Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of alkaline mineral complex supplementation on production performance, serum variables, and liver transcriptome in calves

Calf diarrhea causes huge economic losses to livestock due to its high incidence and mortality rates. Alkaline mineral complex water is an alkaline solution containing silicon, sodium, potassium, zinc, and germanium, and has biological benefits and therapeutic effects. This study aimed to evaluate the impact of alkaline mineral complex water supplementation on the health of calves and to investigate the effect of Alkaline mineral complex water supplementation on neonatal calf serum variables and the liver transcriptome. Sixty Holstein calves (age 1.88 ± 0.85 days, weight 36.63 ± 3.34 kg) were selected and randomly divided into two groups: the T group (treatment group with alkaline mineral complex water supplemented during the experiment) and C group (control group without alkaline mineral complex water supplementation). Alkaline mineral complex water supplementation significantly increased the body weight for calves aged 60 d and average daily gain during the experimental period (1–60 d). In addition, Alkaline mineral complex water supplementation could significantly decrease the diarrhea rate for calves aged 16–30 d, enhance the T-AOC, IgG, IGF-1, and IGFBP-2 in concentrations. The results of KEGG enrichment analysis in transcriptomics indicate that Alkaline mineral complex water supplementation inhibited the target IL-1B gene of the NF-kappa B signaling pathway of liver. Alkaline mineral complex water supplementation decreased calf diarrhea and improved partial immune function, anti-inflammatory activity, antioxidant capacity, and health of calves. Alkaline mineral complex is a candidate to replace medicated feed additives. Alkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex water.
A Web-based Point of Sales for Automotive Component Industry using Rapid Application Development model

This research aims to increase efficiency in Micro, Small, and Medium Enterprises (MSMEs) in the automotive components industry, focusing on CV Bengkel Megamakmur. This workshop is one of the MSMEs engaged in Indonesia's car spare parts industry. In the ongoing business process, these MSMEs need some help in inventory management, stock of goods, and less integrated sales transaction recording. The main problem identified was the discrepancy between the number of products sold and sales transaction reports. A web-based Point of Sale (POS) application was implemented, which allows the integration of inventory data and sales transactions. The method used in this research is Rapid Application Development (RAD), suitable for projects with limited resources and short work schedules. This research results in a Point of Sale application that can optimize business processes for managing inventory by monitoring stock and recording sales transactions in an integrated manner. This application has been tested using the System Usability Scale (SUS) method and obtained an average score of 86.6, included in the "very good" category. The test results show that this application has good functionality and can optimize MSME business processes in the automotive components industry.
Vascular anastomosis device

Disclosed is a blood vessel side (the lateral part) readily anastomosed to the side of another vessel, to provide a novel vascular anastomosis device. A vascular anastomosis device of the present invention includes a pair of assembled members, and the protruding member, and the connecting member, and a semi-circular opening, with the use of the vascular anastomosis device of the present invention, a suture a simple treatment which does not use, the type connecting the general side surface and the side surface is very difficult in the field of anastomosis, it is possible to anastomose two vessels, whereby operation time is significantly reduced. Furthermore, since there is no need to fully open the surgical site, it is possible to relieve the patient's pain. FIELD 1A
Flood mapping through principal component analysis of multitemporal satellite imagery considering the alteration of water spectral properties due to turbidity conditions

ABSTRACT We propose a methodology for flood mapping by remote sensing considering the alteration of the spectral response of water due to turbidity conditions using principal component analysis (PCA) of multitemporal satellite imagery limited to the visible and the near IR region of the electromagnetic spectrum. Crosta technique is applied to the resulting load matrix to select the PCs of interest, and to interpret the nature of the changes. Finally, it is proposed the use of linear unmixing, using the selected PCs as input, to classify the categories required for flood mapping. The proposed methodology is applied to mapping the flood areas after the tropical storm Manuel during September 2013 in Acapulco, Mexico. The proposed procedure is a more robust alternative to quotients or index-orientated approaches based on fixed spectral response of the water, e.g. the Normalized Difference Water Index. This approach can be useful to authorities, civil protection and other organizations dedicated to risk management during natural contingences to assess quickly the dimension of affected areas, without the expensive and complicated mobilization of recourses to the site, and to give a more efficient response.
A protocol for a pooled analysis of cohort studies: The association between depression and anxiety in epileptic disorders

Background/Introduction Depressive and anxiety disorders constitute major mental health challenges affecting adults of all ages globally. It has been reported that individuals with depressive or anxiety disorders face an elevated risk of developing neurological conditions, including seizures and epilepsy. Additionally, people with these disorders tend to exhibit distinct clinical outcomes compared to the general population. However, the associations between depressive or anxiety disorders and epilepsy remain contentious. Thus, this study aims to elucidate the associations between these neuropsychiatric disorders, including depressive and anxiety disorders, and epilepsy or seizures. Methods We will systematically search three electronic databases—PubMed, EMBASE, and the Cochrane Library—from inception through March 2023 to identify relevant cohort studies investigating the associations between depressive or anxiety disorders and epilepsy or seizures. Two independent reviewers will extract data from eligible studies using pre-designed standardized data extraction forms, and cross-check results. A third author will resolve any discrepancies. Quality assessment will be performed using the Newcastle-Ottawa Quality Assessment Scale (NOS). Pooled risk estimates (Relative risks or hazard ratios with their 95% CI) will be calculated using the DerSimonian-Laird random-effects model. If between-study heterogeneity is identified, we will conduct subgroup analyses or meta-regressions to explore the possible sources of heterogeneity (participants, exposure, outcome, and study design) stratified by various study characteristics. Potential publication bias will be detected through the inspection of funnel plot asymmetry, complemented by the Egger linear regression approach (Egger’s test) and the Begg rank correlation test (Begg’s test). Discussion This pooled analysis will evaluate the association between depressive or anxiety disorders and epilepsy or seizures, providing high-level evidence to inform early identification and prevention strategies for epilepsy or seizures. Ethics and dissemination Given that the data utilized for analysis in this pooled analysis does not involve human subjects or medical records, no ethical approval is required for this study. We intend to present the results of this study at national or international conferences or submit the findings to a peer-reviewed journal. OSF registration number DOI 10.17605/OSF.IO/WM2X8
Development and Validation of the Sense of Online Community Scale

This study focused on the development and validation of the Sense of Online Community Scale (SOCS), which includes 28 Likert-type scale items across six subscales: (a) program community, (b) program academic activities, (c) program social activities, (d) institutional academic activities, (e) institutional social activities, and (f) affiliation. The validation process included an implementation with 293 learners enrolled in online programs at a higher education institution in the eastern United States. The model was evaluated with and without outliers, and results show that the model aligned well with the SOCS. The means of all items except one exceeded 3.5 on a 5.0 scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Time in an online program was not a statistically significant predictor of the validation model, though most of our participants were in the first or second year of their degree programs. Findings demonstrate that the SOCS is a reliable and valid instrument that other researchers may use to investigate community in online environments on both the program and the institutional level.
The Neural-SRP Method for Universal Robust Multi-Source Tracking

Neural networks have achieved state-of-the-art performance on the task of acoustic Direction-of-Arrival (DOA) estimation using microphone arrays. Neural models can be classified as end-to-end or hybrid, each class showing advantages and disadvantages. This work introduces Neural-SRP, an end-to-end neural network architecture for DOA estimation inspired by the classical Steered Response Power (SRP) method, which overcomes limitations of current neural models. We evaluate the architecture on multiple scenarios, namely, multi-source DOA tracking and single-source DOA tracking under the presence of directional and diffuse noise. The experiments demonstrate that our proposed method compares favourably in terms of computational and localization performance with established neural methods on various recorded and simulated benchmark datasets.
How does the digital economy empower corporate ESG? Evidence from China

Based on the realistic background of corporate digitalization and green development, this paper explored how the digital economy can empower corporate Environmental, Social, and Corporate Governance (ESG). Taking A-share listed companies from 2011 to 2021 as a research sample, this paper used methods such as mediation effect analysis, moderating effect analysis, and endogenous testing. This paper found that the digital economy could drive the improvement of corporate ESG performance significantly, especially for the environmental and social aspects. The improvement effect is more obvious for companies with heavily pollution and green financial environments. The results of the mechanism showed that the empowerment of the digital economy to corporate ESG could be achieved through two paths: Easing financing constraints and promoting green economic development. The results showed that the digital economy could achieve deep integration with corporate environmental governance, social responsibility, and internal governance. Moreover, the digital economy could improve the level of corporate ESG through policy support and have inspirational meaning for the empowerment of the digital economy to corporate ESG.
Perceived impact of digital health technology on health professionals and their work: A qualitative study in Southern Ghana

Background Digital health technology (DHT) has become an essential part of an effective and efficient healthcare information system. Although DHT promises great potential it does not always meet the expectation of users. Often, in low- and middle-income countries (LMICs), the implemented DHT does not function as intended and impacts negatively on health professionals and their work. Therefore, this study explored the views of participants about the impact of DHTs on the work of health professionals after it has been introduced in Ghana. Methodology The study used a qualitative research approach where in-depth interviews (IDIs) were conducted with study participants across three health facilities in Ghana. A purposive sampling technique was used to select participants. All interviews were audio recorded, transcribed, and coded into themes using QSR Nvivo 12 software before thematic content analysis. Results Our findings revealed that DHT reduced the workload on the healthcare providers and also ensures continuity of care. Participants perceived that DHT was fast, and ensures quality and accurate information, which could be easily accessed by health professionals for better decision making. However, poor internet connectivity and erratic power supplies were reported as the main impediments causing delays and frustrations to the staff at the study health facilities. Conclusion The study found that DHT has a positive effect on the work of health professionals. However, poor internet connectivity and unstable power supply caused delays in the provision of care and disruptions in the work process affecting the smooth operation of the DHT and threatening to erode the potential benefits to the health system and users.
Persistence of Cryptosporidium parvum in bovine feces during summer and winter exposure

iii! PREFACE . iv! TABLE OF CONTENTS . vi! LIST OF TABLES . ix! LIST OF FIGURES . x! GLOSSARY OF ABBREVIATIONS . xiii! ACKNOWLEDGEMENTS . xiv! CHAPTER
Seasonal variation of organic carbon fluxes in the Yangtze River and influence of Three-Gorges engineering

The water samples of the surface layer sampled in the lower Yangtze River from June 2003 to July 2005 were used for determination of dissolved organic carbon (DOC) and particulate organic carbon (POC). The concentrations of DOC and POC during the observation were 1.59±0.21 and 0.91±0.42mg/L, respectively, in which DOC in dry season was higher than that in flood; while POC showed the opposite tendency. POC concentration and total suspended matter (TSM) in waters had marked positive correlationship, the POC% in TSM decreased with the increasing of TSM concentration. The DOC fluxes of Yangtze River in 2003, 2004 years were 1.32×106t and 1.20×106t respectively, the POC fluxes were 2.69×106t and 1.63×106t, and about 76% of the total organic carbon was transported into sea in flood season with its composition being mainly particular phase. In 2003~2004 years POC fluxes decreased rapidly. The ratio value of DOC and POC fluxes increased rapidly, related possibly with retaining, reforming and eutrophication.
VANISHING POINT AIDED LANE DETECTION USING A MULTI-SENSOR SYSTEM

Abstract. Lane Detection is a critical component of an autonomous driving system that can be integrated alongside with High-definition (HD) map to improve accuracy and reliability of the system. Typically, lane detection is achieved using computer vision algorithms such as edge detection and Hough transform, deep learning-based algorithms, or motion-based algorithms to detect and track the lanes on the road. However, these approaches can contain incorrectly detected line segments with outliers. To address these issues, we proposed a vanishing point aided lane detection method that utilizes both camera and LiDAR sensors, and then employs a RANSAC-based post-processing method to remove potential outliers to improve the accuracy of the detected lanes. We evaluated this method on four datasets provided from the KITTI Benchmark Suite and achieved a total precision of 87%.
Exploring Types of Multi-Focus Image Fusion

- This paper explains methods. Fusion of multiple-focus images can actually take care of the profundity of field issue in optical focal point regions, the blurred picture appears strange due to the high frequency degradation Information. Most often, the camera is to blame for this. The absence of a deep field is caused by optics in the cameras. The picture becomes sharper as a result. Only in particular locations for a comprehensive focal length image, Fusion of multiple-focus images primary objective is to solve a problem with depth of field cameras. By blending at least two to some degree centred pictures into a solitary totally centred picture, Combination of various centre pictures can tackle the optical focal point's profundity of field issue.
Layout-Aware Area Optimization of Transposable STT-MRAM for a Processing-In-Memory System

This article presents a layout-aware area optimization methodology for transposable spin-transfer torque magnetic random access memory (STT-MRAM). Although transposable STT-MRAM achieves high performance in processing-in-memory (PIM) systems for a spiking neural network (SNN), challenges in layout design and optimization remain owing to the vertical arrangement of its two wordlines (WLs). We propose three different layout design techniques to address these challenges. We also analyze the cell area changes of our proposed layout design according to the width of two access transistors. The proposed layout designs for transposable STT-MRAM are implemented in a 28-nm CMOS technology coupled with a SPICE-compatible model for a magnetic tunnel junction. Results show that in the metal pitch limited region, our proposed perpendicular poly with metal column-WL-based layout design achieves minimum cell area, with at least 5.3% area savings in comparison with other proposed layout designs. Furthermore, by targeting an identical design specification of 35% write margin (WM) and 160% cell tunnel magnetoresistance, the resulting cell area falls in the transistor width-limited region. In this case, our proposed parallel poly with metal-WL-based layout design achieves at least 21% area savings compared with the other proposed layout designs. This result demonstrates that our proposed layout design and analysis offer valuable insights for circuit designers in selecting the optimal design that meets target specifications and requirements.
Snake: A Variable-length Chain-based Prefetching for GPUs

Graphics Processing Units (GPUs) utilize memory hierarchy and Thread-Level Parallelism (TLP) to tolerate off-chip memory latency, which is a significant bottleneck for memory-bound applications. However, parallel threads generate a large number of memory requests, which increases the average memory latency and degrades cache performance due to high contention. Prefetching is an effective technique to reduce memory access latency, and prior research shows the positive impact of stride-based prefetching on GPU performance. However, existing prefetching methods only rely on fixed strides. To address this limitation, this paper proposes a new prefetching technique, Snake, which is built upon chains of variable strides, using throttling and memory decoupling strategies. Snake achieves 80% coverage and 75% accuracy in prefetching demand memory requests, resulting in a 17% improvement in total GPU performance and energy consumption for memory-bound General-Purpose Graphics Processing Unit (GPGPU) applications.
Photon: A Fine-grained Sampled Simulation Methodology for GPU Workloads

GPUs, due to their massively-parallel computing architectures, provide high performance for data-parallel applications. However, existing GPU simulators are too slow to enable architects to quickly evaluate their hardware designs and software analysis studies. Sampled simulation methodologies are one common way to speed up CPU simulation. However, GPUs apply drastically different execution models that challenge the sampled simulation methods designed for CPU simulations. Recent GPU sampled simulation methodologies do not fully take advantage of the GPU’s special architecture features, such as limited types of basic blocks or warps. Moreover, these methods depend on up-front analysis via profiling tools or functional simulation, making them difficult to use.To address this, we extensively studied the execution patterns of a variety of GPU workloads and propose Photon, a sampled simulation methodology tailored to GPUs. Photon incorporates methodologies that automatically consider different levels of GPU execution, such as kernels, warps, and basic blocks. Photon does not require up-front profiling of GPU workloads and utilizes a lightweight online analysis method based on the identification of highly repetitive software behavior. We evaluate Photon using a variety of GPU workloads, including real-world applications like VGG and ResNet. The final result shows that Photon reduces the simulation time needed to perform one inference of ResNet-152 with batch size 1 from 7.05 days to just 1.7 hours with a low sampling error of 10.7%. CCS CONCEPTS• Computing methodologies → Modeling and simulation; Graphics processors; Cluster analysis.
Drug-specific risk of tuberculosis in patients with rheumatoid arthritis treated with anti-TNF therapy: results from the British Society for Rheumatology Biologics Register (BSRBR)

Background The risk of tuberculosis (TB) in patients with rheumatoid arthritis (RA) is thought to be increased following anti-tumour necrosis factor (anti-TNF) therapy, with a proposed differential risk between the anti-TNF drugs etanercept (ETA), infliximab (INF) and adalimumab (ADA). Objective To compare directly the risk between drugs, to explore time to event, site of infection and the role of ethnicity. Methods Data from the British Society for Rheumatology Biologics Register (BSRBR), a national prospective observational study, were used to compare TB rates in 10 712 anti-TNF treated patients (3913 ETA, 3295 INF, 3504 ADA) and 3232 patients with active RA treated with traditional disease-modifying antirheumatic drugs. Results To April 2008, 40 cases of TB were reported, all in the anti-TNF cohort. The rate of TB was higher for the monoclonal antibodies ADA (144 events/100 000 person-years) and INF (136/100 000 person-years) than for ETA (39/100 000 person-years). After adjustment, the incidence rate ratio compared with ETA-treated patients was 3.1 (95% CI 1.0 to 9.5) for INF and 4.2 (1.4 to 12.4) for ADA. The median time to event was lowest for INF (5.5 months) compared with ETA (13.4 months) and ADA (18.5 months). 13/40 cases occurred after stopping treatment. 25/40 (62%) cases were extrapulmonary, of which 11 were disseminated. Patients of non-white ethnicity had a sixfold increased risk of TB compared with white patients treated with anti-TNF therapy. Conclusion The rate of TB in patients with RA treated with anti-TNF therapy was three- to fourfold higher in patients receiving INF and ADA than in those receiving ETA.