for grain yield, days to 50% flowering and 50% physiological maturity, percentage of productive tillers and panicle area. Results further showed inconsistency in ranking of genotypes between methods; although Cultivar Superiority, REML, Yield Stability Index and GGE biplot were consistently correlated and identified high yielding and stable genotypes. Keywords: GGE biplot, grain yield, pearl millet, stability analysis, Uganda
Automatic Classification of Prostate Cancer Gleason Scores from Digitized Whole Slide Tissue Biopsies

Histological Gleason grading of tumor patterns is one of the most powerful prognostic predictors in prostate cancer. However, manual analysis and grading performed by pathologists are typically subjective and time-consuming. In this paper, we propose an automatic technique for Gleason grading of prostate cancer from H&E stained whole slide biopsy images using a set of novel completed and statistical local bi-nary pattern (CSLBP) descriptors. First the technique divides the whole slide image into a set of small image tiles, where salient tumor tiles with high nuclei densities are selected for analysis. The CSLBP texture features that encode pixel intensity variations from circularly surrounding neighborhoods are then extracted from salient image tiles to characterize different Gleason patterns. Finally, CSLBP texture features computed from all tiles are integrated and utilized by the multi-class support vector machine (SVM) that assigns patient biopsy with different Gleason score of 6, 7 or ≥8. Experiments have been performed on 312 different patient cases selected from the cancer genome atlas (TCGA) and have achieved more than 79% classification accuracies, which is superior to state-of-the-art textural descriptors for prostate cancer Gleason grading.
V483a – an Emerging Mutation Hotspot of Sars-Cov-2

Exploring the biological significance of mutations in SARS-CoV-2 coronavirus, causing the COVID–19 pandemic, has recently become an area of paramount interest for many researchers, who are pouring their tremendous efforts, in cracking the COVID–19 pandemic code. One of many such mutations that have occurred in the viral genome is V483A mutation, which is a part of the receptor-binding motif (RBM), present in the S1 domain of the spike protein. V483A mutant virus is becoming popular in North America with 36 cases so far, due to its frequent occurrences in recent days. In this review, we have assembled all information, currently available on V483A mutation, and have made a critical analysis based on the perspectives of many researchers all around the world. Comparison is made between the wild type and the V483A mutants to analyze certain factors like the type of interaction between the virus and host cell interface, binding affinity, stability, partition energy, hydrophobicity, occurrence rate, and transmissibility. Insilico dynamic analysis shows minimal alteration in the receptor-binding domain (RBD) of V483A mutant protein in free-state and no significant change of mutant tertiary structure of RBM upon binding to the ACE2 receptor. Comprehensive details about infectivity and evasion of the immune system by the virus are discussed. This information can in turn be of monumental importance in the field of vaccine and drug development because the mutants are becoming resistant to the vaccines and monoclonal antibodies.
Efficient BFCN for Automatic Retinal Vessel Segmentation

Retinal vessel segmentation has high value for the research on the diagnosis of diabetic retinopathy, hypertension, and cardiovascular and cerebrovascular diseases. Most methods based on deep convolutional neural networks (DCNN) do not have large receptive fields or rich spatial information and cannot capture global context information of the larger areas. Therefore, it is difficult to identify the lesion area, and the segmentation efficiency is poor. This paper presents a butterfly fully convolutional neural network (BFCN). First, in view of the low contrast between blood vessels and the background in retinal blood vessel images, this paper uses automatic color enhancement (ACE) technology to increase the contrast between blood vessels and the background. Second, using the multiscale information extraction (MSIE) module in the backbone network can capture the global contextual information in a larger area to reduce the loss of feature information. At the same time, using the transfer layer (T_Layer) can not only alleviate gradient vanishing problem and repair the information loss in the downsampling process but also obtain rich spatial information. Finally, for the first time in the paper, the segmentation image is postprocessed, and the Laplacian sharpening method is used to improve the accuracy of vessel segmentation. The method mentioned in this paper has been verified by the DRIVE, STARE, and CHASE datasets, with the accuracy of 0.9627, 0.9735, and 0.9688, respectively.
An Efficient HPLC Approach to Quantify Kunitz Trypsin Inhibitor in Soybean Seeds

Trypsin inhibitor (TI), an important antinutritional factor present in soybean [Glycine max (L.) Merr. ] seeds, prevents animal protein digestibility. Accurately determining seed TI concentration is essential for screening soybean breeding lines to select genotypes with low TI. A colorimetric assay is widely used to measure TI activity in soybean seeds. This bioassay is time consuming, expensive, and has repeatability issues. This study developed a high-performance liquid chromatography (HPLC) method as a high-throughput, less expensive, and more reliable assay to quantify Kunitz trypsin inhibitor (KTI), the major TI, in soybean seeds. We extracted KTI using sodium acetate buffer, separated on a Poros R2/H perfusion column and detected at 220 nm. The HPLC method was compared with two popular enzymatic bioassays using 100 soybean lines. For the bioassays, TI was extracted using HCl or NaOH extractants and determined according to Kakade et al. (1974). The KTI from the HPLC method ranged from 0.52 to 12.15 mg g⁻¹ with an average of 5.25 mg g⁻¹ and a limit detection of 0.05 mg g⁻¹. The recovery of KTI in spiked soybean samples was 82.33%. The KTI data from HPLC and both bioassays were strongly correlated (r = 0.82 and 0.80, p ≤ 0.0001). The CVs of KTI data (66.20% for HPLC, 18.84 and 32.55% for bioassays) suggest that the HPLC method is capable of detecting a wider range of KTI quantities and providing a better sensitivity for quantifying KTI in soybean seed samples.
Choice in Insurance Markets: A Pigouvian Approach to Social Insurance Design

Should choice be offered in social insurance programs? This review presents a conceptual framework that identifies the key forces determining the social value of offering choice. We show that the value of offering choice is higher the larger the variation in individual valuations for extra insurance is, but it gets reduced by both selection on risk and selection on moral hazard. Besides adverse selection, the implementation of choice-based policies is further challenged by the presence of choice frictions or the obligation to offer basic uncompensated care. All these inefficiencies can be seen as externalities that do not rationalize the absence of providing choice per se but point to the need for regulatory policies and suggest the potential value of corrective pricing à la Pigou. Applying this framework to the existing evidence on these forces in the context of unemployment insurance, we find that offering insurance choice can be valuable even in the presence of significant adverse selection. We conclude by showing how this framework can constitute a fruitful guide for further empirical research in different insurance domains.
Association of miR-146a Gene Polymorphism with Systemic Lupus Erthymatous Disease

The present study was carried out to detect the association of microRNA-146a haplotypes polymorphisms with Systemic lupus erythematous (SLE) in Iraqi patients, PCRSSCP technique used in present study, blood was used to DNA extraction, the results show that there was strong association between microRNA-146a and SLE in one haplotype from two . The present study concluded that there was association between microRNA-146a polymorphisms with SLE, our finding need more investigation to use this polymorphism as early indication of SLE incidence.
Optimization of Probabilistic Switching Models Based on a Two-Step Clustering Approach

This paper proposes a method for optimizing the clusters employed as discrete random variables in probabilistic switching models. The proposed optimization facilitates obtaining a low number of discrete components while guaranteeing a high performance at predicting and detecting abnormalities in time series of data. Our method is composed of a two-step clustering approach that first considers a partitional clustering to obtain an initial semantic representation of data. Then it performs a hierarchical clustering to decrease the number of clusters while preserving coherent models employed for predicting future time instances at the testing phase. Odometry data from a real vehicle that performs different tasks in a closed, controlled environment is used to evaluate the proposed method.
Chitin- and Chitosan-Based Derivatives in Plant Protection against Biotic and Abiotic Stresses and in Recovery of Contaminated Soil and Water

Biotic, abiotic stresses and their unpredictable combinations severely reduce plant growth and crop yield worldwide. The different chemicals (pesticides, fertilizers, phytoregulators) so far used to enhance crop tolerance to multistress have a great environmental impact. In the search of more eco-friendly systems to manage plant stresses, chitin, a polysaccharide polymer composed of N-acetyl-D-glucosamine and D-glucosamine and its deacetylated derivative chitosan appear as promising tools to solve this problem. In fact, these molecules, easily obtainable from crustacean shells and from the cell wall of many fungi, are non-toxic, biodegradable, biocompatible and able to stimulate plant productivity and to protect crops against pathogens. In addition, chitin and chitosan can act as bioadsorbents for remediation of contaminated soil and water. In this review we summarize recent results obtained using chitin- and chitosan-based derivatives in plant protection against biotic and abiotic stresses and in recovery of contaminated soil and water.
CytoGAN: Generative Modeling of Cell Images

We explore the application of Generative Adversarial Networks to the domain of morphological profiling of human cultured cells imaged by fluorescence microscopy. When evaluated for their ability to group cell images responding to treatment by chemicals of known classes, we find that adversarially learned representations are superior to autoencoder-based approaches. While currently inferior to classical computer vision and transfer learning, the adversarial framework enables useful visualization of the variation of cellular images due to their generative capabilities.
The Influence of Sorbitan Monooleate as a Surfactant and Octanol as a Co-surfactant to Restore Biodieselâ€™s Flow Properties at the Cold Temperatures

The application of the biodiesel-diesel mixed fuel at the cold temperatures causes problem stoppage in the diesel engine. This is caused by the precipitation of agglomerate Saturated Monoglycerides (SMG). From the previous study, the addition of 1% Sorbitan Monooleate (SMO) could reduce the Cloud Point (CP) and Cold Filter Plugging Point (CFPP) respectively by 4.2°C and 2°C. In this study, SMO was used as a surfactant with octanol as a co-surfactant. For each biodiesel with 0.4-0.6% MG, the SMO was varied by 0.1-1% v/v. The molar ratio of the SMO/octanol is 1:1. Samples of biodiesel were stored at the cold temperatures (±16°C). The effect of addition SMO and octanol was analyzed by Differential Scanning Calorimetry (DSC) and the changes of MG’s droplet particle size were analyzed by Particle Size Analyzer (PSA). As the results, the addition of SMO and octanol reduced CP by 4.6°C and CFPP by 3°C. The PSA and DSC method proved that there were changes in MG’s particle diameter and onset temperature respectively from 8.18-68.30 µm to 0.29-8.88 µm and from 9.79°C to 4.97°C. The changes indicate that the SMO and octanol have roles in reducing the agglomeration of MG in biodiesel.
Spectral Analysis of High-Resolution Aeromagnetic Data for Geothermal Energy Reconnaissance across Sokoto Basin, Northwest, Nigeria

This study interprets aeromagnetic data of across Sokoto Basin with the aim of estimating theThis study interprets aeromagnetic data across Sokoto Basin with the aim of estimating the Curie point depth, geothermal gradient and heat flow for geothermal energy. The study area lies between the longitude of 30E and 60E and latitudes 110N and 130N. The total magnetic intensity of the area was subjected to regional/residual separation using polynomial fitting. The residual data was divided into 30 overlapping spectral blocks, where the log of spectral energies was plotted against the frequency, hence the centroid depth and the top to the magnetic sources were deduced. These depth results were used in estimating the Curie point Depth and geothermal gradient. The total magnetic intensity indicated a variation of 32932.84 to 33118.27 nT, while the residual map shows magnetic anomalies which vary from -82 to 51 nT, both maps indicated high, low and intermediary magnetic anomalies. The centroid depth results vary from 4.67 to 28.80 km and the top to the magnetic source varies from 1.04 to 4.65 km with an average depth of 2.21 km. The Curie point depth range from 6.92 to 55.04 km with an average depth of 18.65 km, and the geothermal gradients revealed ranges from 10.54 oCkm-1 at the Southwest (Danko and Gummi) areas to 83.82 oCkm-1 at the northwest (Argungu) area. Therefore, these areas with high geothermal gradients are good indicators of geothermal energy potential and should be exploited for more power generation.
Mining the spatio‐temporal pattern using matrix factorisation: a case study of traffic flow

Realising the spatio-temporal evolutionary pattern of urban traffic can give advice about making personal trip route planning and improving road construction. A novel pattern-discovering model is presented to identify the traffic regularity and characteristics from spatial and temporal dimensions. To unveil this new method, there are two main parts as follows: first, by employing the constrained projected gradient of the non-negative matrix factorisation algorithm, the original traffic data matrix is decomposed into the feature matrix and the weight matrix. Necessary constraints are newly added so that the resulting matrices are ensured to make practical sense for reflecting the traffic spatio-temporal regular pattern. Then, the self-organising maps network is further used to cluster the factorisation error into several classes representing the disparate traffic pattern of each time. In addition, the experiment is conducted on real historical data to verify the performance of the algorithm. The global urban traffic flow for a week is summarised through a set of basic patterns with related weight distribution. The well-visualised result demonstrates that the authors method can achieve significant improvement in terms of computational efficiency and accuracy when compared with other widely-used methods.
Time domain flutter analysis of bend-twist coupled large composite wind turbine blades: a parametric study

Abstract This article presents flutter prediction of composite wind turbine blades through time domain aeroelastic analysis using unsteady blade element momentum (BEM) theory based aerodynamic model. Comparison of the flutter speeds obtained in the present study with those previously obtained through Eigen solution based approach using Theodorsen’s theory based aerodynamic model for several different lamination sequences and blade configuration has been presented. It has been observed that both the approaches predict highest flutter speed at the same blade configuration and lamination sequence. However, flutter limit obtained through the present approach is less as compared to that obtained through Eigen solution based approach.
Genetic diversity of aromatic rice in Bangladesh

The nature and magnitude of diversity in 53 aromatic rice genotypes was evaluated in rain fed condition at BRAC Agricultural Research and Development Centre, Gazipur in 2012. The Euclidian method of divergence analysis indicated the presence of appreciable amount of genetic diversity in the material. These aromatic rice genotypes were grouped into six clusters where cluster I was the largest. Inter-cluster distances were larger than the intra-cluster distance revealed that there situated considerable genetic diversity among the genotypes. Based on positive value of vector I and II days to 50% flowering, seed length, and grain yield per hill had maximum contribution towards genetic divergence. Maximum yield contributing traits were accumulated in cluster V and as a result higher grain yield (42.0 g/hill) was obtained in this cluster. The genotypes of cluster V can be used in hybridization program to produce higher yielding breeding materials with all other clusters. The genotypes Cluster IV and cluster V were found most suitable for the respective characters and can be used as potential donor for future breeding programs. Res. Agric. , Livest. Fish.4(1): 1-6, April 2017
Early career researchers’ perceptions of the benefits and challenges of sharing research with academic and non-academic end-users

ABSTRACT Contemporary early career researchers (ECRs) must share their research findings with both academic and non-academic audiences in order to advance their careers. With university organisational factors potentially both demanding and inhibiting ECR research dissemination, more needs to be known about ECRs’ perceptions and experiences of the benefits and challenges of sharing research for diverse audiences. This article investigates ECRs’ perceptions of sharing research with academic and non-academic end-users, drawing on perspectives from 30 ECRs in Australia and Japan. Findings hold cross-contextual and disciplinary salience. Benefits of sharing research with the academic community included collaboration and networking, exposure and career development, contribution to knowledge, and learning and feedback. We found that sharing research with non-academic end users offered benefits in relation to end user utility, social change, securing future funding, and knowledge mobilisation. However, respondents also identified a range of notable barriers that constrained their capacity to share their research within academia and beyond. Findings can be used to support ECRs' skills and knowledge development in sharing research with diverse audiences.
Repetitive transcranial magnetic stimulation increases phase-amplitude coupling

A prominent feature of brain activity with relevance to cognitive processes is Phase-Amplitude Coupling (PAC) between slow and fast oscillatory signals. A newly developed neural mass model of cross-frequency coupling [1] predicts, counter-intuitively, that PAC shows sustained increases after repetitive Transcranial Magnetic Stimulation (rTMS). This is because rTMS leads to simultaneous neuronal firing in distinct regions, thereby enhancing the connectivity that, according to the model, is needed for PAC to be increased. We tested this prediction in healthy human volunteers. Two seconds of 10Hz rTMS were applied to the intraparietal sulcus, temporal-parietal junction, and lateral occipital complex. PAC in the subsequent electro-encephalogram was analyzed for two band pairs, theta-gamma and alpha-gamma, and compared to a sham condition. For all stimulation loci, PAC was higher in both band pairs after rTMS than in the sham condition. These results were found to be conform the model prediction. The perspective for using rTMS to modulate cross-band coupling is discussed.
Primary care communication and palliative care in the era of COVID-19

Jenny is a 61-year-old teacher who was recently diagnosed with breast cancer and is receiving first line chemotherapy. She is a mother of 3 adult children, married, and an avid gardener. She was previously healthy, with no comorbidities, but developed a dry cough yesterday. She remains afebrile and has had no recent travel history or sick contacts. Per local public health recommendations, she is carefully monitoring her symptoms at home. After hearing conflicting information on the news and online, her husband, attempting to clarify information, calls his wife's primary care provider.