Miracle-dz/UniFAR-FTUs huggingface dataset:
Geographical Patterns of Genetic Variation in Locoto Chile (Capsicum pubescens) in the Americas Inferred by Genome-Wide Data Analysis

The locoto chile (Capsicum pubescens) is a regionally important food crop grown and marketed throughout the mid-highlands of South andCentral America, but little is known about its evolution and the diversity it harbours. An initial scan of genetic diversity and structure across its cultivation range was conducted, the first one using a genomic approach. The RAD-sequencing methodology was applied to a sampling of C. pubescens germplasm consisting of 67 accessions from different American countries, covering its range of distribution/cultivation on the continent. The RAD-seq SNP data obtained clustered the accessions into three major groups, with a high degree of admixture/reticulation among them. Moderate but significant differentiation and geographic structuration were found, depicting a south–north pattern in the distribution of genetic variation. The highest levels of diversity were found among central-western Bolivian individuals, while the lowest was found across Central America-Mexican germplasm. This study provides new genome-wide supported insights into the diversity and differentiation of C. pubescens, as well as a starting point for more efficient use of its genetic variation and germplasm conservation efforts. The findings also contribute to understanding the evolutionary history of C. pubescens, but further investigation is needed to disentangle its origin and diversification under domestication.
Pollution characteristics and diffusion mechanism of antibiotic resistance genes in aquaculture

a b s t r a c t Antibiotic resistance genes in aquaculture have different breeding effects on different kinds of aquatic animals. Therefore, the pollution characteristics and diffusion mechanism of antibiotic resistance genes in aquaculture were studied. Based on the whole genome selection model, the growth param - eters were calculated, the genomic breeding values of different traits of animals were estimated, and the overall relationship matrix of pedigree structure was obtained; The noise variable is intro - duced to reduce breeding algebra, the influence of external environmental variables on genes and systems is comprehensively considered, and the noise statistical standard deviation is calculated; Trace the genetic breeding pedigree of aquaculture animals, construct the genetic breeding pedigree structure of aquaculture animals, and study the pollution characteristics and diffusion mechanism of antibiotic resistance genes in aquaculture. The experimental results show that the research con tent can better optimize and improve the genetic breeding of aquaculture animals and improve the yield of aquaculture.
Impact of social media brand blunders on brand trust and brand liking

More companies are engaging with consumers in real-time on digital platforms, which may lead to accidental or unintentional sharing of messages. Accordingly, how to manage online brand crises has become an increasingly important issue for marketing managers. The present research explores how online brand blunders influence consumers’ trust and liking toward the blunderer brand, and the role of brand commitment in this relationship. Three studies show that consumers evaluate online brand blunders differently than they do product performance problems. Specifically, upon receiving negative brand blunder information, high (vs. low)-commitment consumers’ brand trust and brand liking decrease to a higher extent due to finding the blunder less humorous and more offensive. On the contrary, upon receiving negative product performance information, low (vs. high)-commitment consumers’ brand trust and brand liking decrease to a higher extent, which supports previous literature. Our findings suggest that managers should prioritize high and low-commitment consumers differently and tailor blunder communication in handling online brand crises.
A Comparison of Mental Health among Earthquake, Tsunami, and Nuclear Power Plant Accident Survivors in the Long Term after the Great East Japan Earthquake

Even now, ten years after the Great East Japan Earthquake (GEJE), thousands of residents of Fukushima Prefecture are still living as evacuees. To understand the mental health states and needs for psychological care of the survivors, we conducted a questionnaire survey of survivors who were evacuated from Fukushima to Ibaraki due to the nuclear power plant accident and of the residents of two areas in Ibaraki where damage was particularly severe due to the tsunami or liquefaction. Our results show that stress related to participants’ hometowns and to the disaster was a risk factor for depression and post-traumatic stress among the survivors in the medium to long term in all regions examined. Other risk factors for post-traumatic stress differed by region. This study shows that in a complex disaster such as the GEJE, where damage is widespread, the causes of damage and the experiences of disaster survivors differ greatly from region to region and that risk factors for depression and post-traumatic stress among disaster survivors over the medium to long term may also differ. To provide appropriate care to disaster survivors, it is necessary to determine what is causing the risk of depression and post-traumatic stress at any given time and in specific regions.
Bibliometric analysis of harassment and bullying in sport

Background and Study Aim. This study aims to chart the trend of publications in the Scopus database and the Web of Science as well as the global evolution of harassment and bullying in sports. Material and Methods. ScientoPy and VOSviewer software were used in this study to analyze the number of publications, well-known research topics, proactive authors, author keywords, preferred sources, and institutional data. This study uses data reconciliation with 1, 883 different items from the Scopus database and the Web of Science. An increasing trend in sports nutrition research was found using the Scopus and WoS databases. Results. This field has grown significantly since 2015. In addition, the percentage of documents published in the last two years (2020 to 2021) shows that 22.40% were published on WoS and 22.04% on Scopus. The five keywords that are trending topics between 2020 and 2021 are "Sports", "Racism", "Race", "Sexual Harassment", and "Gender". Meanwhile, the keywords with the highest total link strength were "sports" (244), "racism" (169), "bullying" (165), "adolescents" (161), and "physical activity" (150). The University of Toronto, Canada, became the most productive institution with 22 publications. Conclusions. The most prestigious institutes and researchers in the field of harassment and bullying research in sports have been recognized, along with key research areas, keywords, and related papers. The study also offers potential readers and researchers a global perspective on the hottest issues in harassment and bullying in sport today. In addition, it provides various analyses to assist in the organization of data for the development of harassment and bullying research theories and methodologies in strong sports.
Real-Time Drilling Parameter Optimization Model Based on the Constrained Bayesian Method

To solve the problems of the low energy efficiency and slow penetration rate of drilling, we took the geological data of adjacent wells, real-time logging data, and downhole engineering parameters as inputs; the mechanical specific energy and unit footage cost as multi-objective optimization functions; and the machine pump equipment limit as the constraint condition. A constrained Bayesian optimization algorithm model was established for the optimization solution, and drilling parameters such as weight-of-bit, revolutions per minute, and flowrate were optimized in real time. Through a comparison with NSGA-II, random search, and other optimization algorithms, and the application results of example wells, we show that the established Bayesian optimization algorithm has a good optimization effect while maintaining timeliness. It is suitable for real-time optimization of drilling parameters, can aid a driller in identifying the drilling rate and potential tapping area, and provides a decision-making basis for avoiding the low-efficiency rock-breaking working area and improving rock-breaking efficiency.
Multiple target tracking with the probability hypothesis density filter

The random-set framework for multiple target tracking offers a distinct alternative to the traditional approach to multiple target tracking by treating the collections of individual targets and observations as finite-sets. The multi-target state is predicted and updated recursively based on the set-valued observation. The complexity of computing the multi-target recursion grows exponentially with the number of targets and so a method for approximating the optimal filter using a recursion for the first-order moment of the multi-target posterior, known as the Probability Hypothesis Density (PHD) filter, was developed. This thesis addresses some of the essential issues required for the PHD filter to be of practical value in multiple target tracking applications. Two implementations of the PHD filter are studied in detail; the Particle PHD filter, which is a Sequential Monte Carlo technique based on particle filtering, and the Gaussian Mixture PHD filter, which provides a closed form solution to the PHD filter. A detailed study of the convergence properties is conducted which gives theoretical justification for the use of the algorithms. Novel methods to determine the trajectories of the targets for each of the algorithms are developed which enable the PHD filter to be used for true multiple target tracking. These methods are implemented on forward-looking sonar data and demonstrate that the multiple target tracking methods developed for the PHD filter can be used for real applications. Acknowledgements A big thanks to Judith Bell for her excellent supervision throughout the course of my PhD, her consistent support and guidance has been invaluable. Thanks to QinetiQ for supporting this work, and, in particular, Douglas Carmichael and Samantha Dugelay for their interest in this work. At Heriot-Watt, thanks to Yvan Petillot and Ioseba Tena Ruiz for their expertise on tracking and sonar and for developing the tracking algorithm with Kalman filters on sonar data. Also at Heriot-Watt, thanks to Yves de Saint-Pern for providing his code, Chris Haworth for the tracking work on millimetre wave images, Chris Capus for helping me recover this thesis from my dead laptop, and to the excellent support staff in the department. Thanks to Ba-Ngu Vo for an interesting couple of months in Melbourne and for developing the algorithms on which this thesis is based. Also in Melbourne, thanks to Kusha Panta for his contribution to the Fusion paper. In Cambridge, thanks to Sumeetpal Singh for helping with the complicated mathematics and his high level of rigour. Thanks to Ronald Mahler for developing this interesting area in mathematics and engineering and for inviting me to Florida to present some of this work. The anonymous reviewers, some of whom have refereed a number of the articles in this thesis, have contributed substantially to improving this work and deserve a special thanks. Thanks to Špela for inspiring me to do something good. Finally, the biggest thanks go to my parents for always supporting me, without whom this work would not have been possible.
Multiscale structures and noise in magnetized plasmas line-tied at conducting surfaces

In magnetized plasma situations where magnetic fields intersect massive conducting boundaries, ‘line-tied’ boundary conditions are often used, analytically and in numerical simulations. For ideal magnetohydrodynamic (MHD) plasmas, these conditions are arrived at given the relatively long time scales for magnetic fields penetrating resistively into good conductors. Under line-tied boundary conditions, numerical simulations often exhibit what could be construed as numerical ‘noise’ emanating from the boundaries. We show here that this ‘noise’ is real. By combining numerical and analytical methods, we highlight the existence of sharp spatial structures near the conductors and confirm the appearance of short wavelength structures riding on long wavelength modes. We conclude that, for numerical fidelity, the short multiscale structures need to be resolved. Generally, the short structure widths scale as the square root of the plasma $\unicode[STIX]{x1D6FD}$ .
Construction and Evaluation of a Risk Score Model for Lymph Node Metastasis-Associated Circadian Clock Genes in Esophageal Squamous Carcinoma

Background: Studies suggested that circadian clock genes (CCGs) in human esophageal squamous carcinoma (ESCC) samples are dysregulated. However, the relevance of CCGs to lymph node metastasis (LNM) and prognosis of ESCC remains unclear. Methods: The differentially expressed genes (DEGs) between normal and ESCC samples in The Cancer Genome Atlas database (TCGA) database were intersected with the genes associated with LNM (LNMGs) in ESCC samples and 300 CCGs to obtain the differentially expressed LNM-associated CCGs (DE-LNM-CCGs). The risk model was constructed by Cox regression analysis in the TCGA-ESCC training set, and the accuracy of the risk model was verified by risk profile and overall survival profile. Furthermore, differences of 23 immune cells, 13 immune functions, and immune checkpoint molecules between the high- and low-risk groups were assessed using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Gene set enrichment analysis (GSEA) was conducted to investigate the functional differences between low- and high-risk groups. Finally, we validated the mRNA expression levels of prognostic model genes by quantitative real-time polymerase chain reaction (qRT-PCR). Results: A total of six DE-LNM-CCGs were identified in TCGA-ESCC. TP53 and NAGLU were selected by Cox regression analysis to construct the risk model. Risk profile plots, overall survival plots, and validation results of the risk model in the validation set indicated that the constructed risk model was reliable. The result of ssGSEA showed that the percentages of activated B cells, activated dendritic cells, effector memory CD8 T cells, immune function in neutrophils, plasmacytoid dendritic cells, T cell co-inhibition, and Type 17 T helper cells were different between the high- and low-risk groups. In addition, the expression of CD274, PDCD1, TNFRSF18, and TNFRSF9 was dysregulated between the high- and low-risk groups. GSEA revealed that the high-risk group was associated with cell differentiation, oxidative phosphorylation, and steroid biosynthesis pathways, while the low-risk group was associated with chromosome, ECM–receptor interaction, and other pathways. Finally, qRT-PCR results showed that the mRNA expression levels of two prognostic genes were consistent with TCGA. Conclusion: In conclusion, the risk model constructed based on TP53 and NAGLU could accurately predict the prognosis.
A Multi-Task Dense Network with Self-Supervised Learning for Retinal Vessel Segmentation

Morphological and functional changes in retinal vessels are indicators of a variety of chronic diseases, such as diabetes, stroke, and hypertension. However, without a large number of high-quality annotations, existing deep learning-based medical image segmentation approaches may degrade their performance dramatically on the retinal vessel segmentation task. To reduce the demand of high-quality annotations and make full use of massive unlabeled data, we propose a self-supervised multi-task strategy to extract curvilinear vessel features for the retinal vessel segmentation task. Specifically, we use a dense network to extract more vessel features across different layers/slices, which is elaborately designed for hardware to train and test efficiently. Then, we combine three general pre-training tasks (i.e., intensity transformation, random pixel filling, in-painting and out-painting) in an aggregated way to learn rich hierarchical representations of curvilinear retinal vessel structures. Furthermore, a vector classification task module is introduced as another pre-training task to obtain more spatial features. Finally, to make the segmentation network pay more attention to curvilinear structures, a novel dynamic loss is proposed to learn robust vessel details from unlabeled fundus images. These four pre-training tasks greatly reduce the reliance on labeled data. Moreover, our network can learn the retinal vessel features effectively in the pre-training process, which leads to better performance in the target multi-modal segmentation task. Experimental results show that our method provides a promising direction for the retinal vessel segmentation task. Compared with other state-of-the-art supervised deep learning-based methods applied, our method requires less labeled data and achieves comparable segmentation accuracy. For instance, we match the accuracy of the traditional supervised learning methods on DRIVE and Vampire datasets without needing any labeled ground truth image. With elaborately training, we gain the 0.96 accuracy on DRIVE dataset.
Factors Associated with an Increase in On-Site Time of Pediatric Trauma Patients in a Prehospital Setting: A Nationwide Observational Study in Japan

The factors that prolong the on-site time in pediatric trauma cases in a prehospital setting are unknown. We investigated these factors using a national trauma registry in Japan. We identified pediatric trauma patients aged ≤18 years, from January 2004 to May 2019. We categorized cases into shorter (≤13 min) and longer (>13 min) prehospital on-site time groups. We performed multivariable logistic regression analysis with multiple imputations to assess the factors associated with longer prehospital on-site time. Overall, 14,535 patients qualified for inclusion. The median prehospital on-site time was 13 min. In the multivariable logistic regression analysis, the longer prehospital on-site time was associated with higher age; suicide (Odds ratio [OR] 1.27; 95% confidence interval [CI] 1.03–1.57); violence (OR 1.74; 95%CI 1.27–2.38); higher revised trauma score, abbreviated injury scale > 3 in the spine (OR 1.25; 95%CI 1.04–1.50), upper extremity (OR 1.26; 95%CI 1.11–1.44), and lower extremity (OR 1.25; 95%CI 1.14–1.37); immobilization (OR 1.16; 95%CI 1.06–1.27); and comorbid mental retardation (OR 1.56; 95%CI 1.11–2.18). In light of these factors, time in the field could be reduced by having more pediatric emergency physicians and orthopedic surgeons available.
Kaon production in relativistic heavy ion collisions at 14.6 GeV/c per nucleon

We present a systematic study of charged kaon production in Si+A collisions at 14.6 AGeV/c. Using a 25 millisteradian magnetic spectrometer at the Brookhaven National Laboratory's Alternate Gradient Synchrotron, the high statistics data set (80K K+s and 70K K-s for the Au target, 64K K+s and 30K K-s for Al target) was made possible because of a second level trigger performing particle identification online within 40 microseconds. Target and centrality dependencies are examined for the two targets and for two centralities (central and peripheral). Central events correspond to the upper 7% of the inelastic cross-section and peripheral events to the lower 50%. Our analysis has included the extended particle identification detectors which allows kaon identification up to a momentum of 3.0 GeV/c. This considerably extends the limit of 1.8 GeV/c imposed if we only had the time-of-flight available. We have measured over a broad region of phase space about midrapidity. The kaon yields, dN/dy, and inverse ml slopes (T) are studied systematically as a function of rapidity, centrality and target. We present the A yield and inverse ml slope within the rapidity range of 1.1 and 1.7. A measurement of the A to A ratio in the E802 spectrometer is also made. Our results indicate that the inverse slopes of the kaons are explainable in terms of the kinematics of their production mechanisms and multiple scattering. We observe that in general, TK+ > TK-, and that the inverse mi slopes for both particles increase about equally in going from peripheral to central collisions. It is doubtful that the inverse slope parameters are indicative of the existence of a phase transition, as has been suggested. The K+ yields are more backward peaked than the Kyields in central Si+Au collisions, possibly reflecting different production mechanisms or absorption. We estimate that some 80% of the K+s are from associated production, consistent with p+p data. K+ production in these collisions seems more dominated by N+N collisions, rather than other mechanisms such as 7r+N K+ + A. The invariance of the K+/K ratio for either target or centrality is evidence for this. A comparison between p+A and Si+A data indicates that the increase in the K+/r+ ratio is due in part to K +
Comparative Cytotoxic Evaluation of Zygophyllum album Root and Aerial Parts of Different Extracts and Their Biosynthesized Silver Nanoparticles on Lung A549 and Prostate PC-3 Cancer Cell Lines

The current work demonstrates a comparative study between aerial and root parts of Zygophyllum album L. The total phenolic (TPC) and flavonoid content (TFC), in addition to the antioxidant activity, of the crude extracts were investigated, where the aerial parts revealed a higher value overall. By means of UV–VIS and HPLC, rutin and caffeic acid were detected and then quantified as 5.91 and 0.97 mg/g of the plant extract, respectively. Moreover, the biosynthesis of AgNPs utilizing the crude extract of the arial parts and root of Z. album L. and the phenolic extracts was achieved in an attempt to enhance the cytotoxicity of the different plant extracts. The prepared AgNPs formulations were characterized by TEM and zeta potential measurements, which revealed that all of the formulated AgNPs were of a small particle diameter and were highly stable. The mean hydrodynamic particle size ranged from 67.11 to 80.04 nm, while the zeta potential ranged from 29.1 to 38.6 mV. Upon biosynthesis of the AgNPs using the extracts, the cytotoxicity of the tested samples was improved, so the polyphenolics AgNPs of the aerial parts exhibited a potent cytotoxicity against lung A549 and prostate PC-3 cancer cells with IC50 values of 6.1 and 4.36 µg/mL, respectively, compared with Doxorubicin (IC50 values of 6.19 and 5.13 µg/mL, respectively). Regarding the apoptotic activity, polyphenolics AgNPs of the aerial parts induced apoptotic cell death by 4.2-fold in PC-3 and 4.7-fold in A549 cells compared with the untreated control. The mechanism of apoptosis in both cancerous cells appeared to be via the upregulation proapoptotic genes; p53, Bax, caspase 3, 8, and 9, and the downregulation of antiapoptotic gene, Bcl-2. Hence, this formula may serve as a good source for anticancer agents against PC-3 and A549 cells.