Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of rare earth-chitosan chelate on growth performance, antioxidative and immune function in broilers

Abstract This research aims to study the effects of rare earth-chitosan chelates (RECC) on growth performance, immunity and antioxidant function in broilers. A total of 192 one-day-old mixed-sex Arbour Acres (AA) broilers were allotted into 4 treatment groups with 6 replicates per treatment and 8 broilers per pen. Broilers were fed the basal diet supplemented with, respectively, 0 (control group), 150, 200 and 250 mg/kg RECC for 42 d. The results showed that dietary RECC improved average daily gain and decreased feed/gain (p < .05). Broilers fed with appropriate dose of RECC increased total antioxidant capacity (T-AOC) in serum (d 42) and liver (d 21). And the activity of glutathione peroxidase (GSH-Px), catalase (CAT) and superoxide dismutase (SOD) were increased, whereas malonaldehyde (MDA) concentration was decreased on d 42 in liver of broilers (p < .05) by enhancing the related gene expression in nuclear factor erythroid 2-related factor 2 (Nrf2) pathway. In addition, supplementing appropriate dose of RECC in diet increased the concentrations of interleukin 2 (IL-2), IL-4 in serum and jejunum (d 42). And the concentrations of immunoglobulin M (IgM) (d 21), and secretory immunoglobulin A (sIgA), IgG (d 42) (p < .05) in jejunum were elevated by decreased the related gene expression in Toll-like receptor 4/nuclear factor kappa-B (TLR4/NF-κB) pathway. In conclusion, RECC could exert beneficial effects on growth performance, immune function and antioxidant capacity of broilers, and the optimal supplemental dose for broiler production is 175 − 200 mg/kg. HIGHLIGHTS This paper was very important in revealing the action mechanism of rare earth-chitosan chelate on immune function and antioxidant capacity of animals. The results of this study will provide a theoretical basis for further developing rare earth-chitosan chelate as antibiotic alternatives. The optimal dose range of rare earth-chitosan chelate in diet of broilers was 175–200 mg/kg.
SOIL ORGANIC CARBON DATING OF PALEOSOILS OF ALLUVIAL FANS IN A BLOWN SAND AREA (NYÍRSÉG, HUNGARY)

ABSTRACT The most widely used dating techniques in quaternary research are the radiocarbon (14C) and optically stimulated luminescence (OSL) dating methods. In some environments, the investigated sediments do not contain enough material for 14C dating. In these cases, 14C dating of bulk sediment may be used as a last resort. The major aim of the present study was to determine the reliability and limitations of the different fractions of the soil organic carbon (SOC) 14C ages in the Nyírség blown-sand study area, in Hungary. Therefore, the low- and high-temperature combustions of SOC (LT-SOC and HT-SOC) 14C age of fossil soils were compared with the charcoal ages from the same fossil soil layer, and their (LT-SOC, HT-SOC, and charcoal) age reliability was verified independently by applying OSL to the quartz fraction of the sediment samples. The 14C data show variable agreement with OSL ages. Charcoal fragments were collected from some of the best material for 14C dating and their ages are in agreement with the LT and HT-SOC 14C ages and OSL data. The 14C age LT-SOC gives a reliable, credible ages, which were confirmed by independent OSL measurements. If buried soils do not contain any other macroscopic remnants for 14C dating, the LT-SOC 14C ages can be used, in the case of the Nyírség study area. The LT-SOC, which is the younger fraction of the soil organic carbon, may be considered to represent the burial time of the fossil soil layer. The HT-SOC 14C ages are sometimes unrealistically older than expected and cannot be considered to be reliable.
Impacts of factors affecting the business efficiency of seafood companies listed on the stock market of Vietnam

This study aims to examine the factors affecting the business efficiency of companies in the seafood industry listed on the Vietnamese stock market. The article analyzes the data collected from the financial statements of 20 listed seafood companies operating in Vietnam from 2016 to 2020. The study uses EViews software in quantitative analysis to build a panel data regression model to determine the relationship and level of impact of internal factors on the business performance of seafood companies. Business efficiency is measured by return on assets (ROA), return on equity. The research results show that the factors affecting the business efficiency of listed seafood companies include: capital structure, firm size, growth rate of assets, solvency.
ECOLOGICAL RELEASE ANALYZED AMONG INDIVIDUALS, ACROSS TWO GENERATIONS, AND ALONG MULTIPLE NICHE AXES IN ANOLIS CAROLINENSIS

Abstract. A population freed from a constraining interspecific interaction (e.g., competition or predation) may experience niche shifts and expansions. This phenomenon, termed ecological release, is an eco-evolutionary process driven by individual behaviors and interindividual interactions. However, empirical studies of these interactions seldom observe them directly, instead inferring process from pattern. Here, we set up experimental conditions for ecological release of the lizard Anolis carolinensis (green anole) from constraining interactions with its congener, Anolis sagrei (brown anole), by constituting populations of lizards on small islands. We monitored individual and population habitat use along three niche axes (perch height, perch diameter, and lateral movement between perches) on one experimental (one-species) and one control (two-species) island, for three time periods: 1) preremoval, when both islands had both species; 2) postremoval, shortly after A. sagrei were cleared from the experimental island; and 3) delayed postremoval, 7 months later, when long-lived lizards were joined by a second generation born in the intervening months. We found that green anole perch height decreased on the one-species island and increased on the two-species island. These shifts did not occur during postremoval but were evident by delayed postremoval, when both generations on the one-species island were perching nearly 130 cm lower than their counterparts on the two-species island. We also documented correlated changes in perch diameter at both the individual and population level but no changes in the extent of individuals' lateral movement. Lastly, changes in population-level niche width (i.e., perch height and diameter variances) occurred without detectable changes in niche overlap among individuals. Our results demonstrate that that the dynamics of ecological release in nature need not be inferred, because experiments can observe them directly in individuals, across generations, and along multiple niche axes.
Refined Capsid Structure of Human Adenovirus D26 at 3.4 Å Resolution

Various adenoviruses are being used as viral vectors for the generation of vaccines against chronic and emerging diseases (e.g., AIDS, COVID-19). Here, we report the improved capsid structure for one of these vectors, human adenovirus D26 (HAdV-D26), at 3.4 Å resolution, by reprocessing the previous cryo-electron microscopy dataset and obtaining a refined model. In addition to overall improvements in the model, the highlights of the structure include (1) locating a segment of the processed peptide of VIII that was previously believed to be released from the mature virions, (2) reorientation of the helical appendage domain (APD) of IIIa situated underneath the vertex region relative to its counterpart observed in the cleavage defective (ts1) mutant of HAdV-C5 that resulted in the loss of interactions between the APD and hexon bases, and (3) the revised conformation of the cleaved N-terminal segments of pre-protein VI (pVIn), located in the hexon cavities, is highly conserved, with notable stacking interactions between the conserved His13 and Phe18 residues. Taken together, the improved model of HAdV-D26 capsid provides a better understanding of protein–protein interactions in HAdV capsids and facilitates the efforts to modify and/or design adenoviral vectors with altered properties. Last but not least, we provide some insights into clotting factors (e.g., FX and PF4) binding to AdV vectors.
Structural Models of Customer Loyalty on Star Hotel in Medan, Indonesia

This study aims to analyze directly and indirectly the service quality and hotel image on consumer satisfaction and customer loyalty. The location of this study is in several star hotels in Medan such as Graha Serela, Santika Premier Dyandra, Polonia, Grand Swiss-Bell, JW Marriot, Garuda Plaza, and Grand Aston City Hall Hotel. Populations in this study are guests who staying at a Starred Hotel in Medan in 2019, while the sample is determined as many as 215 consumers (hotel guests). Data answering techniques used are interviews, questionnaires and documentation studies. The data analysis method used in this study is Structural Equation Modelling (SEM). The results of research show directly, the quality of service provided to Consumer Satisfaction, Service Quality affect on Customer Loyalty, Hotel Image against Consumer Satisfaction, Hotel Image affect Customer Loyalty and Consumer Satisfaction against Customer Loyalty. Directly, the service quality and hotel image of customer loyalty through customer satisfaction.
THE QUALITY OF LIFE OF PATIENTS AFTER LIVER TRANSPLANTATION

Aim: With increased survival rates after liver transplantation (LT), studies have focused on improving the quality of life in these patients. The purpose of this study is to assess the quality of life levels of recipients after LT. Materials and Methods: This descriptive study was conducted with 103 voluntary patients between January 01-May 15, 2015. The sample of the study consisted of the patients who had liver transplantation and met the inclusion criteria. The data were collected using personal and disease information form and SF-36 health survey. Results: It was found in the study that the mean score of the Physical Component Summary (PCS) was 39.90±8.53 and the mean score of the Mental Component Summary (MCS) was 43.93±9.86. The patients who underwent LT had a moderate quality of life. The MCS score enhanced with increasing level of education. The PCS score is higher in those with men, single patients, cadavers as the source of transplantation, and those without a prolonging post-operative hospitalisation. Another finding of the study indicated that PCS score enhanced as the time elapsed after transplantation increased. In addition, patients with chronic diseases had lower physical health quality of life. Conclusion: Although many complications develop in most of the patients, LT can make the patient more functional in many areas of life compared to their pre-transplantation life. The patients should be referred to other departments regularly to keep chronic diseases under control.
An Analysis of the Willingness to the COVID-19 Vaccine Booster Shots among Urban Employees: Evidence from a Megacity H in Eastern China

Many studies have shown that urban workers may have a higher acceptance rate of coronavirus disease (COVID-19) vaccine uptake compared to their rural counterparts. As Omicron spreads globally, the COVID-19 booster vaccination has been acknowledged as the primary strategy against this variant. In this study, we identify factors related to the willingness of workers in megacities to take the vaccine booster shots and their main reasons accounting for their booster willingness. This research survey was conducted in megacity H in eastern China, and a total of 1227 employees from different industries were interviewed. The study at hand examines the relationship between various characteristics (including both economic and non-economic factors) of urban employees and their intention/desire to accept the COVID-19 booster shoots. The survey results show that some characteristics, namely work organization, vaccine knowledge, and social network, affect their intention to take COVID-19 vaccine booster shots. Urban employees with a strong work organization, a high degree of vaccine knowledge, and a dense social capital are more likely to receive booster injections than other employees. Therefore, work organization, vaccine knowledge, and social networks provide fundamental entry points for designing enhanced injection strategies to increase the acceptance of COVID-19 vaccines among employees in megacities.
Quantity of Acellular Dermal Matrix in Immediate Breast Reconstruction and Outcomes

Purpose This study aimed to determine the impact of the quantity of acellular dermal matrix (ADM), “ADM burden,” used in implant-based breast reconstruction on infection, drain duration, and seroma formation. Methods A single-institution, retrospective review from 2015 to 2020 was conducted for patients who underwent immediate, implant-based breast reconstruction after mastectomy. Three cohorts were generated based on the amount of ADM used: (1) total ADM, (2) sling ADM, and (3) no ADM. Results In total, there were 374 patients who satisfied the inclusion criteria yielding 641 breasts with 143, 432, and 66 breasts in the total ADM, sling ADM, and no-ADM groups, respectively. The no-ADM group had higher mastectomy weights (788.4 g) than the sling (654.2 g) and total ADM (503.4 g) groups (F = 10.8, P < 0.001). Total ADM had higher rates of explantation secondary to infection compared with no ADM (P < 0.001). Linear regression analysis for drain duration was significant for body mass index (P < 0.0001) but not for ADM quantity (P = 0.52). Logistic regression analysis demonstrated a higher risk of infection in the total ADM group (odds ratio [OR], 5.4; P < 0.0001). Diabetes mellitus was a risk factor for both infection (OR, 3.6; P = 0.05) and seroma formation (OR, 0.04; P = 0.04). Conclusions Higher ADM burden is associated with an increased risk of infections and device explantation secondary to those infections. Although ADM has created new avenues in breast reconstruction, these findings indicate a need to evolve the technique to minimize the ADM burden. By doing so, patients can minimize their risk of postoperative complications while reducing the financial impact on institutions.
Geopolitical Risk as a Determinant of Renewable Energy Investments

The advent of various initiatives around the globe in shaping an energy transition towards a “greener” energy production future sparked a research interest towards the determinants that will shape their success. In this paper, we depart from the relevant literature evaluating the potential effect of geopolitical tensions on renewable energy investments, building on an explicit quantitative approach that provides clear empirical evidence. In doing so, we compile a large panel of 171 economies and measure the effect of geopolitical risk on “green” investing as measured by popular geopolitical risk indices, while controlling for all major variables proposed by literature. Our flexible Autoregressive Distributed Lag model with heterogenous effects across economies suggests that geopolitical risk has a significantly measurable effect on green investments both in the short and the long run. In fact, our results suggest that proper model specification is robust across alternate risk assessments. Overall, our study has direct policy implications suggesting that renewable energy could be an important part of our energy mix only if we take into account its linkages with geopolitical tensions.
Opportunities and Barriers for Truck Platooning on Norwegian Rural Freight Routes

Truck platooning can potentially make road freight transportation safer and greener. Technological readiness, business opportunities, and acceptance of truck platooning have mainly been studied for multilane highways with ample truck volumes. Less is known about truck platooning in areas with low traffic volumes and challenging roads and weather conditions. This paper investigates the opportunities and barriers for truck platooning on Norwegian rural freight routes, through stakeholder interviews and realistic case examples. Given modest freight volumes, dispersed industry clusters, and challenging road conditions, this study identified several prerequisites to deploying platooning and achieving economic savings. The paper discusses the future steps required to organize platooning across carriers, ensure appropriate infrastructure, and gain acceptance among truck drivers, motorists, and other road users.
Whole-leg chemical-shift encoded MRI analysis reveals differential subcutaneous adipose tissue accumulation in lipedema

Lipedema is a painful connective tissue disease involving excessive subcutaneous adipose tissue (SAT) accumulation in the lower extremities. Lipedema remains poorly recognized as a unique clinical entity and is often misdiagnosed as obesity. Whole-body magnetic resonance imaging (MRI) acquisitions could provide insight into the unique body composition of lipedema, yet methodologies for multi-slice analyses are lacking. In this work, a semi-automated processing workflow was developed to segment and quantify adiposity from whole-leg chemical-shift encoded (CSE) MRI to distinguish lipedema. Patients with lipedema (N=15) and controls (N=13) matched for age and body mass index underwent a CSE MRI exam in eight stacks from the head-to-ankles. Slices from thighs-to-ankles were segmented via Chan-Vese segmentation, clustering, and morphological techniques to separate SAT and skeletal muscle. SAT and muscle volume per slice and the SAT-to-muscle volume ratio were recorded in decades of slices and compared between groups using Mann-Whitney U test with two-sided significance criteria p<0.05. SAT volume was significantly elevated in participants with lipedema in all decades (p<0.001), while muscle volume was not significantly different. SAT-to-muscle volume ratio was elevated in lipedema compared to controls (p<0.001), with the greatest effect size (rrb = 0.74) observed in the eighth decade corresponding to the mid-thigh region. These findings reveal SAT distribution is uniquely elevated throughout the legs of participants with lipedema as discerned from whole-leg CSE MRI. CSE MRI and analysis methods developed herein for SAT quantification could inform the diagnosis of lipedema, which suffers from few objective strategies to differentiate the disease from obesity.
Flexural properties of visually graded southern pine 2×4 and 2×6 structural lumber

Flexural properties of visually graded southern pine structural lumber were evaluated. Several grade controlling characteristics were considered relative to bending properties and compared with current design values. A total of 751 southern pine lumber specimens were obtained from a broad spectrum of regions in the southeastern United States. Visually graded No. 2, nominally two inch thick specimens, in four and six inch widths, were obtained from commercial sawmills. All specimens were evaluated by a certified grader in the laboratory. Actual dimensions, weight, and moisture content (MC) were measured. Growth and manufacturing related characteristics were identified and classified into two categories: strength reducing characteristics (SRC) and grade reducing characteristics (GRC). Specific gravity (SG), bending modulus of elasticity (MOE), and modulus of rupture (MOR), were determined for each specimen. The presence of knots was identified as the most significant SRC; their presence had the most significant impact on SG, MOE and MOR. For GRC, specimens with knots, warp and specimens that fell into the category none, were significantly lower in SG, MOE and MOR. MOE and the allowable design bending strength values yielded in this study met the current design value criteria for both widths tested.
Smart Home’s Energy Management Through a Clustering-Based Reinforcement Learning Approach

Smart homes that contain renewable energy sources, storage systems, and controllable loads will be key components of the future smart grid. In this article, we develop a reinforcement-learning (RL)-based scheme for the real-time energy management of a smart home that contains a photovoltaic system, a storage device, and a heating, ventilation, and air conditioning (HVAC) system. The objective of the proposed scheme is to minimize the smart home’s electricity cost and the residents’ thermal discomfort by appropriately scheduling the storage device and the HVAC system on a daily basis. The problem is formulated as a Markov decision process, which is solved using the deep deterministic policy gradient (DDPG) algorithm. The main contribution of our study compared to the existing literature on RL-based energy management is the development of a clustering process that partitions the training data set into more homogeneous training subsets. Different DDPG agents are trained based on the data included in the derived subsets, while in real time, the test days are assigned to the appropriate agent, which is able to achieve more efficient energy schedules when compared to a single DDPG agent that is trained based on a unified training data set.
Transfer learning based fully automated kidney segmentation on MR images

Multi-parametric magnetic resonance imaging (mp-MRI) is a promising tool for diagnosis of renal masses and may outperform computed tomography (CT) to differentiate between benign and malignant renal masses due to superior soft tissue contrast. Deep learning (DL)-based methods for kidney segmentation are under-explored in mp-MRI which consists of several pulse sequences, including primarily T2-weighted (T2W) and contrast-enhanced (CE) images. Multi-parametric MRI images have domain shift due to differences in acquisition systems and image protocols, leading to lack of generalizability of methods for image segmentation. To perform similar automated kidney segmentation on another mp- MRI sequence, the model needs a large dataset with manual segmentations to train a model from scratch, which is labor intensive and time consuming. In this paper, we first trained a DL-based method using 108 cases of labeled data to contour kidneys using T1 weighted-Nephrographic Phase CE-MRI (T1W-NG). We then applied a transfer learning approach to other mp-MRI images using pre-trained weights from the source domain, thus eliminating the need for large manually annotated datasets in target domain. The fully automated 2D U-Net for kidney segmentation in source domain containing total 108 3D images of T1W-NG, yielded Dice-similarity coefficient (DSC) of 0.91 ± 0.07 on test cases. The transfer learning of pretrained weights of T1W-NG model on the smaller target domain T2W dataset containing total 50 3D images for automated kidney segmentation generated DSC of 0.90 ± 0.06 (p<0.05), which was an improvement of 3.43% in DSC by compared to the without transfer learning approach (T2W-UNet model).