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African swine fever (ASF) is a highly contagious and severe hemorrhagic transboundary swine viral disease with up to a 100% mortality rate, which leads to a tremendous socio-economic loss worldwide. The lack of safe and efficacious ASF vaccines is the greatest challenge in the prevention and control of ASF. In this study, we generated a safe and effective live-attenuated virus (LAV) vaccine candidate VNUA-ASFV-LAVL3 by serially passaging a virulent genotype II strain (VNUA-ASFV-L2) in an immortalized porcine alveolar macrophage cell line (3D4/21, 50 passages). VNUA-ASFV-LAVL3 lost its hemadsorption ability but maintained comparable growth kinetics in 3D4/21 cells to that of the parental strain. Notably, it exhibited significant attenuation of virulence in pigs across different doses (103, 104, and 105 TCID50). All vaccinated pigs remained healthy with no clinical signs of African swine fever virus (ASFV) infection throughout the 28-day observation period of immunization. VNUA-ASFV-LAVL3 was efficiently cleared from the blood at 14–17 days post-infection, even at the highest dose (105 TCID50). Importantly, the attenuation observed in vivo did not compromise the ability of VNUA-ASFV-LAVL3 to induce protective immunity. Vaccination with VNUA-ASFV-LAVL3 elicited robust humoral and cellular immune responses in pigs, achieving 100% protection against a lethal wild-type ASFV (genotype II) challenge at all tested doses (103, 104, and 105 TCID50). Furthermore, a single vaccination (104 TCID50) provided protection for up to 2 months. These findings suggest that VNUA-ASFV-LAVL3 can be utilized as a promising safe and efficacious LAV candidate against the contemporary pandemic genotype II ASFV. [ABSTRACT FROM AUTHOR]

Accurate seismic ground response analysis is crucial for the design and safety of civil infrastructure and establishing effective mitigation measures against seismic risks and hazards. This is a complex process due to the nonlinear soil properties and complicated underground geometries. As a simplified approach, the one-dimensional wave propagation model, which assumes that seismic waves travel vertically through a horizontally layered medium, is widely adopted for its reasonable performance in many practical applications. This study explores the potential of sequence deep learning models, specifically 1D convolutional neural networks (1D-CNNs), long short-term memory (LSTM) networks, and transformers, as an alternative for seismic ground response modeling. Utilizing ground motion data from the Kiban Kyoshin Network (KiK-net), we train these models to predict ground surface acceleration response spectra based on bedrock motions. The performance of the data-driven models is compared with the conventional equivalent-linear analysis model, SHAKE2000. The results demonstrate that the deep learning models outperform the physics-based model across various sites, with the transformer model exhibiting the smallest average prediction error due to its ability to capture long-range dependencies. The 1D-CNN model also shows a promising performance, albeit with occasional higher errors than the other models. All the data-driven models exhibit efficient computation times of less than 0.4 s for estimation. These findings highlight the potential of sequence deep learning approaches for seismic ground response modeling. [ABSTRACT FROM AUTHOR]

The relationship between DM yield/cutting and the fermentable organic matter (FOM) content of tropical grasses was appropriately investigated to re-assess optimal grass maturity to feed dairy cattle. Nine different grass species belonging to the genera Brachiaria spp. (Mulato II, Ruzi), Panicum spp. (Guinea, Hamil, Mombasa, TD58), and Pennisetum spp. (King, Napier, VA06) were chemically analysed and subjected to an in vitro gas production (IVGP) test. For 72 h, gas production (GP) was continuously recorded with fully automated equipment. A triphasic, nonlinear, regression procedure was applied to analyse GP profiles. Across all the grasses, it was found that the neutral detergent fibre (NDF) contents increased with increasing maturity of the grass while the CP contents decreased with increasing NDF contents. In all nine grasses, digestible organic matter (dOM) was significantly affected by the week of cutting but IVGP was similar between the weeks of cutting in Ruzi, Hamil, Mombasa, and Napier grasses. Except for Guinea grass, the lowest dOM values were found when the grasses were cut after ≥5 weeks of regrowth. Harvesting grass one or two weeks earlier than the normal cutting time is a practically relevant intervention in increasing forage quality and productivity of dOM and fermentation potential. [ABSTRACT FROM AUTHOR]

This research presents an innovative solution aimed at addressing the cost and accessibility challenges associated with soil stiffness analysis in construction projects. Traditional lightweight deflectometer (LWD) systems have limitations due to their high cost and proprietary nature, prompting the need for a more widely accessible technology. To fulfill this purpose, a low-cost, open-source LWD onboard sensor signal interpretation system, utilizing Electro-Mechanical and Micro-Electro-Mechanical-System (MEMS) technology-based sensors in conjunction with an Arduino® Uno and ADS1262 Breakout Board, has been developed. This system efficiently processes raw signal data into deflection and force units, enabling precise soil property analysis. Thorough enhancements, calibration, and alignment procedures have been applied and validated through field tests, which have produced highly satisfactory results. By significantly reducing costs while maintaining accuracy, this developed system has the potential to popularize quality control and assurance practices in the construction industry. This open-source approach not only enhances affordability but also broadens accessibility, making soil property analysis more efficient and attainable for a wider range of construction projects. [ABSTRACT FROM AUTHOR]

Online consumer reviews (OCRs) significantly influence consumer purchase decisions for new products. Therefore, today's companies actively seek practical approaches for analyzing these OCRs. This study proposes a comprehensive method for OCR analysis using topic modeling and association rule analysis to overcome the current limitations in topic interpretation and topic overlap in text mining. Meanwhile, to examine the development of the high-tech industry and customer interest in the pet care field, this study synthesizes and analyzes reviews from consumers who are using healthcare products in the pet industry. To this end, we first collected 20,820 customer reviews from Amazon.com (accessed on 2 August 2023) for high-tech pet products and categorized them into three distinct product categories. Topic modeling was then conducted on each category, revealing five key topics per category. Subsequently, association rules analysis was performed on the customer reviews associated with the most representative topic. As a result, we were able to demonstrate that 'satisfaction' emerged as the most crucial topic across all three categories of high-tech pet products. Satisfaction is a topic expressing consumers' attitudes after experiencing the product, and they used words to describe their feelings in the product reviews. A diverse range of associated terms was also identified that represented the essence of each product's corresponding representative explanations. By leveraging these approaches, we are confident that pet product companies and market players will gain valuable insights into consumer preferences and behavior. [ABSTRACT FROM AUTHOR]

The transplantation of mesenchymal stem cell (MSC) sheets derived from human umbilical cords (hUCs) was investigated in this study as a potential application in treating myocardial infarction (MI). Two groups of hUC-MSC sheets were formed by populating LunaGelTM, which are 3D scaffolds of photo-crosslinkable gelatin-based hydrogel with two different cell densities. An MI model was created by ligating the left anterior descending coronary artery of healthy BALB/c mice. After two weeks, the cell sheets were applied directly to the MI area and the efficacy of the treatment was evaluated over the next two weeks by monitoring the mice's weight, evaluating the left ventricle ejection fraction, and assessing the histology of the heart tissue at the end of the experiment. Higher cell density showed significantly greater efficiency in MI mice treatment in terms of weight gain and the recovery of ejection fraction. The heart tissue of the groups receiving cell sheets showed human-CD44-positive staining and reduced fibrosis and apoptosis. In conclusion, the hUC-MSC sheets ameliorated heart MI injury in mice and the efficacy of the cell sheets improved as the number of cells increased. [ABSTRACT FROM AUTHOR]

In entrepreneurship management, the evaluation and selection of startups for acceleration programs, especially technology-based startups, are crucial. This process involves considering numerical and qualitative criteria such as sales, prior startup experience, demand validation, and product maturity. To effectively rank startups based on the varying importance of these criteria, a fuzzy multi-criteria decision-making (MCDM) approach is needed. Although MCDM methods have been successful in handling complex problems, their application in startup selection and evaluating criteria interrelationships from the accelerator perspective is underexplored. To address this gap, a hybrid DEMATEL-ANP-based fuzzy PROMETHEE II model is proposed in this study, facilitating startup ranking and examining interrelationships among factors. The resulting preference values are fuzzy numbers, necessitating a fuzzy ranking method for decision-making. An extension of ranking fuzzy numbers using a spread area-based relative maximizing and minimizing set is suggested to enhance the flexibility of existing ranking MCDM methods. Algorithms, formulas, and a comparative analysis validate the proposed method, while a numerical experiment verifies the viability of the hybrid model. The final ranking of four startup projects is A 4 < A 1 < A 3 < A 2 which indicates that startup project A2 has the highest comprehensive potential, followed by startup project A3. [ABSTRACT FROM AUTHOR]

Plasmodium vivax cases represent more than 50% of a diminishing malaria case load in Vietnam. Safe and effective radical cure strategies could support malaria elimination by 2030. This study investigated the operational feasibility of introducing point-of-care quantitative glucose-6-phosphate dehydrogenase (G6PD) testing into malaria case management practices. A prospective interventional study was conducted at nine district hospitals and commune health stations in Binh Phuoc and Gia Lai provinces in Vietnam over the period of October 2020 to October 2021. The STANDARD™ G6PD Test (SD Biosensor, Seoul, Republic of Korea) was incorporated to inform P. vivax case management. Case management data and patient and health care provider (HCP) perspectives, as well as detailed cost data were collected. The G6PD test results were interpreted correctly by HCP and the treatment algorithm was adhered to for the majority of patients. One HCP consistently ran the test incorrectly, which was identified during the monitoring and resulted in provision of refresher training and updating of training materials and patient retesting. There was wide acceptability of the intervention among patients and HCP albeit with opportunities to improve the counseling materials. Increasing the number of facilities to which the test was deployed and decreases in the malaria cases resulted in higher per patient cost for incorporating G6PD testing into the system. Commodity costs can be reduced by using the 10-unit kits compared to the 25 unit kits, particularly when the case loads are low. These results demonstrate intervention feasibility while also highlighting specific challenges for a country approaching malaria elimination. [ABSTRACT FROM AUTHOR]

Single-walled carbon nanotube (SWCNT)/TiO2 hybrids were synthesized using 1,10-bis(decyloxy)decane-core PAMAM dendrimer as a molecular glue. Upon photoirradiation of a water dispersion of SWCNT/TiO2 hybrids with visible light (λ > 422 nm), the hydrogen evolution reaction proceeded at a rate of 0.95 mmol/h·g in the presence of a sacrificial agent (1-benzyl-1,4-dihydronicotinamide, BNAH). External quantum yields (EQYs) of the hydrogen production reaction photosensitized by (6,5), (7,5), and (8,3) tubes were estimated to be 5.5%, 3.6%, and 2.2%, respectively, using monochromatic lights corresponding to their E22 absorptions (570 nm, 650 nm, and 680 nm). This order of EQYs (i.e., (6,5) > (7,5) > (8,3)SWCNTs) exhibited the dependence on the C2 energy level of SWCNT for EQY and proved the hot electron extraction pathway. [ABSTRACT FROM AUTHOR]

To mitigate the damage of oil spills, a filter modified with a hydrophilic and oleophobic coating is proposed for affordable and efficient oil separation and recovery from water. The sol–gel method was chosen to produce a colloidal suspension of titanium dioxide particles for its ease of production and its versatility in application for many different substrates, including paper and cloth fabric. After immersing the substrates into a titanium-containing solution, three techniques were applied to increase the production of titanium dioxide—microwave-assisted, refrigeration, and ultra-sonication. Contact angle tests were done to investigate the change in the filter's oleophobicity. The titanium dioxide present on the surface of the filter was amorphous, but all treatment methods showed an improvement in oleophobicity. All treated filters improved oil filtration performance by up to eighty percent. The filters isolated motor oil from a mixture while allowing water to pass through. The coated filters also displayed photocatalytic activity by degrading methylene blue on its surface when exposed to sunlight, demonstrating the filter's self-cleaning ability. For real-world applications, the filter can be supported by a stainless mesh for enhanced strength and durability. While being dragged through the water, the filter collects the surface oil, allowing water to pass through via gravity. [ABSTRACT FROM AUTHOR]

In this study, activated carbon derived from mangosteen peel (abbreviated as ACMP) was successfully fabricated. This as-prepared ACMP possessed graphite and had a porous structure with a specific surface area of 419.8554 m2/g. Investigations of the influencing factors on the ciprofloxacin (CIP) adsorption capability of the ACMP based on the static adsorption method showed that: adsorption equilibrium can be achieved in 60 min, the optimal pH for CIP adsorption was a pH of 6, and the optimal ratio between the material mass and solution volume was 3 g/L. The CIP adsorption process of the ACMP follows the Langmuir, Freundlich, Tempkin, Elovich, and Redlich–Peterson isotherm adsorption models. The maximum adsorption capacity calculated according to the Langmuir isothermal adsorption model for the CIP of the ACMP was (qmax = 29.76 mg/g). The CIP adsorption process of the ACMP followed the apparent quadratic kinetic equation, as well as spontaneous, endothermic, physical, and chemical adsorption. The adsorption rate was governed by membrane diffusion. [ABSTRACT FROM AUTHOR]

One of the purposes of earthquake engineering is to mitigate the damages in buildings and infrastructures and, therefore, reduce the impact of earthquakes on society. Seismic ground response analysis refers to the process of evaluating the ground surface motions based on the bedrock motion. On the other hand, deep learning techniques have been developing fast, and they are establishing their application in the civil engineering field. This study proposes two convolutional neural network (CNN) models to estimate the seismic response of the surface based on the seismic motion measured at 100 m level beneath the surface, and selected the one which outperforms the other as the main model. The performances of the main model are compared with those of a physical software SHAKE2000. Twelve sites that include 100 earthquake datasets, whose moment magnitude is higher than 6 and PGA is higher than 0.1 g, were selected. In addition, the corresponding earthquake datasets are used for the CNN model. Whereas the conventional software overestimated the values of the amplitudes for most of the sites, the proposed CNN model predicts fairly well both the values of the amplitudes and the natural periods where responses amplify the most with few exceptions. The proposed model especially outperforms the conventional software when the natural periods range from 0.01 to 0.3 s. For specific sites, the average mean squared errors of the proposed model are even dozens of times lower than those of the conventional physical software. [ABSTRACT FROM AUTHOR]

Exopolysaccharides (EPSs) produced by Bacillus species have recently emerged as promising commercial antioxidants in various industries, such as pharmaceutics and biomedicine. However, little is known about EPS production and function from Bacillus velezensis so far. In the present study, the effect of sugar sources on EPS production by B. velezensis VTX20 and the genetic biosynthesis, characteristics, and antioxidant activity of the resulting EPS were evaluated. The strain VTX20 produced the maximum EPS yield of 75.5 ± 4.8 g/L from an initial 200 g/L of sucrose after a 48-h cultivation. Through genomic analysis, ls-levB operon was found, for the first time, to be responsible for the levan-type EPS production in B. velezensis. Biochemical and structural characterization further confirmed the majority of levan, followed by an extremely low level of dextran biopolymer. The water solubility index and water holding capacity of the EPSs were 81.9 ± 3.4% and 100.2 ± 3.4%, respectively. In vitro antioxidant activity analyses showed strong scavenging activity for 1,1-diphenyl-2-picrylhydrazyl and hydroxyl radical values of 40.1–64.0% and 16.0–40%, respectively. These findings shed light on the EPS biosynthesis of B. velezensis at both structural and genetic levels and the potential application of EPS as a natural antioxidant for pharmaceutical and biomedical industries. [ABSTRACT FROM AUTHOR]

Anti-aging is one of the top goals in the field of health care and aesthetics. Anti-aging cosmetics derived from nature are oriented to long-term development, bringing safety to users and being environmentally friendly. The aim of this study was to develop an anti-aging cosmetic formulation process based on coconut oil in combination with deer antler stem cell extract. The results show that the presence of deer antler stem cell extract added to the foundation made the serum product highly stable and helped improve skin aging significantly after 2 weeks of use. The skin site where the serum product was applied showed a smooth and elastic skin surface, with very few fine lines and shallow wrinkles. Serum reduced the number of wrinkles (48.09% compared to commercial serum (ME) and 60.31% compared to positive control (PC)), reduced skin recovery time (39.31% compared to ME and 67.1% of PC) after two weeks of use. After 2 weeks of use, collagen density increased 10.18% compared to ME and 63.76% compared to control. Epidermal thickness increased by 106.1% compared to PC and 121.7% compared to ME. [ABSTRACT FROM AUTHOR]

Nonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide. An accumulation of fat, followed by inflammation, is the major cause of NAFLD progression. During inflammation, macrophages are the most abundant immune cells recruited to the site of injury. Macrophages are classified into "proinflammatory" M1 macrophages, and "anti-inflammatory" M2 macrophages. In NAFLD, M1 macrophages are the most prominent macrophages that lead to an excessive inflammatory response. Previously, we found that baicalin could polarize macrophages into anti-inflammatory M2c subtype macrophages with an increased level of MERTK expression. Several studies have also shown a strong correlation between MERTK expression and cholesterol efflux, efferocytosis, as well as phagocytosis capability. Therefore, in this study, we aim to elucidate the potential and efficacy of mononuclear-cell (MNC)-derived MERTK+/hi M2c macrophages induced by baicalin as a cell-based therapy for NAFLD treatment. In our results, we have demonstrated that a MERTK+/hi M2c macrophage injection to NAFLD mice contributes to an increased level of serum HDL secretion in the liver, a decline in the circulating CD4+CD25− and CD8+CD25− T cells and lowers the total NAFLD pathological score by lessening the inflammation, necrosis, and fibrosis. In the liver, profibrotic COL1A1 and FN, proinflammation TNFα, as well as the regulator of lipid metabolism PPARɣ expression, were also downregulated after injection. In parallel, the transcriptomic profiles of the injected MERTK+/hi M2c macrophages showed that the various genes directly or indirectly involved in NAFLD progression (e.g., SERPINE1, FADS2) were also suppressed. Downregulation of cytokines and inflammation-associated genes, such as CCR5, may promote a pro-resolving milieu in the NAFLD liver. Altogether, cell-based therapy using MERTK+/hi M2c macrophages is promising, as it ameliorates NAFLD in mice. [ABSTRACT FROM AUTHOR]

This study aims to determine the governance factors that influence the scientific research output of lecturers through the application of PLS-SEM, in conjunction with ANOVA and t-test. Based on a survey of 398 lecturers in twelve higher education institutions (HEIs) in Vietnam, the psychometric properties of the scales measuring the considered dimensions of scientific research outputs were initially examined through the Exploratory Factor Analysis (EFA) procedure, prior to being input into the PLS-SEM model. The SEM model comprised six constructs for the scientific research outputs: scientific research objectives of HEIs, leadership, decentralization, policies for lecturers, support for scientific research activities, and resources for scientific research. The results reveal that resources for scientific research have the most impact on lecturers' scientific research output, followed by policies for lecturers, support for scientific research activities, scientific research objectives of HEIs, and finally, leadership. [ABSTRACT FROM AUTHOR]

Simple Summary: Bovine leukemia virus (BLV) caused a severe cattle neoplastic disease called enzootic bovine leukosis (EBL). EBL causes significant economic losses in farming by reducing milk production, reproductive performance, and fertility, and through cattle culling or death. The BLV proviral load (PVL) represents the quantity of BLV genome that has integrated into the host's genome in BLV-infected cells. It has been reported that PVLs differ according to the genetic background of the host, and some studies of BLV-associated host factors have reported on polymorphisms within the bovine major histocompatibility complex (MHC), namely bovine MHC is bovine leukocyte antigen (BoLA-DRB3). However, there is a great diversity in the PVLs associated with carrying various combinations of these alleles, especially for heterozygous alleles. Therefore, this research investigated whether heterogeneity in BoLA-DRB3 allele combinations would affect PVLs during BLV infections in different ages and breeds of cattle in Japan. This is the first report where the association between heterozygous allelic combinations and BLV PVLs phenotypes (HPLs, LPLs) was analyzed. Our findings augment current understanding about the immunological role played by BoLA heterozygosity in BLV-associated PVLs and biocontrol in BLV infections. Enzootic bovine leukosis is a lethal neoplastic disease caused by bovine leukemia virus (BLV), belongs to family Retroviridae. The BLV proviral load (PVL) represents the quantity of BLV genome that has integrated into the host's genome in BLV-infected cells. Bovine leukocyte antigen (BoLA) class II allelic polymorphisms are associated with PVLs in BLV-infected cattle. We sought to identify relationships between BoLA-DRB3 allelic heterozygosity and BLV PVLs among different cattle breeds. Blood samples from 598 BLV-infected cattle were quantified to determine their PVLs by real-time polymerase chain reaction. The results were confirmed by a BLV-enzyme-linked immunosorbent assay. Restriction fragment length polymorphism-polymerase chain reaction identified 22 BoLA-DRB3 alleles. Multivariate negative binomial regression modeling was used to test for associations between BLV PVLs and BoLA-DRB3 alleles. BoLA-DRB3.2*3, *7, *8, *11, *22, *24, and *28 alleles were significantly associated with low PVLs. BoLA-DRB3.2*10 was significantly associated with high PVLs. Some heterozygous allele combinations were associated with low PVLs (*3/*28, *7/*8, *8/*11, *10/*11, and *11/*16); others were associated with high PVLs (*1/*41, *10/*16, *10/*41, *16/*27, and *22/*27). Interestingly, the BoLA-DRB3.2*11 heterozygous allele was always strongly and independently associated with low PVLs. This is the first reported evidence of an association between heterozygous allelic combinations and BLV PVLs. [ABSTRACT FROM AUTHOR]