Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on melanoma image segmentation method based on improved SwinUNet

Aiming at the problems of fuzzy boundary and poor segmentation effect of SwinUNet in melanoma image segmentation, an improved SwinUNet network segmentation method was proposed. Firstly, Dice loss function is used to alleviate the background and regional imbalance. Secondly, each decoder layer is made to fuse the smaller scale from the encoder, the same scale feature map and the larger scale feature map from the decoder, so that the fine-grained semantics and coarse-grained semantics at the full scale can be captured . Finally, the size of the sliding window is increased, the receptive field of the model is enlarged, and the Dice coefficient is used to evaluate the segmentation results. The average Dice values of the original SwinUNet and the three improved models were 0.8311, 0.8689, 0.8719 and 0.8661, respectively. The experimental results show that the improved model proposed in this paper can effectively improve the accuracy of the original model, which is extremely important for the early diagnosis and treatment of melanoma.
De novo variants in MAST4 related to neurodevelopmental disorders with developmental delay and infantile spasms: Genotype-phenotype association

Objective This study aims to prove that the de novo variants in MAST4 gene are associated with neurodevelopmental disorders (NDD) with developmental delay (DD) and infantile spasm (IS) and to determine the genotype-phenotype correlations. Methods Trio-based exome sequencing (ES) was performed on the four families enrolled in this study. We collected and systematically reviewed the four probands’ clinical data, magnetic resonance images (MRI), and electroencephalography (EEG). We also carried out bioinformatics analysis by integrating published exome/genome sequencing data and human brain transcriptomic data. Results We described four patients whose median age of seizure onset was 5 months. The primary manifestation was infantile spasms with typical hypsarrhythmia on EEG. Developmental delays or intellectual disabilities varied among the four individuals. Three de novo missense variants in MAST4 gene were identified from four families, including chr5:66438324 (c.2693T > C: p.Ile898Thr) z, chr5:66459419 (c.4412C > T: p.Thr1471Ile), and chr5:66462662 (c.7655C > G:p.Ser2552Trp). The missense variant p.Ile898Thr is mapped to the AGC-kinase C-terminal with phosphatase activity. The other variant p.Ser2552Trp is located in a phosphoserine-modified residue which may affect cell membrane stability and signal transduction. Besides, the variant p.Thr1471Ile is a recurrent site screened out in two unrelated patients. Compared to private mutations (found only in a single family or a small population) of MAST4 in the gnomAD non-neuro subset, all de novo variants were predicted to be damaging or probably damaging through different bioinformatic analyses. Significantly higher CADD scores of the variant p.Thr1471Ile indicate more deleteriousness of the recurrent site. And the affected amino acids are highly conserved across multiple species. According to the Brainspan Atlas database, MAST4 is expressed primarily in the mediodorsal nucleus of the thalamus and medial prefrontal cortex during the prenatal period, potentially contributing to embryonic brain development. Conclusion Our results revealed that the variants of MAST4 gene might lead to neurodevelopmental disorders with developmental delay and infantile spasm. Thus, MAST4 variants should be considered the potential candidate gene in patients with neurodevelopmental disorders clinically marked by infantile spasms.
Model Test Study on the Transmission Law of Explosion Stress Wave in Rock Mass with Filling Joints

In order to study the propagation and attenuation law of explosive stress wave in rock mass with filling joints, and consider the influence of different crustal stress conditions, different strength mortar is used to simulate rock mass and joints, and the multi-functional simulation test device of geotechnical engineering is used to carry out explosive model test research, the influence characteristics of different in-situ stress conditions on the attenuation of explosive stress wave in rock mass with different thickness filling joints are analyzed, and obtain the transmission law of stress wave. The results show that: when the explosion stress wave propagates in the joined rock mass, the thicker the filling joint is, the greater the attenuation range of the stress wave energy and the samller the transmission coefficient; In-situ stress will change the attenuation of explosive stress wave in rock mass. With the increase of in-situ stress, the transmission coefficient of stress wave in intact rock mass and joined rock mass will increase. When the local stress is fixed, the transmission coefficient of stress wave in joined rock mass also increase gradually with the increase of explosion load.
Sparsity regularised recursive least squares adaptive filtering

The authors propose a new approach for the adaptive identification of sparse systems. This approach improves on the recursive least squares (RLS) algorithm by adding a sparsity inducing weighted l 1 norm penalty to the RLS cost function. Subgradient analysis is utilised to develop the recursive update equations for the calculation of the optimum system estimate, which minimises the regularised cost function. Two new algorithms are introduced by considering two different weighting scenarios for the l 1 norm penalty. These new l 1 relaxation-based RLS algorithms emphasise sparsity during the adaptive filtering process, and they allow for faster convergence than standard RLS when the system under consideration is sparse. The authors test the performance of the novel algorithms and compare it with standard RLS and other adaptive algorithms for sparse system identification.
Statistical analysis of correlated phase error in transmission characteristics of arrayed-waveguide gratings

Transmission characteristics of arrayed waveguide gratings (AWGs) are significantly influenced by phase errors in a waveguide array, which are easily caused by the variation of fabrication process. In this paper, the statistical analysis of transmission characteristics is presented using correlation and spectral density of phase errors. A simple statistical approach, based on a simplified model of a waveguide array, is newly introduced to clarify statistical behavior of phase errors in AWGs. Spectral density is modeled from measured phase errors, and then average transmission characteristics are simulated for AWGs with different channel spacing. Average transmission characteristics, simulated with the spectral density model, almost describe measured results in the cases of various channel spacing. It is also indicated that an AWG may have larger adjacent-channel crosstalk with narrower channel spacing because the adjacent-channel crosstalk is affected by phase errors with a smaller spatial frequency.
Reliability of pathophysiological markers reflective of exercise-induced gastrointestinal syndrome (EIGS) in response to 2-h high-intensity interval exercise: A comprehensive methodological efficacy exploration

The study aimed to determine the test-retest reliability of exercise-induced gastrointestinal syndrome (EIGS) biomarkers, and assess the association of pre-exercise short chain fatty acid (SCFA) concentration with these biomarkers in response to prolonged strenuous exercise. Thirty-four participants completed 2 h of high-intensity interval training (HIIT) on two separate occasions with at least 5-days washout. Blood samples were collected pre- and post-exercise, and analysed for biomarkers associated with EIGS [i.e., cortisol, intestinal fatty-acid binding protein (I-FABP), sCD14, lipopolysaccharide binding protein (LBP), leukocyte counts, in-vitro neutrophil function, and systemic inflammatory cytokine profile]. Fecal samples were collected pre-exercise on both occasions. In plasma and fecal samples, bacterial DNA concentration was determined by fluorometer quantification, microbial taxonomy by 16S rRNA amplicon sequencing, and SCFA concentration by gas-chromatography. In response to exercise, 2 h of HIIT modestly perturbed biomarkers indicative of EIGS, including inducing bacteremia (i.e., quantity and diversity). Reliability analysis using comparative tests, Cohen’s d, two-tailed correlation, and intraclass correlation coefficient (ICC) of resting biomarkers presented good-to-excellent for IL-1ra (r = 0.710, ICC = 0.92), IL-10 (r = 0.665, ICC = 0.73), cortisol (r = 0.870, ICC = 0.87), and LBP (r = 0.813, ICC = 0.76); moderate for total (r = 0.839, ICC = 0.44) and per cell (r = 0.749, ICC = 0.54) bacterially-stimulated elastase release, IL-1β (r = 0.625, ICC = 0.64), TNF-α (r = 0.523, ICC = 0.56), I-FABP (r = 0.411, ICC = 0.21), and sCD14 (r = 0.409, ICC = 0.38), plus fecal bacterial α-diversity; and poor for leukocyte (r = 0.327, ICC = 0.33) and neutrophil (r = 0.352, ICC = 0.32) counts. In addition, a medium negative correlation was observed between plasma butyrate and I-FABP (r = −0.390). The current data suggest a suite of biomarkers should be used to determine the incidence and severity of EIGS. Moreover, determination of plasma and/or fecal SCFA may provide some insight into the mechanistic aspects of EIGS instigation and magnitude in response to exercise.
Relationship between Vitreous IL-6 Levels, Gender Differences and C-Reactive Protein (CRP) in a Blood Sample of Posterior Uveitis

This study retrospectively determined the relationship between vitreous IL-6 levels and clinical and laboratory data collected from uveitis patients. We examined an unknown cause of posterior uveitis, collecting vitreous fluid to investigate vitreous IL-6 levels. The samples were analyzed in consideration of clinical and laboratory factors, such as the male/female ratio. The present study included 82 eyes from 77 patients with a mean age of 66.20 ± 15.41 years. The IL-6 concentrations of the vitreous specimens were 6255.0 ± 14,108.3 pg/mL in males and 277.6 ± 746.3 pg/mL in females, which was found to be a statistically significant difference (p = 0.048) (n = 82). There was also a statistically significant correlation between vitreous IL-6 concentrations, serum C-reactive protein (CRP) value and white blood cell counts (WBCs) (n = 82). In multivariate analysis, vitreous IL-6 levels were significantly correlated with gender and CRP in all cases (p = 0.048 and p < 0.01, respectively) and were also significantly correlated with CRP in non-infectious uveitis (p < 0.01). In infectious uveitis, there were no significant differences between IL-6 level and several variables. Vitreous IL-6 concentrations were higher in males than in females in all cases. In non-infectious uveitis, vitreous IL-6 levels were correlated with serum CRP. These results might suggest that intraocular IL-6 levels depend on gender differences in posterior uveitis, and intraocular IL-6 levels in non-infectious uveitis may reflect systemic inflammations, including increased serum CRP.
Online Learning for Wearable EEG-Based Emotion Classification

Giving emotional intelligence to machines can facilitate the early detection and prediction of mental diseases and symptoms. Electroencephalography (EEG)-based emotion recognition is widely applied because it measures electrical correlates directly from the brain rather than indirect measurement of other physiological responses initiated by the brain. Therefore, we used non-invasive and portable EEG sensors to develop a real-time emotion classification pipeline. The pipeline trains different binary classifiers for Valence and Arousal dimensions from an incoming EEG data stream achieving a 23.9% (Arousal) and 25.8% (Valence) higher F1-Score on the state-of-art AMIGOS dataset than previous work. Afterward, the pipeline was applied to the curated dataset from 15 participants using two consumer-grade EEG devices while watching 16 short emotional videos in a controlled environment. Mean F1-Scores of 87% (Arousal) and 82% (Valence) were achieved for an immediate label setting. Additionally, the pipeline proved to be fast enough to achieve predictions in real-time in a live scenario with delayed labels while continuously being updated. The significant discrepancy from the readily available labels on the classification scores leads to future work to include more data. Thereafter, the pipeline is ready to be used for real-time applications of emotion classification.
Phytomediated Silver Nanoparticles (AgNPs) Embellish Antioxidant Defense System, Ameliorating HLB-Diseased ‘Kinnow’ Mandarin Plants

Citrus production is harmed worldwide by yellow dragon disease, also known as Huanglongbing (HLB), or citrus greening. As a result, it has negative effects and a significant impact on the agro-industrial sector. There is still no viable biocompatible treatment for Huanglongbing, despite enormous efforts to combat this disease and decrease its detrimental effects on citrus production. Nowadays, green-synthesized nanoparticles are gaining attention for their use in controlling various crop diseases. This research is the first scientific approach to examine the potential of phylogenic silver nanoparticles (AgNPs) to restore the health of Huanglongbing-diseased ‘Kinnow’ mandarin plants in a biocompatible manner. AgNPs were synthesized using Moringa oleifera as a reducing, capping, and stabilizing agent and characterized using different characterization techniques, i.e., UV–visible spectroscopy with a maximum average peak at 418 nm, scanning electron microscopy (SEM) with a size of 74 nm, and energy-dispersive spectroscopy (EDX), which confirmed the presence of silver ions along with different elements, and Fourier transform infrared spectroscopy served to confirm different functional groups of elements. Exogenously, AgNPs at various concentrations, i.e., 25, 50, 75, and 100 mgL−1, were applied against Huanglongbing-diseased plants to evaluate the physiological, biochemical, and fruit parameters. The findings of the current study revealed that 75 mgL−1 AgNPs were most effective in boosting the plants’ physiological profiles, i.e., chl a, chl b, total chl, carotenoid content, MSI, and RWC up to 92.87%, 93.36%, 66.72%, 80.95%, 59.61%, and 79.55%, respectively; biochemical parameters, i.e., 75 mgL−1 concentration decreased the proline content by up to 40.98%, and increased the SSC, SOD, POD, CAT, TPC, and TFC content by 74.75%, 72.86%, 93.76%, 76.41%, 73.98%, and 92.85%, respectively; and fruit parameters, i.e., 75 mgL−1 concentration increased the average fruit weight, peel diameter, peel weight, juice weight, rag weight, juice pH, total soluble solids, and total sugarby up to 90.78%, 8.65%, 68.06%, 84.74%, 74.66%, 52.58%, 72.94%, and 69.69%, respectively. These findings enable us to develop the AgNP formulation as a potential citrus Huanglongbing disease management method.
Managing irrigation and sowing date can improve oil content and fatty acid composition of Camelina sativa L

ABSTRACT A two-year experiment was arranged as a factorial in a randomized complete block design with three replicates to investigate the response of camelina oil yield and its oil composition to irrigation regimes at different sowing dates in Karaj, Iran. The experiment factors were irrigation regimes including (i) full irrigation (well-watered), (ii) restricted irrigation from silicle formation (late-stress), (iii) restricted irrigation from flowering (mild-stress) and (IV) restricted irrigation from maximum stem length (early-stress) and planting dates consisting of (i) 27-Sep, (ii) 12-Oct and (iii) 25-Oct. The highest oil content (30.04%) was obtained from the first sowing date and was 2% and 5.4% higher than 12-Oct and 25-Oct, respectively. Obtained grains from well-watered irrigation regime had significantly more oil content (31.02%) than the other irrigation regimes. Delaying in sowing date and water-deficit stress raised saturated fatty acids (palmitic, stearic and arachidic acids). While delayed sowing date (12 and 25-Oct) and water-deficit stress (low, mild and severe stresses) increased the content of palmitic, eicosenoic and erucic fatty acids, the oleic, linoleic and linolenic acids were reduced in such conditions. It seems that postponing the sowing date to 12-Oct and restricting irrigation from silicle formation would be reasonable as it can decline water consumption.
Explainable machine learning for long-term outcome prediction in two-center stroke patients after intravenous thrombolysis

Objective Neurological outcome prediction in patients with ischemic stroke is very critical in treatment strategy and post-stroke management. Machine learning techniques with high accuracy are increasingly being developed in the medical field. We studied the application of machine learning models to predict long-term neurological outcomes in patients with after intravenous thrombolysis. Methods A retrospective cohort study was performed to review all stroke patients with intravenous thrombolysis. Patients with modified Rankin Score (mRs) less than two at three months post-thrombolysis were considered as good outcome. The clinical features between stroke patients with good and with poor outcomes were compared using three different machine learning models (Random Forest, Support Vector Machine and Logistic Regression) to identify which performed best. Two datasets from the other stroke center were included accordingly for external verification and performed with explainable AI models. Results Of the 488 patients enrolled in this study, and 374 (76.6%) patients had favorable outcomes. Patients with higher mRs at 3 months had increased systolic pressure, blood glucose, cholesterol (TC), and 7-day National Institute of Health Stroke Scale (NIHSS) score compared to those with lower mRs. The predictability and the areas under the curves (AUC) for the random forest model was relatively higher than support vector machine and LR models. These findings were further validated in the external dataset and similar results were obtained. The explainable AI model identified the risk factors as well. Conclusion Explainable AI model is able to identify NIHSS_Day7 is independently efficient in predicting neurological outcomes in patients with ischemic stroke after intravenous thrombolysis.
Public knowledge of antibiotics, self-medication, and household disposal practices in Jordan

ABSTRACT Background This study aimed to assess public understanding of antibiotics, self-medication, and drug disposal practices. Methods A cross-sectional self-administered online survey was undertaken in Jordan. Results The study was completed by 1,105 participants. When asked about their knowledge of antibiotics, rational antibiotic use, and disposal practices, 16% percent believed they should discontinue antibiotics once they felt better, and 12% agreed to take the same antibiotics prescribed to others for the same illness. Self-medication with antibiotics was practiced by 44% of the participants. Prior experience, healthcare costs, and pharmacy location were all major determinants of self-medication. Only 6.4% of unneeded antibiotics were returned to the pharmacy, 60% were kept at home, and 26.6% were disposed of at home. Almost half of those who kept the antibiotics said they would use them again, and one-third said they would give them to friends and family. Respondents who had used antibiotics within the previous 6 months (p = 0.052) and relied on medication leaflets (p = 0.031) and physician recommendations (p = 0.001) were less likely to self-medicate with antibiotics. Conclusions The study highlighted areas of inappropriate use of antibiotics, self-medication and the improper antibiotic disposal that can inform antimicrobial stewardship.
An experimental investigation of the oscillating lift and drag of a circular cylinder shedding turbulent vortices

The oscillating lift and drag on circular cylinders are determined from measurements of the fluctuating pressure on the cylinder surface in the range of Reynolds number from 4 × 103 to just above 105. The magnitude of the r.m.s. lift coefficient has a maximum of about 0.8 at a Reynolds number of 7 × 104 and falls to about 0.01 at a Reynolds number of 4 × 103. The fluctuating component of the drag was determined for Reynolds numbers greater than 2 × 104 and was found to be an order of magnitude smaller than the lift.
Changes of In Situ Prokaryotic and Eukaryotic Communities in the Upper Sanya River to the Sea over a Nine-Hour Period

The transition areas of riverine, estuarine, and marine environments are particularly valuable for the research of microbial ecology, biogeochemical processes, and other physical–chemical studies. Although a large number of microbial-related studies have been conducted within such systems, the vast majority of sampling have been conducted over a large span of time and distance, which may lead to separate batches of samples receiving interference from different factors, thus increasing or decreasing the variability between samples to some extent. In this study, a new in situ filtration system was used to collect membrane samples from six different sampling sites along the Sanya River, from upstream freshwater to the sea, over a nine-hour period. We used high-throughput sequencing of 16S and 18S rRNA genes to analyze the diversity and composition of prokaryotic and eukaryotic communities. The results showed that the structures of these communities varied according to the different sampling sites. The α-diversity of the prokaryotic and eukaryotic communities both decreased gradually along the downstream course. The structural composition of prokaryotic and eukaryotic communities changed continuously with the direction of river flow; for example, the relative abundances of Rhodobacteraceae and Flavobacteriaceae increased with distance downstream, while Sporichthyaceae and Comamonadaceae decreased. Some prokaryotic taxa, such as Phycisphaeraceae and Chromobacteriaceae, were present nearly exclusively in pure freshwater environments, while some additional prokaryotic taxa, including the SAR86 clade, Clade I, AEGEAN-169 marine group, and Actinomarinaceae, were barely present in pure freshwater environments. The eukaryotic communities were mainly composed of the Chlorellales X, Chlamydomonadales X, Sphaeropleales X, Trebouxiophyceae XX, Annelida XX, and Heteroconchia. The prokaryotic and eukaryotic communities were split into abundant, common, and rare communities for NCM analysis, respectively, and the results showed that assembly of the rare community assembly was more impacted by stochastic processes and less restricted by species dispersal than that of abundant and common microbial communities for both prokaryotes and eukaryotes. Overall, this study provides a valuable reference and new perspectives on microbial ecology during the transition from freshwater rivers to estuaries and the sea.