Miracle-dz/UniFAR-FTUs huggingface dataset:
Outdoor Plant Segmentation With Deep Learning for High-Throughput Field Phenotyping on a Diverse Wheat Dataset

Robust and automated segmentation of leaves and other backgrounds is a core prerequisite of most approaches in high-throughput field phenotyping. So far, the possibilities of deep learning approaches for this purpose have not been explored adequately, partly due to a lack of publicly available, appropriate datasets. This study presents a workflow based on DeepLab v3+ and on a diverse annotated dataset of 190 RGB (350 x 350 pixels) images. Images of winter wheat plants of 76 different genotypes and developmental stages have been acquired throughout multiple years at high resolution in outdoor conditions using nadir view, encompassing a wide range of imaging conditions. Inconsistencies of human annotators in complex images have been quantified, and metadata information of camera settings has been included. The proposed approach achieves an intersection over union (IoU) of 0.77 and 0.90 for plants and soil, respectively. This outperforms the benchmarked machine learning methods which use Support Vector Classifier and/or Random Forrest. The results show that a small but carefully chosen and annotated set of images can provide a good basis for a powerful segmentation pipeline. Compared to earlier methods based on machine learning, the proposed method achieves better performance on the selected dataset in spite of using a deep learning approach with limited data. Increasing the amount of publicly available data with high human agreement on annotations and further development of deep neural network architectures will provide high potential for robust field-based plant segmentation in the near future. This, in turn, will be a cornerstone of data-driven improvement in crop breeding and agricultural practices of global benefit.
Isolation of Elizabethkingia anophelis From COVID-19 Swab Kits

Purpose: To investigate and characterize the putative Elizabethkingia anophelis contaminant isolated from throat and anal swab samples of patients from three fever epidemic clusters, which were not COVID-19 related, in Shenzhen, China, during COVID-19 pandemic. Methods: Bacteria were cultured from throat (n = 28) and anal (n = 3) swab samples from 28 fever adolescent patients. The isolated bacterial strains were identified using matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/MS) and the VITEK2 automated identification system. Nucleic acids were extracted from the patient samples (n = 31), unopened virus collection kits from the same manufacturer as the patient samples (n = 35, blank samples) and from unopened throat swab collection kits of two other manufacturers (n = 22, control samples). Metagenomic sequencing and quantitative real-time PCR (qPCR) detection were performed. Blood serum collected from patients (n = 13) was assessed for the presence of antibodies to E. anophelis. The genomic characteristics, antibiotic susceptibility, and heat resistance of E. anophelis isolates (n = 31) were analyzed. Results: The isolates were identified by MALDI-TOF/MS and VITEK2 as Elizabethkingia meningoseptica. DNA sequence analysis confirmed isolates to be E. anophelis. The patients’ samples and blank samples were positive for E. anophelis. Control samples were negative for E. anophelis. The sera from a sub-sample of 13 patients were antibody-negative for isolated E. anophelis. Most of the isolates were highly homologous and carried multiple β-lactamase genes (blaB, blaGOB, and blaCME). The isolates displayed resistance to nitrofurans, penicillins, and most β-lactam drugs. The bacteria survived heating at 56°C for 30 min. Conclusion: The unopened commercial virus collection kits from the same manufacturer as those used to swab patients were contaminated with E. anophelis. Patients were not infected with E. anophelis and the causative agent for the fevers remains unidentified. The relevant authorities were swiftly notified of this discovery and subsequent collection kits were not contaminated. DNA sequence-based techniques are the definitive method for Elizabethkingia species identification. The E. anophelis isolates were multidrug-resistant, with partial heat resistance, making them difficult to eradicate from contaminated surfaces. Such resistance indicates that more attention should be paid to disinfection protocols, especially in hospitals, to avoid outbreaks of E. anophelis infection.
Contribution of Inflammation and Hypoperfusion to White Matter Hyperintensities-Related Cognitive Impairment

White matter hyperintensities (WMHs) of presumed vascular origin are one of the most important neuroimaging markers of cerebral small vessel disease (CSVD), which are closely associated with cognitive impairment. The aim of this study was to elucidate the pathogenesis of WMHs from the perspective of inflammation and hypoperfusion mechanisms. A total of 65 patients with WMHs and 65 healthy controls were enrolled in this study. Inflammatory markers measurements [hypersensitive C-reactive protein (hsCRP) and lipoprotein-associated phospholipase A2 (Lp-PLA2)], cognitive evaluation, and pseudocontinuous arterial spin labeling (PCASL) MRI scanning were performed in all the subjects. The multivariate logistic regression analysis showed that Lp-PLA2 was an independent risk factor for WMHs. Cerebral blood flow (CBF) in the whole brain, gray matter (GM), white matter (WM), left orbital medial frontal gyrus [MFG.L (orbital part)], left middle temporal gyrus (MTG.L), and right thalamus (Tha.R) in the patients was lower than those in the controls and CBF in the left triangular inferior frontal gyrus [IFG.L (triangular part)] was higher in the patients than in the controls. There was a significant correlation between Lp-PLA2 levels and CBF in the whole brain (R = −0.417, p < 0.001) and GM (R = −0.278, p = 0.025), but not in the WM in the patients. Moreover, CBF in the MFG.L (orbital part) and the Tha.R was, respectively, negatively associated with the trail making test (TMT) and the Stroop color word test (SCWT), suggesting the higher CBF, the better executive function. The CBF in the IFG.L (triangular part) was negatively correlated with attention scores in the Cambridge Cognitive Examination-Chinese Version (CAMCOG-C) subitems (R = −0.288, p = 0.020). Our results revealed the vascular inflammation roles in WMHs, which may through the regulation of CBF in the whole brain and GM. Additionally, CBF changes in different brain regions may imply a potential role in the modulation of cognitive function in different domains.
Fostering Students’ Well-Being: The Mediating Role of Teacher Interpersonal Behavior and Student-Teacher Relationships

Well-being has become extensively viewed as apprehension for administrations in the last decades and schools have been progressively realized as locations for encouraging well-being which is a considerable development in inquiries on mediations connected to learner well-being. In this way, the function of teachers has got specific consideration regarding students’ well-being, given the merits of teacher-student interactions. High-quality educator-learner relationships offer a support base for long-term learners’ education. Educator interpersonal behavior that makes learners feel supported and cared for is known as emotional support. These behaviors can help learners’ emotional and social needs; meet learners’ families, and being available when learners need additional help. This review attempts to consider the eminence of teacher interpersonal behavior and learner-teacher relations in the classroom and indeed illustrate their relationship and influence on students’ well-being. As a final point, this review can provide suggestions and recommendations for teaching participants in the scholastic context.
Identifying Functional Flow Linkages Between Stream Alteration and Biological Stream Condition Indices Across California

Large state or regional environmental flow programs, such as the one based on the California Environmental Flows Framework, rely on broadly applicable relationships between flow and ecology to inform management decisions. California, despite having high flow and bioassessment data density, has not established relationships between specific elements of the annual hydrograph and biological stream condition. To address this, we spatially and temporally linked USGS gage stations and biological assessment sites in California to identify suitable paired sites for comparisons of streamflow alteration with biological condition at a statewide scale. Flows were assessed using a set of functional flow metrics that provide a comprehensive way to compare alteration and seasonal variation in streamflow across different locations. Biological response was evaluated using the California Stream Condition Index (CSCI) and Algal Stream Condition Index (ASCI), which quantify biological conditions by translating benthic invertebrate or algal resources and watershed-scale environmental data into an overall measure of stream health. These indices provide a consistent statewide standard for interpreting bioassessment data, and thus, a means of quantitatively comparing stream conditions throughout the state. The results indicate that indices of biological stream condition were most closely associated with flow alteration in seasonality and timing metrics, such as fall pulse timing, dry-season timing, and wet season timing. Magnitude metrics such as dry-season baseflow, wet season baseflow, and the fall pulse magnitude were also important in influencing biological stream conditions. Development of ecological flow needs in large-scale environmental programs should consider that alteration to any of the seasonal flow components (e.g., dry-season baseflow, fall pulse flow, wet-season baseflow, spring recession flow) may be important in restructuring biological communities.
Genomic Analysis of Visceral Fat Accumulation in Holstein Cows

Visceral fat is related to important metabolic processes, including insulin sensitivity and lipid mobilization. The goal of this study was to identify individual genes, pathways, and molecular processes implicated in visceral fat deposition in dairy cows. Data from 172 genotyped Holstein cows classified at slaughterhouse as having low (n = 77; omental fold < 5 mm in thickness and minimum fat deposition in omentum) or high (n = 95; omental fold ≥ 20 mm in thickness and marked fat deposition in omentum) omental fat were analyzed. The identification of regions with significant additive and non-additive genetic effects was performed using a two-step mixed model-based approach. Genomic scans were followed by gene-set analyses in order to reveal the genetic mechanisms controlling abdominal obesity. The association mapping revealed four regions located on BTA19, BTA20 and BTA24 with significant additive effects. These regions harbor genes, such as SMAD7, ANKRD55, and the HOXB family, that are implicated in lipolysis and insulin tolerance. Three regions located on BTA1, BTA13, and BTA24 showed marked non-additive effects. These regions harbor genes MRAP, MIS18A, PRNP and TSHZ1, that are directly implicated in adipocyte differentiation, lipid metabolism, and insulin sensitivity. The gene-set analysis revealed functional terms related to cell arrangement, cell metabolism, cell proliferation, cell signaling, immune response, lipid metabolism, and membrane permeability, among other functions. We further evaluated the genetic link between visceral fat and two metabolic disorders, ketosis, and displaced abomasum. For this, we analyzed 28k records of incidence of metabolic disorders from 14k cows across lactations using a single-step genomic BLUP approach. Notably, the region on BTA20 significantly associated with visceral fat deposition was also associated with the incidence of displaced abomasum. Overall, our findings suggest that visceral fat deposition in dairy cows is controlled by both additive and non-additive effects. We detected at least one region with marked pleiotropic effects affecting both visceral fat accumulation and displaced abomasum.
Genome Wide Association Study of Beef Traits in Local Alpine Breed Reveals the Diversity of the Pathways Involved and the Role of Time Stratification

Knowledge of the genetic architecture of key growth and beef traits in livestock species has greatly improved worldwide thanks to genome-wide association studies (GWAS), which allow to link target phenotypes to Single Nucleotide Polymorphisms (SNPs) across the genome. Local dual-purpose breeds have rarely been the focus of such studies; recently, however, their value as a possible alternative to intensively farmed breeds has become clear, especially for their greater adaptability to environmental change and potential for survival in less productive areas. We performed single-step GWAS and post-GWAS analysis for body weight (BW), average daily gain (ADG), carcass fleshiness (CF) and dressing percentage (DP) in 1,690 individuals of local alpine cattle breed, Rendena. This breed is typical of alpine pastures, with a marked dual-purpose attitude and good genetic diversity. Moreover, we considered two of the target phenotypes (BW and ADG) at different times in the individuals’ life, a potentially important aspect in the study of the traits’ genetic architecture. We identified 8 significant and 47 suggestively associated SNPs, located in 14 autosomal chromosomes (BTA). Among the strongest signals, 3 significant and 16 suggestive SNPs were associated with ADG and were located on BTA10 (50–60 Mb), while the hotspot associated with CF and DP was on BTA18 (55–62 MB). Among the significant SNPs some were mapped within genes, such as SLC12A1, CGNL1, PRTG (ADG), LOC513941 (CF), NLRP2 (CF and DP), CDC155 (DP). Pathway analysis showed great diversity in the biological pathways linked to the different traits; several were associated with neurogenesis and synaptic transmission, but actin-related and transmembrane transport pathways were also represented. Time-stratification highlighted how the genetic architectures of the same traits were markedly different between different ages. The results from our GWAS of beef traits in Rendena led to the detection of a variety of genes both well-known and novel. We argue that our results show that expanding genomic research to local breeds can reveal hitherto undetected genetic architectures in livestock worldwide. This could greatly help efforts to map genomic complexity of the traits of interest and to make appropriate breeding decisions.
Visual Collaboration Leader-Follower UAV-Formation for Indoor Exploration

UAVs operating in a leader-follower formation demand the knowledge of the relative pose between the collaborating members. This necessitates the RF-communication of this information which increases the communication latency and can easily result in lost data packets. In this work, rather than relying on this autopilot data exchange, a visual scheme using passive markers is presented. Each formation-member carries passive markers in a RhOct configuration. These markers are visually detected and the relative pose of the members is on-board determined, thus eliminating the need for RF-communication. A reference path is then evaluated for each follower that tracks the leader and maintains a constant distance between the formation-members. Experimental studies show a mean position detection error (5 × 5 × 10cm) or less than 0.0031% of the available workspace [0.5 up to 5m, 50.43° × 38.75° Field of View (FoV)]. The efficiency of the suggested scheme against varying delays are examined in these studies, where it is shown that a delay up to 1.25s can be tolerated for the follower to track the leader as long as the latter one remains within its FoV.
Early Phenotype Programming in Birds by Temperature and Nutrition: A Mini-Review

Early development is a critical period during which environmental influences can have a significant impact on the health, welfare, robustness and performance of livestock. In oviparous vertebrates, such as birds, embryonic development takes place entirely in the egg. This allows the effects of environmental cues to be studied directly on the developing embryo. Interestingly, beneficial effects have been identified in several studies, leading to innovative procedures to improve the phenotype of the animals in the long term. In this review, we discuss the effects of early temperature and dietary programming strategies that both show promising results, as well as their potential transgenerational effects. The timing, duration and intensity of these procedures are critical to ensure that they produce beneficial effects without affecting animal survival or final product quality. For example, cyclic increases in egg incubation temperature have been shown to improve temperature tolerance and promote muscular growth in chickens or fatty liver production in mule ducks. In ovo feeding has also been successfully used to enhance digestive tract maturation, optimize chick development and growth, and thus obtain higher quality chicks. In addition, changes in the nutritional availability of methyl donors, for example, was shown to influence offspring phenotype. The molecular mechanisms behind early phenotype programming are still under investigation and are probably epigenetic in nature as shown by recent work in chickens.
Genome-Wide Identification and Comparative Profiling of MicroRNAs Reveal Flavonoid Biosynthesis in Two Contrasting Flower Color Cultivars of Tree Peony

MicroRNA (miRNA)-mediated gene regulation is involved in various physiological processes in plants. Flower color is one of the vital ornamental traits of tree peony (Paeonia suffruticosa Andr.). However, the yellow-flowered tree peony cultivars are particularly rare. To elucidate the miRNA-mediated gene regulatory mechanism underlying yellow pigmentation in tree peony, we combined pigment assessment, miRNA identification, expression analysis, and gene functional verification in two contrasting flower color cultivars “High Noon” and “Roufurong. ” Flavones/flavonols and anthocyanins were found to be the main contributors to the coloration of “High Noon” and “Roufurong” petals, respectively. Subsequently, miRNA analysis based on available genome data identified 9 differentially expressed miRNAs and 12 relevant target genes implicated in flavonoid biosynthesis. Their dynamic expression patterns determined the key role of mdm-miR156b-PsSPL2 module in yellow pigmentation of tree peony flowers. The sequence analysis and subcellular localization validated that PsSPL2 might function as a nuclear-localized transcription factor. Overexpression of PsSPL2 in tobacco resulted in a decrease of anthocyanin content and down-regulation of NtF3′H and NtDFR transcripts. PsSPL2-silenced petals exhibited lighter yellow color, and the contents of THC, Ap, and Ch decreased significantly. Meanwhile, expression levels of PsCHS, PsCHI, and PsF3H were significantly decreased in the petals with PsSPL2 silencing, while those of PsF3′H and PsDFR were remarkably increased. This study offers a novel insight into yellow pigmentation-related miRNA regulation network in tree peony, and further provides the valuable information on physiological changes during yellow coloring process of tree peony.
Precautionary Principle or Evidence-Based Conservation? Assessing the Information Content of Threat Data for the Yangtze Finless Porpoise

Conservation management requires evidence, but robust data on key parameters such as threats are often unavailable. Conservation-relevant insights might be available within datasets collected for other reasons, making it important to determine the information content of available data for threatened species and identify remaining data-gaps before investing time and resources in novel data collection. The Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis) has declined severely across the middle-lower Yangtze, but multiple threats exist in this system and the relative impact of different anthropogenic activities is unclear, preventing identification of appropriate mitigation strategies. Several datasets containing information on porpoises or potential threats are available from past boat-based and fishing community surveys, which might provide novel insights into causes of porpoise mortality and decline. We employed multiple analytical approaches to investigate spatial relationships between live and dead porpoises and different threats, reproductive trends over time, and sustainable offtake levels, to assess whether evidence-based conservation is feasible under current data availability. Our combined analyses provide new evidence that mortality is spatially associated with increased cargo traffic; observed mortality levels (probably a substantial underestimate of true levels) are unsustainable; and population recruitment is decreasing, although multiple factors could be responsible (pollutants, declining fish stocks, anthropogenic noise, reduced genetic diversity). Available data show little correlation between patterns of mortality and fishing activity even when analyzed across multiple spatial scales; however, interview data can be affected by multiple biases that potentially complicate attempts to reconstruct levels of bycatch, and new data are required to understand dynamics and sustainability of porpoise-fisheries interactions. This critical assessment of existing data thus suggests that in situ porpoise conservation management must target multiple co-occurring threats. Even limited available datasets can provide new insights for understanding declines, and we demonstrate the importance of an integrative approach for investigating complex conservation problems and maximizing evidence in conservation planning for poorly known taxa.
Detecting COVID-19-Related Fake News Using Feature Extraction

Since its emergence in December 2019, there have been numerous posts and news regarding the COVID-19 pandemic in social media, traditional print, and electronic media. These sources have information from both trusted and non-trusted medical sources. Furthermore, the news from these media are spread rapidly. Spreading a piece of deceptive information may lead to anxiety, unwanted exposure to medical remedies, tricks for digital marketing, and may lead to deadly factors. Therefore, a model for detecting fake news from the news pool is essential. In this work, the dataset which is a fusion of news related to COVID-19 that has been sourced from data from several social media and news sources is used for classification. In the first step, preprocessing is performed on the dataset to remove unwanted text, then tokenization is carried out to extract the tokens from the raw text data collected from various sources. Later, feature selection is performed to avoid the computational overhead incurred in processing all the features in the dataset. The linguistic and sentiment features are extracted for further processing. Finally, several state-of-the-art machine learning algorithms are trained to classify the COVID-19-related dataset. These algorithms are then evaluated using various metrics. The results show that the random forest classifier outperforms the other classifiers with an accuracy of 88.50%.
ELBOW AND WRIST JOINT LOADING DURING THE ROUND-OFF SKILLS IN MALE GYMNASTICS: A CASE STUDY

Elbow and wrist injuries are a major concern in elite male gymnastics. The aim of the current study was to investigate key elbow and wrist joint injury risk factors (internal and external kinetics) during different round-off techniques in male artistic gymnastics. One international level male gymnast performed 15 trials of a round-off from a hurdle step to back handspring with three different hand positions (parallel (5), T-shape (5) and reverse (5)). Synchronized kinematic and kinetic data were collected for each trial. Effect-size statistics determined differences between each hand position. In conclusion the T-shape technique demonstrated reduced vertical, anterior-posterior and resultant ground reaction forces. Differences in elbow and wrist joint kinetics indicated that the T-shape technique may prevent elbow and wrist joint from overload and reduces potential of injuries.