Hepatotoxic microcystins (MCs) are the most widespread class of cyanotoxins and the one that has most often been implicated in cyanobacterial toxicosis. One of the main challenges in studying and monitoring MCs is the great structural diversity within the class. The full chemical structure of the first MC was elucidated in the early 1980s and since then the number of reported structural analogues has grown steadily and continues to do so, thanks largely to advances in analytical methodology. The structures of some of these analogues have been definitively elucidated after chemical isolation using a combination of techniques including nuclear magnetic resonance, amino acid analysis and tandem mass spectrometry (MS/MS). Others have only been tentatively identified using liquid chromatography-MS/MS without chemical isolation. An understanding of the structural diversity of MCs, the genetic and environmental controls for this diversity and the impact of structure on toxicity are all essential to the ongoing study of MCs across several scientific disciplines. However, because of the diversity of MCs and the range of approaches that have been taken for characterizing them, comprehensive information on the state of knowledge in each of these areas can be challenging to gather. We have conducted an in-depth review of the literature surrounding the identification and toxicity of known MCs and present here a concise review of these topics. At present, at least 269 MCs have been reported. Among these, about 20% (54 of 269) appear to be the result of chemical or biochemical transformations of MCs that can occur in the environment or during sample handling and extraction of cyanobacterial, including oxidation products, methyl esters, or post-biosynthetic metabolites. The toxicity of many MCs has also been studied using a range of different approaches and a great deal of variability can be observed between reported toxicities, even for the same congener. This review will help clarify the current state of knowledge on the structural diversity of MCs as a class and the impacts of structure on toxicity, as well as to identify gaps in knowledge that should be addressed in future research.

We report here the synthesis of uniform nanospheres-like silver nanoparticles (AgNPs, 5-10 nm) and the dumbbell-like Fe3O4-Ag hybrid nanoparticles (FeAgNPs, 8-16 nm) by the use of seeding growth method in the presence of oleic acid (OA)/oleylamine (OLA) as surfactants. The antibacterial activity of pure nanoparticles and nanocomposites by monitoring the bacterial lag–log growth has been investigated. The electron transfer from AgNPs to Fe3O4NPs which enhances the biological of silver nanoparticles has been proven by nanoscale Raman spectroscopy. The lamellae structure in the spherulite of FeAgNPs/PE nanocomposites seems play the key role to the antibacterial activity of nanocomposites, which has been proven by nanoscale AFM-IR. An atomic force microscopy coupled with nanoscale infrared microscopy (AFM-IR) is use to highlight the distribution of nanoparticles on the surface of nanocomposite at the nanoscale. The presence of FeAgNPs in PE nanocomposites has a better antibacterial activity than that reinforced by AgNPs due to the faster Ag+ release rate from the Fe3O4-Ag hybrid nanoparticles and the ionization of AgNPs in hybrid nanostructure.

Background: Acute hepatopancreatic necrosis disease (AHPND), is a bacterial disease of whiteleg shrimp, which has a high mortality rate (100%) and incurs economic losses. Our objective was to identify the genes which lead to cell and organ damage and investigate bioproducts to prevent and treat. Methods: Litopenaeus vannamei shrimp in Thua Thien Hue province, Vietnam were collected from an infected pond and analysed at the Institute of Biotechnology, Hue University. The PirA gene of Vibrio parahaemolyticus strain K5 was isolated and analyzed for nucleotide sequence and paired with the expression vector pQE30. The expression vector was transformed into E. coli strain M15, the PirA recombinant protein was expressed in the form of 6xHis-PirA fusion protein of about 15 kDa. PirA recombinant protein was purified and determined the PirAvp binding ratio, cloning and sequencing of PirA gene from Vibrio parahaemolyticus strain K5 causing AHPND by PCR method with specific primers and molecular weights of PirAvp and the PirAvp complex. Results: PirA gene from Vibrio parahaemolyticus strain K5 was cloned into pGEM-T easy vector (Promega, USA) and screened E. coli TOP10 colonies containing pGEM T easy/PirA recombinant plasmid on LB agar/ampicillin/IPTG/X-Gal medium. PCR showing a band of about 347 bp, matching the size of PirA gene and two nucleotide sequences (BamHI and HindIII). The results showed that PirA gene has a length of 336 bp and similar to PirA gene on GenBank (Code: KU556825.1). The results of protein extracted from E. coli M15 recombinant cells and 6xHis-PirA target protein was collected in elution fractions from EF2 to EF6, showed that the concentration of 6xHis-PirA protein and EF3 elution fraction collected a highest protein concentration (1,586.54 µg/ml). Conclusions: The purified PirA recombinant protein will provide materials for development research to create biological products to prevent and treat AHPND.

Butyl rubber-based composite (BRC) is one of the most popular materials for the fabrication of protective glove against chemical and mechanical risks. However, in many working places such as metal manufacturing or automotive mechanical services, its mechanical hazards usually appear together with metalworking fluids (MWFs). The presence of these contaminants, particularly at high temperature, could modify its properties due to the scission, the plasticization, the crosslinking of polymer network and thus led to severe modification of mechanical and physicochemical properties of material. This work aims to determine the effect of temperature and a metalworking fluid on mechanical behavior of butyl rubber composite dealing with crosslinking density, cohesion forces and elastic constant of BRC on the based on Mooney-Rivlin’s theory. The effect of temperature with and without MWFs on thermo dynamical properties and morphology of butyl membranes is also investigated. The prediction of service lifetime is then evaluated from extrapolation of Arrhenius plot at different temperatures.

Atomic force microscopy (AFM) has been extensively used for the nanoscale characterization of polymeric materials. The coupling of AFM with infrared spectroscope (AFM-IR) provides another advantage to the chemical analyses and thus helps to shed light upon the study of polymers. In this perspective paper, we review recent progress in the use of AFM-IR in polymer science. We describe first the principle of AFM-IR and the recent improvements to enhance its resolution. We discuss then the last progress in the use of AFM-IR as a super-resolution correlated scanned-probe IR spectroscopy for chemical characterization of polymer materials dealing with polymer composites, polymer blends, multilayers and biopolymers. To highlight the advantages of AFM-IR, we report here several results in studying crystallization of both miscible and immiscible blends as well as polymer aging. Then, we demonstrate how this novel technique can be used to determine phase separation, spherulitic structure and crystallization mechanisms at the nanoscale, which have never been achieved before. The review also discusses future trends in the use of AFM-IR in polymer materials, especially in polymer thin film investigation.

The exposure to extreme temperatures in workplaces involves physical hazards for workers. A poorly acclimated worker may have lower performance and vigilance and may therefore be more exposed to accidents and injuries. Due to the incompatibility of the existing standards implemented in some workplaces and the lack of thermoregulation in many protective equipment, thermal stress remains one of the most frequent physical hazards in many work sectors. However, many of these problems can be overcome with the use of smart textile technologies that enable intelligent thermoregulation in personal protective equipment. Smart textiles can detect, react and adapt to many external stimuli. Interconnected sensors and actuators that interact and react to existing risks can provide the wearer with increased safety, protection and comfort. Thus, the skills of smart protective equipment can contribute to the reduction of errors and the number and severity of accidents in the workplace, and thus promote improved performance, efficiency and productivity.This review provides an overview and opinions of authors on the current state of knowledge on these types of technologies by reviewing and discussing the state of the art of commercially available systems and the advances made in previous research works.

This work emphasizes to use silver decorative method to enhance the antibacterial activity of TiO₂ and ZnO nanoparticles. These silver decorated nanoparticles (hybrid nanoparticles) were synthesized by using sodium borohydride as a reducing agent, with the weight ratio of Ag precursors: oxide nanoparticles = 1: 30. The morphology and optical property of these hybrid nanoparticles were investigated using transmission electron microscopy (TEM) and UV–vis spectroscopy. The agar-well diffusion method was used to evaluate their antibacterial activity against both Staphylococcus aureus and Escherichia coli bacteria, with or without light irradiation. The TEM images indicated clearly that silver nanoparticles (AgNPs, 5-10 nm) were well deposited on the surface of nano-TiO₂ particles (30-60 nm). Besides, smaller AgNPs (< 2 nm) were dispersed on the surface of nano-ZnO particles (20-50 nm). UV-vis spectra confirmed that the hybridization of Ag and oxide nanoparticles led to shift the absorption edge of oxide nanoparticles to the lower energy region (visible region). The antibacterial tests indicated that both oxide pure nanoparticles did not exhibit inhibitory against bacteria, with or without light irradiation. However, the presence of AgNPs in their hybrids, even at low content (< 40 mg/mL) leads to a good antibacterial activity and the higher inhibition zones under light irradiation as compared to that in dark was observed.

Nonwoven fabrics have been widely used in textile manufacturing industry as a sheet or web structure because of soft, water-repellent, recycle, ecological and resilient functions. Ultrasonic welding method has been applied for bonding nonwoven fabrics due to clean, fast and reliable approach. In this work, the ultrasonic stepped horn is designed to generate uniform amplitudes on the working surface by using finite element analysis (FEA) simulation. Chromium carbon steels are utilized to produce ultrasonic horns due to high wear resistant and hardness. Isotactic polypropylene nonwoven fabrics fabricated by spunbond process were bonded by continuous ultrasonic sewing machine. Ultrasonic horn with 70 mm in diameter working at 20 kHz, polypropylene (PP) nonwoven density of 80 gsm and various design of welding joints were applied. A typical image in the case of number one was investigated by the scanning electron microscope (SEM) images of inter-facial micro-structure. However, welding joints of totally eight roller patterns was test the tensile strength of the ultrasonic welding joints on PP nonwoven fabrics. The tensile strength of the welding joints is proportional to the area ratio between the welding area and cycling area. The results showed that the melted zone without welding defects such as crack or blowhole can be seen. Furthermore, the tensile strength of welding joints in eight cases of roller patterns (No.1-No.8) was described in details. The ultrasonic welding joints with brick structures give higher tensile strength while the solid line in the pattern gave less strength.

Livestock farming is a major source of greenhouse gas and ammonia emissions. In this study, we estimate methane, nitrous oxide and ammonia emission from livestock sector in the Red River Delta region from 2000 to 2015 and projection to 2030 using IPCC 2006 methodologies with the integration of local emission factors and provincial statistic livestock database. Methane, nitrous oxide and ammonia emissions in 2030 are estimated at 132 kt, 8.3 kt and 34.2 kt, respectively. Total global warming potential is 9.7 MtCO_2eq in 2030, accounts for 33% greenhouse gas emissions from livestock in Vietnam. Pig farming is responsible for half of both greenhouse gases and ammonia emissions in the studied region. Other major livestock for greenhouse gas emission is cattle and for ammonia emission is poultry. Hanoi contributes for the largest emissions in the region in 2015 but will be caught up and surpassed by other provinces in 2030.

Land-use planning plays an important role in agricultural development, however it lacks tools to support planner in proposing land-use planning solutions especially, under saltwater intrusion condition in the coastal regions. This study aims to apply optimization in analyzing land-use solutions for agricultural land-use planning. In which a multi-objective optimization model is developed to optimize land-use area including land-use allocation taking into account socio-economic and environmental factors. The model has been applied in three districts of Soc Trang province, Vietnam (Long Phu, My Xuyen and Tran De) representing three ecological regions including salt water, brackish water and freshwater in the Mekong Delta of Vietnam. The results showed that two multi-objective optimization scenarios (in terms of profit, labor, environment benefits and risk reduction) have been implemented: (i) Multi-objective optimization of agricultural land-use until 2030 under normal conditions; (ii) Optimizing agricultural land-use until 2030 under climate change conditions similar to the 2016 drought and saltwater intrusion phenomenon in the Mekong Delta. The results showed that the second scenario is the option considered for implementing land-use plan thanks to the balance between good profits and minimizing economic and environmental risk. The land allocation was carried out taking into account household economic, the influence of adjacent production types, local traffic and canal systems factors to allocate optimal land-use areas. The combination of land-use optimization and spatial allocation process can help planners improve the quality of agricultural land-use planning.

(1) This study aimed to examine the prevalence of depression and its correlation with acculturative Stress and Social Connectedness among domestic and overseas students in Japan International University. (2) Methods: A Web-based survey was distributed among students of International University, which resulted in 263 responses. On the survey together with socio-demographic data, a nine-item tool from the Patient Health Questionnaire (PHQ-9), was used to measure the prevalence of Depression and its relationship with socio-demographic data, Social Connectedness Scale was used to measure Social Connectedness, and Acculturative Stress Scale for International Students (ASSIS) was used to measured acculturative stress. (3) Results: Depression was significantly high in international and domestic students (37.81% and 29.85% respectively). English language proficiency and students age (20 years old) showed a significant correlation with depression among domestic students (β=-1.63, p=0.038 and β=2.24, p=0.048). Stay length (third year) also displayed a significant correlation with depression among international students (β=1.08, p=0.032). Among international and domestic students statistically significant positive correlation between depression and acculturative stress, negative associations of social connectedness with depression and acculturative stress were also found. Suicidal or self-hurting ideation thoughts are found among around 20% of all students. (4) Conclusions: These findings indicate a relatively high prevalence of depression among students of International University, and overseas students are more affected. Depression, Acculturation stress and Social Connectedness show statistically strong intercorrelation, which highlights the need of host University to recognise the role of Acculturation and Social Connectedness in the development of Depression among students.

This article summarizes studies using the AIQS-DB method to analyze various types of samples for different purposes. This is a method developed to simultaneously analyze nearly 1500 compounds and is widely used worldwide. The method is highly effective for environmental samples such as water, soil, sediment, and air. Recognizing its potential, this article aims to promote the further application and development of AIQS-DB in research related to food analysis and source tracing. Furthermore, if a suitable dataset can be constructed, it could help research quickly and cost-effectively discover the new bioactive compounds from plant medicine.

This study proposes a novel hybrid machine learning approach for modeling of rainfall-induced shallow landslides. The proposed approach is a combination of an instance-based learning algorithm (k-NN) and Rotation Forest (RF), state of the art machine techniques that have seldom explored for landslide modeling. The Lang Son city area (Vietnam) is selected as a case study. For this purpose, a spatial database for the study area was constructed, and then, was used to build and evaluate the hybrid model. Performance of the model was assessed using Receiver Operating Characteristic (ROC), area under the ROC curve (AUC), success rate and prediction rate, and several statistical evaluation metrics. The results showed that the model has high performance with both the training data (AUC = 0.948) and the validation data (AUC = 0.848). The results were compared with those obtained from soft computing techniques i.e. Random Forest, J48 Decision Trees, and Multilayer Perceptron Neural Networks. Overall, the performance of the proposed model is better than those obtained from the above methods. Therefore, the proposed model is a promising tool for landslide modeling. The research result can be highly useful for land use planning and management in landslide prone areas.

In this article, the research team has systematically developed a method to model the kinematics and dynamics of a 3-wheeled robot subjected to external disturbances and sideways wheel sliding. These models will be used to design control laws that compensate for wheel slippage, model uncertainties, and external disturbances. These are control algorithms developed based on Dynamic Surface Control (DSC). Adaptive trajectory tracking DSC algorithm using fuzzy logic system (AFDSC) and radial neural network (RBFNN) with fuzzy logic system to overcome the disadvantages of DSC and expand the application domain for wheeled Mobile Robots (WMR). However, this Adaptive Fuzzy Neural Network Dynamic Surface Control (AFNNDSC) adaptive controller ensures the closed system is stable and follows the preset trajectory in the presence of wheel slippage model uncertainty and is affected by significant amplitude disturbances. The stability and convergence of the closed-loop system are guaranteed based on the Lyapunov analysis. The AFNNDSC adaptive controller is evaluated by simulation on MATLAB/Simulink software and in a steady state. The maximum position error on the right wheel and left wheel is 0.000572 (m) and 0.000523 (m), and the angular velocity tracking error in the right and left wheels of the control method is 0.000394 (rad/s). The experimental results show the correctness of the theoretical analysis, the effectiveness of the proposed controller, and the possibility of practical application.

The enhancement of health-beneficial omega-3 long chain polyunsaturated fatty acid (n-3 LC-PUFA) contents in the muscle, liver, heart and kidney of Australian prime lambs through pasture grazing and supplementation with oil infused pellets was investigated. Forty-eight first-cross prime lambs were randomly assigned into a split-plot design with pasture type as the main plot effect and pellet supplementation as a sub-plot effect in a feeding trial that lasted for nine weeks. The n-3 LC-PUFA content in Longissimus dorsi muscle of all lambs was well above the 30 mg threshold for “omega-3 source” nutrition claim under the Australian Food Standards and Guidelines. Pasture type impacted the fatty acid contents in muscle, heart and kidney of prime lambs. Lambs grazing cocksfoot only had the highest 18:3n-3 (ALA) and n-3 LC-PUFA contents (67.1 mg/100g and 55.2 mg/100 g, respectively). Supplementation of pellets with or without oil infusion to grazing lambs decreased the ALA and n-3 LC-PUFA contents and increased n-6/n-3 ratio in Longissimus dorsi muscle. The fatty acid content in internal organs of grazing lambs was also affected by pellet supplementation. The liver and kidney of grazing lambs were both “good sources” (60 mg/100 g) of omega-3. The cocksfoot grass showed considerable potential for producing healthy, premium quality meat with high contents of n-3 and n-3 LC-PUFA which may consequently enhance the omega-3 intake of Australian lamb consumers.

This study investigated live animal performance and carcass characteristics of Australian prime lambs fed oil based polyunsaturated fatty acid (PUFA) enriched pellets in a feedlot system. The tested hypothesis was that supplementation of lambs with a variety of dietary oil based PUFA enriched pellets would enhance growth and carcass characteristics compared with the control lambs on lucerne only. Seventy-two, 6 months old White Suffolk x Corriedale first-cross prime lambs with an average liveweight (LWT) of 35.7 ± 0.9 kg were allocated to six treatment groups in a completely randomised experimental design. The treatments were: (1) control: lucerne hay only; or lucerne hay plus wheat-based pellets infused with 50 ml/kg DM of oils from (2) rice bran (RBO); (3) canola (CO); (4) rumen protected (RPO); (5) flaxseed (FO) and (6) safflower (SO) dietary sources. All lambs had ad libitum access to lucerne hay and clean fresh water. Supplemented lambs were fed 1kg of pellet/head/day for 10 weeks. Feed intake, final LWT, average daily gain (ADG), body conformation and carcass characteristics of lambs in the supplemented groups were all greater than for the control group. SO lambs had the lowest ADG of 190.3 g/day. RBO and CO treatments had the lowest feed cost per unit gain of AU$ 3.0/kg. Supplemented lambs had similar over the hooks (OTH) incomes that were all higher than that of the control group. This empirical evidence-based data demonstrated that supplementation of lambs with RBO and CO had comparatively lower feed costs without compromising ADG, carcass characteristics and OTH income.

Curcuma longa is only a rich source of curcumin (1) and its major analogues demethoxycurcumin (2) and bisdemethoxycurcumin (3) among the Curcuma species. The content ratio of these three curcumins in turmeric is depended on the varieties and growing environment. Recently, curcumin (1) has been reported as potential inhibitor of hepatic and enzymatic protein tyrosine phosphatase 1B (PTP1B) and its related disorders such as hypertriglyceridemia, hyperlipidemia and liver steatosis. Thus, we further purified curcumins (1–3) from C. longa and investigated their inhibitory effects against PTP1B and α-glucosidase enzymes. As the result, curcumins (1–3) exhibited potential PTP1B inhibition with IC50 values of 37.8 ± 1.4, 45.3 ± 0.7, and 72.6 ± 1.1 μM, respectively, and α-glucosidase inhibition with similar manner (IC50 values of 78.2 ± 0.2, 82.4 ± 0.6, and 90.6 ± 1.0 μM, respectively). These results reveal a key role of methoxylation in the variation of PTP1B and α-glucosidase inhibitory activity for these curcumins. In addition, density functional theory (DFT) was used accompanying with molecular docking (MD) to analyze the ligand stability and the interaction of curcumins (1–3) with PTP1B and glucoside hydrolase proteins. Assay-based results and the MD data obtained are highly correlation suggesting that the deterioration of the enzyme activity caused by the distortion of structural conformation of PTP1B and glucoside hydrolase may be related to the arrangement of amino acids in protein structure. This reported for the first time that inhibitory effects of curcumins (1–3) against PTP1B and glucoside hydrolase have been examined in vitro and in silico as well.

In the context of economic development and international economic integration, the logistics industry in Vietnam is developing to meet the market demand for the transportation of goods; thus, many logistics enterprises have been formulated and grown up in recent years. This research aims to measure the efficiency of logistics enterprises and recommend a feasible solution to improve their future performance by integrating the Super Slacked-based Measure model (Super-SBM) in Data Envelopment Analysis and Fuzzy Analytic Hierarchy Processes (Fuzzy AHP) in multi-criteria decision-making. The super-SBM model was utilized to conduct the efficiency scores of logistics enterprises from 2016 to 2022 based on calculating the ratio between input and output variables; the empirical result determined each enterprise's effectiveness and ineffectiveness. Next, the Fuzzy AHP method evaluated and ranked criteria that directly impacted the operational process of logistics enterprises based on experts' opinions; the examined result suggested a feasible direction to improve their business efficiency in the future. The proposed hybrid models are a helpful solution for efficiency determination and development direction for logistics enterprises. An overall picture of the logistics enterprises was also drawn to describe their operational business process.

Recently, there is a growing need for sensors that can operate autonomously, without the need for an external power source. This is especially important in applications where conventional power sources, such as batteries, are impractical or difficult to replace. Self-powered sensors have emerged as a promising solution to this challenge, offering a range of benefits such as low cost, high stability, and environmental friendliness. One of the most promising self-powered sensor technologies is L-S TENG, which stands for the liquid-solid triboelectric nanogenerator. This technology works by harnessing the mechanical energy generated by external stimuli such as pressure, touch, or vibration, and converting it into electrical energy that can be used to power sensors and other electronic devices. Therefore, self-powered based on L-S TENG, which provides numerous benefits such as rapidly responding, portability, cost-effectiveness, and miniaturization, is critical for increasing living standards and optimizing industrial processes. In this review paper, the working principle with three basic modes has been briefly introduced firstly. After that, affecting parameters to L-S TENG are reviewed based on the properties of the liquid and solid phases. With different working principles, L-S TENG has designed a lot of structure that works as a self-powered sensor for pressure/force change, liquid flow motion, concentration, and chemical detection or biochemical sensing. Moreover, the continuous output signal of TENG plays an important role in a real-time sensor that is vital to the growth of the Internet of Things.

Background: Strongyloidiasis, a neglected disease caused by intestinal nematodes of the genus Strongyloides, is endemic to tropical and subtropical areas such as Vietnam. The morphological diagnosis of larvae by Hara Mori culture technique and microscopicare are considered the standard diagnostic procedures in the endemic areas of Strongyloides spp. However, they could only identify the genus, not the species of Strongyloides. DNA-molecular techniques which are highly sensitive and more cost-effective have been increasingly utilized in detection of Strongyloides species. This study aims to determine prevalence and the species of Strongyloides among resident population in Duc Hoa district, Long An province, Southern Vietnam. Methods: A cross-sectional study was conducted using 1,190 stool samples collected in Duc Hoa district, Long An province, Vietnam, from July, 2017 to November 2018. The stool specimens were transported to the Laboratory of Medical Parasitology, Pham Ngoc Thach University of Medicine within two hours of collection at an appropriate temperature of 25 oC. All samples were stored at 2 - 8°C and processed within 48 hours for microscopic examination. Molecular detection was carried out at Laboratory of Molecular Biology, Pham Ngoc Thach University of Medicine, Hochiminh city, VietNam. Results: Of the 1,190 samples tested, Strongyloides spp. larvae were detected in 79 specimens (6.6%) by two classical parasitological methods, namely direct microscopy and the modified Harada-Mori filter paper culture. DNA was extracted from 70 of the 79 samples of Strongyloides spp. larvae, which was subsequently characterized by real-time PCR amplification of the 18S and 28S regions of the rDNA gene. The results showed that 97.1% of the DNA samples were S. stercoralis, 2.9% were co-infections with S. ratti and S. stercoralis, and 2.9% belonged to S. ratti. For all 14 isolates, nucleotide sequencing was compared with other human pathogenic species of Strongyloides whose sequences are available in GenBank. The identity of 12/14 sequences were confirmed as S. stercoralis with a high level of similarity (91.3% - 100%) and over 98% for S. ratti. Between the two co-infection samples, the higher similarity belonged to S. stercoralis. Conclusion: A molecular amplification of small subunit ribosome RNA followed by sequence analysis has been proved to be a suitable method for discrimination of Strongyloides spp. retrieved from stool samples.

Nowadays, wearable devices for human health monitoring are increasingly become popular and widely used. Typically, the wearable device is small size and operates with batteries. Therefore, the wearable device acquires bio-signals and transfers to smartphones or personal computers (PC) via WiFi/ Bluetooth for processing data. To reduce power consumption is one of the most important challenges of designing wearable devices. To solve this problem, the proposed signal quality valuation (SQV) method can be select the high-quality signal and reduce the transfer time to other devices. In this paper, the proposed SQV and data compression method rely on real-time PPG signals analysis to retain important information of PPG signal, improve performance and power consumption of PPG devices. Besides, we also proposed Heuristic rules for heart rate (HR) estimation with compression data. The experimental results show that the highest compression ratio (CR) is 387.8 with BIDMC Physionet database (sampling frequencies of 125 Hz) and HR error as 1.43 bpm for averaging absolute error (avAE), the standard deviation absolute error (sdAE as 0.4) and relative error mean (avRE as 0.019). The proposed real-time PPG measurement system (sampling frequency as 100/ 200/ 400 Hz) reduce power consumption and open the new structure for healthcare application systems

The Australian dairy sheep industry is small and mostly based on a natural grass grazing system which can limit productivity. The current study tested different plant oil-infused and rumen protected polyunsaturated fats and their interactions with sire breeds to improve lactation traits and body condition score (BCS) of ewes grazing low quality pastures. It was hypothesised that supplementing lactating ewe diets plant-derived polyunsaturated oils will improve milk production and composition without compromising BCS. Sixty ewes (n=10/treatment) in mid-lactation, balanced by sire breed, parity, milk yield, body condition score, and liveweight were supplemented with: 1) control: wheat-based pellets without oil inclusion; wheat-based pellets including 2) canola oil (CO); 3) rice bran oil (RBO); 4) flaxseed oil (FSO), 5); safflower oil (SFO) and 6) rumen protected fat containing eicosapentaenoic acid and docosahexaenoic acid (RPO). Except for the control group, all supplementary diets included the same level of 50 ml/kg DM of oil and all diets were isocaloric and isonitrogenous. Experimental animals were grazed in the same paddock with ad libitum access to pasture, hay and water during the 10-week study. RPO was the most effective diet that enhanced milk, fat and protein yields by approximately 30, 13, and 31% respectively (P<0.0001). Significant increase in milk production was also observed in CO, RBO, and SFO (P<0.0001). Breed significantly influenced animal performance with higher milk yield recorded for crossbred Awassi x East Friesian (AW x EF) (578 g/day) vs purebred Awassi (452 g/day) (P<0.0001). This study provides empirical evidence for the use of rumen-protected and plant-derived oil-infused pellets as supplements under low quality pasture grazing conditions, to improve production performance of purebred Awassi and crossbred AW x EF ewes.

(1) Background: Ectopic pregnancy (EP) is when fertilized ovum implanted outside of uterine cavity. The incidence was 1.5% to 2.0% of all pregnancies [1, 2]. EP decreases fertility ability [3]. This study focused on the pregnancy rate after EP and various parameters influencing pregnancy. (2) Methods: The data was extracted from National Health Insurance Research Database (NHIRD) during 2000-2013. The study group enrolled women with one EP history. Those who did not have EP was put into the control group. Chi-square/Fisher exact test was performed on category variable and t-test was used on continue variables. (3) Results: The EP group had a higher cumulative rate of conceive, 41.55% than control group, 37.14% and 1.16 times higher risk in developing pregnancy (P&lt;0.001). The conceiving rate was lower than the control group in the first 5 years, but higher than the control group in the 10th to 14th years. (4) Conclusions: The fecundability after EP is lower at the beginning, but regained after long term follow.

The fishmeal production industry is essential for providing protein for animal feed in the aquaculture sector. However, the industry faces challenges related to energy consumption and environmental sustainability. This study evaluates the energy efficiency and environmental benefits of waste heat recovery (WHR) technologies in a fishmeal production plant in Vietnam. Data were collected from the plant between 2016 and 2022, and a specific energy consumption (SEC) indicator and a comprehensive methodology were utilized. Implementing an economizer as a WHR technology resulted in a 55.5% decrease in SEC compared to the state before installation. The enhanced energy efficiency also translated to reduced energy consumption per output unit. Moreover, the economizer contributed to annual energy savings of 4,537.57 GJ/year and cost savings of $26,474.49. Additionally, carbon dioxide (CO2) emissions associated with producing one ton of fishmeal decreased by 58.37%. These findings highlight the potential for WHR technologies to improve energy efficiency and reduce the environmental footprint of fishmeal production. The study's results provide valuable insights for practitioners and policymakers in promoting energy efficiency practices and reducing environmental impact in the industry.

Investigating the network response to node removal and the efficacy of the node removal strategies are related and fundamental questions in network science. Research studies proposed many node centralities based on the network structure ranking node to remove. The random walk (RW) on networks describes a stochastic process in which a walker travels among nodes. RW can be a model of transport, diffusion, and search on networks, and an essential tool for studying the importance of network nodes. In this manuscript, we propose four new measures of node centrality based on RW. Then, we compare the efficacy of the new RW node removal strategies to network dismantle with effective node removal strategies from the literature, such as betweenness and closeness node removal over synthetic and real-world networks. We evaluate the network dismantle along node removal using the size of the largest connected component (LCC). We find that, hence the betweenness nodes attack is the best strategy overall, the new node removal strategies based on RW show the highest efficacy in peculiar network topology. Specifically, RW strategies based on covering times emerge as the most effective strategy on a synthetic lattice network and two real-world road networks. Our results may be useful in selecting the best node attack strategies in a specific class of networks and in building more robust network structures.

Recently, Indium Tin Oxide, a highly transparent, well conductive, and CMOS-compatible material, has been paying strong attention to the thermo-optic controlled silicon photonics industry because it allows a miniature of the gap between the core silicon and the heater, thus enabling reducing the electric power consumption and enhancing the switching speed. In this article, we propose an ultralow loss and small-size ITO microheater for the phase shift tuning. The designated microheater is manipulated in realizing a numerical co-design of compact and high bandwidth three-mode converter and three-mode selective router. Simulation results illustrate the 3-dB bandwidth for the three-mode converter and three-mode selective router as much as 100-nm and 40-nm during crosstalk under -25 dB, respectively. Besides, co-designed devices attain relatively large fabrication tolerances corresponding to width and height tolerances of ±50 nm and ±5 nm. In addition, the proposed devices consumed less than 90 mW total power consumption and took a fast switching time below 8 μs. Moreover, both two co-designs can be integrated into an estimated compact footprint of 8 μm2160 μm. Such excellent performances demonstrate the attractive potential of ITO as low-loss thermo-optic phase shifters and open an alternative way for enabling ultrafast and high-speed mode division multiplexing systems and very large-scale photonic integrated circuits.

In industry 4.0 era, video applications such as surveillance visual systems, video conferencing, or video broadcasting have been playing a vital role. In these applications, for manipulating and tracking objects in decoded video, the quality of decoded video should be consistent because it largely affects to the performance of the machine analysis. To cope with this problem, we propose a novel perceptual video coding (PVC) solution in which a full reference quality metric named Video Multimethod Assessment Fusion (VMAF) is employed together with a deep convolutional neural network (CNN) to obtain the consistent quality while still achieving the high compression performance. First of all, to achieve the consistent quality requirement, we propose a CNN model with an expected VMAF as input to adaptively adjust the quantization parameters (QP) for each coding block. Afterwards, to increase the compression performance, a Lagrange coefficient of Rate-Distortion optimization (RDO) mechanism is adaptively computed under Rate-QP and Quality-QP models. Experimental results show that the proposed PVC has achieved two targets simultaneously: the quality of video sequence is kept consistently with an expected quality level and the bit rate saving of the proposed method is higher than traditional video coding standards and relevant benchmark, notably with around 10% bitrate saving in average.

Bacillus veleznesis RB.EK7 was recently found as a potent rhizobacterial strain for effective management of black pepper root-knot nematodes. This work aimed to produce, purify, and elucidate the chemical structures of antinematode compounds (ANCs). Concerning cost-effectiveness and environmental issues, this study used organic wastes for the bioproduction of ANCs. Among various substrates, shrimp shells powder was the most suitable carbon/nitrogen source to produce ANCs. The fermentation process for enhancement of antinematode activity was investigated. The targeting ANCs were purified from the fermented culture broth, and their structures were elucidated. Two active compounds were thymine (1) and hexahydropyrrolo [1,2-a]pyrazine-1,4-dione (2). Notably, for the first time, these purified compounds showed potential and moderate anti- J2 nematodes and anti-eggs hatching, respectively. The docking study results indicated that the potent antinematode effect of these compounds may be possibly due to the inhibition of the targeting enzyme acetylcholinesterase. The data of this work suggest that organic waste SSP can be potentially reused for the production of thymine and hexahydropyrrolo [1,2-a] pyrazine-1,4-dione with promising use for the management of black pepper nematodes.

Damage assessment is one of the most crucial issues for bridge engineers, especially for existing steel bridges. Among several methodologies, the vibration measurement test is a typical approach in which the natural frequency variation of the structure is monitored to detect the existence of damage. However, locating and quantifying the damage is still a big challenge. In this regard, the artificial intelligence (AI)-based approach seems a potential way to accomplish those obstacles. This study deploys a comprehensive campaign to determine all dynamic parameters of a pre-damage steel truss bridge structure. Based on the results of mode shape, natural frequency, and damping ratio, a finite element model (FEM) is created and keeps updating. The artificial intelligence network's input data will be analyzed and evaluation from damage cases. The trained artificial neural network model will be curated and evaluated to confirm the approach's feasibility. During the actual operational stage of the steel truss bridge, this damage assessment system is showing good performance in terms of monitoring the structural behavior of the bridge under some unexpected accidents.

The Aβ cascade and alternations of biomarkers in neuro-inflammation, synaptic dysfunction and neuronal injury followed by Aβ have progressed. But the question is how to use the biomarkers. Here, we examine the evidence and pathogenic implications of protein interactions and the time order of alternation. After the deposition of Aβ, the change of tau, NfL and NG is the main alternation and connection to others. The neuro-inflammation, synaptic dysfunction and neuronal injury function is exhibited prior the structural and metabolic changes in the brain following Aβ deposition. The time order of such biomarkers compared to the tau protein is not clear. Despite the close relationship between biomarkers and plaque Aβ deposition, several factors favor one or the other. There is an interaction between the proteins that CSF SNAP-25, VILIP-1 and YKL-40 can predict the brain amyloid burden. The Aβ cascade hypothesis could be the pathway, but not all subjects are converted to AD, even with very high elevated Aβ. The interaction of biomarkers and the time order of change require further research to identify the right subjects and right molecular target for precision medicine therapies.

IntroductionThe aim of this study is to describe the epidemiology of all COVID-19 patients in Vietnam and to describe the measures of disease control and prevention implemented. MethodsData were recovered from Wikipedia regarding the 2020 coronavirus pandemic in Vietnam. The period covered was from 23 January to 20 April 2020. Descriptive analysis was stratified by gender, age, country of origin, travel history, clinical symptoms and outcome. A survey of disease control and prevention measures was conducted at the Centre for Disease Control in the Thai Binh province, which is responsible for screening and isolating individuals at high risk of COVID-19. ResultsAs of 20 April 2020, Vietnam had recorded 268 confirmed COVID-19 patients. 55.2% were female. 67.9% were aged 20-49 years and 82.5% were Vietnamese. 60.4% of cases were imported from outside Vietnam. Other cases were acquired in Vietnam by individuals in close contact with imported cases. Only one patient who had not travelled had had no known contact with a confirmed case. 63.1% of patients were asymptomatic. 75.7% of patients were discharged. No deaths were recorded. The Thai Binh CDC surveyed a total of 2,203 persons at risk of COVID-19. 336 persons (15.2%) were isolated at hospitals and 1,411 (64.0%) in dedicated isolation facilities. 16.4% reported at least one respiratory symptom. No positive cases confirmed by RT-PCR have been reported in the Thai Binh province to date. ConclusionThe effect of the systematic screening and isolation strategy made it possible to limit local transmission in Vietnam. Vietnam needs to reinforce diagnostic capacities, prevention measures and provide the necessary epidemiological data on which to base interventions. The wider use of rapid serological tests is also advisable in order to be able to conduct extensive screening in the community.

At the end of the dry season in early March to early April each year, extensive agricultural biomass waste burnings occur throughout insular mainland Southeast Asia. During this biomass burnings period, smoke aerosols blanket the whole regions and were transported and dispersed by predominant westerly and south westerly winds to southern China, Taiwan and as far southern Japan and the Philippines. The extensive and intense burnings coincided with some wildfires in the forests due to high temperature making the region one of the global hot spots of biomass fires. In this study, we focus on the effect of pollutants emitted from biomass burnings in March 2019 at the height of the burnings period to the exposed population and their health impact. The Weather Research Forecast- Chemistry (WRF-Chem) model was used to predict the PM2.5 concentration over the simulating domain and health impacts are then assessed on the exposed population in the four countries of Southeast Asia, namely Thailand, Laos, Cambodia and Vietnam. Using the health impact based on log-linear concentration response function and Integrated Exposure Response (IER), the results show that at the peak period of the burnings from 13 to 20 March 2019, Thailand experienced the highest impact, with an estimated 2170 premature deaths. Laos, Vietnam, and Cambodia followed, with estimated mortalities of 277, 565, and 314 deaths respectively. However, when considering the impact per head of population, Laos exhibited the highest impact, followed by Thailand, Cambodia, and Vietnam. The results highlight the significant health impact and associated economic cost of agricultural waste burnings in Southeast Asia at the end of the dry season. And hence policy makers should take these into account to design measures to reduce the negative impact of widespread burnings on exposed population in the region.

African swine fever (ASF) is a lethal and highly contagious transboundary animal disease with the potential for rapid international spread. Currently, there is no ASF vaccine commercially available. All infected animals must be isolated and culled immediately upon confirmation of the presence of the virus. Works leading to the rational development of protective ASF vaccines are urgently needed. Here, we generated a safe and efficacious live-attenuated vaccine (LAV) VNUA-ASFV-LAVL2 by serial passaging of a field isolate (VNUA-ASFV-05L1, genotype II) in porcine alveolar macrophage (PAMs, 65 passages) and an immortalized porcine alveolar macrophage cell line (3D4/21, 55 passages). VNUA-ASFV-LAVL2 can efficiently replicate in both PAMs and 3D4/21 cells. It provides 100% protection, even with the low dose of 10^2 HAD50, for the vaccinated pigs against the challenge of contemporary pandemic ASFV field isolate. Pigs vaccinated with this LAV at a dose range of 10^2 to 10^5 HAD50 remained clinically healthy during both the 28-day observation period of immunization and the 28-day observation period of challenge. VNUA-ASFV-LAVL2 was completely eliminated from blood by 28 days post inoculation (DPI), and from feces or oral fluids by 17 DPI. It remained a safe, stable, and attenuated phenotype after five passages in pigs. Consistently high levels of ASFV-specific IgG antibodies and significant cellular immunity were detected in vaccinated pigs before the ASFV challenge. These results indicate that the VNUA-ASFV-LAVL2 strain is a safe and efficacious LAV against the genotype II ASFV strain responsible for current ASF outbreaks in Asia.

Introduction: Hemostatic dysfunction during extracorporeal membrane oxygenation (ECMO) due to blood-circuit interaction and the consequences of shear stress by flow rates lead to rapid activation of the coagulation cascade and thrombus formation in the ECMO system and blood vessels. In this study, we aimed to identify the incidence and risk factors for cannula-associated arterial thrombosis (CaAT) post-decannulation. Methods: A retrospective study of patients undergoing arterial cannula removal following ECMO. We evaluated the incidence of CaAT and compared clinical characteristics, pre-ECMO severity, and daily hemostasis parameters in patients with and without CaAT. Multivariate analysis revealed the risk factors for CaAT. Results: Forty-seven patients requiring venoarterial ECMO or hybrid methods were recruited to be screened for thrombosis. The median SOFA score was 11 (8-13). CaAT occurred in 29 patients (61.7%), with thrombosis in the superficial femoral artery accounting for 51.7%. Limb ischemia complications in the group with CaAT was 17.2%. In multivariate analysis, an ECMO flow rate of 100 mL/min was determined to be the independent factor for CaAT with an OR of 0.84 (95% CI, 0.73–0.95, p=0.008). Conclusion: In patients successfully weaned from ECMO, the incidence of CaAT was 61.7%. Our study found that a low-flow rate of ECMO was an independent risk factor for CaAT.

Over the past decade and a half, dynamic functional imaging has revolutionized the neuroimaging field. Since 2009, it has revealed low dimensional brain connectivity measures, has identified potential common human spatial connectivity states, has tracked the transition patterns of these states, and has demonstrated meaningful alterations in these transition and spatial patterns in neurological disorders, psychiatric disorders, and over the course of development. Recently, researchers have begun to analyze this data from the perspective of dynamic system and information theory in the hopes of understanding how these dynamics support less easily quantified processes, such as information processing, cortical hierarchy, and consciousness. Consciousness, in particular, appears to be strongly linked to entropy production in the brain. Little attention has been paid to the effects of psychiatric disease on entropy production in the human brain, however. Even disorders characterized by substantial changes in conscious experience have not been widely analyzed from this perspective. We begin to rectify this by examining the complexity of subject trajectories in state space through the lens of information theory. Specifically, we identify a basis for the dynamic functional connectivity state space and track subject trajectories through this space over the course of the scan. The dynamic complexity of these trajectories is assessed along each dimension of the proposed basis space. Using these estimates, we demonstrate that schizophrenia patients display substantially simpler trajectories than demographically matched healthy controls, and that this drop in complexity concentrates along specific dimensions. We also demonstrate that entropy generation in at least one of these dimensions is linked to cognitive performance. Overall, results suggest great value in applying dynamic systems theory to problems of neuroimaging and reveal a substantial drop in the complexity of schizophrenia patients’ brain function.

Micro elastofluidics is a transformative branch of microfluidics, leveraging fluid-structure interaction (FSI) at the microscale to enhance the functionality and efficiency of various microdevices. This review paper elucidates the critical role of advanced computational FSI methods in the field of micro elastofluidics. By focusing on the interplay between fluid mechanics and structural responses, these computational methods facilitate the intricate design and optimisation of microdevices such as microvalves, micropumps, and micromixers, which rely on the precise control of fluidic and structural dynamics. In addition, these computational tools extend to the development of biomedical devices, enabling precise particle manipulation and enhancing therapeutic outcomes in cardiovascular applications. Furthermore, this paper addresses the current challenges in computational FSI and highlights the necessity for further development of tools to tackle complex, time-dependent models under microfluidic environments and varying conditions. Our review highlights the expanding potential of FSI in micro elastofluidics, offering a roadmap for future research and development in this promising area.

The Vu Gia - Thu Bon River Basin (VG-TB) is confronting numerous challenges related to water security (WS), particularly in the face of the impacts of climate change. These challenges manifest in salinity intrusion, altered rainfall patterns, and reduced water supply in downstream areas. To assess the current state of water security in the basin, the study employed statistical analysis methods, Process Analysis Method (PAM), SMART, and Analytic Hierarchy Process (AHP) to develop a comprehensive Assessment Framework for Water Security (AFWS) in the VG-TB. The AFWS encompasses five key dimensions, 17 indicators, and 28 variables, aligning with the UN-Water definition of water security and addressing the Sustainable Development Goal 6 (SDG6) criteria for global water sustainability. It also adheres to the Asian Development Bank's (ADB) approach to water security assessment as outlined in the Asian Water Development Outlook (AWDO) reports. This allows for the computation of a comprehensive Water Security Index (WSI) for specific regions, serving as a foundation for decision-making and policy formulation aimed at enhancing water security in the context of climate change and facilitating sustainable basin development in the future.

Dynamic optical structural color is always desired in various display applications and usually involves active materials. Full-color generation, especially bi-directional full-color generation in both reflective and transmissive modes, without any active materials included has been rarely investigated. Herein, we demonstrate a scheme of bi-directional full-color generation based on a plasmonic metasurface modulated by rotation of the polarization angle of the incident light without varying the geometry and the optical properties of the materials and the environment where the metasurface resides. The metasurface unit cell consists of plasmonic modules aligning in three directions and is patterned in a square array. The metasurface structural color device generates full colors in both reflection and transmission. Based on the proposed polarization-dependent structural color, information encoding of three multiplexed animal images and quick-responsive (QR) codes is demonstrated to verify the efficient information encoding and decoding of the proposed scheme. The animals can be seen under different polarization incidence and the QR codes can be successfully decoded by the polarization rotation in transmission. The proposed bi-directional full-color generation metasurface has great potential in applications such as kaleidoscope generation, anti-counterfeiting, dynamic color display, and optical information encoding.

Nanocomposites of TiO₂ Degussa P25 nanoparticles/activated carbon (TiO₂/AC ) were prepared at various mass ratios of (4:1), (3:2), (2:3), and (1:4) by a facile process. The effects of TiO₂/AC mass ratios on the structural, morphological, and photocatalytic properties were systematically studied in comparison with bare TiO₂ and bare AC. TiO₂ nanoparticles exhibited dominant anatase and minor rutile phases, and a crystallite size of approximately 21 nm; while AC had XRD peaks of graphite and carbon, and a crystallite size of 49 nm. The composites exhibited tight decoration of TiO₂ nanoparticles on micron-/submicron AC particles, and uniform TiO₂/AC composites were obtained as evidenced by the uniform distribution of Ti, O, and C in an EDS mapping. Moreover, Raman spectra show the typical vibration modes of anatase TiO₂ (e.g., E_1g⁽¹⁾, B_1g⁽¹⁾, E_g⁽³⁾) and carbon materials with D and G bands. The TiO₂/AC with (4:1), (3:2), and (2:3) possessed higher reaction rate constants (k) in photocatalytic degradation of methylene blue (MB) than that of either TiO₂ or AC. Among the investigated materials, TiO₂/AC = 4:1 achieved the highest photocatalytic activity with a high k of 55.2×10^-3 min^-1 and an MB removal efficiency of 96.6% after 30 min treatment under UV-Vis irradiation (120 mW/cm²). The enhanced photocatalytic activity for TiO₂/AC is due to the synergistic effect of the high adsorption capability of AC and the high photocatalytic activity of TiO₂. Furthermore, TiO₂/AC promotes the separation of photoexcited electron/hole (e^-/h⁺) pairs to reduce their recombination rate and thus enhance photocatalytic activity. The optimal TiO₂/AC composite in this study can be used for treating industrial or household wastewater with organic pollutants.

Hydraulic fracturing has enabled production from unconventional reservoirs in the U.S., but production rates often decline sharply, limiting recovery factors to under 10%. This study optimizes the CO2 huff-n-puff process for multistage-fractured horizontal wells in Wolfcamp A formation in the Delaware Basin. The potential for enhanced oil recovery and CO2 sequestration simultaneously was addressed using a coupled geomechanics-reservoir simulation. Geomechanical properties were derived from a 1D mechanical earth model and integrated into reservoir simulation to replicate hydraulic fracture geometries. The fracture model was validated using a robust production history matching. Fluid phase behavior analysis refined the equation of state, and 1D slim tube simulations determined a minimum miscibility pressure of 4300 psi for CO2 injection. After the primary production phase, various CO2 injection rates were tested from 1 to 25 MMSCFD/well, resulting in incremental oil recovery ranging from 6.3% to 69.3%. Different injection, soaking, and production cycles were analyzed to determine the ideal operating condition. The optimal scenario improved cumulative oil recovery by 68.8% while keeping the highest CO2 storage efficiency. The simulation approach proposed by this study provides a systematic workflow for evaluating and optimizing CO2 huff-n-puff in hydraulically fractured wells, enhancing the recovery factor of unconventional reservoirs.

This comprehensive article explores Massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, Cell-Free MIMO, and security considerations, the article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of Federated Learning in M-MIMO systems. By examining these cutting-edge developments, the article aims to contribute to advancing knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.

Soybean seed sugars are among the most abundant beneficial compounds for human and animal consumption in soybean seeds. Higher seed sugars such as sucrose are desirable as it contributes to taste and flavor in soy-based food. Therefore, the objectives of this study were to use ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) soybean population (n=309) to identify quantitative trait loci (QTL) and candidate genes that control seed sugar (sucrose, stachyose, and raffinose) contents in two environments (North Carolina and Illinois) over two years (2018 and 2020). A total of 26 QTL that control seed sugars contents were identified and mapped on 16 soybean chromosomes (chrs.). Interestingly, five QTL regions were identified in both locations, Illinois and North Carolina, in this study on chrs. 2, 5, 13, 17, and 20. Amongst 57 candidate genes identified in this study, 16 were located within 10 Megabase (MB) of the identified QTL. Amongst them a cluster of four genes involved in the sugars’ pathway was collocated within 6 MB with two QTL that were detected in this study on chr. 17. Further functional validation of the identified genes could be beneficial in breeding programs to produce soybean lines with high beneficial sucrose and low raffinose family oligosaccharides.

The steep decline in the price of wind and solar photovoltaics provides a possibility to decarbonize electricity deeply and affordably. This study uses HOMER Pro energy modeling tool to model an optimized grid-connected renewable energy system for a community in southern Alberta, Canada. The study's goal is to identify the best renewable energy technology combinations that can provide electricity at the lowest levelized cost of energy (LCOE) and has lesser greenhouse gas emission as compared to the electricity produced by traditional fossil fuel. Gleichen, is a small town in southern Alberta and is near to numerous commercial wind and solar projects given the region’s high quality renewable resources. “Tri-brid” systems consisting of wind turbines, solar photovoltaics, and battery energy storage systems (BESS) are considered and compared based on electricity prices, net present cost, and greenhouse gas emissions savings. This tri-brid system is connected to the grid to sell excess electricity generated or buying electricity when there is less or no availability of solar and wind. The tri-brid energy system has an estimated LCOE of 0.0705 CAD/kWh which is competitive with the price of electricity generated by natural gas and coal which is 0.127 CAD/kWh.

The topological index is a numerical quantity based on the characteristics of various invariants or molecular graph. For ease of discussion, these indices are classified according to their logical derivation from topological invariants rather than their temporal development. Degree based topological indices depends upon the degree of vertices. This paper computes Zagreb polynomials and redefined first, second and third Zagrebindices of Bismuth Tri-Iodide chains and sheets.

As technology advances, people are increasingly adopting IoT (Internet of Things) devices in smart cities. These devices are equipped with sensors that are connected everywhere, from energy infrastructure and transportation to telecommunications, health and human services, waste management, public safety, and more. People want to access sensor data anytime and everywhere to make better decisions and improve their lives. To achieve this, a sensor integration model has been developed where multiple sensors are integrated under one gateway to manage and share sensor data. However, effective sharing of sensor data requires data security, privacy, confidentiality, fairness, effective architectural design, and low communication and computation costs. These issues need to be addressed in the sensor integration model in smart cities. Existing storage models face challenges in managing sensor data effectively. To overcome these issues and hurdles, a data storage framework leveraging blockchain technology has been proposed within the sensor integration model. This framework ensures data security, privacy, confidentiality, and a fair and transparent financial model, all while minimizing communication and computation costs.

Unmanned aerial vehicles (UAV) provide an unprecedented capacity to monitor the development and dynamics of tree growth and structure through time. It is generally thought that the pruning of tree crops encourages new growth, has a positive effect on fruiting, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. To establish the response of pruning in an orchard of lychee trees, an assessment of changes in tree structure, i.e. tree crown perimeter, width, height, area and Plant Projective Cover (PPC), was undertaken using multi-spectral UAV imagery collected before and after a pruning event. While tree crown perimeter, width and area could be derived directly from the delineated tree crowns, height was estimated from a produced canopy height model and PPC was most accurately predicted based on the NIR band. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in tree crown perimeter of 1.94 m, tree crown width of 0.57 m, tree crown height of 0.62 m, tree crown area of 3.5 m², and PPC of 14.8%. In order to provide guidance on data collection protocols for orchard management, the impact of flying height variations was also examined, offering some insight into the influence of scale and the scalability of this UAV based approach for larger orchards. The different flying heights (i.e. 30, 50 and 70 m) produced similar measurements of tree crown width and PPC, while tree crown perimeter, area and height measurements decreased with increasing flying height. Overall, these results illustrate that routine collection of multi-spectral UAV imagery can provide a means of assessing pruning effects on changes in tree structure in commercial orchards, and highlight the importance of collecting imagery with consistent flight configurations, as varying flying heights may cause changes to tree structural measurements.

Traditional silicon binary circuits continue to face challenges such as high leakage power dissipation and large area of interconnections. Multiple-Valued Logic (MVL) and nano-devices are two feasible solutions to overcome these problems. In this paper, we present a novel method to design ternary logic circuits based on Carbon Nanotube Field Effect Transistors (CNFETs). The proposed designs use the unique properties of CNFETs, e.g., adjusting the Carbon Nanotube (CNT) diameters to have the desired threshold voltage and have the same mobility of P-FET and N-FET transistors. Each of our designed logic circuits implements a logic function and its complementary via a control signal. Also, these circuits have a high impedance state which saves power while the circuits are not in use. We show a more detailed application of our approach by designing a two-digit adder-subtractor circuit. We simulate the proposed ternary circuits using HSPICE via standard 32nm CNFET technology. The simulation results indicate the correct operation of the designs under different process, voltage and temperature (PVT) variations. Moreover, we designed a two-digit adder/subtractor and a power efficient ternary logic ALU based on the proposed gates. Simulation results show that the two-digit adder/subtractor using our proposed gates has 12X and 5X lower power consumption and PDP (power delay product) respectively, compared to previous designs.

It is unavoidable that the characteristics of the robot system alter inexactly or cannot be correctly determined during movement and are impacted by external disturbances. There are many adaptive control methods, such as sliding control or neural control, to improve the quality of trajectory tracking for robot motion systems. Still, those methods require a large amount of computation related to solving the problem of constrained nonlinear optimization problem. The article presents some techniques for determining an intelligent controller's online learning function parameters, including two circuits: the inner circuit is a state feedback linearized controller, and the outer course is an Interactive learning controller and does not use the robot's mathematical mode with function parameters online optimal learning and intelligent online learning closely following the joint model to stabilize the robot system. Finally, the 2-DOF planar robot simulation is performed on Matlab software R2022b. The findings indicate that outstanding tracking performance is achievable.

The topological index is a numerical quantity based on the characteristics of various invariants or molecular graph. For ease of discussion, these indices are classified according to their logical derivation from topological invariants rather than their temporal development. Degree based topological indices depends upon the degree of vertices. This paper computes degree based topological indices of Bismuth Tri-Iodide chains and sheets with the help of M-polynomial.

This study aims to determine the cash sales accounting information system that is suitable for online store applications. Using qualitative methods with the object of research, namely the online stores. Sources of data obtained from several online stores. Data collection methods used are semi-structured interviews, observation, and document analysis. From the analysis and design of the buying and selling cycle information system in online business development, it was found that the development of information systems is a very important stage in the efficiency and effectiveness of the buying and selling cycle. By implementing a good and correct accounting information system design on an online store, it can facilitate the recording and minimize the occurrence of errors/loss of data. In addition, with a good information system design, the division of tasks between various sections becomes clear.

Babies born prematurely are at risk of experiencing visual disturbances, hearing loss, disabilities, the risk of infection and even death. Care for premature babies requires serious attention for both health workers and parents. The role of parents is very important both during hospitalization and at home. Therefore, in order to improve the abilities of parents, it is necessary to make educational efforts with the right method.ObjectivesThis literature review aims to provide an overview of educational methods that nurses can use to improve the ability of parents to care for or care for the development of premature babies. The method used is to search for literature that fits the established theme using 5 data based, namely Scopus, ProQuest, Science Direct, Elsevier Clinicaly for Nursing and Web of Science. The strategy used in finding literature that fits the theme and is used in this literature review uses the PICOS framework. Then conducted a review with the PRISMA method. The literature selection results obtained 572 publications, after going through the selection obtained 11 literatures that match the theme, with 11 educational methods. These methods can be grouped into ideas, namely increasing parental involvement during treatment, using technology, stress management and continuous monitoring. The ability of parents to care for premature babies is needed in order to minimize complications in infants, reduce morbidity, avoid disabilities, increase growth and development of premature babies optimally and reduce parental stress levels, increase parental confidence and good parents' self-efficacy. Choosing the right educational method can improve the ability of parents to properly care for and provide developmental care for premature babies.

Diseases pose a significant and pressing concern for the sustainable development of the aquaculture sector, particularly as their impact continues to grow due to climatic shifts such as rising water temperatures. While various approaches, ranging from biosecurity measures to vaccines, have been devised to combat infectious diseases, their efficacy is disease- and species-specific and contingent upon a multitude of factors. The field of genetics and genomics offer effective tools to control and prevent disease outbreaks in aquatic animal species. In this study, we present the key findings from our recent research, focusing on the genetic resistance to three specific diseases: White Spot Syndrome Virus WSSV) in white shrimp, Bacterial Necrotic Pancreatitis (BNP) in striped catfish and skin fluke (a parasitic ailment) in yellowtail kingfish. Our investigations reveal that all three species possess substantial heritable genetic components for disease resistant traits, indicating their potential responsiveness to artificial selection in genetic improvement programs tailored to combat these diseases. Also, we observed a high genetic association between disease traits and survival rates. Through selective breeding aimed at enhancing resistance to these pathogens, we achieved substantial genetic gains, averaging 10% per generation. These selection programs also contributed positively to the overall production performance and productivity of these species. Although the effects of selection on immunological traits or immune responses were not significant in white shrimp, they yielded favourable results in striped catfish. Furthermore, our genomic analyses, including shallow genome sequencing of pedigreed populations, enriched our understanding of the genomic architecture underlying disease resistance traits. These traits are primarily governed by a polygenic nature, with numerous genes or genetic variants, each with small effects. Leveraging a range of advanced statistical methods, from mixed models to machine and deep learning, we developed prediction models that demonstrated moderate to high levels of accuracy in forecasting these disease-related traits. In addition to genomics, our RNA-seq experiments identified several genes that undergo upregulation in response to infection or viral loads within the populations. Preliminary microbiome data, while offering limited predictive accuracy for disease traits in one of our studied species, underscore the potential for combining such data with genome sequence information to enhance predictive power for disease traits in our populations. Lastly, this paper briefly discusses the roles of precision agriculture systems, AI algorithms, and outlines the path for future research to expedite the development of disease-resistant genetic lines tailored to our target species. In conclusion, our study underscores the critical role of genetics and genomics in fortifying the aquaculture sector against the threats posed by diseases, paving the way for more sustainable and resilient aquaculture development.

Extracts of Cordyceps militaris which possess the bioactive capacity such as antimicrobial activity and DPPH-free radical scavenging capacity, are applied to the serum product. This finished serum product has been evaluated the in vitro bioactivity and the stability with expect to find out a good extract with a suitable percentage used for serum product as natural materials on preservatives and antioxidation.

This research investigates precision enhancement in regional quasi-geoid refinement through ADS80 tri-linear array scanning stereoscopic imagery for aerial triangulation, coupled with GNSS gravity-potential modeling. Acquiring stereoscopic imagery and analyzing triangulation accuracy with the ADS80 camera, we performed this study over the Qinghai-Tibet Plateau's elevated, desolate terrain, collecting 593 GNSS points following high-precision stereoscopic imagery model. Utilizing 12 gravity satellite models, we computed geoid heights and China 1985 Yellow Sea elevations for 28 benchmarks and GNSS points, thereby refining the Qinghai Province Quasi-Geoid Model (QPQM) using geometric techniques. The findings reveal that POS-assisted ADS80 stereoscopic imagery yields high-precision triangulation with maximal horizontal and elevation accuracies of 0.083/0.116 cm and 0.053/0.09 cm, respectively, across five control point arrangements. The RMSE of normal heights for 1985, processed via these GNSS points, achieved decimeter precision. By applying error corrections from benchmarks to the 1985 elevation data from gravity satellites and performing weighted averaging, the precision of EGM2008, SGG-UGM-2, and SGG-UGM-1 models improved to 8.61 cm, 9.09 cm, and 9.38 cm, respectively, surpassing the QPQM by 9.22 cm to 9.99 cm. This research demonstrates that the proposed methods can significantly enhance the precision of regional quasi-geoid surfaces. Additionally, these methods offer a novel approach for rapidly establishing regional quasi-geoid models in the uninhabited areas of the Qinghai-Tibet Plateau.

Objective: This study aimed to demonstrate the availability of portable devices for nasal FeNO measurement, which could replace exhaled NO measurement based on the continuous aspiration of multiple flow measurement systems. Methods: A descriptive cross-sectional study. The healthy subjects without rhinosinusis disorders (control group) and those with diagnosed allergic rhinitis (AR group) were enrolled in the study. They underwent nasal and bronchial FeNO measurements by both fixed flow NObreath® connected to nasal mask and multiple flows HypAir FeNO®. Results: A total of 153 people were recruited including 63 healthy subjects and 90 subjects with AR. There were no statistically significant differences in anthropometric characteristics between the two groups (P > 0.05). There were a significant increase in FeNO values in the AR group compared to the control group; concentrations of nasal and bronchial FeNO mearsured by NObreath® were 76.0 ± 50.7 ppb (vs 36.0 ± 28.1 ppb, P < 0.01) and 32.3 ± 15.4 ppb (vs 9.2 ± 5.6 ppb, P < 0.001), and those mearsured by NObreath® Hypair FeNO® were 1796.9 ± 523.3 ppb (vs 400.2 ± 123.1 ppb, P < 0.001) and 37.3 ± 23.0 ppb (vs 17.4 ± 18.3 ppb, P < 0.01). A weak correlation between the values measured by NObreath® and Hypair FeNO® devices was observed (r = 0.023 and r = 0.089, respectively; p < 0.05). Conclusions: The handheld NObreath® device is effective in measuring FeNO concentrations in both normal subjects and AR patients. The advantages in price and size, creating a compact, low-cost device that is convenient for use and research.

A very high-resolution DSM covering an area of 400km² over the Athens Metropolitan Area has been produced using Pleiades 1B 0,5m panchromatic tri-stereo images. Applied Remote Sensing and Photogrammetry tools have been used resulted in a 1x1m DSM over the study area. DSM accuracy has been evaluated by comparison with measured elevations with D-GPS and a reference DSM provided by the National Cadaster & Mapping Agency S.A. In addition, different combinations of stereo images have been prepared for further exploitation of the quality of the produced DSM by stereo vs. tri-stereo images. Results show that the produced by the tri-stereo images DSM has an RMSE of 1.17m in elevation (z), which is among the best reported in the relevant literature. Stereo based DSMs from the same sensor have worst performance to this end. Satellite Remote Sensing (SRS) based DSMs over urban areas provide the best cost-effective approach in comparison to airborne-based datasets due to high spatial coverage, lower cost and high temporal coverage. Pleiades-based high-quality DSM products can serve the domains of urban planning/climate, hydrological modelling and natural hazards, as major input for simulation models and morphological analysis at local scale.

Neuroinflammatory responses are implicated in the pathogenesis of neurodegenerative diseases. In neurodegenerative diseases, neuroinflammatory reactions to neuronal injury are modulated by microglial cells, which are vital innate immune cells in the central nervous system. Activated microglial cells release proinflammatory cytokines, mediators, and neurotoxic factors that induce fatal neuronal injury. The present study investigated the anti-neuroinflammatory effects of cudratricusxanthone L (1), which was isolated from Cudrania tricuspidata. This compound reduced the levels of lipopolysaccharide-stimulated inflammatory mediators and cytokines, including nitric oxide, prostaglandin E2, interleukin (IL)-1β, tumor necrosis factor-α, IL-6, and IL-12. These effects suggested that cudratricusxanthone L (1) suppressed the nuclear factor-kappa B (NF-κB) signaling pathway. Specifically, cudratricusxanthone L (1) also attenuated the phosphorylation of Jun kinase and inhibited p38 mitogen-activated protein kinase (MAPK) signaling in BV2 and rat primary microglial cells. These results indicated that cudratricusxanthone L (1) effectively repressed neuroinflammatory processes in BV2 and rat primary microglial cells by inhibiting NF-κB and the MAPK signaling pathway.

Lean is one of the systematic approach to achieve higher value for organizations through eliminate non-value-added activities. It is an integrated set of tools, techniques, and principles designed to optimize cost, quality and delivery while improving safety. In Vietnam, industry waste management and treatment has become serious issue. The aim of this research is to present the effective of Lean application for industrial wastes collecting and delivery improvement. Through a case study, this paper showed the way of Lean tools and principles applied for wastes management and treatment such as Value Stream Mapping, Pull system, Visual Control, and Andon.... to get benefit on both economic and environment. In addition, the results introduced a good experience for Vietnamese enterprises in cost saving and sustainable development in waste management.

This research delves into librarians' perceptions of artificial intelligence (AI) support in learning experiences, lifelong learning, and digital literacy within the library context, undertaking a comparative analysis between Malaysia and Indonesia. Employing a survey methodology, a self-developed questionnaire was administered to 59 librarians in Malaysia and 85 in Indonesia. The questionnaire, utilizing a Likert scale, systematically explored subjective judgments on AI's impact across various dimensions. A noteworthy finding is the consistent and harmonized perception among librarians in both countries, underscoring a universal recognition of AI's perceived support for learning experiences, lifelong learning, and digital literacy. Of particular interest is the emphasis on sustainability in librarians' perspectives, as they recognize the enduring value of AI in fostering educational growth. Despite the limitations inherent in perceptual measures and a relatively modest sample size, the empirical and practical contributions of this study are significant. It offers a nuanced exploration of librarians' viewpoints, providing valuable insights for future research endeavors. Moreover, the study's findings have immediate practical implications for the integration of AI tools in library services, policy-making, and professional development, with a focus on ensuring sustainable implementation for long-term benefits.

Communication, compression of information, transmission of information through noisy channels, interconnecting different information systems, cryptography, gate construction –– these areas all depend on classical information theory. We show that, in classical terms, semantic aspects of communication are not at all irrelevant to the engineering problem, contrary to Shannon, and affect the message intended to be transmitted. This is revisited and captured by an analogy to trust, in that they are essential to the channel (for proper use), but cannot be transferred (under risk of flaws) through that same channel. Information is also described by, at least, a tri-state system — not by binary logic. The trust analogy semantics can be coded as the Curry-Howard relationship, connecting computer code with structural logic, by way of different categories. Two-state and Boolean logic (aka Shannon semantics) was used classically before, with Shannon theory, but without trust analogy semantics – found to be a sine qua non condition. This is now familiar in classical gate construction with physical systems with, e.g., Verilog and SystemVerilog. The applications to computation and quantum theory are further explored. The most fundamental entity in today`s theory of information is proposed to use at least three logical states, not bits, in all applications, including: cyber-physical systems, devices, in computation, and in quantum theory.

Fluctuating stock prices make it difficult for investors to see investment opportunities. One tool that can help investors overcome this is forecasting techniques. Long Short-Term Memory (LSTM) is one of deep learning methods used in forecasting time series. The training and success of deep learning is strongly influenced by the selection of hyperparameters. This research uses a hybrid method between the Genetic Algorithm (GA) and LSTM to find a suitable model for predicting stock prices. GA is used in optimizing the architecture such as the number of epochs, window size, and the number of LSTM units in the hidden layer. Tuning optimizer is also carried out using several optimizers to achieve the best value. From method that has been applied, it shows that the method has a good level of accuracy with MAPE values below 10% in every optimizer used. The error rate generated is quite low, in case-1 with a minimum RMSE value of 93.03 and 94.40, & in case-2 with an RMSE value of 104.99 and 150.06 during training and testing. A fairly stable and small value is generated by setting it using the Adam Optimizer.

Due to its application as an anti-cancer drug, pazopanib (1) has attracted the interest of many researchers and several studies on pazopanib synthesis have been reported over the years. This paper provides a novel route for synthesizing N,2,3-trimethyl-2H-indazol-6-amine (5) which is a crucial building block in the synthesis of pazopanib from 3-methyl-6-nitro-1H-indazole (6). By alternating between the reduction and two methylation steps compound 5 was obtained in comparable yield (55.0%) to what has been reported (54%). Noteworthy, the last step of N2-methylation also yielded N,N,2,3-tetramethyl-2H-indazol-6-amine (5’) as a new compound ever reported. Furthermore, the data presented in this paper can serve as instrumental for future research aimed at further refining the synthesis process of pazopanib.

The utilization of gold nanoparticles (AuNPs) has garnered significant attention in recent times, particularly in the field of biomedical research. The utilization of AuNPs in chemical synthesis procedures raises apprehensions regarding their potential toxicity in living organisms, which is inconsistent with their purported eco-friendly and cost-effective aspects. In this investigation, AuNPs were synthesized via the green synthesis approach utilizing Jeju Hallabong peel extract (HPE), a typical fruit variety indigenous to South Korea. The visible-range absorption spectrum of gold nanoparticles from green synthesis (HAuNPs) that are red wine in color occurs at a wavelength of λ = 517 nm. The morphology and particle size distribution were analysed using transmission electron microscopy (TEM) and ImageJ software. The TEM images reveal that the HAuNPs exhibit a high degree of dispersion and uniformity in their spherical shape, with an average size of approximately 7 nm. Moreover, elevating the initial pH level of the mixed solution has an impact on the decrease in particle dimensions, as evidenced by the blue shift observed in the UV-visible spectroscopy absorbance peak. Elevating the reaction temperature may accelerate the synthesis duration. However, it does not exert a substantial impact on the particle dimensions. The outcomes of an avidin-biocytin colorimetric assay provide preliminary analyses of possible sensor tunability using HAuNPs. The cytotoxicity of HAuNPs was evaluated through in vitro studies using the MTT assay on RAW 264.7 cell lines. The results indicated that the HAuNPs exhibited lower cytotoxicity compared to both chemically reduced gold nanoparticles (CAuNPs) and commercially available gold nanoparticles (SAAuNPs).

Vietnam is the second largest coffee producer in the world, mostly from the Central Highlands region where water has been becoming a scarce resource. Since 2014, drought has been strongly affecting Central Highlands’ agriculture, particularly coffee production. The drought leads to changes in flowering, ripening and thus harvesting times of coffee. Coffee productivity has reduced about 50 percent. Ultimately, coffee quantity and quality is jeopardized which endangers coffee farmers who occupy 90 per cent of population and their livelihoods mainly rely on coffee. Most of coffee farmers have had to develop alternative strategies to respond to the drought. Based on quantitative and qualitative data collected from 50 coffee households in a community in the Central Highlands, this research has indicated that farmers had to find the ways to adapt as well as to cope with drought. The ways of adaptation and coping were diverse, including short, medium and long-term plans. To strengthen the adaptation and coping strategies of farmers with drought in the short term, it is recommended that authorities provide more technical and financial support to farmers. Furthermore, longer term strategies need to focus on land use planning, investment in irrigation schemes, and consolidated afforestation schemes in appropriate areas.

In the realm of physical activity and sports science, motion tracking emerges as an important tool for specialists aiming to analyze movement data, whether for daily life activities or enhancing athletic performance. This study introduces an innovative approach to motion tracking through the development of a fully embedded smart shoe sensor system, which employs an inertial measurement unit (IMU) affixed to the shoe sole, coupled with six pressure sensors, to provide real-time calculation of individual stride lengths along with other vital movement statistics. Traditional motion tracking methods, which typically rely on various body-attached sensors, often necessitate substantial post-processing, delaying the feedback loop. In contrast, our system is designed to overcome these limitations by offering high-accuracy, real-time feedback with a minimal error rate of 1.88% from our experiments. Such prompt data acquisition facilitates immediate interventions by sports performance coaches or healthcare professionals, significantly contributing to injury prevention and performance enhancement. The experimental outcomes of this study underscore the system’s capability to deliver precise stride length measurements instantaneously, marking a significant advancement in motion tracking technology and its application in sports science and healthcare.

The PB Sudirman hydroelectric power plant, built in 1988, has fewer than 50 years of operational life. In contrast, the planned operating life for this dam is 50 years. This dam is experiencing intensive sedimentation, which results in siltation. Dredging efforts and catchment area management are conducted to extend the operational life of the dam. Therefore, technical and economic analysis of dredging activities and the potential benefits of dredged sediment is needed to determine the solution's effectiveness. We use the site survey method to conduct an environmental impact analysis and interviews with dam managers. The identification of the extent and distribution of erosion-sedimentation was carried out as part of the technical assessment. In the economic study, we calculate the dredging costs and profits from selling dredged sediments, mainly sand. The analysis results show that the dredging of deposits in the foreset slope area is not profitable. There are 17 areas of bank spoil that have economic benefits. This study concludes that the need for dredging costs on foreset slopes is higher than the profit from selling dredging sediments.

Abstract. This paper proposes a Second Order Terminal Sliding Mode (2TSM) approach to the trajectory tracking of Differential Drive Mobile Robot (DDMR). Within this cascaded control scheme, the 2TSM dynamic controller, at the inner most loop, tracks the robot’s velocity quantities; while a kinematic controller, at the outer most loop, regulates the robot’s positions. In this manner, chattering is greatly attenuated and finite time convergence is guaranteed by the second order TSM manifold which involves higher order derivatives of the state variables, resulting in inherently robust as well as fast and better tracking precision. The simulation results demonstrate the merit of the proposed control methods.

The on-site wastewater treatment system (OWTS) with a sand trench is an economical option for residents in rural areas or the countryside where a centralised sewer system is inaccessible. 2A sand achieves improved filtration, microbial activity and consistent long term performance when compared to gravel or scoria based trench systems. However, it is expensive and only readily available in a few areas across New Zealand. Additionally, it has a reputation for premature blockage when overloaded or compacted. The aim of this study is not only to critically evaluate the performance of Crushed Glass (CG) with respect to 2A sand, but also to investigate different loading rates for CG when treating primary treated effluent from a septic tank. A test rig was designed and constructed to simulate the real environment of the sand column in a discharge control trench. The treatment efficiency of three filters was recorded and compared in this study. Overall, the CG loaded at 25mm/day (CG₂₅) and 50mm/day (CG₅₀) provided an average of 13% and 6% more Total Nitrogen (TN) reduction than the sand filter, respectively. The removal rates for the TN were up to 69.5%. The CG₅₀ filter performed similarly at 50mm/day as the 2A sand filter in terms of Total Suspended Solids (TSS) and Biochemical Oxygen Demand (BOD)₅ removal of more than 94%. The CG₂₅ removal rates for TSS and BOD₅ at the start of the trial (likely due to residual liquid contamination from the bottles when crushed) improved over the sampling period and ultimately achieved similar results of 92% and 91.3% to the filters loaded at 50mm/day. Lifecycle cost analyses and carbon balances were completed for the two media. It highlighted that the current price of CG is only half of 2A sand, yet it produces significantly less CO₂ emissions than 2A sand. A 3-bedroom dwelling could save up to $500 and reduce 200kg of CO₂ released to the environment annually when 2A sand is substituted for CG. Based on the findings of this paper, it is likely that the reduced installation cost, lessened environmental impact and theoretical availability will lead to CG systems becoming more common in New Zealand and abroad.

In this work, silver nanoparticles (AgNPs) were synthesized rapidly and eco-friendlily using the extract of Mulberry leaves and aqueous solution of silver nitrate without any toxic chemical [1,2]. The Mulberry leaves extract acts as both reducing agent and stabilizing agent. The UV-Vis spectrum shows peak at 430 nm. The TEM image of synthesized AgNPs sample shows spherical shaped particles whose size range from 15 to 20 nm. TEM image of nano silver solution sample synthesized by microwave assisted method shows nearly spherical particles with an average particle size of 10 nm. The absorption UV-vis spectrum of silver nanoparticles synthesized by microwave assisted method (AgNPsmw) shows a sharp absorption band around 415 nm. After two month storage of AgNPsmw, the absorption spectrum of AgNPsmw was taken again. The UV-Vis spectrum shows negligible peak changes of silver nanoparticles have occurred after two months of storage. The synthesized AgNPs material could be used as an antimicrobial, used in the field of textile and in wastewater treatment.

Antibiotic-free approaches are more important than ever to deal with the rapidly growing problem of antibiotic resistance. The blue light 460nm (BL460nm) has been shown to effectively attenuate Staphylococcus aureus to chemical and physical agents through photolysis of the bacterial virulence factor Staphyloxanthin. However, the phototherapy using BL640nm has yet to be investigated in detail for its safety in eradicating Staphylococcus aureus in vitro and in vivo. In this study, we used a LED source producing a continuous wavelength of 460 nm along with hydrogen peroxide to treat S. aureus in culturing conditions and a wound abrasion mouse model. The results proved the safety of the combined therapy when it did not modify the bacterial virulence factors or the susceptibility to the widely used antibiotics. In addition, the experimental results on the mouse skin infection model also showed that the combined therapy is safe to apply to mouse skin and that it did not cause adverse skin irritation. Furthermore, the therapy can help Staphylococcus aureus-infected wounds heal with efficacy comparable to the topical antibiotic Fucidin. The above results suggest that the combination therapy of 460nm blue light and hydrogen peroxide can be safely used as an alternative to or adjunct to antibiotics in treating S. aureus-infected wounds.

Integrated Fixed Film Activated Sludge (IFAS) technology greatly enhances nitrogen removal effectiveness and treatment capacity in municipal wastewater treatment plants, addressing the issue of limited land availability. Hence, this method is appropriate for treating household wastewater from office buildings. The research was conducted at the wastewater treatment plant in an office building in Ho Chi Minh City, Vietnam. Experiments were conducted to ascertain the most favorable working conditions, including Hydraulic Retention Time (HRT), alkalinity dosage, and Dissolved Oxygen (DO). According to the study, the IFAS system had the highest nitrogen removal effectiveness when operated at a hydraulic retention time (HRT) of 7 hours, an alkalinity dose of 7.14 mgCaCO3/mgN-NH4+, and a dissolved oxygen (DO) value of 6 mg/L. The nitrification efficiency ranges from 89.2% to 98.8%. The nitrate concentration post-treatment is within the range of 27 – 45 mg/L, which is lower than the allowable discharge limit of 60 mg/L as per Vietnam's wastewater discharge requirements. The research findings have enhanced the efficiency of the office building management process, thereby promoting the sustainable growth of society.

While the container crane is an important part of daily port operations, it has received little attention compared with other infrastructures, such as buildings and bridges. Crane collapse due to earthquake affects the operation of the port, and indirectly impacts the economy. This study proposes fragility analyses for various damage levels of the container crane that allow the port owner and partners to better understand the seismic vulnerability presented by container cranes. A large quantity of nonlinear time history analyses was applied for a three-dimensional (3D) finite element model to quantify the vulnerability of the container crane in considering the uplift and derailment behavior. The uncertainty of demand and capacity of the crane structures were also considered through random variables, i.e. elastic modulus of members, ground motion profile, and intensity. The results analyzed in the case of a Korean container crane showed that the probability of exceeding the first uplift with or without derailment is shown before the crane reaches the structure’s limit states. This means that under low seismic excitation, the crane might be derailed without any structural damage. But when the crane reaches the minor damage state, it is always coupled with a certain probability of uplift with or without derailment. This study also proposes the fragility curves developed for different structural periods to enable port stakeholders to assess the risk of their container crane.

An explosive growth in vehicular wireless services and applications gives rise to spectrum resource starvation. Cognitive radio has been used to vehicular networks to mitigate the impending spectrum starvation problem by allowing vehicles to fully exploit spectrum opportunities unoccupied by licensed users. Efficient and effective detection of licensed user is a critical issue to realize cognitive radio applications. However, spectrum sensing in vehicular environments is a very challenging task due to vehicles mobility. For instance, vehicle mobility has a large effect on the wireless channel, thereby impacting the detection performance of spectrum sensing. Thus, gargantuan efforts have been made in order to analyze the fading properties of mobile radio channel in vehicular environments. Indeed, numerous studies have demonstrated that the wireless channel in vehicular environments can be characterized by a temporally correlated Rayleigh fading. In this paper, we focus on energy detection for spectrum sensing and a counting rule for cooperative sensing based on Neyman-Pearson criteria. Further, we go into the effect of the sensing and reporting channels condition on spectrum sensing performance under temporally correlated Rayleigh sensing channel. For local and cooperative sensing, we derive some alternative expressions for average probability of miss detection. The pertinent numerical and simulating results are provided to further validate our theoretical analyses under a variety of scenarios.

A simple and sensitive liquid chromatography-tandem mass spectrometry (LC– MS/MS) method has been developed for the simultaneous determination of atorvastatin (ATOR), ezetimibe (EZM) and their three metabolites including o-hydroxyl atorvastatin (o-OH ATOR), p-hydroxyl atorvastatin (p-OH ATOR), and ezetimibe-glucuronide (EZM-G) in human plasma using benzyl paraben (BP) as internal standard (IS). The analytes and IS were ionized using ESI positive ion mode (ATOR, o-OH ATOR, and p-OH ATOR), ESI negative ion mode (EZM, EZM-G, and BP), and operated in multiple reaction monitoring (MRM) mode. They were next extracted by salting-out assisted liquid–liquid extraction with acetonitrile, and then analyzed by liquid chromatography on a reversed-phase chromatographic column (50 mm × 4.6 mm; 3.5 µm), using a mixture of ac-etonitrile and an acetic acid solution (0.5%) as the mobile phase, showing high extraction effi-ciency (>70%), and a minimized matrix effect. The method was satisfactorily validated, and showed excellent linearity over wide concentration ranges of 0.06–15 ng/mL, 0.6–150 ng/mL, 0.4–100 ng/mL, 0.12–30 ng/mL, and 0.05–3 ng/mL for EZM, EZM-G, ATOR, o-OH ATOR, and p-OH ATOR, respectively.

A derivative series of 3,4-dimethoxy-β-nitrostyrene were synthesized and identified including new compound 6. The effect of antimicrobial activity of 3,4-alkyloxy modification of β-nitrostyrene was investigated. A molecular docking was also performed to obtain information about their interactions with Protein Tyrosine Phosphatase 1B (PTP1B). PTP1B containing cysteine 215 and arginine 221 as essential active residues plays a key role in signaling pathways that regulate various cell functions of microorganisms, which also act as negative regulator in signaling pathways of insulin that are involved in type 2 diabetes and other metabolic diseases. Compound 5 and 6 were the most potent as fragment of PTP1B inhibitor based on molecular docking, but compound 5 was more effective against Candida albicans. These compounds interact with serine 216 and arginine 221 residues. However, further research is needed to investigate their potential medicinal use.

Lipid nanoparticles have an interesting part of drug delivery system. In this study, the modification of the convention nano-lipid based soybean lecithin was demonstrated. Ginger oil derived Zingiber officinale was used along with lecithin, cholesterol and span 80 to fabricate nano-lipid (GL nano-lipid) using thin-film method. Through TEM and confocal microscope, GL nano-lipid exposes the liposome- like morphology. The average size of the resultant nanoparticles was 249.1nm with monodistribution (PDI= 0.021). The ζ-potential of GL nano-lipid was negative as similar to as prepared nano-lipid based lecithin. GL nano-lipid express the highly stable over 60 days of storage at room temperature in term of size, ζ-potential. A shift of pH value from alkaline to acid was detected in lecithin nano-lipid, while with the incorporation of ginger oil, pH value of nano-lipid dispersion was around 7.0. Furthermore, due to the rich of shogaol-6 and other active compounds in ginger oil, the GL nano-lipid is endowed with intrinsic antibacterial feature. In addition, the sulforhodamine B (SRB) assay and live/dead imaging revealed the excellent biocompatibility of GL nano-lipid. Notably, GL nano-lipid was capable to carry the hydrophobic agents as curcumin and perform a pH-dependent release profile. A subsequent characterization are a suitable potential for drug delivery system.

AI integration is becoming more important in today’s world and could potentially be very useful in the life sciences and biotechnology. This study evaluates the effectiveness of AI systems in teaching molecular cloning techniques to newcomers in molecular biology, focusing on a comparison between Gemini Advanced (powered by Gemini Ultra 1.0) and ChatGPT (GPT-4o). Molecular or DNA cloning is a lab technique for creating multiple copies of a specific DNA segment. It involves isolating the DNA fragment, inserting it into a vector, and introducing it into a host cell, typically bacteria, which then generates numerous copies of the DNA. This essential technique underpins genetic engineering, allowing for gene study, protein expression, and the creation of genetically modified organisms. The primary objective of this study was to assess whether individuals with limited laboratory experience could effectively acquire a specific molecular biology skill set solely through an AI system, rather than relying on the more traditional ‘learning by shadowing’ approach. Participants with limited lab experience completed these tasks using both Gemini and GPT-4o, and evaluated on quality of instructions, conciseness, scientific accuracy, and user satisfaction. Results indicated that both AI systems demonstrated strengths in delivering clear and comprehensive instructions, but in different ways. Gemini, although more interactive with images and diagrams lacked directness and had a harder time keeping past steps in its “memory”. On the other hand, GPT-4o was much more direct and concise in the steps listed and had more accurate results akin to what is performed in the lab. This study underscores the potential of AI-driven tools to simplify complex biotechnological procedures, making them accessible for learners at all levels.

Accurate pathogenic detection in wastewater is critical for safeguarding public health and the environment. However, the presence of free nucleic acids in wastewater samples poses significant challenges to molecular detection accuracy. This comprehensive review explores the current status and future potential of pretreatment methods to remove free nucleic acids from wastewater samples. The study contributes a comprehensive analysis of the mechanisms, strengths, and limitations of various pretreatment approaches, including physical, chemical, and enzymatic processes. The effect of various factors on the removal efficiency of these pretreatment methods is also discussed. This review enhances our comprehension of pretreatment techniques and their vital role in achieving precise pathogenic detection in complex wastewater matrices. Furthermore, it outlines future perspectives and developments for improving the speed and effectiveness of pathogenic detection, contributing significantly to disease surveillance, early warning systems, and environmental protection.

The material flow dynamic and velocity distribution on the melted domain surface play a crucial role on the joint quality and formation of welding defects. In this study, authors investigated the effects of the low and high currents of plasma arc welding on the material flow and thermodynamics of molten pool and its relationship to the welding defects. The high-speed video camera (HSVC) was used to observe the convection of the melted domain and welded-joint appearance. Furthermore, to consider the Marangoni force activation, the temperature on the melted domain was measured by a thermal HSVC. The results revealed that the velocity distribution on the weld surface was higher than that inside the molten weld pool due to the difference of the massive density between the air and the steel. Moreover, in the case of low welding current (80A) the convection speed of molten was faster than that of the high welding current case (160A) owing to the difference of main driving forces direction and strength, which leading to undercut and humping defects on the weld surface and excessive convex (burn-through) defect at the bottom weld side, respectively. The medium welding current (120A) had two convection patterns with the main flow in backward direction, which resulted in better welding quality without defect. The interaction between the shear force and Marangoni force played a solid state on the convection and heat transportation processes in the plasma arc welding process.

The Soil and Water Assessment Tool (SWAT) is one of the most widely used hydrologic models. SWAT has been undergoing constant changes since its development. However, compartment review and testing of SWAT are comparably limited, especially the flood routing functions. In this study, the daily flood routing subroutines of different SWAT versions were reviewed and tested using a well observed segment of the Weser river located in Germany. Results show several problems with the flood routing subroutines of SWAT. The variable storage subroutine of SWAT (revision 664) does not transform the flood wave. Unphysical results could be obtained with the variable storage routing of SWAT (revision 528). The Muskingum subroutine of SWAT (revisions 664 and 528) overestimates channel evaporation (resulting in a bias of 14\% to 19% in streamflow) and underestimates transmission losses. Simulated results show that the timing and shape of the flood wave could be improved with a corrected Muskingum subroutine. Based on the results of this study, we suggest the SWAT user community to review their existing SWAT models to see how the aforementioned issues will affect their methods, findings and conclusions.

Polyploid seeds production is laborious, complicated, and costly work. Tetraploid and triploid plants produce a fewer number of seeds/fruit, and triploid embryos are fairly weak, covered with a more hardened seed coat as compared to diploid seeds. Here we investigated the interactive effect of new grafting technique of polyploid watermelon scion onto rootstock on plants' survival rate, biochemical, and hormones contents. In this study, three different branches, apical meristem (AM), branch with 1 node (1N), and 2 nodes (2N) from di, Tri, and tetraploid watermelon plants, were used as scion and grafted onto squash rootstock. The results showed highly significant differences between polypoid watermelon when 1N using as a scion, tetraploid showed maximum survival rates, higher contents of hormones, and antioxidants (AOX) activities, compared to diploid, these may be the possible reasons for high compatibility in tetraploid and degrading the grafting zone in diploid. RTq-PCR results confirm that the expression of genes linked to compatibility is consistent with the hormonal and AOX activities. This study provides an alternative and economical approach to produce more tetraploid and triploid plants for breeding or seeds production by using branches as scions.

The energy transition towards Net Zero Emission by 2060 hinges on the renewable energy power plants in Indonesia. Good practices in several countries suggest a peer-to-peer (P2P) energy trading system using blockchain technology, supported by renewable energy (solar panels), an innovation to provide equal access to sustainable electricity while reducing the impact of climate change. The P2P energy trading concept has a higher social potential than the conventional electricity buying and selling approach, such as that of PLN (the grid management concept), but does not have a sharing element. This model implements a solar-powered mini-grid system and produces a Smart Contract that facilitates electricity network users to buy, sell, and trade electricity in rural areas via smartphones. This study aims to analyze the stakeholders' perceptions of the peer-to-peer (P2P) energy trading model using blockchain technology in Gumelar District, Banyumas Regency, Central Java Province, Indonesia. The stakeholders include households, the Ministry of Energy and Mineral Resources (ESDM), the State Electricity Company (PLN), the Institute for Essential Services Reform (IESR), Awina Company, and IPB University. The strength factors of this model are the freedom to generate and sell electricity (0.1) and transparency in electricity usage and sales by disclosing the amount, duration, and price of electricity (0.1). Regarding weakness factors, this model is primarily suitable for the lower middle class residing in rural or remote areas (0.02). Additionally, the intermittent electricity production to meet the substantial demand is a weakness (0.03). The opportunity factor for the model is the increase in public awareness and cooperation in using environmentally friendly, pollution-free electricity (0.12). Furthermore, there is an opportunity for additional income (0.12) and new business investment (0.12). Regarding threat factors, the model faces significant threats from the implementation aspect involving multiple parties (0.04). There is a potential threat in the form of losses for state utilities such as PLN or individuals who have already established electricity infrastructure if this program is implemented on a large scale (0.04). This model is located at the coordinate point (-0.40; 0.31), placing it in quadrant II. This indicates that the model should apply the Stability Strategy and focus on the Selective Maintenance Strategy for improvement. The stability strategy goal is to maintain the current situation by leveraging opportunities and addressing weaknesses. For effectiveness and efficiency, the strategy emphasizes fostering collaboration with PLN, which holds the legal authority as the sole utility company in Indonesia with an extensive electricity network, as well as advocating for regulations that support the independent purchase and sale of solar-powered electricity, particularly in areas without PLN network coverage.

Generative artificial intelligence (GenAI) has been developing with many incredible achievements like ChatGPT and Bard. Deep generative model (DGM) is a branch of GenAI, which is preeminent in generating raster data such as image and sound due to strong points of deep neural network (DNN) in inference and recognition. The built-in inference mechanism of DNN, which simulates and aims to synaptic plasticity of human neuron network, fosters generation ability of DGM which produces surprised results with support of statistical flexibility. Two popular approaches in DGM are Variational Autoencoders (VAE) and Generative Adversarial Network (GAN). Both VAE and GAN have their own strong points although they share and imply underline theory of statistics as well as incredible complex via hidden layers of DNN when DNN becomes effective encoding/decoding functions without concrete specifications. In this research, VAE and GAN is unified into a consistent and consolidated model called Adversarial Variational Autoencoders (AVA) in which VAE and GAN complement each other, for instance, VAE is good at generator by encoding data via excellent ideology of Kullback-Leibler divergence and GAN is a significantly important method to assess reliability of data which is realistic or fake. In other words, AVA aims to improve accuracy of generative models, besides AVA extends function of simple generative models. In methodology this research focuses on combination of applied mathematical concepts and skillful techniques of computer programming in order to implement and solve complicated problems as simply as possible.

Expectation maximization (EM) algorithm is a powerful mathematical tool for estimating statistical parameter when data sample contains hidden part and observed part. EM is applied to learn finite mixture model in which the whole distribution of observed variable is average sum of partial distributions. Coverage ratio of every partial distribution is specified by the probability of hidden variable. An application of mixture model is soft clustering in which cluster is modeled by hidden variable whereas each data point can be assigned to more than one cluster and degree of such assignment is represented by the probability of hidden variable. However, such probability in traditional mixture model is simplified as a parameter, which can cause loss of valuable information. Therefore, in this research I propose a so-called conditional mixture model (CMM) in which the probability of hidden variable is modeled as a full probabilistic density function (PDF) that owns individual parameter. CMM aims to extend mixture model. I also propose an application of CMM which is called adaptive regressive model (ARM). Traditional regression model is effective when data sample is scattered equally. If data points are grouped into clusters, regression model tries to learn a unified regression function which goes through all data points. Obviously, such unified function is not effective to evaluate response variable based on grouped data points. The concept “adaptive” of ARM means that ARM solves the ineffectiveness problem by selecting the best cluster of data points firstly and then evaluating response variable within such best cluster. In order words, ARM reduces estimation space of regression model so as to gain high accuracy in calculation.

Magnetorheological (MR) fluid is recognized as one of intelligent materials that is widely used for various kinds of controllable devices since its rheological characteristics can be controlled by an external magnetic field (or input current). However, the density mismatch of the compositions between iron particles and carrier oil leads to inevitable sedimentation. Therefore, many works on the sedimentation problem of MR fluids have been carried out to improve the sedimentation stability using appropriate additives, surfactants, nanoparticles, particle coating as well as using several carrier oils with different densities. However, a study on the effect of the current magnitudes and profiles on the sedimentation is considerably rare. This study experimentally investigates the sedimentation behaviors due to the different current magnitudes and different profiles such as square and sine wave. It is shown that average sedimentation rate is 98.61% by applying 1 A of the square wave, while it is 97.83% under the sine type of the current. It is also identified that the higher intensity of the applied current results in stronger electromagnetic which can slow down the sedimentation rate. The results presented in this work are very helpful in designing a controller which provides the input current in terms of the magnitude and profile configuration.

We investigated experimentally, analytically and numerically the formation process of double emulsion formations under dripping regime in a tri-axial co-flow capillary device. The results show that mismatches of core and shell droplets under a given flow condition can be captured both experimentally and numerically. We propose a semi-analytical model using the match ratio between the pinch-off length of the shell droplet and the product of the core growth rate and its pinch-off time. The mismatch issue can be avoided if the match ratio is lower than unity. We considered a model with the wall effect to predict the size of the matched double emulsion. The model shows slight deviations with experimental data if the Reynolds number of continuous phase is lower than 0.06, but asymptotically approaches to good agreement if the Reynolds number increases from 0.06 to 0.14. The numerical simulation generally agrees with the experiments under various flow conditions.

2-Methylquinazolin-4(3H)-one was prepared by reaction of anthranilic acid, acetic anhydride and ammonium acetate. The reaction of 2-methylquinazolin-4(3H)-one with N-aryl-2-chloroacetamides in acetone in the presence of potassium carbonate gave nine N-aryl-2-(2-methyl-4-oxoquinazolin-3(4H)-yl)acetamide compounds. The structures of these compounds were elucidated on the basis of their IR, 1H-NMR, 13C-NMR and HR-MS spectral data. These synthesized compounds containing the 2-methyl-3,4-dihydroquinazolin-4-one moiety exhibited excellent activity against Aedes aegypti mosquito larvae with LC50 values in the range of 2.085-4.201 μg/mL after 72 h exposure. Interestingly, these compounds did not exhibit toxicity to the non-target organism Diplonychus rusticus. In silico molecular docking revealed acetylcholine binding protein (AChBP) and acetylcholinesterase (AChE) to be potential molecular targets. These data indicated the larvicidal potential and environmental friendliness of these N-aryl-2-(2-methyl-4-oxoquinazolin-3(4H)-yl)acetamide derivatives.

Effective and rapid mixing is essential for various chemical and biological assays. The present work reports a simple and low-cost micromixer based on magnetofluidic actuation. The device takes advantage of magnetoconvective secondary flow, a bulk flow induced by an external magnetic field, for mixing. A paramagnetic stream of diluted ferrofluid and a non-magnetic stream are introduced to a straight microchannel. A permanent magnet placed next to the microchannel induced a non-uniform magnetic field. The magnetic field gradient and the mismatch in magnetic susceptibility between the two streams create a body force, which leads to rapid and efficient mixing. The micromixer reported here could achieve a high throughput and a high mixing efficiency of 90 % in a relatively short microchannel.

Dyadic data which is also called co-occurrence data (COD) contains co-occurrences of objects. Searching for statistical models to represent dyadic data is necessary. Fortunately, finite mixture model is a solid statistical model to learn and make inference on dyadic data because mixture model is built smoothly and reliably by expectation maximization (EM) algorithm which is suitable to inherent spareness of dyadic data. This research summarizes mixture models for dyadic data. When each co-occurrence in dyadic data is associated with a value, there are many unaccomplished values because a lot of co-occurrences are inexistent. In this research, these unaccomplished values are estimated as mean (expectation) of random variable given partial probabilistic distributions inside dyadic mixture model.

The purpose of this study is to elucidate the factors influencing the voluntary adoption of IFRS by examining, analyzing, and synthesizing findings from empirical studies conducted worldwide. The research scrutinizes 185 relevant studies on the voluntary adoption of IFRS published before August 2023. Our assessment reveals that, in prior research, the factors influencing the voluntary adoption of IFRS are categorized into seven main factors, including corporate operations, capital structure, ownership structure, internationalization, financial performance, corporate governance, and several other factors. These studies employ various methodologies, including data surveys, and cross-sectional data, to estimate the relationships between these factors and the voluntary adoption of IFRS. In addition to providing an evaluation of the research in this field, this study can serve as a framework for future researchers to link and compare the results of different studies. We anticipate that this research will be beneficial for future scholars interested in the factors influencing the voluntary adoption of IFRS. Furthermore, the study proposes essential guidance for future research considerations.

(1) Background: This study aimed to evaluate the role of cervical pessary for preventing preterm birth in singleton pregnant women with a cervical length (CL) ≤25 mm and a uterocervical angle (UCA) ≥95o and ≥105o. (2) Methods: A quasi-experimental study was conducted on 225 singleton pregnant women with a gestational age of 16+o-23+6 weeks and transvaginal ultrasound CL measurements ≤25 mm, whose pregnancy was man-aged at the Haiphong Hospital of Obstetrics and Gynecology, Vietnam, from September 2020 to September 2022. Participants were allocated into two groups: prophylactic treatment with progesterone (123 pregnant women) and combined with a cervical pessary (102 pregnant women). The UCAs measured via transvaginal ultrasound by a single sonographer were divided into groups with UCA measurements ≥95o and ≥105o. The gestational age at birth was classified into full-term and preterm <37 weeks and <34 weeks. A binary regression model assessed the association between CL, UCA, and pre-term birth outcomes. The difference was statistically significant, with p<0.05. (3) Results: There was no statistically significant difference in the rate of preterm birth <37 weeks and <34 weeks between the two groups (16.3% vs. 11.8% and 6.5% vs. 4.9%, p>0.05). The probability of preterm birth <37 weeks in the group of pregnant women with a UCA ≥95o treated via cervical pessary plus progesterone decreased by 60.6%, OR (95% CI) of 0.394 (0.165-0.941), p<0.05. In the group of pregnant women with a UCA ≥105o, there was a significant association in the group of progesterone treatment combined with a cervical pessary, with the lower rate of PTB <37 weeks and <34 weeks, with OR (95% CI) of 0.028 (0.005-0.146), p<0.001, and 0.141 (0.030-0.664), p<0.05, respectively. (4) Conclusion: The results of this study suggest that cervical pessary is beneficial to the prevention of preterm birth in singleton pregnant women with an obtuse uterocervical angle. Further randomized studies among pregnant women with obtuse uterocervical angles will be needed to clarify the role of a cervical pessary in preventing preterm birth.

In central area of Liaoning province, the thermal performance of rural building envelopes are mostly non-standardized in Northern China, resulting in a significant heat loss. In this study, The objective was to propose some low-cost and energy-efficient solutions. Through a field of inves-tigations, heating energy consumption was saved by 20% and increased construction costs was less than 8000 RMB, which was acceptable for rural residents. In order to achieve this target, NSGA-II algorithm was integrated with Rhino+Grasshopper and EnergyPlus simulation kernel to establish a thermal performance optimization model for heat transfer of the rural building envelopes. Among the above Pareto optimal solutions, the recommended thickness of insulation layer for the room floors, ceilings, and external walls were 70mm, 50mm, and 40mm respectively. Furthermore, try to reduce the window to wall ratio as much as possible. Finally, based on the lower total cost, three technical solutions that rural residents could select according to their specific needs have been put forward.

This paper examines the potential of large language models, specifically ChatGPT, BingChat, and Bard, in enhancing the work of teachers in various educational settings. These models, powered by cutting-edge artificial intelligence, offer a wide range of applications that can aid educators in curriculum development, personalized instruction, student engagement, and administrative tasks. By harnessing the capabilities of these language models, teachers can not only streamline their workload but also improve the overall quality of education. This paper explores the ways in which these models can empower educators and revolutionize teaching practices.

Modern agriculture demands for comprehensive information about the plant itself. Conventional chemistry-based analytical methods - due to their low throughput and high associated cost - are no longer capable of providing these data. In recent years, remote reflectance-based characterization has developed as one of the most promising solutions for rapid assessments for plant attributes. However, in many cases, expensive equipment is required because accurate quantifications need assessment of the full reflectance spectrum. We examined the versatility of visible colour sensors as reflectance measuring devices for biological / biochemical quantifications on sweet basil (Ocimum basilicum). Our results indicate for the wide potential of spectral colour sensors for quantitative determination of leaf phenolic compounds, flavonoids in particular, and non-invasive plant phenotyping in agricultural applications by low-cost sensors.

This paper presents an improved indoor localization system based on RF and ultrasonic signal which we named SNSH system. This system composes of a transmitter mounted in a mobile target, and a series of receiver nodes which are managed by a coordinator. By measuring Time Delay of Arrival (TDoA) of RF and ultrasonic signal from the transmitter, distance from target to receiver node is calculated and sent to the coordinator through CAN network, and all the information are gathered in PC to estimate 3D position of the target. Sine wave detector and dynamic threshold filter are applied to provide excellent accuracy of range measurement from TDoA result, and multilateration algorithms is realized to optimize coordinate determination accuracy. Specifically, Linear Least Square and Non-linear Least Square techniques are implemented to contrast their performances in target coordinate estimation. RF signal encoding/decoding time, time delay in CAN network and math calculating are carefully considered to ensure optimal system performance and get ready for field application. Experiments show that sine wave detector algorithm has greatly improved range measurement accuracy, with mean error at 2.2mm and maximum error at 6.7 mm, for distance below 5m. In addition, 3D position accuracy is greatly enhanced by multilateration methods, with mean error in position stay under 15mm, and 90% confident error values at 23mm for LLS, 20mm for NLS. Overall system update period has been verified in real system operation, with maximum rate at 25ms, and compared with other existing researches.

Countless disasters have resulted from climate change, causing severe damage to infrastructure and the economy. These disasters have significant societal impacts, necessitating mental health services for the millions affected. To prepare for and respond effectively to such events, it is crucial to understand people's emotions and the life incidents they experience both before and after a disaster strikes. In this case study, we mined the emotions and life incidents expressed on Twitter during the 2017 Hurricane Harvey. Between August 20 and August 30, we collected a dataset of approximately 400,000 public tweets related to the storm. Using a BERT-based model, we predicted the emotions associated with each tweet. Following emotion prediction, we applied various natural language processing techniques to analyze the content of the tweets, aiming to uncover the 'topics' discussed alongside specific 'emotions.' To efficiently identify these topics, we utilized the Latent Dirichlet Allocation (LDA) technique for topic modeling, which allowed us to bypass manual content analysis and extract meaningful patterns from the data. However, rather than stopping at topic identification, we further refined our analysis by integrating Graph Neural Networks (GNN) and Large Language Models (LLM). The GNN was employed to generate embeddings and construct a similarity graph of the tweets, which was then used to optimize clustering. This step ensured that related tweets were accurately grouped together based on their content and context. Subsequently, we used an LLM to automatically generate descriptive names for each event cluster. This advanced approach allowed us to identify and label life incidents automatically, providing a nuanced understanding of the key issues faced by the community during the hurricane. The results revealed significant emotional shifts as the hurricane reached its most devastating phase. These shifts coincided with pressing concerns and demands from the population, such as evacuation plans, animal safety, safety updates, public policy, help requests, flood impacts, and the spread of fake news. By combining GNN and LLM for automatic event name prediction, our study not only mapped out the emotions but also accurately categorized the specific life incidents that were most relevant during the disaster, offering critical insights for disaster preparedness and response strategies.

Better understanding of the quality of life among nursing home residents with dementia is im-portant for developing interventions. The objectives of this cross-sectional study were to examine factors associated with poor health-related quality of life in older adults with dementia living in nursing homes in Hanoi, Vietnam. In-person interviews were conducted with 140 adults 60 years and older with dementia and information about their quality of life was obtained using the Quality of Life in Alzheimer’s Disease scale (QOL-AD). A number of sociodemographic and clinical factors associated with poor health-related quality of life (lowest tertile) were assessed through the results of physical tests, interviews with nursing home staff, and review of medical records. The average age of the study sample was 78.3 years, 65% were women, and their av-erage QOL-AD total score was 27.3 (SD = 4.4). Malnutrition, total dependence in activities of daily living, and urinary incontinence were associated with poor quality of life after controlling for multiple potentially confounding factors. Our findings show that Vietnamese nursing home residents with dementia have a moderate quality of life and interventions based on comprehen-sive geriatric assessment remain needed to modify risk factors associated with poor health-related quality of life.

With the unceasing advancement in wide-bandgap (WBG) semiconductor technology, the minimal reverse-recovery charge Qrr and other more powerful natures of WBG transistors enable totem-pole bridgeless PFC to become a dominant solution for energy storage systems (ESS). This paper focuses on design and implementation of a control structure for a totem-pole boost PFC with newfangled enhancement-mode Gallium Nitride (eGaN) FETs, not only to simplify the control implementation, but also to achieve high power quality and efficiency. The converter is designed to convert a 90-264-VAC input to a 385-VDC output for a 2.6-kW output power. Lastly, to validate the methodology, an experimental prototype is characterized and fabricated. The uttermost efficiency at 230 VAC attains 99.14%. The lowest total harmonic distortion in the current (ITHD) at high line condition (230 V) reaches 1.52% while the power factor gains 0.9985.

A new algorithm is developed in this study to automatically detect reinforced concrete structures' rebar locations and diameters using the ground penetrating radar technique. The method approximates the hyperbolic signatures using two-way travel time and bi-quadratic equations. The study includes formulating electromagnetic wave speed in reinforced concrete (RC) structures. The algorithm was used in a computer code to provide an automated analysis of ground-penetrating radar data collected from a pre-planned survey grid. Two RC slabs were fabricated and tested to validate the proposed method. The proposed method is efficient in signal processing and accurately and reliably determining the rebar information.