Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular survey and genetic diversity of Plasmodium sp. infesting domestic poultry in northeastern Thailand

Abstract Introduction Haemosporidian parasites are prevalent worldwide and can cause economic losses in poultry production. These parasites are arousing interest in Thailand and are found in many avian species. There is insufficient information on the genetic diversity of these alveolates from the largest families – Plasmodidae, Haemoprotidae and Leucocytozoidae – specifically parasitising ducks, turkeys, and geese. Material and Methods Blood samples from 116 backyard poultry (60 ducks, 36 turkeys and 20 geese) in northeastern Thailand were investigated for Plasmodium spp. , Haemoproteus spp. and Leucocytozoon spp. infections using microscopic examination and molecular approaches. Results A total of 37/116 birds (31.9%) had confirmed Plasmodium infections. The prevalence was 69.4% (25/36) in turkeys, 18.3% (11/60) in ducks, and 5.0% (1/20) in geese. Of these 37 positives, 86.5% were Plasmodium sp. , 10.8% were P. gallinaceum and 2.7% were P. juxtanucleare. Sequence analysis based on the cytochrome b gene identified seven lineages, of which two were new lineages in backyard poultry. Conclusion This is the first report on the prevalence of haemosporidian parasites in backyard poultry in northeastern Thailand. The results provide important data for better understanding the molecular epidemiology of haemosporidian parasites infection in poultry in this region, which will be helpful in controlling these blood parasites.
Motion Artifact Reduction Using U-Net Model with Three-Dimensional Simulation-Based Datasets for Brain Magnetic Resonance Images

This study aimed to remove motion artifacts from brain magnetic resonance (MR) images using a U-Net model. In addition, a simulation method was proposed to increase the size of the dataset required to train the U-Net model while avoiding the overfitting problem. The volume data were rotated and translated with random intensity and frequency, in three dimensions, and were iterated as the number of slices in the volume data. Then, for every slice, a portion of the motion-free k-space data was replaced with motion k-space data, respectively. In addition, based on the transposed k-space data, we acquired MR images with motion artifacts and residual maps and constructed datasets. For a quantitative evaluation, the root mean square error (RMSE), peak signal-to-noise ratio (PSNR), coefficient of correlation (CC), and universal image quality index (UQI) were measured. The U-Net models for motion artifact reduction with the residual map-based dataset showed the best performance across all evaluation factors. In particular, the RMSE, PSNR, CC, and UQI improved by approximately 5.35×, 1.51×, 1.12×, and 1.01×, respectively, and the U-Net model with the residual map-based dataset was compared with the direct images. In conclusion, our simulation-based dataset demonstrates that U-Net models can be effectively trained for motion artifact reduction.
Shared Knowledge-Based Contrastive Federated Learning for Partial Discharge Diagnosis in Gas-Insulated Switchgear

Recently, deep neural networks have shown remarkable success in fault diagnosis in power systems using partial discharges (PDs), thereby enhancing grid asset safety and reliability. However, the prevailing approaches often adopt centralized large-scale datasets for training, without taking into account the impact of noise environments for Intelligent Electronic Devices (IEDs). Noise environments for PD measurements in gas-insulated switchgear (GIS) introduce variations in feature distributions and class representations, challenging the generalization ability of the trained models in new and diverse conditions. In this study, we propose a Shared Knowledge-based Contrastive Federated Learning (SK-CFL) for PD diagnosis in different noise environments for IEDs. The proposed SK-CFL combines federated learning principles with contrastive learning, empowering IEDs to collaboratively learn and share knowledge as regards PD and noise patterns. The proposed framework can learn representations between the same patterns across different IEDs while ensuring data privacy. Experimental results for PD diagnosis in GIS show that the proposed SK-CFL achieves a performance improvement in fault diagnosis, particularly in new and unseen environments. Specifically, the recall for unknown noise in untrained IED 6 demonstrates 92.86% of the proposed SK-CFL, in comparison with 64.29% and 35.71% of the conventional FL and baseline method, respectively. These results suggest that the proposed SK-CFL approach promises more adaptable, and resilient data-driven approaches since it protects data privacy that can operate effectively in challenging real-world environments.
Detection of Hybrids in Willows (Salix, Salicaceae) Using Genome-Wide DArTseq Markers

The genus Salix, comprising some 400–500 species, is important in various alluvial or wet habitats of the northern hemisphere. It is a promising crop for applications such as biomass production, biofuels, or environmental projects. Clear species delimitation is crucial in ecology, biotechnology, and horticulture. DArTseq markers, a genome-wide technique, were tested for species and hybrid identification. A total of 179 willow samples were analysed, including six species of Salix subgen. Salix and four species of Salix subgen. Vetrix, including those used in biomass crop production, representing important European taxa. Identification of species-specific markers, clustering analyses (principal coordinate analysis, neighbor-joining) and Bayesian methods (Structure) unambiguously identified putative hybrids. In addition to demonstrating the high efficiency of DArT-seq markers in identifying willow hybrids, we also opened-up new questions about hybridisation processes and systematics. We detected unidirectional hybridisation between S. alba and S. fragilis, forming backcross hybrids, and we rejected the hypothesis that S. fragilis does not occur naturally in Europe. Further, the isolated position of Salix triandra within the genus was confirmed.
Ensemble and Pre-Training Approach for Echo State Network and Extreme Learning Machine Models

The echo state network (ESN) is a recurrent neural network that has yielded state-of-the-art results in many areas owing to its rapid learning ability and the fact that the weights of input neurons and hidden neurons are fixed throughout the learning process. However, the setting procedure for initializing the ESN’s recurrent structure may lead to difficulties in designing a sound reservoir that matches a specific task. This paper proposes an improved pre-training method to adjust the model’s parameters and topology to obtain an adaptive reservoir for a given application. Two strategies, namely global random selection and ensemble training, are introduced to pre-train the randomly initialized ESN model. Specifically, particle swarm optimization is applied to optimize chosen fixed and global weight values within the network, and the reliability and stability of the pre-trained model are enhanced by employing the ensemble training strategy. In addition, we test the feasibility of the model for time series prediction on six benchmarks and two real-life datasets. The experimental results show a clear enhancement in the ESN learning results. Furthermore, the proposed global random selection and ensemble training strategies are also applied to pre-train the extreme learning machine (ELM), which has a similar training process to the ESN model. Numerical experiments are subsequently carried out on the above-mentioned eight datasets. The experimental findings consistently show that the performance of the proposed pre-trained ELM model is also improved significantly. The suggested two strategies can thus enhance the ESN and ELM models’ prediction accuracy and adaptability.
EOLMAP: A web tool to assess the wind resource over Spain

A wind data base and a web tool have been developed to estimate the wind power over the Iberian Peninsula (IP). This tool also allows estimating the most appropriate Small Wind Turbine (SWT) for a given location. The wind database includes observational and simulated wind data. The simulated data consists on a 10 km hindcast, covering the period 1960-2007, generated with a Regional Climate Model (RCM) driven by ERA40. The observational data base has been built from hourly records encompassing the period 1999-2007 and includes more than 450 stations evenly distributed over Spain. A quality control has been applied to the data in order to assess the reliability of the observational data set. Although the web tool provides information which allows the users to estimate the reliability of the modelled data in the location of the interest, a previous general validation of the simulation has been performed. This previous validation indicates that most of the disagreements between simulation and observations are attributable to the too coarse spatial resolution of the regional model.
Clinical features and prognosis of systemic lupus erythematosus complicated by active cytomegalovirus infection: a retrospective cohort study

Objective The aim of this study was to investigate the clinical traits and consequences of systemic lupus erythematosus (SLE) complicated by active cytomegalovirus (CMV) infection. Methods This retrospective review involved the examination of medical records for patients diagnosed with SLE who had an active CMV infection at the time of their discharge from Peking Union Medical College Hospital between June 2016 and December 2022. The consistency between plasma CMV deoxyribonucleic acid (DNA) viral load and pp65 antigenemia was analyzed using the chi-square test. Related factors for CMV disease in SLE complicated by active CMV infection patients were analyzed by univariate analysis and multivariable stepwise logistic regression. Cox hazards regression analysis was used to determine predictors for all-cause mortality and CMV recurrence within 3 months. Results A total of 206 patients were enrolled in this study. Of the 123 patients who were detected with both plasma CMV DNA viral load and pp65 antigenemia within an interval not exceeding 72 h, the consistency between plasma CMV DNA viral load and pp65 antigenemia was not good (Kappa = −0.304, p < 0.001). Plasma CMV DNA viral load ≥ 1,600 copies/mL [odds ratio (OR) 4.411, 95% CI 1.871–10.402, p = 0.001], current glucocorticoids dose (equivalent to prednisolone) ≥60 mg/d (OR 2.155, 95% CI 1.071–4.334, p = 0.031), and elevated alanine transaminase (OR 3.409, 95% CI 1.563–7.435, p = 0.002) were significant clinical clues indicating CMV disease in SLE. Multivariable Cox hazards regression analysis showed that CMV organ involvement [hazard ratio (HR) 47.222, 95% CI 5.621–396.689, p < 0.001], SLE multi-system involvement (HR 1.794, 95% CI 1.029–3.128, p = 0.039), and elevated hypersensitive C-reactive protein (hsCRP) (HR 5.767, 95% CI 1.190–27.943, p = 0.030) were independent risk factors for 3-month all-cause mortality. CMV organ involvement (HR 3.404, 95% CI 1.074–10.793, p = 0.037) was an independent risk factor for CMV recurrence within 3 months. Conclusion In SLE patients, plasma CMV DNA viral load seemed to have a higher value in the diagnosis of CMV disease; patients with CMV organ involvement, SLE multi-system involvement, and elevated hsCRP might have a higher risk of 3-month all-cause mortality; and patients with CMV organ involvement might have a higher risk of CMV recurrence within 3 months.
Green Human Resources Management in Supporting Environmental Performance at Six Senses Uluwatu, Bali

As a hotel that carries the concept of sustainability, it is very important to Six Senses Uluwatu, Bali to understand how green human resources management affects employees' environmentally friendly behavior, which in turn affects the company's environmental performance. Until now, the implementation of green human resources management has not been fully implemented at Six Senses Uluwatu, Bali, because there are still several things that hinder it. This research aims to analyze the implementation of green human resources management and to find out how green human resources management can support the environmental performance at Six Senses Uluwatu, Bali. This research uses a qualitative approach with data analysis techniques Miles and Huberman model, which consists of data reduction, data display, and conclusion drawing/verification. The implementation of Green Human Resources Management at Six Senses Uluwatu, Bali has been running at 75% so far. In addition, practices that have not been implemented are currently in the planning stage to be implemented in the future. Although it is not perfect, there is already a process in implementing green human resources management which is always reviewed and improved.
Okkhor-Diffusion: Class Guided Generation of Bangla Isolated Handwritten Characters Using Denoising Diffusion Probabilistic Model (DDPM)

Bangla has a unique script with a complex set of characters, making it a fascinating subject of study for linguists and cultural enthusiasts. Unique in some of its similar characters which are only distinguishable by subtle differences in their shapes and diacritics, there has been a notable increase in research on Bangla character recognition and classification using machine learning-based approaches. However, Handwritten Bangla Character Recognition (HBCR) training requires an adequate amount of data from a diversely distributed dataset. Making diverse datasets for HBCR training is a challenging and tedious task to carry out. Yet, there is limited research on the automatic generation of handwritten Bangla characters. Motivated by this open area of research, this paper proposes a novel approach ‘Okkhor-Diffusion’ for class-guided generation of Bangla isolated handwritten characters using a novel Denoising Diffusion Probabilistic Model (DDPM). No prior research has used DDPM for this purpose, making the proposed approach novel. The DDPM is a generative model that uses a diffusion process to transform noise-corrupted data into diverse samples; despite being trained on a small training set. In our experiments, StyleGAN2-ADA had notably inferior performance compared to Okkhor-Diffusion in generating realistic isolated handwritten Bangla characters. Experimental results on the BanglaLekha-Isolated dataset demonstrate that the proposed Okkhor-Diffusion model generates realistic isolated handwritten Bangla characters, with a mean Multi-Scale Structural Similarity Index Measure (MS-SSIM) score of 0.178 compared to 0.177 for the real samples. The Fréchet Inception Distance (FID) score for the synthetic handwritten Bangla characters is 5.426. Finally, the newly proposed Bangla Character Aware Fréchet Inception Distance (BCAFID) score of the proposed Okkhor-Diffusion model is 10.388. The code for the proposed Okkhor-Diffusion framework is available at https://github.com/MubtasimFuad10/Okkhor-Diffusion.
Crustal Footprint of the Hainan Plume Beneath Southeast China

Although global and regional seismic tomography results have revealed the presence of a mantle plume beneath Hainan Island, there is little evidence for a hotspot track associated with the Hainan plume. Here a joint inversion of satellite gravity measurements and seismic surface wave dispersion data was performed, and the results show that a linear corridor of high seismic velocity anomalies beneath the crust is located northeast of Hainan Island beneath the Southeast China. Geodynamic modeling further demonstrates that this corridor could have been formed by the interactions between a mantle plume and the continental lithosphere with a weak lower crust. Volcanic age distributions of sporadic oceanic island basalts suggest that this track was likely formed since the late Cretaceous, which helps to constrain the averaged plate velocity of the South China Block, relative to the Hainan plume, to be ~1.8 cm/year to the northeast since 80 Ma. Our result provides a novel explanation for the crustal thickness variations, related Vs anomalies, and observed oceanic island basalts in this area. It also provides an independent way for constraining plate motion history of the continental lithosphere.
The Correlation between Sex Hormone-Binding Globulin and Clinical Characteristics According to Anti-Müllerian Hormone in Women with Regular Menstrual Cycles: A Prospective Study

Background: Polycystic ovarian syndrome (PCOS) can be diagnosed when the anti-Müllerian hormone (AMH) levels are high, but in clinic, women who do not meet the diagnosis of PCOS but have elevated AMH levels are often seen. This study aimed to compare the differences in menstrual cycle patterns and hormone levels in women with regular menstrual cycles, but not PCOS, by dividing them into high and low AMH groups. Material and Methods: This multicenter prospective study included 68 healthy women. Participants with regular menstrual cycles were divided into two groups according to their AMH levels. The main outcome measures were menstrual cycle pattern, body mass index, and hormone levels (thyroid stimulating hormone, prolactin, testosterone, sex hormone-binding globulin, and free androgen index), which were compared between the groups according to AMH levels. The ovulation was assessed by performing pelvic ultrasound, and by assessing the hormone levels of the luteinizing hormone and progesterone. Results: The criteria for determining normal and high AMH levels were based on previous literatures. The participants were divided into normal (39 people) and high (29 people) AMH group. No differences were found in age or BMI between the two groups, and no other differences were observed in TSH, prolactin, testosterone, or free androgen index. However, the high AMH group had significantly higher SHBG levels than the normal group (normal group: 65.46 ± 25.78 nmol/L; high group: 87.08 ± 45.05 nmol/L) (p = 0.025). Conclusions: This study is the first to analyze the association between SHBG and AMH levels in women with regular menstrual cycles. Elevated AMH levels are associated with increased levels of SHBG levels.
Evaluating projects for improving fish and wildlife habitat on National Forests.

Everest, Fred H. ; Talhelm, Daniel R. Evaluating projects for improving fish and wildlife habitat on National Forests. Gen. Tech. Rep. PNW-146. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station; 1982. 12 p. Recent legislation (PL. 93-452; P.L. 94588) has emphasized improvement of fish and wildlife habitat on lands of the National Forest System. A sequential procedure has been developed for screening potential projects to identify those producing the greatest fishery benefits. The procedure which includes program planning, project p I an n in g , and in ten sive ben ef i t/cost analysis has nationwide application for both fish and wildlife projects. Fisheries and wildlife values are difficult to assess and available estimates are far from ideal, but better estimates are gradually becoming available. '
Biomimetic Structure and Surface for Grasping Tasks

Under water, on land, or in the air, creatures use a variety of grasping methods to hunt, avoid predators, or carry food. Numerous studies have been conducted to construct a bionic surface for grasping tasks. This paper reviews the typical biomimetic structures and surfaces (wedge-shaped surface, suction cup surface and thorn claw surface) for grasping scenarios. Initially, progress in gecko-inspired wedge-shaped adhesive surfaces is reviewed, encompassing the underlying mechanisms that involve tuning the contact area and peeling behavior. The applications of grippers utilizing this adhesive technology are also discussed. Subsequently, the suction force mechanisms and applications of surfaces inspired by octopus and remora suction cups are outlined. Moreover, this paper introduces the applications of robots incorporating the principles of beetle-inspired and bird-inspired thorn claw structures. Lastly, inspired by remoras’ adhesive discs, a composite biomimetic adhesive surface is proposed. It integrates features from wedge-shaped, suction cup, and claw thorn surfaces, potentially surpassing the adaptability of basic bioinspired surfaces. This surface construction method offers a potential avenue to enhance adhesion capabilities with superior adaptability to surface roughness and curvature.
The Ease of Ignition of 13 Landscape Mulches

The ease of ignition of 13 commonly used landscape mulches was evaluated. Mulches have different ignition potentials based on several factors, including the length of exposure to heat and to the ignition source. Some materials ignited more frequently when exposed to a lit propane torch for 15 seconds. The most to least commonly ignited materials were ground rubber, pine straw, oat straw, shredded hardwood bark, shredded cypress bark, recycled pallets, 2.5 to 5 cm pine bark nuggets, 1.3 to 2.5 cm pine bark nuggets, shredded pine bark, cocoa shells, composted yard waste, bluegrass sod, and brick chips. Not all organic mulches readily ignited, nor were inorganic mulches uniformly ignition resistant. The results of this research show that there are definite differences in the ease of ignition between commonly used mulches. The results demonstrate that landscapers do not have to resort to using inorganic materials such as brick chips and gravel for ignition-resistant mulches. Under high-temperature ignition, one inorganic material, ground rubber was ignited consistently and was difficult to extinguish. Conversely, there are organic materials that are unlikely to ignite. These also are maintenance practices that will prevent or reduce ignition of these mulches.
Photometric sample of early B-type pulsators in eclipsing binaries observed with TESS

Asteroseismology coupled with eclipsing binary modelling shows great potential in improving the eﬃciency of measurements or calibrations of the interior mixing proﬁle in massive stars. This helps, for instance in treating the challenging and mysterious discrepancies between observations and models of its stellar structure and evolution. This paper discusses the ﬁndings in our work titled β Cephei pulsators in eclipsing binaries observed with TESS , which aimed to compile a comprehensive catalogue of β Cep pulsators in eclipsing binaries. Seventy-eight (78) pulsators of the β Cep type in eclipsing binaries among which 59 new discoveries were reported. Here, we also report a fresh analysis of eight additional stars that were outside the scope of the earlier-mentioned work. Six β Cep pulsators in eclipsing binaries are reported, among which 5 are new discoveries and 1 is a conﬁrmation of a candidate earlier suggested in the literature. Our sample allows for future ensemble asteroseismic modelling of massive pulsators in eclipsing binaries to treat the discrepancy between observations and models.