The Covid-19 pandemic and the subsequent implementation of lockdown measures have significantly impacted global electricity consumption, necessitating accurate energy consumption forecasts for optimal energy generation and distribution during a pandemic. In this study, we propose a new forecasting model called the Multivariate Multilayered LSTM with Covid-19 case injection ($\proposedModel$) for improved energy forecast during the next occurrence of a similar pandemic. We utilize data from commercial buildings in Melbourne, Australia during the Covid-19 pandemic to predict energy consumption and evaluate the model's performance against commonly used methods such as LSTM, Bi-LSTM, Linear Regression, Support Vector Machine and the previously published work of Multilayered LSTM (M-LSTM). The proposed forecasting model was analyzed using the following metrics of mean percent absolute error (MPAE), normalized root mean square error (NRMSE), and $R^2$ score values. The model $\proposedModel$ demonstrates superior performance, achieving the lowest MPAE values of 0.061, 0.093, and 0.158 for data sets from 3 different buildings, respectively. Our results highlight the improved precision and accuracy of the model, providing valuable information for energy management and decision-making during the challenges posed by the occurrence of a pandemic like Covid-19 in the future.

The global demand for energy has been steadily increasing due to population growth, urbanization, and industrialization. Numerous researchers worldwide are striving to create precise forecasting models for predicting energy consumption to manage supply and demand effectively. In this research, a time-series forecasting model based on multivariate multilayered long short-term memory (LSTM) is proposed for forecasting energy consumption and tested using data obtained from commercial buildings in Melbourne, Australia: the Advanced Technologies Center, Advanced Manufacturing and Design Center, and Knox Innovation, Opportunity, and Sustainability Center buildings. This research specifically identifies the best forecasting method for subtropical conditions and evaluates its performance by comparing it with the most used methods at present, including LSTM, bidirectional LSTM, and linear regression. The proposed multivariate multilayered LSTM model was assessed by comparing mean average error (MAE), root-mean-square error (RMSE), and mean absolute percentage error (MAPE) values with and without labeled time. Results indicate that the proposed model exhibits optimal performance with improved precision and accuracy. Specifically, the proposed LSTM model achieved a decrease in MAE by 30%, RMSE by 25%, and MAPE by 20% compared to the LSTM method. Moreover, it outperformed the bidirectional LSTM method with a reduction in MAE by 10%, RMSE by 20%, and MAPE by 18%. Furthermore, the proposed model surpassed linear regression with a decrease in MAE by 2%, RMSE by 7%, and MAPE by 10%. These findings highlight the significant performance increase achieved by the proposed multivariate multilayered LSTM model in energy consumption forecasting.

Coastal erosion is threatening the infrastructures of coastal community at the Ma River mouth in Thanh Hoa province, Vietnam. When coastal erosion happens, people try to prevent it by emergency solutions like hard structures. However, this approach usually leads to more severe problem since the mechanism for coastal erosion is not investigated and understood properly. In this study the long-term configuration of Ma River mouth in Thanh Hoa Province, Central Vietnam has been investigated using Landsat imagery from 1987 to 2023. An analytical solution of one-line model for shoreline change was also employed to calculate the sand discharge from Ma River as well as the diffusion coefficient for sand transported along-shore by breaking waves. There was an asymmetric configuration of the Ma River mouth during the last 37 years. The sand supply from the Ma River is around 350,000 m3/year. This amount of sand is going mainly to the northern beach of the Ma River delta (from 55% to 75%). The asymmetric morphology of the Ma River mouth delta is the trigger for severe coastal erosion reported recently. This study provides a quick and easy method to investigate the morphological change of cuspate deltas where measured data is limited.

Burn injuries have profound implications for aesthetics, functionality, and patient survival. Umbilical cord lining mesenchymal stem cells (SCL-MSCs) have emerged as a potential therapeutic approach for burn wounds due to their easy isolation, favorable differentiation capabilities, and low immunogenicity. This study aimed to evaluate the growth characteristics of SCL-MSCs and their effectiveness in treating burn wounds. Mechanical isolation was employed to extract mesenchymal stem cells from the umbilical cord lining membrane. The isolated cells underwent characterization, including analysis of HLA-E, G, and DR expression, and assessment of immunogenicity against rabbit antigens using ELISA. A rabbit model was utilized to administer burn treatment. SCL-MSCs exhibited typical morphology of mesenchymal stem cells and demonstrated robust proliferation. These cells expressed CD90, HLA-E, and HLA-G markers while lacking HLA-DR expression. Intact cells and supercrushed cell fluid displayed minimal and unstable immunogenicity. SCL-MSCs exhibited remarkable differentiation potential toward fibroblast lineages, with differentiated fibroblasts showing elevated collagen production and efficient sheet formation. In the experimental rabbit model, burn wounds covered with SCL-MSC tegaderm material plates exhibited superior healing compared to controls. The stem cell material plate area demonstrated reduced inflammatory cell counts (P < 0.01) and increased fibroblast count, neovascularization, and mitotic index (P < 0.01). These findings highlight the potential of SCL-MSCs as a valuable resource for burn wound research and treatment.

Nowadays, there are several electric vehicle (EV) on the market, due to the innovation of technology that promotes the new components such as battery, transmission, electric motors. This paper proposes a design approach for the configuration synthesis and simulation of the in-wheel-hub motor transmissions with the six-link mechanisms. The synthesis process shows 6 mechanisms with six members and eight joints, 15 new clutchless motor transmissions and 16 new clutched motor transmissions. A novel motor transmission in the feasibility of the synthesized configurations is selected as an example to analyze the working principle with operation modes and power flow paths. And, this design is modeled for the simulation process that generates the results of operation mode transition and energy regulation.

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

Background. There is limited evidence on the relationship between chronic kidney disease (CKD) and frailty in older people in Vietnam. This study aimed to examine the prevalence of frailty and its impact on mortality in older patients with end-stage renal disease. Method. This is a prospective, observational study at two large Dialysis Centres in Vietnam from November 2020 to June 2021. Consecutive older patients diagnosed with end-stage renal disease and on dialysis were recruited. Participants’ frailty status was defined by the Clinical Frailty Scale (CFS). The study outcome was all-cause mortality at 6th month. Results. A total of 175 participants were recruited (mean age 72.4 years, 58.9% female). Using the cut-point of CFS ≥4, 87.4% of the participants were frail. Mortality at 6th month was 14.9%, 31.9% in participants with CFS ≥7, 12.8% in participants with CFS=6, 7.5% in participants with CFS from 4 to 5, and 4.5% in participants with CFS ≤3 (p=0.001). Cox regression analysis showed that compared to the non-frail participants, the probability of death over 6 months was nearly 2-fold higher in the mildly frail, 3-fold higher in the moderately frail, and 9-fold higher in the severely frail participants. Conclusion. This study demonstrated a very high prevalence of frailty in older patients with end-stage renal disease and dialysis and the significant impact of frailty severity on mortality. Healthcare providers should consider incorporating frailty screening into routine care for older patients with end-stage renal disease and dialysis.

Advances in cardiovascular therapies and cancer treatments result in longer patient survival. The coexistence of cancer and cardiovascular disease has been recognized as a complex clinical scenario. Beside cardiovascular disease, older people with cancer are at greater risk of experiencing multimorbidity and the geriatric syndromes such as frailty. In older people, the concurrent presence of cancer and cardiovascular disease increased the risk of mortality, and the presence of frailty can exacerbate their conditions and hinder the treatment effectiveness. Given the significant intersection among frailty, cardiovascular disease and cancer in older people, this paper aims to provide an overview of the current research in this field and identifies gaps in research to understand the burden and impact of frailty in these populations. While many studies have examined the prevalence and impact of frailty on adverse outcomes in patients with cancer or with cardiovascular disease, evidence of frailty in individuals with both conditions is lacking. There is no universally accepted definition of frailty, which leads to inconsistencies in identifying and measuring frailty in older adults with cardiovascular disease and cancer. The frailty index seems to be a preferred frailty definition in studies in patients with cancer, while the frailty phenotype seems to be more commonly used in cardiovascular research. However, differences in how the frailty index was categorised and in how patients were classified as ‘frail’ depending on the cut points may have negative effect on understanding the impact of frailty in the studied populations. This makes it challenging to compare findings across different studies and limits our understanding of the prevalence and impact of frailty in these populations. Addressing these research gaps will contribute to our understanding of the burden of frailty in older people with cardiovascular disease and cancer, and improved clinical care protocols in this vulnerable population.

In an age of market liberalization, globalization, and expanding agribusiness, there is a danger that small-scale farmers will find difficulty in fully participating in the market economy. One of the solutions to solve the above situation is to strengthen linkages between farmers and firms through contract farming. The purpose of this study is to assess the factors affecting the level of linkages between businesses and farmers in crop development in Thai Binh province, Vietnam. The two main research methods used were exploratory factor analysis (EFA) and regression analysis with survey data which was conducted from 300 farmers, 10 firms, and 15 factors related to contract-farming. The results indicated that there are 5 factors that significantly affect the level of participation of farmers in the linking process, the order of impacts from strong to weak is as follows: (1) Commitment and sharing of benefits and risks between farmers and firms in the linking process, (2) Issues related to management skills and enterprises capacity of link firms, (3) Price issues that farmers are interested in in the process of implementing links with firms, (4) Policy environment - Institutions related to farmer contracts between firms and farmers, (5) Household awareness about the benefits brought about by farmer contracts with firms. Based on results, a number of specific solutions have been proposed to enhance the efficiency of farming contracts between firms and farmers in cultivation production.

VNREDSat-1 is the first Vietnamese satellite allowing the survey of environmental parameters such as vegetation and water coverages, or surface water quality at medium spatial resolution (from 2.5 to 10 meters depending on the considered channel). The NAOMI sensor on board VNREDSat-1 has the required spectral bands to assess the suspended particulate matter concentration, SPM. Because recent studies have shown that the remote sensing reflectance, Rrs(), at the blue (450 – 520 nm), green (530 – 600 nm), and red (620 – 690 nm) spectral bands can be assessed from NAOMI with a good accuracy, the present study is dedicated to the development and validation of an algorithm (hereafter referred to as V1SPM) to assess SPM from Rrs() over inland and coastal waters of Vietnam. For that purpose, an in situ data set of hyper-spectral Rrs() and SPM (from 0.47 to 240.14 g.m-3) measurements collected at 205 coastal and inland stations has been gathered. Among the different approaches, including 4 historical algorithms, the polynomial algorithms involving the red-to-green reflectance ratio presents the best performance on the validation data set (MAPD of 18,7%). Compared to the use of a single spectral band, the band ratio allows to reduce the scatter around the polynomial fit as well as the impact of imperfect atmospheric corrections. Due to the lack of matchup data points with VNREDSat-1, the full VNREDSat-1 processing chain (RED-NIR and V1SPM) aiming at estimate SPM from the top-of-atmosphere signal has been applied to the Landsat-8/OLI match-up data points with relatively low to moderate SPM concentration (3.33-15.25 g.m-3) showing a MAPD of 15,8%. An illustration of the use of this VNREDSat-1 processing chain during a flooding event occurring in Vietnam is provided.

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 beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

This study presents a tri-layer broadband metamaterial absorber which operates in the GHz range. The absorber was composed of a polyhedral iron-cobalt alloy/graphite nanosheet material arranged in a flat sheet with two punched-in rings for the top layer, a continuous FR-4 layer at the middle, and a continuous copper layer at the bottom. For the normal incidence of electromagnetic wave, the proposed absorber demonstrated an exceptional broadband absorption in a frequency range of 7.9-14.6 GHz, revealing an absorption exceeding 90%. The absorption magnitude remains to be above 90% in a frequency range of 8-11.1 GHz for transverse-electric-polarized waves at incident angles up to 55°. For both transverse-magnetic- and electric-polarized waves, the absorption exceeds 90% in a frequency range of 9.5-14.6 GHz. The physical mechanism behind the absorption properties is analyzed thoroughly through the electric- and magnetic-field distributions. The obtained results could contribute potentially to the development of microwave applications based on metamaterial absorbers, such as radar-stealth technology, electromagnetic shielding for health safety and reduced electromagnetic interferences for high-performance communications and electronic devices.

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.

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.

This study examines the Willingness-To-Pay (WTP) of consumers and the determinants of eco-labeling for the organic cocoa powder produced in the Dong Nai UNESCO Biosphere Reserve (DNBR), Southern Vietnam. Eco-labels are designed according to Tiers of eco-labeling for biosphere reserves (BR) introduced by UNESCO include BR Destination (Tier 1), BR Quality Label (Tier 2), and Professional Certification Label (Tier 3). Questionnaires are delivered to 203 customers in the DNBR and nearby places, such as Dong Nai and HCMC. This study employs a hybrid approach using descriptive statistics, ANOVA test, and Partial Least Squares Structural Equation Model (PLS-SEM). The results indicate that gender and educational level have a positive effect on consumers' preferences. Customers are willing to pay more for cocoa powder with an eco-label than one with an organic label. Perceived food safety and product knowledge lower customers’ WTP, whereas agricultural environment and pricing concerns increase it. Tier 2 is suggested for labeling cocoa powder in the DNBR. The DNBR Management Board, together with the federal and provincial governments, should all follow a similar certification process. Increased eco-label awareness is crucial for the future of environmentally responsible shopping and responsible business practices.

In order to meet the national energy saving goals set in the Vietnam National Energy Efficiency Program in the period of 2019 – 2030 (VNEEP), the Vietnamese government has adopted a series solutions and policies to improve energy efficiency. The Vietnam’s 63 provinces will be as main actor for the national achievement in energy efficiency. Thus, understanding the province’s potentiality of energy efficiency is useful for the harmonious and sustainable development between the economy and energy systems. In this study, provincial and national data from General Statistic Office are analyzed in terms of the energy efficiency levels. With the trends of economic development and energy consumption in both national and regional levels, the Lorenz curve between Vietnamese energy consumption and GDP is investigated. The Lorenz coefficient shows the energy allocation is nether reasonable nor balanced. By using clustering method, the 63 provinces of Vietnam clustered into 7 groups that the provinces in the cluster has the similar indexes of energy efficiency i.e. ability, responsibility, potential and difficulty. The energy consumption and GDP are predicted in the period of 2019 – 2025. Based on the difference of GDP development and energy consumption levels, the target of energy efficiency for each province through clustering is set. The results show that 33 provinces included in the cluster 1, 2, 3, 4 and 6 are heavy contribution. Among them, the provinces in the cluster 2 and 3 need to focus on the industry sector in their energy saving policy. The cluster 7 included the under-developed provinces can learn development’s experiences of the provinces in the cluster 1, 2, 3 and 4 to find the best way of their future development.

Changing climate conditions and rapidly increasing carbon dioxide emissions have severely affected the global ecosystem and world economy. Governments around the world have paid attention to these resulting challenges and enacted many policies to reduce environmental pollution and carbon dioxide (CO2) emissions. This study aimed to determine and understand the relationship between innovation, foreign direct investment, economic growth, renewable consumption and CO2 emission in Vietnam. Information was collected annually based on the annual data of the General Statistics Office of Vietnam and World Bank from 2000 to 2022. Data processing was conducted using the STATA 17.0 software. The innovation affects Vietnam’s environmental pollution. Innovation positively affect environmental pollution in Vietnam; if Vietnam’s innovation were to increase by 1%, CO2 emissions would increase by 0.68%. The empirical research results of this study also show that renewable energy consumption has a negative effect on environmental pollution in Vietnam; if renewable energy were consumed at a 1% increase, CO2 emission would decrease by 0.51%. In addition, FDI inflows and economic growth have strongly positive affecting to environmental pollution; if Vietnam’s FDI inflows were to increase 1%, CO2 emissions would increase 1.39%; if Vietnam’s GDP increase 1% then CO2 emission would increase 1.26%. This paper also provides some recommendations that can assist Vietnam in developing a green and sustainable economy in the technology revolution 4.0 to achieve the United Nations Sustainable Development Goals (SDGs) over a long-term period.

We demonstrate a method for realization of highly nonlinear optical 4-(4-dimethylaminostyryl)-1-methylpyridinium tosylate (DAST) two-dimensional structures by a double step technique. The desired polymeric structures have been first fabricated by using the multiple-exposure of two-beam interference technique, and the DAST nanoscrystals were then prepared inside the air-voids of these photoresist templates, resulting in nonlinear periodic structures. The nonlinear properties were characterized by optical and scanning microscopies, as well as by second-harmonic generation technique. This nonlinear modulation is very promising for the enhancement nonlinear conversion rates, such as terahertz generation, by using the quasi-phase matching technique.

The aim of this work is to synthesis and characterize the Ta/TaN multilayer thin film coatings on 52100 tool steel under three different levels of N2 gas flow rate. The High Power Impulse Magnetron Sputtering (HiPIMS) technique was used for the deposition of Ta/TaN thin film multilayers on the substrate. Microstructure, coating thickness, composition, hardness and tribological properties of Ta/TaN multilayer coatings were characterized using scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), microhardness tester and pin-on-disc tester, respectively. Adhesion property was evaluated via scratch testing of the thin film thin film layer. The lowest coefficient of friction was observed with the thin film layer of higher N2 gas flow rate due to the highest adhesion value of the coating on the surface. The obtained results on hardness, adhesion and coefficient of friction properties demonstrated that this Ta/TaN multilayer thin film coating can be used for tribological applications.

This article explored how some state policies on rehabilitation, protection and utilization of mangroves are implemented at two locals; namely, Ca Mau provice and its sub-unit Ngoc Hien District as well as Ho Chi Minh City and its sub-unit Can Gio District and what are considered as emgerging issues in the implementation process. The study employed mixed research methods including document and thematic analysis, in-depth interviews, and group discussion. The findings showed that state policies would be adapted through the ways in which these two locals manage to silmultaneously orient their work toward accommodating the madates placed upon them and cope with the reality of socio-economic difficulties at their levels. The findings also showed some issues that need to consider addressing; namely, locals’ struggles to fill the gaps between written and implemented policies in mangrove rehabilitation, conflict among sectors and stakeholders in mangrove utilization and protection, problems in guaranteeing adequate budget for in-need-locals, inconsistence in policies on "forest: water surface” ratio in mangrove-shrimp farm, and unintended consequences in forest thinning and exploitation regimes. Based on the finding analysis, the articles discussed lessons learned from the policy implementation process on mangrove rehabilitation, management and forest allocation to household in the south of Vietnam.

This study investigates how the determinants including risk preference affect farmers’ decision to adopt SLM practices in upland areas of Vietnam. Empirical data collected through in-depth interviews with 200 farmers in Na Ri district, Bac Kan province were used. The factors affecting SLM adoption of farmers in Na Ri district were examined by the 2SLS or IV-Probit model. The estimated 2SLS regression indicated that there is a set of factors affecting SLM adoption, namely, relative risk aversion, farming experience, farm size, knowledge of SLM, membership in farmers’ organization, number of labors, and slope of farm land. Specifically, relative risk aversion had a negative effect on SLM practices adoption. The farmers who are less risk averse are more likely to adopt more SLM practices. This implies that reducing farmer’ risk exposure could promote SLM practices. This result is also helpful for policymakers to understand farmers’ behaviors and promote the diffusion of SLM practices across regions on a large scale.

COVID-19 pandemic and its restrictive measures have present serious unprecedented challenges to human eating behavior. Given that Google Search has become a valuable information resource to examine, predict, and estimate human online interests and behavior, that somehow linked to real people concerns. This study aimed to investigate the features and evaluate the impacts of the COVID-19 pandemic and its lockdown on consumer worldwide interest in eating behavior and its related factors. Google Trends-Relative Search Volumes (RSV) of distinct keywords related to eating behavior, were obtained from a timeframe before and during the COVID-19 pandemic, from January 1, 2018, to December 13, 2020. During the global lockdown from March 11, 2020, to June 30, 2020, RSV curves exhibited a short-term fluctuation of interest in multiple keywords related to eating behavior and its related factors such as food purchasing, food security, food poisoning, panic buying, stocking up, health awareness and mental illness. Spearman’s correlation analysis showed a strong correlation between daily confirmed cases and examined keywords. Univariate repeated measures ANOVA following with Bonferroni Post-hoc test revealed that during the year with the presence of COVID-19 pandemic, people worldwide pay more concerns in each keyword (1) environmental and economic factors (unemployment: +269%, food shortage: +180%, food bank: +50%); (2) health- and food-safety concerns (immunity: +138%, vitamin C: +90%, vitamin D: +55%, zinc: +47%, food storage containers: +40%, food packaging: +31%); (3) food choices and interest (local meat: +84%, frozen food: +67%, CSA: +65%, flour: +66%, bread: +53%, soybean oil: +45%, local fruit: +43%, canned tomato: +42%, refrigerated food: +41%, canned meat: +39%, pancake: +37%, cookie: +29%, butter: +29%, canned fish: +29%, liquior: +20%); (4) social and individual factors (take-out: +128%, deliver: +53%), (6) lifestyle factors (stationary bicycle: +110%, dumbbell: +89%, yoga mat: +84%, treadmill: +65%, grocery store: +51%); (6) psychological factors (isolation: +113%). COVID-19 pandemic and its lockdown have had far-reaching effects on global concerns in many factors related to human eating behavior. Swift action is necessarily performed to strengthen the resilience of the food supply chain system, support and adapt to the new normal behavior, and mitigation the profound negative changes, especially targeting those in high-risks and vulnerable groups and food-insecure regions.

Building on the carbon reduction targets agreed in the Paris Agreements, many nations have renewed their efforts toward achieving carbon neutrality by the year 2050. In line with this ambitious goal, nations are seeking to understand the appropriate combination of technologies which will enable the required reductions in such a way that they are appealing to investors. Around the globe, solar and wind power lead in terms of renewable energy deployment, while carbon capture and storage (CCS) is scaling up toward making a significant contribution to deep carbon cuts. Using Japan as a case study nation, this research proposes a linear optimization modeling approach to identify the potential contributions of renewables and CCS toward maximizing carbon reduction and identifying their economic merits over time. Results identify that the combination of these three technologies could enable a carbon dioxide emission reduction of between 55 and 67 percent in the energy sector by 2050 depending on resilience levels and CCS deployment regimes. Further reductions are likely to emerge with increased carbon pricing over time. The findings provide insights for energy system design, energy policy making and investment in carbon reducing technologies which underpin significant carbon reductions, while identifying potential regional social co-benefits.

The venom proteome of Temple Pit Viper (Tropidolaemus wagleri) is unique among pit vipers, characterized by a high abundance of a neurotoxic peptide, waglerin. To further explore the genetic diversity of its toxins, the present study de novo assembled the venom gland transcriptome of T. wagleri from west Malaysia. Among the 15 toxin gene families discovered, gene annotation and expression analysis reveal the dominating trend of bradykinin-potentiating peptide/angiotensin-converting enzyme inhibitor-C-type natriuretic peptide (BPP/ACEI-CNP, 76.19% of all-toxin transcription) in the transcriptome, followed by P-III snake venom metalloproteases (13.91%) and other toxins. The transcript TwBNP01 of BPP/ACEI-CNP represents a large precursor gene (209 amino acid residues) containing the coding region for waglerin (24 residues). TwBNP01 shows substantial sequence variations from the corresponding genes of its sister species, T. subannulatus of Northern Philippines, and other viperid species which diversely code for proline-rich small peptides such as bradykinin-potentiating peptides (BPPs). The waglerin/waglerin-like peptides, BPPs and azemiopsin are proline-rich, evolving de novo from multiple hyper-mutatable propeptide regions within the orthologous BPP/ACEI-CNP genes. Neofunctionalization of the peptides results in phylogenetic constraints consistent with a phenotypic dichotomy, where Tropidolaemus spp. and Azemiops feae convergently evolve a neurotoxic trait while vasoactive BPPs evolve only in other species.

Abstract: In the Western of Mekong Delta belong to Vietnam a amount of alluvium sediments flows from upstream China to Vietnam, they are going from the river branches to in the Mekong Delta, then get out the Western Sea of Vietnam. This sediments accumulated gradually elevation the new land. The increase elevation of the land creates a fertile coastal plain where mangrove forests with a rich ecosystem of plants and animals. Over time, these forests change, with different plant species succeeding each other. This aims of this study to finding plant species in the forest, classification of forest types based on ecological regions, assessement the biodiversity of tree species, and compare the abundance communities, measuring the growth of the forest in these regions. In 2023, a comprehensive survey was conducted by using a systematic approach. The number of survey plots have done depend on the density of the forest, Base on the width of the forest range, the number of survey plots from 500m to 1,000m set up 1-2 plots, sub region set up from 10 to 15 plots. In total, 68 plots have done established in the erea, the area of plot is 100 square meters (10m x 10m). Using the statistical software in forestry to survey and analysis data. The result provided a complete picture of the tree species composition, distribution, and community structure characteristics in each ecological sub-region. The result of survey showed in the sub-region 1 have seven species as Sonneracia ovate, Rhzophora apiculata, Excoecaria agallochha, Avicennia officinalis, Avicennia alba, Agricerasvcoculatum, Bruguiera gymnorhiza. In the sub region 2 have eleven species as Sonneracia caseolaris, Annona reticulata, Lumnitzera littorea, Lumnizera racemosa, Rhizophora apiculata, Excoecaria agallocha, Avicennia officinalis, Avicennia alba, Hibiscus tillacerus, Bruguiera gymorhiza, Aericeras comiculatum. In the sub region 3 have eight as Sonratia caseolaris, Rhizophora mucronata, Rhizophora apiculata, Excoecaria agallocha, Avicennia marine, Avicennia alba, Bruguiera gymorhiza. In the region 4 have ten species as Sonneracia caseolaris, Sonneracia ovate, Lumnizera racemosa, Rhizophoa apiculata, Excoecaria agallocha, Avicennia marina, Avicennia officinalis, Aviecnnia alba, Bruguiera gymorhiza, Bruguiera cylindrica The total species of the mangrove forest in the Western Mekong Delta have 16 species from 11 plant families have been identified. Among these species have 6 dominant species include Avicennia oficinali),Avicennia alba, Rhizophora apiculata, Excoecaria agallocha, Someratia caseolaris, and Bruguiera yipamoriza. Two species easy grow on the new land are Avicennia officinalis Avicennia alba this findings show they can develope on the original new land for the shore of the Western Mekong Delta. The surveyed results also calculated the average of the height, diameter (D1.3), canopy, health of the nature mangrove tree for each sub region and total region. From these results showed the division of foresty structure, the structure of height, diameter (D1.3), canopy, vitality of the sub region and total region in the Western Mekong Delta.

The objectives of the research are to investigate the characteristics of the board of directors on the financial performance of the enterprise. Using a sample data from 52 construction and real estate enterprises listed on Vietnam stock exchange in the period 2006-2020. Using typical regression methods such as pooled OLS, FEM, REM and assessing the defects of the research model, the FGLS method is selected. At the same time, due to the existence of endogenous phenomena and the nature of interdependence among enterprises in Vietnam, research using the instrumental variables two-step generalized method of moments (IV-GMM) in order to correct for cross-sectional dependence, autocorrelation, endogeneity, and heteroskedasticity in the analysis. Research results suggest that board size, female board members, meeting frequency, and board members' education have a positive influence on financial performance. Moreover, the independence of the Board of Directors increases, the business efficiency decreases. The research also found a positive relationship of tangible fixed assets, and a negative relationship between capital structure choice, firm size and corporate financial performance.

In recent years, the unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) has become a highly sought-after topic for its wide applications in the field of target recognition, detection, and tracking. However, SAR automatic target recognition (ATR) models based on deep neural networks (DNN) are suffering from adversarial examples. Generally, non-cooperators rarely disclose any information about SAR-ATR models, making adversarial attacks challenging. In this situation, we propose Transferable Adversarial Network (TAN) to attack these models with highly transferable adversarial examples. The proposed method improves the transferability via a two-player game, in which we simultaneously train two encoder-decoder models: a generator that crafts malicious samples through a one-step forward mapping from original data, and an attenuator that weakens the effectiveness of malicious samples by capturing the most harmful deformations. In particular, compared to traditional iterative methods, our approach is able to one-step map original samples to adversarial examples, thus enabling real-time attacks. Experimental results indicate that the proposed approach achieves state-of-the-art transferability with acceptable adversarial perturbations and minimum time costs compared to existing attack methods, i.e., it excellently realizes real-time transferable adversarial attacks.

Students with disabilities are often framed as “the problem” and have limited opportunities to engage in standards based mathematics, leading to persistent underachievement. In this paper, we investigate a research divide between mathematics educational research for students with and without disabilities, a divide with significant differences in the theoretical orientations and research methodologies used to understand learners. Based on an analysis of 149 mathematics educational research articles published between 2013 and 2015, we found significant differences between articles focused on learners with and without disabilities. For those with disabilities, mathematical problem solving was understood primarily from behavioral and information processing theoretical perspectives, while for those without disabilities, problem solving was understood primarily through constructivist and sociocultural perspectives. While 86% of research on problem-solving including students with disabilities was quantitative, only 35% of research on students without disabilities was quantitative. Fifty percent of problem-solving research on students without disabilities was qualitative, compared to only 6% of research on students with disabilities. Problem solving, then, is studied in very different ways for learners with and without disabilities. Students without disabilities are studied through close analysis of learning, often individual. Students with disabilities are most often studied quantitatively, in groups, with little analysis of individual thinking. By offering only a limited range of methods and theoretical orientations, this research divide reifies deficit constructions of students with disabilities.

Biologists seek to identify a small number of significant features that are important, non-redundant, and relevant from diverse omics data. For example, statistical methods like LIMMA and DEseq distinguish differentially expressed genes between a case and control group from the transcript profile. Researchers also apply various column subset selection algorithms on genomics datasets for a similar purpose. Unfortunately, genes selected by such statistical or machine learning methods are often highly co-regulated, making their performance inconsistent. Here, we introduce a novel feature selection algorithm that selects highly disease-related and non-redundant features from a diverse set of omics datasets. We successfully applied this algorithm to three different biological problems: a) disease to normal sample classification, b) multiclass classification of different disease samples, and c) disease subtypes detection. Considering classification ROC-AUC, False-positive, and False-negative rates, our algorithm outperformed other gene selection and differential expression (DE) methods for all six types of cancer datasets from TCGA considered here for binary and multiclass classification problems. Moreover, genes picked by our algorithm improved the disease subtyping accuracy for four different cancer types over the state-of-the-art methods. Hence, we posit that our proposed feature reduction method can support the community to solve various problems, including the selection of disease-specific biomarkers, precision medicine design, and disease sub-type detection.

The study aimed to compare the cardiovascular benefits of Omega-3 Polyunsaturated Fatty Acids from fish oil versus krill oil in different forms and dosages. Following PRISMA 2015, data analysis with R software, and databases were searched from 1993 to 2023, (ID PROSPERO: CRD42024502338). Sixty high-quality studies were analyzed, covering various forms of fish oil and krill oil at different dosages (fish oil (ethyl ester-EE, triglyceride-TG, re-esterified triglycerides-rTG, capsules, emulsion-EM); krill oil (phospholipid/free fatty acid-PL/FFA, high concentration phospholipid-HPL, low concentration phospholipid-LPL)). Meta-analysis revealed that krill oil with phospholipid/free fatty acid at doses 2000-2900 mg effectively lowered triglycerides, while fish oil in ethyl ester form at doses above 3000 mg significantly reduced total cholesterol. Fish oil in triglyceride form at doses 2000-2900 mg and other variations positively impacted HDL-C levels. Fish oil in EE form above 3000 mg and triglyceride form below 2000 mg notably reduced LDL-C. However, there was limited effectiveness observed for other interventions. Analysis for LDL-C exhibited publication bias, while other parameters demonstrated reliability (Egger's test). In conclusion, krill oil - PL/FFA, Fish oil - EE above 3000 mg, Fish oil - TG 2000-3000 mg, and fish oil - rTAG 300-1900 mg effectively in reducing heart risk patients.

The COVID-19 pandemic and associated restrictive measures implemented may considerably affect people’s lives. This study aimed to assess the well-being of Vietnamese people after COVID-19 lockdown measures were lifted and life gradually returned to normal. An online survey was organized from 21st to 25th April 2020 among Vietnamese residents aged 18 and over. Besides collecting socio-demographic and COVID-19-related data, the WHO-5 Well-Being Index (scored 0–25) was used to score participants’ well-being. A multivariate logistic regression model was used to determine the predictors of well-being. A total of 1922 responses were analyzed (mean age: 31 years; 30.5% male). Mean well-being score was 17.35±4.97. Determinants of high well-being score (≥13) included older age, eating healthy food, practising physical exercise, working from home, and adhering to the COVID-19 preventive measures. Female participants, persons worried about their relatives’ health, and smokers were more likely to have a low well-being score. In conclusion, after the lockdown measures were lifted, the Vietnamese people continued to follow COVID-19 preventive measures and most of them scored high on the well-being scale. Waiting to achieve large scale COVID-19 vaccine coverage, promoting preventive COVID-19 measures remains important, together with strategies to guarantee the well-being of the Vietnamese people.

The research is designed for developing the pilot small-scale clean development mechanism bundled project activities in Vietnam electricity/ energy sector. Its overall purpose is to assess the potential of rice husk - fuelled bio-power development projects in Mekong delta. Based on estimating the electricity potential of a bundle of rice husk-fuelled bio-power development projects in Mekong delta with the capacity of 11 MW per project, assessing their CO₂ emission reductions (CERs) and CER credits, calculating and comparing their financial indices (NPV, B/C, IRR) in two cases: W/O CDM and W/CDM, the research expects to establish a rice husk energy balance flowchart for the whole Mekong delta in the year 2021 and recommend policies to use for bio-power generation the unused rice husk that is dumped and discharged from local paddy milling centers into rivers and canals, as well as, to put forward a safe and environmentally friendly solution to minimize thoroughly the current serious pollution of rivers and canals in Mekong delta with the increasing unused rice husk quantity in the context is where the sea level rise phenomenon is the strongest in the world .

Wireless Sensor Networks are critical for modern applications ranging from environmental monitoring to smart city infrastructures. This research proposes a novel optimization learning and deployment strategy for Wireless Sensor Networks (WSNs) by 3D WUSN model is uniformly distributed M sensor nodes across diverse terrains, with clusters representing 20% of sensors, showcasing its ability to balance power consumption and extend network longevity, grounded in fuzzy clustering based protocol using the Fuzzy C-Means (FCM) method, called FCM-3DWUSN. Comparative analysis against established models including LEACH-C, K-Means and LEACH emphasized FCM-3DWUSN's outperformed performance, with average power consumption such as 134.990, 341.790, 143.895, and 192.984; respectively. The experimental result shows that FCM protocol in the 3D WUSN model can reduce energy consumption and improve the network lifetime to gather data and send the information.

Objective: The study aimed to provide a picture total of the forest and erosion status of the beach and dykes of Kien Giang and Ca Mau. Theoretical framework: Kien Giang and Ca Mau are located in the West Sea, and in recent years, along the coast of this region, erosion of the coast and sea dykes has been profound. Method: There are 18 sample plots for testing. The map also includes 68 survey plots that are predefined and used as a basis for positioning in the field. The measurement indicators include tree species identification. Results and conclusion: The level of erosion in Ha Tien’s forests varies based on tree density and environmental factors. The forest with no erosion has a thickness of 9,600 trees/ha and a stem diameter of 19 cm, while the extremely erosion forest has 2,000 trees/ha and a stem diameter of 6 cm. Topographically, Ha Tien has little erosion, while U Minh is a low-lying area with high erosion. Erosion levels are 1-2 in January-April, 4-5 in May-October, and 3 in November-December. Currently, the section is divided into 28 sub-sections, with Kien Giang having 23. One sub-section is level 1, 11 sub-sections are level 2, 1 is level 3, 3 are level 4, and 3 are level 5. In Ca Mau, two sub-sections are level 4, and 3 are level 5. Implications of the research: With climate change and rising sea levels, erosion levels tend to increase one level in sub-section areas in the coming years.

In this study, we aimed to identify the factors affecting the night-time economy in Hanoi to achieve the sustainable development of this economy. We surveyed four selected groups of subjects: people, tourists, business establishments, and managers in Hanoi City, in which tourists were nationwide but have been on a night tour in Hanoi. We chose a nonrandom convenience sample. With the above sample size, the number of respondents was insufficient, so we selected districts with potential for night economic development including Hoan Kiem, Tay Ho, Dong Da, Nam Tu Liem, Ha Dong, and Gia Lam. We obtained 463 usable surveys. We processed and analyzed the data using SPSS Statistics 26.0 software. Our quantitative study included: (1) testing the suitability of the scale for the variables using Cronbach’s alpha, (2) analyzing the EFA factors to check the convergence of the observed variables and the separation between the independent variables, (3) checking the correlation to evaluate the problem of multicollinearity of the model; , and (4) performing regression analysis to evaluate the impact of the factors on night-time economic development in Hanoi City. The results showed that the variables positively impacted night-time economic development in Hanoi, but we found differences in the levels of their impact. Among the four factors, factor 3 (promotion and sharing) had the strongest impact on night-time economic development, followed by factor 2 (infrastructure and safety), factor 1 (institutions and environment), and factor 4 (nature and resources.)

The movement of liquid droplets on the energy gradient surface has attracted extensive attention. Inspired by biological features in nature, such as the periodic spindle-shaped nodes in spider silks and conical-like barbs of cacti, the structure-property-function relationship of multifunctional gradient surfaces. In this study, a series of specific patterns are fabricated by 3D printing technology, followed by modification via the atmospheric pressure plasma treatment and liquid phase chemical deposition, resulting in enhancing the ability of water droplets of 5μL to travel 18.47mm on a horizontal plane and 22.75mm against gravity up to 20° tilting angle. Additionally, analysis techniques have been employed including contact angle analyzer, ESCA and laser confocal microscope to evaluate the sample performance. This work could further be applied to many applications related to microfluidic devices, drug delivery and water/fog collection.

Postpartum haemorrhage remains a significant contributor to maternal mortality and morbidity worldwide, particularly in low- and middle-income countries. PPH continues to pose challenges in both developed and developing nations despite being preventable. This review examines the current state of knowledge regarding PPH within the context of Vietnam, a country with its unique healthcare landscape. This review identifies critical areas for improvement and future research directions based on a comprehensive literature analysis, including epidemiological insights, risk factors, prevention strategies, and management approaches. Discrepancies in PPH definitions and prevalence rates across regions highlight the need for tailored interventions and policies. Understanding the specific challenges and opportunities related to PPH in Vietnam is crucial for informing evidence-based interventions and policies to improve maternal health outcomes. This review contributes to the broader global effort to reduce maternal mortality by addressing gaps in knowledge and proposing strategies to enhance PPH prevention and management in Vietnam.

Enhancing the effectiveness of search and rescue operation at sea is always a duty of utmost importance of the coastal states. The search area for distressed objects can be determined by using Monte Carlo simulation, combined with the Median-Filter. Once the search area has been identified, the success of search and rescue operations depends on the sweeping ability of search and rescue vessel at the probability area of the distress object with the minimum time. This is the important element to the success of the search and rescue operation as it minimizes the risk and cost for Search and rescue team. In this article, the authors study and propose the use of Bacterial Foraging Optimization Algorithm (BFOA) to calculate the optimal search and co-ordination route for many search and rescue vessels in Vietnam sea. The simulation results show that it is quite consistent with reality and BFOA can be effectively applied to determine a quick search.

Robotic path planning is a field of research which is gaining traction given the broad domains of interest to which path planning is an important systemic requirement; the aim being to optimise the efficacy of robotic movements in a defined operational environment. For example, robots have been employed in many domains including: cleaning robots (such as vacuum cleaners), automated paint spraying robots, window cleaning robots, forest monitoring robots, agricultural robots (often driven using satellite and geostationary positional satellite data). Additionally, mobile robotic systems have been utilised in disaster areas and locations hazardous to humans (such as war zones in mine clearance). The coverage path planning problem describes an approach which is designed to determine the path that traverses all points in a defined operational environment while avoiding static and dynamic (moving) obstacles. In this paper we present our proposed Smooth-STC model, the aim of the model being to identify an optimal path, avoid all obstacles, prevent (or at least minimise) backtracking, and maximise the coverage in any defined operational environment. The experimental results in a simulation show that, in uncertain environments, our proposed smooth STC method achieves an almost absolute coverage rate and demonstrates improvement when measured against alternative conventional algorithms.

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.

In Southeast Asia, the Malayan Pit Viper (Calloselasma rhodostoma) is a venomous snake species of medical importance and bioprospecting potential. To unveil the diversity of its toxin genes, this study assembled and analyzed the de novo venom gland transcriptome of C. rhodostoma from Malaysia. The expression of toxin genes dominates the gland transcriptome by 53.78% of total transcript abundance (based on overall FPKM), in which 92 non-redundant transcripts belonging to 16 toxin families were identified. Snake venom metalloproteinase (SVMP, PI>PII>PIII) is the most dominant family (37.84% of all toxin FPKM), followed by phospholipase A2 (29.02%), bradykinin/angiotensinogen-converting enzyme inhibitor-C-type natriuretic peptide (16.30%), C-type lectin (CTL, 10.01%), snake venom serine protease (SVSP, 2.81%), L-amino acid oxidase (2.25%) and others (1.78%). The expressions of SVMP, CTL and SVSP correlate with hemorrhagic, anti-platelet and coagulopathic effects in envenoming. The SVMP metalloproteinase domains encode hemorrhagins (kistomin and rhodostoxin), while disintegrin (rhodostomin from P-II) is platelet-inhibitory. CTL gene homologues uncovered include rhodocytin (platelet aggregators) and rhodocetin (platelet inhibitor), which contribute to thrombocytopenia and platelet dysfunction. The major SVSP is a thrombin-like enzyme (ancrod homolog) responsible for defibrination in consumptive coagulopathy. The findings provide insight into the venom complexity of C. rhodostoma and the pathophysiology of envenoming.

To date, viruses closely related to SARS-CoV-2 have been reported in four bat species: Rhinolophus acuminatus, Rhinolophus affinis, Rhinolophus malayanus, and Rhinolophus shameli. Here, we analysed 343 sequences of the mitochondrial cytochrome c oxidase subunit 1 gene (CO1) from georeferenced bats of the four Rhinolophus species identified as reservoirs of SARS-CoV-2-like viruses. Haplotype networks were constructed in order to investigate patterns of genetic diversity among bat populations of Southeast Asia. No strong geographic structure was found for the four Rhinolophus species, suggesting high dispersal capacity. The ecological niche of SARS-CoV-2 like viruses was predicted using the four localities of bat SARS-CoV-2-like viruses and the localities where bats showed identical or very similar CO1 haplotypes than virus-positive bats. The ecological niche of SARS-CoV-like viruses was deduced from the localities where bat SARS-CoV-like viruses were previously detected. The results show that the ecological niche of SARS-CoV2-like viruses includes several regions of mainland Southeast Asia whereas that of SARS-CoV-like viruses is mainly restricted to China. In agreement with these results, human populations in Laos, Vietnam, Cambodia, and Thailand appear to be much less affected by the Covid-19 pandemic than other countries of Southeast Asia. In the climatic transitional zone between the two ecological niches (southern Yunnan, northern Laos, northern Vietnam, and possibly Hainan and Taiwan), genomic recombination between highly divergent viruses is more likely to occur. Since recombinant viruses can threaten the benefit of vaccination campaigns, these regions should be under surveillance.

A dynamic view is conjectured for not only the universe but also the underlying theories in contrast to the convectional pursuance of single unification theory. As the 4 -d spacetime evolves dimension by dimension via the spontaneous symmetry breaking mechanism, supersymmetric mirror models consistently emerge one by one at different energy scales and scenarios involving different sets of particle species and interactions. Starting from random Planck fluctuations, the time dimension and its arrow are born in the time inflation process as the gravitational strength is weakened under a 1-d model of a “timeron” scalar field. The “ timeron” decay then starts the hot big bang and generates Majorana fermions and U(1) gauge bosons in 2-d spacetime. The next spontaneous symmetry breaking results in two space inflaton fields leading to a double space inflation process and emergence of two decoupled sectors of ordinary and mirror particles. In fully extended 4-d spacetime, the supersymmetric standard model with mirror matter before the electroweak phase transition and the subsequent pseudo-supersymmetric model due to staged quark condensation as previously proposed are justified. A set of principles are postulated under t his new framework. In particular, new understanding of the evolving supersymmetry and Z2 or generalized mirror symmetry is presented.

The study examines the behavior of the Mechanically Stabilized Earth (MSE) wall using available reinforcement materials in Danang, Vietnam. The MSE was reinforced by the self-fabricated galvanized steel grids using CB300V steel with 3 cm ribs. The backfill soil is a sandy clay soil from the local area with a low cohesion. A full-scale model with full instrumentation was installed to investigate the distribution of tensile forces along the reinforcement layers. The highest load that caused the wall to collapse due to internal instability (reinforcement rupture) was 302 kN/m2, which is 15 times the design load of 20 kN/m2. The failure surface within the reinforced soil had a parabolic sliding shape which is similar to the theoretical studies. At the failure load level, the maximum lateral displacement at the top of the wall facing was small (3.9 mm) which is significantly lower than the allowable displacements for the retaining wall. Furthermore, a numerical model using FLAC software was applied to simulate the performance of the MSE wall. The modeling results are in good agreement with the physical model. Thus, the self-fabricated galvanized steel grids could be confidentially used in combination with the local backfill soil for the MSE walls.

The emergence of the COVID-19 pandemic triggered a swift transition to online learning, remote work and an increased demand for proficiency in telehealth and digital health among health professions students as they prepare for their future careers. In responding to the question: “What are the essential constructs and the validity of a digital competence assessment scale for health professions students", this study sought to develop and validate a digital competence assessment scale (DigiCAS-HPS). The present study followed a mixed-methods approach: qualitative methods (phase 1) for generating and refining items in the scale through literature review on digital frameworks, pilot testing and expert review, and quantitative methods (phase 2) including exploratory and confirmatory factor analysis for its validation. The study revealed a two-factor structure, encompassing Digital Communication, Collaboration, and Online Security (Factor 1) and Digital Content Development and Software Mastery (Factor 2), demonstrating strong construct validity and reliability. Regarding differences in digital competence across groups, older and soon-to-graduate students exhibited higher proficiency in digital content development and software mastery. The two critical facets of DigiCAS-HPS scale could tailor training programs and ensure that health professions students are well-prepared for the evolving telehealthcare landscape. This promotes the growth and accessibility of telehealth, which is increasingly vital in the post-COVID-19 new normal era.

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.

In this study, two heterogeneous fluorescence immunoassays using CdSe/ZnS quantum dot (QD) to label anti-progesterone antibody (P4Ab) for the determination of progesterone (P4) were performed in the wells of a 96-well microtiter plate. First, P4Ab was conjugated to hydrophilic CdSe/ZnS QDs via ethyl-3-(dimethylaminopropyl) carbodiimide(EDC)-N-hydroxysuccinimide) chemistry(NHS) (QDs-P4Ab conjugates). The QDs-P4Ab conjugate was employed as a second antibody in a sandwich assay, where the P4Ab was immobilized onto the 3-aminopropyltrimethoxysilane (APTMS) sol-gel membrane of the wells of a 96-well microtiter plate, and P4 was bound between the immobilized P4Ab and the QDs-P4Ab conjugate. In this assay, the fluorescence intensity of the QDs increased with increasing P4 concentrations. This assay had a detection limit of 553.9 pg/ml and a sensitivity of 18,251.96 pg/ml with a linear range of 2,184.6 – 117,082 pg/ml. In the direct binding assay, P4 was directly bound to the QDs-P4Ab conjugates immobilized onto the APTMS sol-gel membrane of the wells of a 96-well microtiter plate. In this direct binding assay the fluorescence intensity of the QDs decreased with increasing P4 concentrations, and this assay had a linear range of 28.95 – 26,607.7 pg/ml with a detection limit of 3.32 pg/ml and a sensitivity of 987.24 pg/ml. These fluorescence immunoassays have been successfully applied for the determination of P4 in real human serum, and the results were well correlated with those of a certified radioimmunoassay (RIA) method.

The TiO₂ nanostructures resulted by pyrolysis of TiCl₄ at low temperature of 80 ^oC are found to be a mixture of amorphous TiO₂ complexes and anatase nanostructure whose ratio depends on the pH of the pyrolysis medium. At low pH level, the resulting TiO₂ nanostructure is predominant anatase and gradually shifts to the amorphous TiO₂ complexes with pH level increasing. By means of heat treatment, the amorphous TiO₂ complexes can be converted back to the anatase nanostructure and then transform to rutile with the elevating temperature. Amongst of the TiO₂ nanostructure recovered from amorphous TiO₂ complexes, the anatase shows to be the most effective photocatalyst in decomposition of methylene blue.

Thrombotic microangiopathies (TMA) can be attributed to a wide variety of causes and the diagnostic process is often challenging, especially when the clinical scenario is full of other confounding factors. Hemolysis can be due to complement-mediated thrombotic microangiopathies and drug-induced hemolytic anemia in the appropriate clinical context. In this case presentation, two patients with TMA including a patient diagnosed with complement-mediated TMA after a through screen of other differential diagnoses, and a multiple myeloma patient on chemotherapy with primaquine-induced hemolytic anemia in the background of treatment for possible pneumocystis jirovecii pneumonia. A thorough review of the drug history of patients presenting with TMA should be conducted, along with a heightened index of suspicion for complement-mediated disorders such as complement-mediated TMA, which should be entertained after ruling out a wide variety of differential diagnoses.

Background and Objectives: To investigate the relationship between the SII index and the micro-macro complications and death that develop in the first year and the following 3 years, following the calculation of the index in type 2 diabetic retinopathy patients. Materials and Methods: This study was performed retrospectively with 523 type 2 diabetic retinopathy patients admitted to the endocrinology outpatient clinic of our hospital between January 2019 and December 2019. The demographic, and clinical characteristics of the patients were evaluated using descriptive statistics. Shapiro-Wilk test was used for the normal distribution of quantitative data; Mann-Whitney U, Mc Nemar Chi-square, and Cochran's Q tests were used to analyze SII values between groups and complication rates by years; sensitivity and specificity were determined by ROC analysis and considered statistically significant with a significance level of P

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.

There is an accelerating requirement for ocean sensing where autonomous vehicles can play an essential role in assisting engineers, researchers, and scientists with environmental monitoring and collecting oceanographic data. This paper is performed to develop a rigid sail for the autonomous sailing drone. Our study aims to numerically analyze the aerodynamic characteristics of curvy twin sail and compare it with wing sail. Because racing regulations limit the sail shape, only the two-dimensional geometry was open for an optimization. Therefore, this study’s first objective was to identify the aerodynamic performance of such curvy twin sails. Simultaneously, a secondary objective was to estimate the effect of the sail’s spacing and shapes. A viscous Navier-Stokes flow solver is used for the numerical aerodynamic analysis. The 2D aerodynamic investigation is a preliminary evaluation. The results have shown that the curvy twin sail designs have improved lift, drag, and driving force coefficient compared to the wing sails. The spacing between the port and starboard sails of curvy twin sail is an important parameter. The spacing is 0.035L, 0.07L, and 0.14L shows the lift coefficient reduction because of dramatically stall effect, while flow separation is improved with spacing is 0.21L, 0.28L, and 0.35L. Significantly, the spacing 0.28L shows the maximum high pressure at the lower area and the small low pressure area at leading edges, so the highest lift is generated.

The main ideas of F-transform came from representing expert rules. It would be therefore re reasonable to expect that the more accurately the membership functions describe human reasoning, the more efficient will be the corresponding F-transform formulas. We know that an adequate description of our reasoning corresponds to complicated membership functions -- however, somewhat surprisingly, most efficient applications of F-transform use the simplest possible triangular membership functions. There exist some explanations for this phenomenon which are based on local behavior of the signal. In this paper, we supplement this local explanation by a global one: namely, we prove that triangular membership functions are the only one that provide the accurate description of appropriate global characteristics of the signal.

The skyrocketing growth in the number of Internet of Things (IoT) devices will certainly pose a huge traffic demand for fifth-generation (5G) wireless networks and beyond. In-band full-duplex (IBFD), which is theoretically expected to double the spectral efficiency of a half-duplex (HD) wireless channel and to connect more devices, has been considered as a promising technology to accelerate the development of IoT. To exploit the full potential of IBFD, the key challenge is how to handle network interference (including self-interference, co-channel interference and multiuser interference) more effectively. In this paper, we propose a simple yet efficient user grouping method, where a base station (BS) serves strong downlink users and weak uplink users and vice versa in different frequency bands, mitigating severe network interference. We aim to maximize a minimum rate among all users subject to bandwidth and power constraints, which is formulated as a highly nonconvex optimization problem. By leveraging inner approximation framework, we develop a very efficient iterative algorithm to solve this problem, which guarantees at least a local optimal solution. Numerical results are provided to show not only the benefit of using full-duplex raido at BS, but also the advantage of the proposed user grouping method.

Novel molecular pinball machines of the plasma membrane control cytosolic Ca²⁺ levels that regulate plant metabolism. [https://youtu.be/zABg7LiBk88] Essential components involve: 1. an auxin-activated proton pump; 2. arabinogalactan glycoproteins (AGPs); 3. Ca²⁺ channels; 4. auxin-efflux “PIN” proteins. Typical pinball machines release pinballs that trigger various sound and visual effects. However, in plants “proton pinballs” eject Ca²⁺ bound by paired glucuronic acid residues of numerous glycomodules in periplasmic AGP-Ca²⁺. Freed Ca²⁺ ions flow down the electrostatic gradient through open Ca²⁺ channels into the cytosol thus activating numerous Ca²⁺-dependent activities.Clearly cytosolic Ca²⁺ levels depend on activity of the proton pump, the state of Ca²⁺ channels and size of the periplasmic AGP-Ca²⁺ capacitor: Proton pump activation is a major regulatory focal point tightly controlled by the supply of auxin: auxin efflux carriers conveniently known as “PIN” proteins [null mutants are pin-shaped!] pump auxin from cell to cell. Mechanosensitive Ca²⁺ channels and their activation by reactive oxygen species (ROS) are yet another factor regulating cytosolic Ca²⁺.Cell expansion also triggers proton pump/pinball activity by mechanotransduction of wall stress via Hechtian adhesion thus forming a Hechtian oscillator that underlies cycles of wall plasticity and oscillatory growth.Finally, Ca²⁺ homeostasis of plants depends on cell surface external storage as source of dynamic Ca²⁺, unlike the internal ER storage source of animals where the added regulatory complexities ranging from vitamin D to parathormone contrast with the elegant simplicity of plant life. This paper summarises a sixty year Odyssey.

The problem of scheduling is an area that has attracted a lot of attention from researchers for many years. Its goal is to optimize resources in the system. The assigning task to the lecturer is an example of the timetabling problem, a class of scheduling. This study introduces a mathematical model to assign fixed tasks (the time and required skills to be fixed) to university lecturers. Our model is capable of generating a calendar that maximizes faculty expectations. The formulated problem is in the form of a multi-objective problem that optimal makes decisions require the trade-off presence of trade-offs between two or more conflicting objectives. To solve this, we use the Compromise Programming approach to multi-objective programming. We then proposed the new version of the Genetic Algorithm to solve the introduced model. Finally, the model and algorithm tested with real scheduling data collected at the Computing Fundamental Department, FPT University, Hanoi, Vietnam.

News on the stock market contains positive or negative sentiments depending on whether the information provided is favorable or unfavorable to the stock market. This study aims to discover the news sentiment and classify news according to its sentiments with the application of PhoBERT, a Natural Language Processing model designed for the Vietnamese language. A collection of nearly 40,000 articles on financial and economic websites is used to train the model. After training, the model succeeds in assigning news to different classes of sentiments with an accuracy level of over 81%. The research also aims to investigate how investors concern about the daily news by testing the movements of the market before and after the news is released. The analysis results show that there is an insignificant difference in the stock price as a response to the news. However, investors tend to overreact to negative and positive news in the Vietnam stock market.

This study uses machine learning to identify key factors influencing the cost-effectiveness of over-the-counter (OTC) medications. By developing a novel cost-effectiveness rating (CER) from user ratings and prices, we analyzed data from Amazon. The findings indicate that FSA/HSA eligibility, symptom treatment range, safety warnings, special effects, active ingredients, and packaging size significantly impact cost-effectiveness across cold, allergy, digestion, and pain relief medications. Medications eligible for FSA or HSA funds, treating a broader range of symptoms, and having smaller packaging are perceived as more cost-effective. Cold medicines with safety warnings were found to be cost-effective due to their lower average price and effective ingredients like phenylephrine and acetaminophen. Allergy medications with kid-friendly features showed higher cost-effectiveness, and ingredients like calcium, famotidine, and magnesium boosted the cost-effectiveness of digestion medicines. These insights help consumers make informed purchasing decisions and assist manufacturers and retailers in enhancing product competitiveness. Overall, this research supports better decision-making in the pharmaceutical industry by highlighting factors that drive cost-effective medication purchases.

United States is the largest producer and the second largest exporter of broiler meat in the world. In the U.S, broiler production is largely converting to antibiotic-free programs which has caused an increase in morbidity and mortality within broiler farms. Escherichia coli and Clostridium perfringens are two important pathogenic bacteria readily found in the broiler environment and result in annual billion-dollar losses from colibacillosis, gangrenous dermatitis, and necrotic enteritis. Broiler industry is in search of non-antibiotic alternatives including novel vaccines, prebiotics, probiotics, and housing management strategies to mitigate production losses due to these diseases. This review provides an overview of the broiler industry and antibiotic free production, current challenges, and emerging research on antibiotic alternatives to reduce pathogenic microbial presence and improve bird health.

Three isoenergetic diets differing on their fishmeal/ soy protein concentrate (SPC) ratio were assessed on tissue growth and energy budget of juvenile crabs Scylla serrata in postmolt stages (PMolt) and in intermolt stages (IMolt). The average growth rate on dry matter basis, were 2.064 ± 0.324% and 0.492 ± 0.08% initial BW.day-1 during PMolt and IMolt stages respectively. The efficiency in feed conversion (FCE, %), protein retention (PRE, %) and energy retention (ERE, %) were similar for the 3 experimental diets. However, FCE, PRE and ERE in PMolt stages were 4 to 5 times higher than in IMolt stages. Feed intake, energy and protein required for growth in PMolt stages were obviously higher than in IMolt stages. The energy budgets (%total energy intake) were marginally affected by diet but were significantly affected by the molt stage. Maintenance energy was lower in PMolt stages (49.84 ± 4.9%) than in IMolt stages (83.33 ± 2.45%). The excess of maintenance energy in IMolt stages represents the portion set aside for next molt: shell energy content (4.97 ± 0.31%) and energy for ecdysis (± 28%). Conversely, recovery energy was significantly higher in PMolt stages (34.39 ± 0.99%) than in IMolt stages (8.33 ± 1.7%). In conclusion SPC sustained good tissue growth and good feed utilization and can be used as a main source of dietary protein for crab juveniles in captivity.

How complex morphological patterns form is an intriguing question in developmental biology. However, the mechanisms that generate complex patterns remain largely unknown. Here we sought to identify the genetic mechanisms that regulate the tan (t) gene in a multi-spotted pigmentation pattern on the abdomen and wings of Drosophila guttifera. Previously, we showed that yellow (y) gene expression completely prefigures the abdominal [1] and wing [2] pigment patterns of this species. In the current study, we demonstrate that the t gene is co-expressed with the y gene in nearly identical patterns, both transcripts foreshadowing the adult abdominal and wing melanin spot patterns. We identified cis-regulatory modules (CRMs) of t, one of which drives reporter expression in six longitudinal rows of spots on the developing pupal abdomen, while the second CRM activates the reporter gene in a spotted wing pattern. Comparing the abdominal spot CRMs of y and t, we found a similar composition of putative transcription factor binding sites that are thought to regulate the complex expression patterns of both terminal pigmentation genes y and t. In contrast, the y and t wing spots appear to be regulated by distinct upstream factors. Our results suggest that the D. guttifera abdominal and wing melanin spot patterns have been established through the co-regulation of y and t, shedding light on how complex morphological traits may be regulated through the parallel coordination of downstream target genes.

In this study, the resource blocks (RB) are allocated to user equipment (UE) according to the evolutional algorithms for long term evolution (LTE) systems. Particle Swarm Optimization (PSO) algorithm is one of the evolutionary algorithms, based on the imitation of a flock of birds foraging behavior through learning and grouping the best experience. In previous work, the Simple Particle Swarm Optimization (SPSO) algorithm was proposed for RB allocation to enhance the throughput of Device-to-Device (D2D) communications and improve the system capacity performance. In simulation results, with less population size of M = 10, the SPSO can perform quickly convergence to sub-optimal solution in the 100^th generation and obtained sub-optimum performance with more 2 UEs than the Rand method. Genetic algorithm (GA) is one of the evolutionary algorithms, based on Darwinian models of natural selection and evolution. Therefore, we further proposed a Refined PSO (RPSO) and a novel GA to enhance the throughput of UEs and to improve the system capacity performance. Simulation results show that the proposed GA with 100 populations, in 200 generations can converge to suboptimal solutions. Therefore, with comparing with the SPSO algorithm the proposed GA and RPSO can improve system capacity performance with 1.8 and 0.4 UEs, respectively.

In this study, a preload monitoring method using impedance signatures obtained from a piezoelectric-based smart interface is presented for bolted girder connections. Firstly, the background theory of the piezoelectric-based smart interface and its implementation into health monitoring of bolted connections are outlined. A simplified electro-mechanical (EM) impedance model of a smart interface-embedded bolted connection system is formulated to interpret mechanistic understanding of EM impedance signatures under the effect of bolt preload. Secondly, finite element modeling of a bolted connection is carried out to show the numerical feasibility of the presented method and to predetermine the sensitive frequency band of impedance signatures. Finally, impedance measurements are conducted on a lab-scaled bolted girder connection to verify the predetermined sensitive frequency range and to assess the bolt preload changes in the test structure.

During the coronavirus disease 2019 (COVID-19) pandemic, individuals with immune-mediated inflammatory diseases (IMIDs), such as systemic lupus erythematosus and rheumatoid arthritis, face a heightened risk of infection and severe outcomes due to immunological alterations resulting from their underlying conditions and immunosuppressive treatments. Even as the pandemic has transitioned to an endemic state, it remains crucial to recognize that these patients continue to be at risk. In this narrative review, we analyzed existing literature to explore the impact of IMIDs, clinical risk factors, and the influence of immunosuppressive therapies on COVID-19-related risks and outcomes. Notably, certain disease-modifying antirheumatic drugs (DMARDs), like rituximab, are associated with worse COVID-19 outcomes, and rituximab-treated patients show impaired immune responses to COVID-19 vaccination. Additionally, we outline the diverse effects of glucocorticoids on COVID-19 outcomes and management. To highlight real-life challenges faced by clinicians caring for patients with IMIDs, we present an illustrative scenario that underscores the importance of effective vaccination, timely boosting, and additional mitigation strategies against COVID-19. Given the clinical heterogeneity and diverse disease states within IMIDs, it is crucial to understand the ongoing implications and risks associated with COVID-19 in these patients, to guide the implementation of appropriate measures and optimize care and outcomes in the current endemic era.

Background: The robustness of sero-surveillence has delineated the high burden of SARS-CoV-2 infection in children; however, these existing data showed wide variation. This study aimed to identify the serostatus of antibodies against SARS-CoV-2 and associated factors among children following the fourth pandemic wave in Vietnam. Methods: A cross-sectional study was conducted at Vietnam National Children’s Hospital (VNCH) between March 13 and April 3, 2022. 4,032 eligible children seeking medical care for any medical condition not related to acute Covid-19 infections was tested for IgG SARS-CoV-2 Antibodies by ADVIA Centaur® SARS-CoV-2 IgG (sCOVG) assay using the residuals of routine blood samples. Results: The median age of enrolled children was 39 (IQR=14-82) months. The overall seropositive prevalence was 59.2%, and the median antibody titer was 4.78 [IQR 2.38-9.57] UI/mL. The risk of seropositivity and the median antibody titer was not related to gender (58.6% versus 60.1%, 4.9 versus 4.6 UI/mL, all p>0.05). Among age groups, the highest seroprevalence was reported in the children aged 13 to <36 months old. Children aged ≤12 months were likely to be seropositive compared to children aged 36 to <60 months (59.2% versus 57.5%, p=0.49) and those aged ≥144 months (59.2% versus 65.5%, p=0.16). Children aged ≥144 months exhibited a significantly higher titer of protective COVID-19 antibodies than other age groups (p <0.001). In multivariate logistic regression, we observed independent factors associated with SARS-CoV-2 seropositivity, including the age 13 to <36 months (OR=1.29, 95%CI=1.06-1.56, p=0.01), 60 to <144 months (OR=79, 95%CI=0.67-0.95, p=0.01), ≥144 months (OR=1.84, 95%CI=1.21-2.8, p=0.005), the presence of infected household members (OR=2.36, 95%CI=2.06–2.70, p<0.001), participants from Hanoi (OR=1.54, 95%CI=1.34-1.77, p<0.001), underlying conditions (OR=0.71, 95%CI=0.60-0.85, p<=0.001), and using corticosteroids or immunosuppressants (OR=0.64, 95%CI=0.48-0.86, p=0.003). Conclusions: This study highlights a high seroprevalence of antibodies against SARS-CoV-2 among children seeking medical care for non-COVID-19-related conditions in a tertiary children’s hospital in Hanoi, Vietnam. In the context of reopening in-person schools and future emerged COVID-19 variants, this point will also be a key message about the necessity of “rush-out” immunization coverage for children, especially those under the age of three years.

Magnesium is a promising material. It has a remarkable mix of mechanical and biomedical properties that made it suitable for a vast range of applications. With alloying, many of these inherent properties can be further improved. Today, it is primarily used in the automotive, aerospace, and medical industry. However, magnesium has its own set of drawbacks which the industry and research community are actively addressing. Magnesium’s rapid corrosion is its most significant drawback, and it dramatically impeded magnesium’s growth and expansion into other applications. This article will review both the engineering and biomedical aspects and applications for magnesium and its alloys. It will also elaborate on the challenges the material faces, how they can be overcome, and its outlook.

The gradient descent algorithm has become the standard algorithm for computing the extreme values of functions, but for multivariate functions this algorithm is mostly ineffective. This is because the convergence rate of each element is inconsistent in most cases. However, in this paper, we found that the gradient sign is a self-optimizing operator, ensuring that the convergence rate is consistent across all elements. This also explains, from an optimization perspective, the success of the Fast Gradient Sign Method (FGSM) in generating adversarial samples that are indistinguishable from the normal input, but can easily fool neural networks. We also found that the fractional order gradient is also self-optimizing, and that the convergence speed of this algorithm can be controlled by adjusting the order of the gradient. Experiments suggest that this algorithm not only generates adversarial samples faster than other algorithms, but that a single source image can generate many such samples. This algorithm is also more effective than others at generating adversarial samples from simple images.

Background: There has been evidence that metabolic syndrome (MetS) may increase the risk of frailty. However, there is limited evidence on this association in Asian populations. Aims: This study aims to identify the association between MetS and frailty in older people in Vietnam. Methods: This is a cross-sectional analysis of a dataset obtained from an observational study on frailty and sarcopenia in patients aged ≥60 at a geriatric hospital in Vietnam. Frailty was defined by the frailty phenotype. Participants were defined as having MetS if they had ≥3 out of 5 criteria from the definition of the National Cholesterol Education Program (NCEP) Adults Treatment Panel (ATP) III. Multiple logistic regression models were performed to estimate the risk of having frailty in patients with MetS. Results: There were 669 participants (mean age 71, 60.2% female), 62.3% had MetS and 39.0% was frail. The prevalence of frailty was 42.2% in participants with MetS, 33.7% in participants without MetS (p=0.029). On logistic regression models, MetS was associated with increased likelihood of being frail (adjusted OR 1.52, 95%CI 1.01-2.28), allowing for age, sex, education, nutritional status, history of hospitalisation and chronic diseases. Conclusion: There was a significant association between MetS and frailty in this population. Further longitudinal studies are required to confirm this association.

The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 215 countries and areas in the world, and has significantly affected every aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deaths still increase significantly and have no sign of a well-controlled situation, e.g., as of 14 April 2020, a cumulative total of 1,853,265 (118,854) infected (dead) COVID-19 cases were reported in the world. Motivated by recent advances and applications of artificial intelligence (AI) and big data in various areas, this paper aims at emphasizing their importance in responding to the COVID-19 outbreak and preventing the severe effects of the COVID-19 pandemic. We firstly present an overview of AI and big data, then identify their applications in fighting against COVID-19, next highlight challenges and issues associated with state-of-the-art solutions, and finally come up with recommendations for the communications to effectively control the COVID-19 situation. It is expected that this paper provides researchers and communities with new insights into the ways AI and big data improve the COVID-19 situation, and drives further studies in stopping the COVID-19 outbreak.

This study used double-bounded dichotomous-choice to estimate and analyze the factors affecting households’ willingness to pay (WTP) for water quality improvement. This study notes that households with higher income, living near polluted water source, using tap water instead of natural water, who are handicraft producers, and who have more members are willing to pay more. However, households who rarely hear about environmental pollution issues and who are offered a higher bid are more likely to refuse to pay. Solutions to improve water quality are suggested such as to raise people's awareness through communication channels and social organizations; to increase income associated with environmental protection policies; to construct wastewater treatment plants; to encourage the relocation of production establishments to industrial parks and industrial complexes; to put regulations on collection, payment and sanctions in case of not declaring and paying fees into village conventions; to promulgate circulars, and bylaws to concretize and simplify regulations and policies of the Government, Ministry of Natural Resources and Environment.

Wireless Powered Communication Networks (WPCN), which has attracted much attention of researchers, also been recently recommended in 5^th generation (5G) wireless networks. With the help of the WPCN, the reliability and battery life of wireless low-power devices can be improved. In this paper, we investigate throughput and ergodic capacity in WPCN-assisted amplify-and-forward (AF) relaying system, considering two transmission modes including delay-tolerant and delay-limited. As important achievement, we propose symmetric energy harvesting protocol, namely time power switching relaying (TPSR) in order to find maximal throughput. In particular, both time switching and power switching coefficients in this schemes are considered. Unlike most of the previous works, we further focus on impact of outdated channel state information (CSI) in this WPCN. In order to evaluate information processing efficiency, the performance can be substantially improved by optimally harvesting time and power coefficients of the received signal at relay node for energy and information extraction, and by deploying several scenarios. By deploying Monte Carlo simulation, it is confirmed that the system performance is more sensitive to CSI estimation error, noise variance, signal-to-noise ratio (SNR) and resulting in other reasonable computations of TPSR need be deployed to obtain QoS requirement.

Vector geographic data play an important role in the natural resources and environment sector and other location information services. This is also one of the types of data where the cost to create it is relatively large because of the difficulty in surveying, collecting, and authorizing. The rapid development of the Internet has created many advantages in the distribution, exploitation, and use of vector geographic data, but it also gives rise to many problems such as duplication, redistribution, forgery, and illegal data use. The theft on the Internet is becoming more and more sophisticated and the number of violations is increasing, showing the urgent need to research and develop an effective solution to protect the copyright of vector geographic data and prevent them from being illegally collected and used. Among the major studies and solutions, digital watermarking emerges as an effective method and is an active research area for copyright protection. Towards a good solution for copyright protection of vector geographic data, our study proposes a new algorithm with three main contributions, including: (1) generating short, pseudo-random meaningful watermarks to increase robustness and to enable automated as well as visual manual verifying; (2) building a uniformly distributed mapping between the vertex coordinates and the watermark bit indexes to increase the robustness of the watermarks; and (3) integrate two types of watermarks, namely, spatial domain-based watermarking and zero-watermarking to be resistant to most common attacks on geographic vector data. The algorithm also allows working on all types of vector geographic data, including points, polylines, and polygons.

To solve the problem of energy constraint and spectrum scarcity for cognitive radio wireless sensor networks (CR-WSNs), an underlay decode-and-forward relaying scheme is considered, where the energy constrained secondary source and relay nodes are capable of harvesting energy from a multi-antenna power beacon (PB) and using that harvested energy to forward the source information to the destination. Based on the time switching receiver architecture, three relaying protocols, namely, hybrid partial relay selection (H-PRS), conventional opportunistic relay selection (C-ORS), and best opportunistic relay selection (B-ORS) protocols are considered to enhance the end-to-end performance under the joint impact of maximal interference constraint and transceiver hardware impairments. For performance evaluation and comparison, we derive exact and asymptotic closed-form expressions of outage probability (OP) and throughput (TP) to provide significant insights into the impact of our proposed protocols on the system performance over Rayleigh fading channel. Finally, simulation results validate the theoretical results.

Background and Objectives: To analyze survival in peritoneal and hemodialysis patients using chest radiography and biochemical parameters, determine dialysis etiologies and common mortality causes, reveal prognostic factors, and contribute to clinical practice. Materials and Methods: This retrospective cohort study was based on the analysis of data from 33 peritoneal dialysis and 37 hemodialysis patients who were followed and treated in our hospital between October 2018 and February 2020. Chest X-ray measurements (cardiothoracic index, pulmonary vascular pedicle width, right pulmonary artery diameter, diaphragmatic height) and biochemical parameters (urea, albumin, creatinine, parathormone, ferritin, hemoglobin, arterial blood gas, potassium) were analyzed to assess their impact on survival. Statistical analyses were performed using the Shapiro-Wilk, Wilcoxon signed rank test, Mann-Whitney U test, McNemar test, Kaplan-Meier survival analysis, Cox regression analysis, Spearman correlation test, Phi test, and ROC analysis. Results: The most common etiologies of dialysis were hypertension, type 2 diabetes mellitus, and urogenital disorders. The most common cause of death in peritoneal dialysis patients was peritonitis (38.5%), while in hemodialysis patients, it was cardiovascular diseases (47.4%). In chest X-ray measurements, pulmonary vascular pedicle width (p=0.003) and pulmonary artery diameter increased significantly (p=0.002) in hemodialysis patients, while pulmonary vascular pedicle width (p=0.028) and diaphragmatic height (p=0.004) increased significantly in peritoneal dialysis patients. No significant difference was found between the two groups in terms of biochemical parameters. Kaplan-Meier survival analysis showed that there was no significant difference in survival between peritoneal dialysis and hemodialysis methods (P>0.05). Significant correlations were found between both radiologic status and clinical status and between intact parathormone levels and pulmonary vascular pedicle width (p=0.016, p=0.024). In Cox regression analysis, age, intact parathormone levels, iPTH/PVPW ratio, and clinical status were found to be factors affecting survival (p

Novel effluent treatment solutions for dangerous organic pollutants are crucial worldwide. In recent years, chemical reduction using noble metal-based nanocatalysts and NaBH4, a reducing agent, has become common practice for eliminating organic contaminants from aquatic environments. We suggest a straightforward approach to synthesizing magnetic cellulose nanocrystals (CNC) modified with magnetite (Fe3O4) and silver nanoparticles (Ag NPs) as a catalyst for organic contamination removal. Especially, Ag NPs were decorated on the CNC surface without reducing agents or stabilizers by reducing AgNO3. XRD, FE-SEM, TEM, EDX, VSM, BET, and zeta potential tests characterized the Ag/Fe3O4/CNC nanocomposite. The nanocomposite's catalytic activity was tested by eliminating 4-nitrophenol (4-NP) and organic dyes methylene blue (MB) and methyl orange (MO) in an aqueous solution at 25 oC. The Ag/Fe3O4/CNC nanocomposite reduced 4-NP and decolored these hazardous organic dyes in short time (2 to 5 min) using a tiny amount of catalyst (2.5 mg for 4-NP and 15 mg for MO and MB). The magnetic catalyst was removed and reused three times without losing catalytic activity. This work shows that the Ag/Fe3O4/CNC nanocomposite can chemically reduce harmful pollutants in effluent for environmental applications.

Emergency control load-shedding is a key solution to prevent blackouts in the power system. This paper proposed a new model of emergency controls load shedding based on the fast identification of the unstable state of the power system. K-means clustering algorithm divided the instability mode into the clusters. The results of analysis of this cluster were used as the basis for classification control. Building load shedding strategies is consisted of the pre-designed rules based on AHP algorithm. When the recognition of the power system “instability” is detected, the signal of load shedding control is triggered immediately, therefore the decision time is greatly shortened comparing to the traditional methods. The effectiveness of the proposed method was tested on the IEEE 39-bus to overcome the limitations of the last traditional methods.

Recurrent infections after root canal treatments often involve Enterococcus faecalis, a microorganism closely associated with therapy failures due to its biofilm production, survival in nutrient-deprived conditions, and antibiotic tolerance. Essential oils (EOs), which display anti-inflammatory, antimicrobial, and antibacterial properties, exhibit inhibitory effects on the growth of many microorganisms including E. faecalis. This study assessed the in vitro efficacy of combining antibiotics (Gentamicin 1.5mg/ml, Streptomycin 2.5 mg/ml, Ampicillin 5 mg/ml, and Kanamycin 2.5 mg/ml) with Cinnamon (1.25% to 5%) or Clove (25% to 50%) EOs using disk diffusion tests. Disks were treated with EOs-only, antibiotics-only, or EO-antibiotic combinations, placed on BEA agar plates, incubated for 24 hours, and zones of inhibition were measured against E. faecalis. Results showed robust growth inhibition by cinnamon and clove EOs across all tested concentrations. Furthermore, there were synergistic antimicrobial effects when gentamicin, streptomycin and kanamycin were combined with 2.5% and 50% concentrations of cinnamon and clove EOs, respectively, leading to significant growth inhibition of E. faecalis by 139% to 193% compared to using antibiotics or EOs alone. Clove EO showed positive synergism with three antibiotics (gentamicin, streptomycin, and kanamycin) whereas cinnamon EO showed synergism with two antibiotics (streptomycin and kanamycin). These findings suggest that combining cinnamon and clove EOs with aminoglycoside antibiotics can significantly reduce the expansion of E. faecalis compared to antibiotics alone. Further in vivo studies should determine the safety, efficacy, and treatment duration, with the potential to reduce antibiotic dosages and associated toxicity while preventing recurrent infections.

This study aims to develop an elderly care system for improving the interpersonal relationship of the elderly with mild cognitive impairment (MCI) by employing the speaker recognition technique and association functionality of social network platforms. Firstly, the speaker recognition units based on the Gaussian Mixture Model (GMM) and Gaussian Mixture Model-Universal Background Model (GMM-UBM) are implemented to identify the visitor via individual input utterance. After the visitor is identified, the proposed system will be linked to the private database and social network platforms to extract the associated message of two parties. Experimental results indicate that the speaker recognition unit based on GMM-UBM achieves the best performance. Finally, five elderly persons are invited to measure the usability of the proposed system. A questionnaire is used to survey the five elderly persons, and the result indicates that the proposed system is highly potentially applicable in improving the interpersonal relationship of the elderly with MCI.

This study aimed to evaluate the proliferation and migration of fibroblast cells derived from chronic wounds and investigate the impact of low-level laser therapy (LLLT) on their growth and migration. A total of 60 dermal samples were obtained from three sites of chronic pressure ulcers and diabetic ulcers in 20 patients. Following collection in the operating room, the dermal samples were isolated using the procedure described by Freshney RI. Fibroblasts from the wound base (Site 1) exhibited a slow proliferation rate and a decrease in proliferative capacity. Fibroblasts from wound margins (Site 2) and adjacent healing skin (Site 3) could be successfully isolated and maintained for multiple generations without any morphological changes. Fibroblasts from chronic wounds at Sites 2 and 3 showed slower proliferation rates and reduced migration capabilities compared to normal dermal fibroblasts (control samples). The fibroblast cells were exposed to LLLT at different energy levels (2.5, 3, and 3.5 J/cm2). The laser-treated groups demonstrated a significantly higher increase in cell count compared to the control sample, with the highest increase observed at an energy level of 3 J/cm2. These findings suggest that LLLT at an energy level of 3 J/cm2 could effectively enhance fibroblast migration, indicating its potential as a therapeutic intervention for chronic wounds.

A wealth of Full Waveform (FW) LiDAR data are available to the public from different sources, which is poised to boost the extensive application of FW LiDAR data. However, we lack a handy and open source tool that can be used by potential users for processing and analyzing FW LiDAR data. To this end, we introduce waveformlidar, an R package dedicated to FW LiDAR processing, analysis and visualization as a solution to the constraint. Specifically, this package provides several commonly used waveform processing methods such as Gaussian, adaptive Gaussian and Weibull decompositions, and deconvolution approaches (Gold and Richard-Lucy (RL)) with users’ customized settings. In addition, we also developed functions to derive commonly used waveform metrics for characterizing vegetation structure. Moreover, a new way to directly visualize FW LiDAR data is developed through converting waveforms into points to form the Hyper Point cloud (HPC), which can be easily adopted and subsequently analyzed with existing discrete-return LiDAR processing tools such as LAStools and FUSION. Basic explorations of the HPC such as 3D voxelization of the HPC and conversion from original waveforms to composite waveforms are also available in this package. All of these functions are developed based on small-footprint FW LiDAR data, but they can be easily transplanted to the large footprint FW LiDAR data such as Geoscience Laser Altimeter System (GLAS) and Global Ecosystem Dynamics Investigation (GEDI) data analysis. It is anticipated that these functions will facilitate the widespread use of FW LiDAR and be beneficial for better estimating biomass and characterizing vegetation structure at various scales. The package and code examples can be found at https://github.com/tankwin08/waveformlidar.

Sixty years ago in the lab adjacent to Fred Sanger (1958 Nobel Prize for protein chemistry), I discovered the cell surface hydroxyproline-rich glycoproteins. Nature keeps some of her secrets longer than others. It has taken many years to dissect the molecular function and biological role of extensins and arabinogalactan proteins (AGPs). Extensins template the formation of new cell walls. AGPs remained baffling and enigmatic until a Eureka moment when computer prediction of AGP calcium binding depicted paired glucuronic acid residues and thus the likely role of a cell surface AGP-Ca²⁺capacitor: In conjunction with the auxin-activated proton pump that releases bound Ca²⁺ it led us to formulate the Hechtian Growth Oscillator as A Global Paradigm with a pivotal role in Ca²⁺ homeostasis. The ramifications are profound. They cannot be shrugged off with sceptical disdain but demand critical reappraisal of current dogma. Phyllotaxis is an ancient problem; it involves an essential role for auxin and the auxin efflux “PIN” proteins together with mechanotransduction of stress-strain as phyllotactic determinants. However, a general explanation remains elusive despite much effort, particularly by mathematicians. Here we propose a novel biochemical algorithm: Hechtian oscillator transduction of cell wall stress generates phyllotactic patterns quite independent of a mathematical approach. Plants simply use different rules and follow a different route.

In the book “Everyhing Is A Circle: A New Model For Orbits Of Bodies In The Universe”, and further in the Article “Distance Between Two Circles in Any Number of Dimensions is a Vector Ellipse”, it has been mathematically demonstrated that “distance between points on any two different circles in any number of multiple dimensions” is equivalent to “distance of points on a vector ellipse from another fixed or moving point”. Using this mathematical methodology, a method is provided in this Article as a measure for the amount of interaction between two international economies, which are two countries or economic zones, by modelling each economy in terms of a “circle in four dimensions”. Based on this method, the proximity of the two economies at the end of each fiscal period, which is generally a fiscal year, is then measured by the distance between points at the end of the given period on the two circles in four dimensions, associated with these two economies in our model.

Based on measured astronomical position data of heavenly objects in the Solar System and other planetary systems, all bodies in space seem to move in some kind of elliptical motion with respect to each other. According to Kepler’s 1^st Law, “orbit of a planet with respect to the Sun is an ellipse, with the Sun at one of the two foci.” Orbit of the Moon with respect to Earth is also distinctly elliptical, but this ellipse has a varying eccentricity as the Moon comes closer to and goes farther away from the Earth in a harmonic style along a full cycle of this ellipse. In this paper, our research results are summarized, where it is first mathematically shown that the “distance between points around any two different circles in three dimensional space” is equivalent to the “distance of points around a vector ellipse to another fixed or moving point, as in two dimensional space”. What is done is equivalent to showing that bodies moving on two different circular orbits in space vector wise behave as if moving on an elliptical path with respect to each other, and virtually seeing each other as positioned at an instantaneously stationary point in space on their relative ecliptic plane, whether they are moving with the same angular velocity, or different but fixed angular velocities, or even with different and changing angular velocities with respect to their own centers of revolution. This mathematical revelation has the potential to lead to far reaching discoveries in physics, enabling more insight into forces of nature, with a formulation of a new fundamental model regarding the motions of bodies in the Universe, including the Sun, Planets, and Satellites in the Solar System and elsewhere, as well as at particle and subatomic level. Based on the demonstrated mathematical analysis, as they exhibit almost fixed elliptic orbits relative to one another over time, the assertion is made that the Sun, the Earth, and the Moon must each be revolving in their individual circular orbits of revolution in space. With this expectation, individual orbital parameters of the Sun, the Earth, and the Moon are calculated based on observed Earth to Sun and Earth to Moon distance data, also using analytical methods developed as part of this research to an approximation. This calculation and analysis process have revealed additional results aligned with observation, and this also supports our assertion that the Sun, the Earth, and the Moon must actually be revolving in individual circular orbits.

Carotid intima-media thickness (CIMT) is a surrogate indicator for atherosclerosis and has been shown to predict cardiovascular risk in multiple large studies. Identifying and characterizing molecular markers for carotid atheroma plaque formation can be critical for early intervention and prevention of atherosclerosis. This study performed transcription factor (TF) network analysis of transcriptomic data focusing on two TF genes, ZNF385D, HAND2, whose polymorphisms reportedly associate with carotid atherosclerosis. Gene expression data were measured from pieces of carotid endarterectomy of hypertensive patients each paired with one sample of distant macroscopically intact tissue. TF networks were reconstructed for ZNF385D and HAND2 and their association with carotid atheroma progression examined using gene-set enrichment analysis with high statistical significance (p<6.95e-7) suggesting involvement of expression quantitative loci (eQTL). Examination of the regulation and correlation patterns suggests high clinical and interventional impacts of the two TF genes on impairing carotid atheroma plaque formation and preventing carotid atherosclerosis.

Morphogenesis remains a riddle, wrapped in a mystery, inside an enigma. It remains a formidable problem viewed from many different perspectives of morphology, genetics, and computational modelling. We propose a biochemical reductionist approach that shows how both internal and external physical forces contribute to plant morphogenesis via mechanical stress-strain transduction from the primary cell wall tethered to the plasma membrane by a specific arabinogalactan protein (AGP). The resulting stress vector with direction defined by Hechtian adhesion sites, has a magnitude of a few picoNewtons amplified by a hypothetical Hechtian growth oscillator. This paradigm shift involves stress activated plasma membrane Ca2+channels and auxin-activated H+-ATPase. The proton pump dissociates periplasmic AGP-glycomodules that bind Ca2+. Thus, as the immediate source of cytosolic Ca2+ an AGP-Ca2+ capacitor directs vectorial exocytosis of cell wall precursors and auxin efflux (PIN) proteins. In toto these components comprise the Hechtian Oscillator and also the gravisensor. Thus interdependent auxin and Ca2+ morphogen gradients account for the predominance of AGPs. The size and location of a cell surface AGP-Ca2+ capacitor is essential to differentiation and explains AGP correlation with all stages of morphogenetic patterning from embryogenesis to root and shoot. Finally, evolutionary origins of the Hechtian Oscillator in the unicellular Chlorophycean algae reflect the ubiquitous role of chemiosmotic proton pumps that preceded DNA at the dawn of life.

Natural gas hydrate, also known as combustible ice and mainly composed of methane, it is identified as the potential clean energy in the 21th century. Due to its large reserves, gas hydrate can ease problems caused by energy resource shortage and has gained attention around the world. In this paper, we focus on the exploration and development of gas hydrate as well as discussing its status and future development trend in China and abroad, then we analyze its opportunities and challenges in China from four aspects: resource, technology, economy and police with five forces model and PEST method. The results show, China has abundance gas hydrate resource; however the backward technologies and inadequate investment has seriously hindered the future development of gas hydrate, so China should establish relevant cooperation framework and intuitional arrangement to attract more investment as well as breaking through technical difficulties to make gas hydrate commercialization as soon as possible.

The advance of the medical field in the 21st century has influenced the development of many innovations, including in medical education. PBL (problem-based learning) is one of the pedagogical approaches that has been studying and implementing worldwide to attract medical students’ attention with their learning style and learning environment. China is the most significant “receiver” country of foreign students in Asia, and clinical medicine is one of the most chosen majors for undergraduate. In China, PBL has been implementing in some schools, but mostly with the local students and only a few implementations to the international students. International medical students in China faced a variety of challenges during their studies. In this review paper, we give the solution to adapt to the challenges by focusing on the implementation the integrated organ/system curriculum/syllabus with the PBL method to the school system with the support of the school stakeholders and students’ role.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging infectious disease with currently a pandemic state. Cardiac function can be involved, affecting prognosis, in addition with lung feature severity, particularly in patients with comorbidities. Since the renin angiotensin aldosterone (RAA) system may interact with SARS-Cov-2, researches are still ongoing to assess the prognostic value of RAA blockers in cardiology.

To ensure consumers can purchase high-quality rice, accurate identification of rice varieties is particularly important. Methods: This article conducts research based on machine learning algorithms from the perspectives of image, spectrum, and spectrogram fusion. Six types of hyperspectral image data of rice were preprocessed using convolutional smoothing (SG) and multiple scatter correction (MSC). Texture information of the images was extracted using gray-level co-occurrence matrix. Spectra, texture, and spectrogram data were fused into a new matrix. Spectral, texture, and spectrogram fusion data were used as inputs for the model, and support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) classification models were constructed and compared. Results: From the classification results, the spectrogram fusion classification performance was better than classification models using only spectra or texture. Conclusion: The research results showed that the accuracy of SVM and LR classification models exceeded 90%, and the LR model performed the best, effectively classifying rice varieties.

Donepezil (DPZ) is an acetylcholinesterase inhibitor used for the clinical treatment of mild cognitive impairment. However, DPZ has been reported to have adverse effects, including abnormal cardiac rhythm, insomnia, vomiting, and muscle cramps. However, the existence of these effects in subjects without Dementia is unknown. In this study, we use zebrafish to conduct a deeper analysis of the potential adverse effects of DPZ on the short-term memory and behaviors of normal zebrafish by performing multiple behavioral and biochemical assays. Adult zebrafish were exposed to 1 ppm and 2.5 ppm of DPZ. From the results, DPZ caused a slight improvement in the short-term memory of zebrafish and induced significant elevation in aggressiveness, while the novel tank and shoaling tests revealed anxiolytic-like behavior to be caused by DPZ. Furthermore, zebrafish circadian locomotor activity displayed a higher reduction of locomotion and abnormal movement orientation in both low- and high-dose groups, compared to the control group. Biomarker assays revealed that these alterations were associated with an elevation of oxytocin and a reduction of cortisol levels in the brain. Moreover, the significant increases of reactive oxygen species (ROS) and malondialdehyde (MDA) levels in muscle tissue suggest DPZ exposure induced muscle tissue oxidative stress and muscle weakness, which may underlie the locomotor activity impairment. In conclusion, we show, for the first time, that the chronic waterborne exposure of DPZ can severely induce adverse effects on normal zebrafish in a dose-dependent manner. These unexpected adverse effects on behavioral alteration should be carefully addressed in future studies considering DPZ conducted on zebrafish or other animals.

Based on measured astronomical position data of heavenly objects in the Solar System and other planetary systems, all bodies in space seem to move in some kind of elliptical motion with respect to each other, whereas objects follow parabolic escape orbits while moving away from Earth and bodies asserting a gravitational pull, and some comets move in near-hyperbolic orbits when they approach the Sun. In this article, it is first mathematically proven that the “distance between points on any two different circles in three-dimensional space” is equivalent to the “distance of points on a vector ellipse from another fixed or moving point, as in two-dimensional space.” Then, it is further mathematically demonstrated that “distance between points on any two different circles in any number of multiple dimensions” is equivalent to “distance of points on a vector ellipse from another fixed or moving point”. Finally, two special cases when the “distance between points on two different circles in multi-dimensional space” become mathematically equivalent to distances in “parabolic” or “near-hyperbolic” trajectories are investigated. Concepts of “vector ellipse”, “vector hyperbola”, and “vector parabola” are also mathematically defined. The mathematical basis derived in this Article is utilized in the book “Everyhing Is A Circle: A New Model For Orbits Of Bodies In The Universe” in asserting a new Circular Orbital Model for moving bodies in the Universe, leading to further insights in Astrophysics.

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.

Miscarriage due to blastocyst implantation failure occurs in up to two-thirds of all miscarriage cases in human. The calcium ion has been shown to be involved in many cellular signal transduction pathways as well as in the regulation of cell adhesion, which is necessary for the embryo implantation process. Exposure to endocrine-disrupting chemicals (EDs) during early gestation results in disruption of intrauterine implantation and uterine reception, leading to implantation failure. In this study, ovarian estrogen (E2), bisphenol A (BPA), or 4-tert-octylphenol (OP), with or without ICI 182,780 (ICI) were injected subcutaneously from gestation day 1 to gestation day 3 post-coitus. The expression levels of the calcium transport genes were assessed in maternal uteri and implantation sites. The number of implantation sites was significantly low in the OP group, and implantation sites were absent in the E2 and EDs+ICI groups. There were different calcium transient transport channel expression levels in uterus and implantation site samples. The levels of TRPV5 and TRPV6 gene expression were significantly increased by EDs with/without ICI treatment in uterus. Whereas, TRPV5 and TRPV6 gene expression were significantly lower in implantation sites samples. NCX1 and PMCA1 mRNA levels were significantly decreased by OP and BPA in the implantation site samples. Compared to vehicle treatment in uterus, both the MUC1 mRNA and protein levels were markedly high in all but the BPA group. Taken together, these results suggest that both BPA and OP can impair embryo implantation through alteration of calcium transport gene expressions and by affecting uterine receptivity.

The mutton quality of Chinese Tan lambs (Ovis aries) has declined as feeding patterns have shifted from pasturing to pen rationing. Mutton quality is affected by fatty acids, and rumen microorganisms play a role in the synthesis of short-chain fatty acids, long-chain fatty acids, and conjugated linoleic acids. We used 16S rDNA sequencing to analyze the effects of two feeding patterns on the rumen bacteria of Tan lambs. In a randomized block design with 24 newborn Tan lambs, 12 lambs were fed by ewes in pasture and 12 were fed by pen-fed ewes. At 2 months, the biceps femoris and the longissimus dorsi were analyzed by gas chromatography for intramuscular fat content and fatty acid composition, and DNA in the rumen contents was extracted and used to analyze the structure of the bacterial community. Different feeding patterns had no significant effect on the intramuscular fat content of the biceps femoris and longissimus dorsi of the lambs, but there was a significant effect on fatty acid composition. Rumen bacteria were significantly more diverse in the pasture group than in the pen-ration group (P < 0.01). Twenty-one phyla were identified in the pasture group, and 14 phyla were identified in the pen-ration group. The dominant phyla in the pasture group were Bacteroidetes and Fibrobacteres; the dominant phyla in the pen-ration group were Proteobacteria and Bacteroidetes. The relative abundance of Proteobacteria was significantly higher in the pen-ration group than in the pasture group (P < 0.01). Diversity at the genus level was also higher in the pasture group, with 176 genera in the pasture group and 113 genera in the pen-ration group. The dominant genera in the pasture group were Prevotella_1, Rikenellaceae_RC9_gut_group, and Bacteroidales_BS11_gut_group_Na; the dominant genera in the pen-ration group were Prevotella_1, Prevotella_7, Succinivibrionaceae_UCG-001, and Succinivibrionaceae_NA.

Based on the major, trace element, and isotope data of the Cenozoic basalts in the study area, it is indicated that the basalts in this region can be classified into three distinct magma systems: alka-li basalts, tholeiite basalts, and Nushan alkali basalts. The geochemical characteristics observed in the studied basalts indicate that the mantle source in this region might have experienced met-asomatic processes prior to partial melting, which could be linked to an ancient subduction pro-cess. Combining the geochemical characteristics in the studied basalts with previous research, we propose that the underlying mantle source in Anhui province may have undergone metaso-matism due to the carbonatitic melts. These melts are believed to have originated from car-bonated eclogite, derived from subducted Pacific slab materials present in the deeper mantle. According to the Sr-Nd isotope data, it is suggested that the mantle source in the Nushan region could be derived from a depleted asthenospheric mantle, while the basaltic composition in the Niugang area may be representative of the mantle's end components associated with the EM-I enriched mantle source present in this study area. Therefore, we propose that the Anhui basalts may have originated from the partial melting of a mantle source representing a mixing of two end-members: DMM (Depleted MORB Mantle) and EM-Ⅰ (Enriched Mantle 1). The Anhui basal-tic magmas may have originated from the partial melting of EM-Ⅰ, potentially influenced by upwelling asthenospheric mantle or asthenospheric diapirism processes. The mantle source in the study area experiences partial melting at 1-5%, 15%, and 1-10%, resulting in the formation of parent magmas for alkali basalt, tholeiitic basalt, and Nushan alkali basalt. Subsequently, the parent magmas experienced fractional crystallization processes, which included minerals like olivine, pyroxene, and plagioclase. This led to the formation of various types of basalt in the study area.

Allanite minerals are the principal host of REEs in the Sin Quyen, Iron Oxide Copper Gold (IOCG) type deposit. The studied allanites have concentrations of: REE (14-27 wt%), Ca (9-16 wt%), Al (8-19 wt%), Si (26-34 wt%) and Fe (12-21 wt%). Two populations of allanite are documented, the first is texturally older probably related to the Ca-K alteration (second stage of crystallization). This population has higher REE concentrations ranging from 20 to 27 wt%, and the second population texturally younger has lower total REE concentration ranging from 14 to 19.9 wt%, which occur as a rim surrounding the older and likely arose during the K alteration with Cu-Au mineralization (third crystallization). Differences between the two allanite populations are documented by both optical properties and analysis of their chemical composition. The last parameter indicate that the studied allanites belong to the Ce-La-ferriallanite family, with low HREE with an average of 0.21 wt.%. Temperature 355ºC which was calculated using value of δ34S isotopes is interpreted as a temperature of the second crystallization stage of allanite. The pressure of crystallization solution was calculated and is ranging from 0.98 to 5.88 MPa.

This paper investigates the roll parameter estimation of periodic disturbances where the amplitude, frequency, offset, and phase are hardly recognized in real practice. The key problem is to make an estimation that could eliminate the unknown disturbance parameters. An adaptive mechanism applies these four parameters to the globally exponential convergence using linear second-order filters and parameter estimation errors. Then, a backstepping controller is employed to make an exponential convergence to zero of the state variables. Moreover, reservoir computing is used to forecast chaotic roll motions to support predictability using Lyapunov exponents and the Poincaré map. Numerical simulations are demonstrated to validate the dynamical behaviors and efficacy of the proposed control scheme with machine learning.

Flow sensing in hostile environment is of increasing interest for applications in automotive, aerospace, and chemical and resource industries. Compared to their counterparts, thermal flow sensors are attractive candidates due to the ease of fabrication, lack of moving parts and higher sensitivity. Recently, a number of thermal flow sensor prototypes have been reported in the literature demonstrating the measurement of fluid flows under hostile conditions. This paper summarizes the concept of thermal flow sensing, operational modes and transduction mechanisms. Then, the choice of materials and their corresponding properties are presented in details. The paper also reports recent progress in the development of thermal flow sensors for harsh environment. In addition, the issues and considerations in packaging are reviewed. Finally, we conclude the review with the future prospects.

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.