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

Ca-bentonite (CB) alone and in a mixture with limestone (L), tobacco biochar (TB) and zeolite (Z) on the fixation, geochemical fractions and absorption of Cd and Zn by Chinese cabbage in smelter heavily polluted (S-HP) and smelter low polluted (S-LP) soils were investigated. The results showed that the CB+TB and CB+L+TB treatments significantly immobilized Cd up to 22.03% and 29.68%, respectively, and reduced uptake by Chinese cabbage shoot to 35.98% with CB+Z+L and 61.35% with CB+L in S-HP and S-LP soils compared with the control. The CB+ Z+ L+TB treatment mobilized Cd up to 4.45% and increased absorption in the shoot by 9.85% in S-HP soil. The greatest immobilization of Zn was 53.18% and 58.20% with the CB+Z+L+TB treatment, which reduced Zn uptake in the plant shoot by 9.94% with CB + L and 58.04 with CB+Z+L+TB in S-HP and S-LP soils. The CB+Z+TB and CB+TB treatments mobilized Zn up to 35.40% and 4.80%, respectively, in both soils. Furthermore, the uptake of Zn in plant shoot was observed by 58.96% and 7.82% with application of CB+Z and CB+TB treatments, respectively, in S-HP and S-LP soils. Overall, our results suggest that Ca-bentonite alone and in mixtures with different amendments can be used to reduce the phyto-extraction of Cd and Zn in Zn-smelter polluted soils.

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.

Tidal inlets with attached sand spits are a very common coastal morphology. Since the evolution of the sand spits along the coastline have greatly affected on the social-economic development of local coastal areas. However, previous studies mainly focused on the sand spits which are usually in the scales of hundred meters in width. Therefore, in this study, morphological change of a smaller and unexplored sand spit located in the west coast of Phu Quoc Island, will be investigated. It was found that there is a seasonal variation in the evolution of the sand spit at Song Tranh Inlet. The Longshore sediment transport rates (LSTR) along the spit are in the order from 104 to 105 m3/year. LSTRs of fourteen inlets in the literature were reviewed and the LSTRs at Song Tranh Inlet are higher than half of the LSTRs along the fourteen reviewed inlets. This study aims at contrib-uting to the growing literature on sand spit morphological changes as well as the sustainable coastal management for Phu Quoc Island which is well known as the Pearl Island of Vietnam.

Various methods of polymer surface tailoring have been studied to control the changes in wetting behavior. Polymers having precisely controlled wetting behavior in a specific environment are blessed with a wealth of opportunities and potential applications exploitable in biomaterial engineering. The controlled wetting behavior can be obtained by combining surface chemistry and morphology. Plasma assisted polymer surface modification technique have played a significant part to control surface chemistry and morphology. This review focuses on plasma polymerization and investigations regarding surface chemistry, surface wettability, coating kinetics, as well as coating stability. We begin with brief overview of plasma polymerization; these include growth mechanisms of plasma polymerization and influence of plasma parameters. Next, surface wettability and theoretical background structures and chemistry of superhydrophobic and superhydrophilic surfaces. In this review, overview of recent work on tunable wettability by tailoring surface chemistry and physical appearance (i.e. substrate texture) is also described. The formation of smart polymer coatings, which adjust their surface wettability by according to outside environment, including, pH, light, electric field and temperature. Finally, the applications of tunable wettability and pH responsiveness of polymer coatings in real life are addressed. This review should be of interest to plasma surface science communality specifically focused controlled wettability of smart polymer surfaces.

The electrokinetics methods have a great potential to characterize hydrogeological processes in geological media, especially in complex hydrosystems such as fractured formations. In this work, we conceptualize fractured media as a bunch of parallel capillary fractures following the fractal size distribution. This conceptualization permits to obtain analytical models for both the electrical conductivity and the electrokinetic coupling in water saturated fractured media. We explore two different approaches to express the electrokinetic coupling. First, we express the streaming potential coupling coefficient as a function of the zeta potential and then we obtain the effective charge density in terms of macroscopic hydraulic and electrokinetic parameters of porous media. We show that when the surface electrical conductivity is negligible, the proposed models reduces to the previously proposed one based on a bundle of cylindrical capillaries. This model opens up a wide range of applications to monitor the water flow in fractured media.

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

This article presents a study conducted within a wind tunnel to enhance understanding of the excitation mechanism of stay cable vibration under arid conditions. Numerous wind tunnel tests were meticulously analyzed. Initially, the vibration of the stay cable was measured under steady flow conditions at a flow angle of 45 degrees and an inclination of 25 degrees, while varying wind velocities were applied. Additionally, an investigation into the flow field surrounding the stay cable was conducted in both vertical and horizontal directions. By utilizing two hot wire anemometers in the cable wake, an extensive database of flow field measurements was obtained. The experimental results revealed that the vibration characteristics of the stay cable under the arid conditions considered in this study aligned with findings reported in existing literature. Notably, a deeper comprehension of the excitation mechanism of a stay cable in a dry state was attained. This mechanism is closely associated with the inhibition of Karman vortices and the development of low-frequency vortices. At low wind speeds, Karman vortices predominated, resulting in small-amplitude vibrations. However, as the wind speed increased, the influence of Karman vortices diminished progressively, while the low-frequency vortices grew stronger. These low-frequency vortices exhibited high energy and a significant correlation with shedding along the stay cable, thereby inducing cable vibration in a dry environment.

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.

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

The Inventory Déjà Vu Experiences Assessment (IDEA) is the only screening instrument proposed to evaluate Déjà vu (DV) experience. Here we intended to validate the Italian version of IDEA (I-IDEA) and at the same time to investigate the incidence and subjective qualities of DV phenomenon in Italian healthy adult individuals on basis of an Italian multicentre observational study. In this study we report normative data on the I-IDEA, collected on a sample of 542 Italian healthy subjects aging between 18 to 70 years (average age 40, range 18-70) with a formal educational from 1-19 years. From September 2013 to March 2016 were recruited 542 healthy volunteers from ten outpatient neurological clinics in ItalyAll participants (i.e family members of neurological patients enrolled, medicine’s student, physicians) had no neurological or psychiatric illness and they gave informed consent to participate in the study. All subjects enrolled had self-administered the questionnaire and they are able to complete I-IDEA test without any support. In total 396 (73%) of the 542 healthy controls had DV phenomenon. The frequency of DV was inversely related to age as well as to derealisation, jamais vu, precognitive dreams, depersonalization, paranormal activity, remembering dreams, travel frequency and daydreams (all P<0.012). The Italian version of IDEA maintains good properties in Italian version, thus confirming that this instrument is reliable for detecting and characterising the DV phenomenon.

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 paper analyzes calorie consumption in Vietnam using the household survey data. The data suggest that food insecurity is still a major problem in Vietnam, with nearly 40 percent of the population being unable to meet their calorie requirement. Employing nonparametric and parametric estimation techniques, the paper examines the relationship between household calorie consumption and per capita household expenditure in Vietnam. The analysis indicates a positive and significant relationship between per capita expenditure and per capita calorie consumption. The mean calorie elasticity is estimated to be between 0.21 and 0.31 by the parametric method and 0.20 by non-parametric method. In addition, simulated income and food price changes indicate that undernutrition is very responsive to changes in income and food prices

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.

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.

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

In 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.

BackgroundIntracranial hemorrhage (ICH) in pregnancy, estimated at 1 in 10,000 cases, presents significant diagnostic challenges prenatally despite advanced imaging techniques such as ultrasound (US) and MRI. Detecting ICH is crucial for pregnancy management and future treatment decisions aimed at improving fetal survival and reducing brain damage. This report presents the diagnosis and outcomes of two cases of prenatal ICH.Cases presentationThe first case involves a 30-year-old pregnant woman with irregular prenatal care diagnosed with ICH at 32 weeks of gestation via US and MRI. She chose to continue the pregnancy, delivering a 3160g male infant at 36 weeks via cesarean section. Following NICU care including resuscitation and ventriculoperitoneal shunt placement, the infant was discharged. Subsequent examinations showed a reduction in ventricle size. In the second case, a 27-year-old woman taking acenocoumarol for a mechanical heart valve developed fetal subdural hemorrhage detected by US and MRI. She opted to terminate the pregnancy, resulting in a stillborn male infant weighing 1530g.ConclusionFetal ICH presents with varying severity and prognostic implications, diagnosed and graded using US. Fetal cranial MRI may help clarify the etiology. Management remains controversial, with termination of pregnancy potentially warranted in severe cases due to poor prognosis. Further research is needed to refine management and improve outcomes in fetal ICH.

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.

A highly crystallized monoclinic-scheelite type BiVO4 powders were successfully synthesized by solvothermal method. The as-synthesized BiVO4 powders were characterized by XRD, FE-SEM, Raman spectroscopy, UV-vis DRS spectroscopy and TA-PL. From the XRD data and Raman spectra, the monoclinic-scheelite phase BiVO4 sample can be obtained at higher solvothermal synthesis temperature more than 140 oC. The preparation conditions such as, the Bi/V molar ratio and synthesis temperature, have significantly effects on the morphologies of the BiVO4 samples. BVO2 sample shows the highest PL peak, which has the highest formation rate of OH radicals and the highest photocatalytic activity. This result suggests that the formation rate of OH radicals shows a good correlation with the photocatalytic activity.

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

The objective of this study was to describe the overall pattern of morbidity and mortality of children seen at the Thai Binh Pediatric Hospital in Vietnam, with a focus on infectious diseases. A retrospective review of hospitalisation records was conducted from 1 January 2015 to 31 December 2019. Data were obtained from a total of 113,999 records. The median age of patients was 18 months, with 83.98% of patients aged <5 years. Infectious diseases accounted for 61.0% of all cases. The most prevalent diseases were lower respiratory tract infections (32.8%), followed by gastrointestinal infections (13.3%) and confirmed influenza (5.4%). Most infections were not microbiologically documented. A total of 81.4% patients received at least one antibiotic. Most patients (97.0%) were hospitalised for less than 15 days. Regarding outcomes, 87.8% patients were discharged home with a favourable outcome. 12.0% were transferred to the Vietnam National Children’s Hospital because their condition had worsened and 0.1% died. In total, infectious diseases accounted for 40.4% of deaths, followed by neonatal disorders (34.6%). Our data serves a basis for the identification of needs for diagnostic tools and for future evaluation of the effect of the targeted implementation of such facilities. Point-of-care tests, including real-time PCR assays to identify common pathogens should be implemented for more accurate diagnosis and more appropriate antibiotic use.

High-throughput research on bimetallic nanoparticles brought a vast overview of their characteristics and catalytic activities.¹ However, traditional bimetallic nano-allloy quantification methods serving catalyst preparations are not suitable for the fast and robust data output of high-throughput experiments. Hence, this work designed and validated a more fast, more neat, and reliable quantitative analysis using X-ray fluorescence spectroscopy for bimetallic nanoparticles synthesized by high-throughput setups. The results demonstrated this method to be accurate with high precision. Furthermore, the agreement to qualitative results from an energy-dispersive X-ray spectrometer equiped on a scanning electron microscope provided an option to quantify a bimetallic nano-alloy by just analyzing one of the two composing elements. Thus, this method is proved to be highly compatible with high-throughput experiments.

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.

This study presents the main ideas of sustainable cultural tourism development, a form of tourism associated with work discover and explore the culture of each region. It implies taking into account economic, environmental and socio-cultural aspects by tourism planning and management. The paper presents the historical background of the idea of sustainability, the factors that affect the sustainability of culture in tourism development. The author emphasizes the negative effects of tourism on cultural preservation that can be prevented by applying the principles of sustainable development; at the same time, propose solutions to balance economic development and cultural preservation.

In history and the present, Buddhism holds an important position in the spiritual life of Vietnamese people. For about two thousand years of existence and development with the Vietnamese people, Buddhism has left many valuable (tangible and intangible) heritage, has contributed a significant part in creating the cultural values of the nation. This research focuses on analyzing how did Buddhism creates heritages, how that Buddhism religion heritage becomes the cultural heritage of the Vietnamese people, the values that Buddhism religious heritage contributed to the culture of Vietnam.

In all forms of folk beliefs, ancestor worship is a universal traditional belief form of the Vietnamese people. As a Vietnamese people, “everyone worships their ancestors, everyone worships their parents and grandparent”. Ancestor worship is a common belief in the whole country. It is a belief that expresses the deeply humanistic spirit of the Vietnamese people and has great values in human life. So, what is the nature of ancestor worship? What is the values of ancestor worship in life? And in the context of globalization, how has this the belief changed? This study focuses on analyzing the above contents, thereby highlighting the value of this belief in the spiritual life of Vietnamese people; to point out the positive and negative changes of this belief in the current period; from that, take the right measures to bring into play the positive and limit the negative side of those changes in the spiritual life of Vietnamese people.

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 corrosion of prestressing steel in prestressed concrete bridges is a critical issue for bridge maintenance. To assess structures with corroded strands, it is necessary to define the mechanical properties of the strands and their influence on the structural behavior. In this study, corroded strands are taken from external tendons in existing bridges and tested to define the effects of corrosion on the tensile properties of the strand. Empirical equations for the tensile strength and ductility of the corroded strand are proposed using test results. The most corroded wire governs the mechanical properties of the strand. Experiments on prestressed concrete beams with a single corroded strand are conducted to investigate the structural behavior. A reduction in the flexural strength and maximum deformation is observed from the experiment. According to the section loss of a wire in a strand and its location in a beam, the flexural capacity can be evaluated using the proposed equation. The reduced ultimate strain of the corroded strand can be the governing factor of the flexural strength.

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.

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.

Optical wireless communication is a promising emerging technology that addresses the limitations of radio-frequency-based wireless technologies. This study presents a novel hybrid modulation for optical camera communication (OCC); it integrates two waveforms transmitted from a single transmitter light-emitting diode (LED) and received by two rolling-shutter camera devices. Then, a smart camera with a high-resolution image sensor captures the high-frequency signal, and a low-resolution image sensor from a smartphone camera captures the low-frequency signal. Through this hybrid scheme, two data streams are transmitted from a single LED lamp; this reduces the cost of the indoor OCC device compared to one that transmits two signals from two different LEDs. In proposed scheme, rolling-shutter orthogonal frequency-division multiplexing is used for the high-frequency signals, and M-ary frequency-shift keying is used for the low-frequency signals in the time domain. This proposed scheme is compatible with smart phone camera and USB camera. By controlling the OCC parameters, the hybrid scheme can be implemented with high performance for a communication distance of 10 m.

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 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.

Wearable sensors for human physiological monitoring have attracted tremendous interest from researchers in recent years. However, most of the research was only done in simple trials without any significant analytical algorithms. This study provides a way of recognizing human motion by combining textile stretch sensors based on single-walled carbon nanotubes (SWCNTs) and spandex fabric (PET/SP) and machine learning algorithms in a realistic applications. In the study, the performance of the system will be evaluated by identification rate and accuracy of the motion standardized. This research aims to provide a realistic motion sensing wearable products without unnecessary heavy and uncomfortable electronic devices.

Emerging evidence has shown that microRNAs play pivotal roles in wound healing. MicroRNA-21 (miR-21) was previously found to upregulate in order to fulfill an anti-inflammation role for wounds. Exosomal miRNAs have been identified and explored as essential markers for diagnostic medicine. However, the role of exosomal miR-21 in wounds has yet to be well studied. In order to facilitate the early management of poorly healing wounds, we developed an easy-to-use, rapid, paper-based microfluidic-exosomal miR-21 extraction device to determine wound prognosis in a timely manner. We isolated and then quantitatively examined exosomal miR-21 in wound fluids from normal tissues, acute and chronic wounds. Eight improving wounds displayed lower levels of exosomal miR-21 expression after wound debridement. However, four instances of increased exosomal miR-21 expression levels were notably associated with patients with poor healing wounds despite aggressive wound debridement, indicating a predictive role of tissue exosomal miR-21 for wound outcome. Paper-based nucleic acid extraction device provides a rapid and user-friendly approach for evaluating exosomal miR-21 in wound fluids as a means of monitoring wounds. Our data suggest that tissue exosomal miR-21 is a reliable marker for determining current wound status.

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

In recent years, nonalcoholic fatty liver disease/steatohepatitis (NAFLD/NASH) has become a leading worldwide disease, and its therapies are facing many complexities. Peroxisome proliferator-activated receptors (PPARs) are ligand-activated transcription factors that belong to the nuclear receptor (NR) superfamily and have three subtypes: PPARα (NR1C1), PPARβ/δ (NR1C2), and PPARγ (NR1C3). They have been identified to be essential in the regulation of lipid metabolism by controlling the transcription of genes related to fatty acids, bile acids, and cholesterol metabolism. Many PPAR agonists have been reported, such as natural agonists (fatty acids, eicosanoids, and phospholipids) and synthetic ligands (fibrates, thiazolidinediones, glitazars, and elafibranor). PPAR-based chemicals have a breakthrough in the innovation of therapy for fatty liver disease. This review will provide an overview of how PPARα and PPARγ play roles in lipid homeostasis, discussing the consideration of their agonists as potential therapeutic agents for NAFLD/NASH.

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 .

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

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.

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.

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.

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 &lt; 0.01) and increased fibroblast count, neovascularization, and mitotic index (P &lt; 0.01). These findings highlight the potential of SCL-MSCs as a valuable resource for burn wound research and treatment.

This study aimed to characterize the long non-coding RNA (lncRNA) expression in the bovine mammary gland and to infer their functions in dietary response to 5% linseed oil (LSO) or 5% safflower oil (SFO). Twelve cows (six per treatment) in mid lactation were fed a control diet for 28 days followed by a treatment period (control diet supplemented with 5% LSO or 5% SFO) of 28 days. Mammary gland biopsies were collected from each animal on day-14 (D-14, control period), D+7 (early treatment period) and D+28 (late treatment period) and were subjected to RNA-Sequencing and subsequent bioinformatics analyses. Functional enrichment of lncRNA was performed via potential cis regulated target genes located within 50 Kb flanking regions of lncRNAs and having expression correlation of >0.7 with mRNAs. A total of 4955 lncRNAs (325 known and 4630 novel) were identified which potentially cis targeted 59 and 494 genes in LSO and SFO treatments, respectively. Enrichments of cis target genes of lncRNAs indicated potential roles of lncRNAs in immune function, nucleic acid metabolism and cell membrane organization processes as well as involvement in Notch, cAMP and TGF-β signaling pathways. Thirty-two and 21 lncRNAs were differentially expressed (DE) in LSO and SFO treatments, respectively. Six genes (KCNF1, STARD13, BCL6, NXPE2, HHIPL2 and MMD) were identified as potential cis target genes of six DE lncRNAs. In conclusion, this study indicated potential roles for lncRNAs in mammary gland immune functions and development and provided potential candidate genes and pathways via which lncRNAs can function in diet responses.

Multi-floor environments are usually ignored while designing an autonomous robot for indoor cleaning applications. However, for efficient operation in such environments, the ability of a robotic platform to traverse staircases is crucial. Staircase detection and localization is highly important for planning the traversal on staircases. This paper describes a deep learning approach using Convolutional Neural Networks (CNNs) based Robot Operation System (ROS) to staircase detection and localization. We use an object detection network to detect staircases in images. We also localize these staircases using a contour detection algorithm to detect the target point, a point close to the center of the first step, and the angle of approach to the target point. Experiments are performed with data obtained from images captured on different types of staircases at different view points/angles. Results show that the approach is very accurate in identifying the presence of the staircase in the working environment and is also able to locate the target point with good accuracy.

The proton exchange membrane fuel cell (PEMFC) is a critical and essential component of zero-emission electro-hydrogen generators. An accurate prediction of its performance is important for optimal operation management and preventive maintenance of these generators. However, the prediction is not simple because the PEMFCs have complex electrochemical reactions with multiple nonlinear relations between operating variables as inputs and voltage as output. In this paper, we propose an efficient prediction approach based on XGBRegressor and Tree-structured Parzen Estimator. In addition, to better select relevant features, Kernel Principal Component Analysis and Mutual Information are jointly used. The proposed approach allows consideration of the dynamic operating conditions of the PEMFC. To test and validate the robustness of the proposed approach, a real data-set of ten PEMFCs was considered. Furthermore, a comparison study with traditional machine learning models, such as artificial neural networks and support vector machine regression, was investigated. The obtained results confirm that our model outperforms the considered traditionel machine learning models.

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.

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 paper presents a new high-efficiency-high-step-up based converter integrating two stype DC-DC Boost and Flyback coupled magnetic converter with recovery stage dedicated to smart HVDC distributed architecture in renewable energy production systems. Appropriate duty cycle ratio assumes that the recovery stage work with parallel charge and discharge to achieve high step-up voltage gain. Besides, the voltage stress on the main switch is reduced with a passive clamp circuit and thus, low on-state resistance Rdson of the main switch can be adopted to reduce conduction losses. The circuit is simple to control. As a final point of this research, the simulation and the prototype investigational results are presented to demonstrate the effectiveness of this proposed converter.

This article aims to identify the current development of cross-border tourism between Vietnam and China. The paper analyzes the perception and strategy of cross-border tourism development in the two countries, especially in the context of China’s implementation of the “Belt and Road Initiative” (BRI). The article emphasizes that Vietnam and China have recently made efforts to promote cross-border tourism development. At the same time, Vietnam and China see cross-border tourism development as a significant part of comprehensive border cooperation between the two countries. However, the development plans for cross-border tourism between the two countries are still mainly on the desk, not yet implemented effectively. Thus, its achievements are relatively modest. Besides, the article emphasizes that the interests of the people living in the border area, especially the Vietnam side, are almost “forgotten” in the development of cross-border travel between the two countries. Besides, the article also analyzes the challenges that the two sides are facing, especially the Vietnam side, in promoting the development of cross-border tourism between the two countries.

The response of a single tin oxide nanowire was collected at different temperatures to create a virtual array of sensors working as a nano-electronic nose. The single nanowire, acting as a chemiresistor, was first tested with pure ammonia and then used to determine the freshness status of trout fish (Oncorhynchus mykiss) in a rapid and non-invasive way. The gas sensor reacts to total volatile basic nitrogen, detecting the freshness status of the fish samples in less than 30 seconds. The sensor response at different temperatures correlates well with the total viable count (TVC), demonstrating that it is a good (albeit indirect) way of measuring the bacterial population in the sample. The nano-electronic nose is able to classify the samples according to their degree of freshness, but also to quantitatively estimate the concentration of microorganisms present. The system was tested with samples stored at different temperatures, managing to classify them perfectly (100%) and estimating their log(TVC) with an error lower than 5%.

We report the effects of surface passivation by depositing a hydrogenated amorphous silicon (a-Si:H) layer on the electrical characteristics of low temperature polycrystalline silicon thin film transistors (LTPS TFTs). The a-Si:H layer was optimized by hydrogen dilution and its structural and electrical characteristics were investigated. The a-Si:H layer in the transition region between a-Si:H and µc-Si:H resulted in superior device characteristics. Using an a-Si:H passivation layer, the field-effect mobility of the LTPS TFT was increased by 78.4% compared with a conventional LTPS TFT. Moreover, the leakage current measured at a V_GS of 5 V was suppressed because the defect sites at the poly-Si grain boundaries were well passivated. Our passivation layer, which allows thorough control of the crystallinity and passivation-quality, should be considered a candidate for high performance LTPS TFTs.

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

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

The study aims to evaluate the impact of organizational culture on labor efficiency at foreign-invested logistics service enterprises that are on its ways towards business sustainability. The authors develop theoretical basis on organizational culture and explore factors that contribute to organizational culture and labor efficiency; from which 03 research hypotheses are proposed. Primary data are collected from logistics businesses through questionnaires; multiple linear regresion model is used to analyze the influence of organiational culture on labor effeciency at foreign-invested logistics enterprises. Research results indicate 05 factors of organizational culture contribute positive impact on employee productivity, including employees’ trust, company ideals, leadership styles and authority division, business philosophy and mission, people’s relationship with naturual environment. Based on the research results, proposed recommendations are suggested for improving labor efficiency at foreign-invested logistics service enterprises in a sustainable way.

Invasive fungal infections by Candida albicans frequently cause mortality in immunocompromised patients. Neutrophils are particularly important for fungal clearance at the early phase of infections, yet little has been known regarding which surface receptor controls neutrophil phagocytic activities during systemic C. albicans infection. CD137, which is encoded by Tnfrsf9, belongs to the tumor necrosis receptor superfamily and has been shown to regulate neutrophils in Gram-positive bacterial infection. Here, we used genetic and immunological tools to probe the involvement of CD137 signaling in innate defense mechanisms against systemic C. albicans infection. We first found that Tnfrsf9-/- mice were susceptible to C. albicans infection, whereas injection of anti-CD137 agonistic antibody protected the host from infection, suggesting that CD137 signaling is indispensable for innate immunity against C. albicans infection. Priming of isolated neutrophils with anti-CD137 antibody promoted their phagocytic and fungicidal activities through phospholipase C. In addition, injection of anti-CD137 antibody significantly augmented restriction of fungal growth in Tnfrsf9-/- mice that received WT neutrophils. In conclusion, our results demonstrate that CD137 signaling contributes to defense mechanisms against systemic C. albicans infection by promoting rapid fungal clearance whereby harmful immunopathology-induced tissue injuries are minimalized.

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.

Stroke constitutes a significant public health concern due to its impact on mortality and morbidity. This study investigates the utility of machine learning algorithms in predicting stroke and identifying key risk factors using data from the Suita study, comprising 7,389 participants and 53 variables. Initially, unsupervised K-prototype clustering categorized participants into risk clusters, while five supervised models including Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosted Machine (Light-GBM) were employed to predict stroke outcomes. Stroke incidence disparities among identified risk clusters using the unsupervised K-prototype clustering method are substantial, according to the findings. Supervised learning, particularly RF was a preferable option because of the higher levels of performance metrics. The Shapley Additive Explanations (SHAP) method identified age, systolic blood pressure, hypertension, estimated glomerular filtration rate, metabolic syndrome, and blood glucose level as key predictors of stroke, aligning with findings from the unsupervised clustering approach in high-risk groups. Additionally, previously unidentified risk factors such as elbow joint thickness, fructosamine, hemoglobin, and calcium level demonstrate potential for stroke prediction. In conclusion, machine learning facilitated accurate stroke risk predictions and highlighted potential biomarkers, offering a data-driven framework for risk assessment and biomarker discovery.

MicroRNAs (miRNAs) are small endogenous RNAs that regulate gene expression post-transcriptionally by targeting either the 3′ untranslated or coding regions of genes. They have been reported to play key roles in a wide range of biological processes. The recent remarkable developments of transcriptomics technologies, especially next-generation sequencing technologies and advanced bioinformatics tools, allow more in-depth exploration of messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) including miRNAs. These technologies have offered great opportunities for a deeper exploration of miRNA involvement in farm animal diseases, as well as livestock productivity and welfare. In this review, we provide an overview of the current knowledge of miRNA roles in farm animal diseases with a particular focus on diseases of economic importance. In addition, we discuss the steps and future perspectives of using miRNAs as biomarkers and molecular therapy for livestock disease management as well as the challenges and opportunities for understanding the regulatory mechanisms of miRNAs related to disease pathogenesis.

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.

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.

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.

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.

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.

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.

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.

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.

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

The 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.

Microstructured surfaces are renowned for their unique properties, such as waterproofing and low adhesion, making them highly applicable in the biomedical field. These surfaces play a crucial role in influencing cell response by mimicking the native microenvironment of biological tissues. In this study, we engineered a series of biomimetic micropatterned surfaces using polydimethylsiloxane (PDMS) to explore their effects on primary breast cancer cell lines, contrasting these effects with those observed on conventional flat surfaces. The surface topography was varied to direct cells’ attachment, growth, and morphology. Our findings elucidate that surface-free energy is not merely a background factor but plays a decisive role in cell dynamics, strongly correlating with the spreading behaviour of breast cancer cells. Notably, on micropillar surfaces with high surface-free energy, an increase in the population of cancer cells was observed. Conversely, surfaces characterised by lower surface-free energies noted a reduction in cell viability. Moreover, the structural parameters, such as the gaps and diameters of the pillars, were found to critically influence cellular dispersion and adherence, underscoring the importance of the microstructures’ topography in biomedical applications. These insights pave the way for designing advanced microstructured surfaces tailored to specific cellular responses, opening new avenues for targeted cancer therapies and tissue engineering.

Turbidity is an important water quality parameter, especially for drinking water. The ability to actively monitor the turbidity level in Drinking Water Distribution Systems is of critical importance to the safety and wellbeing of the public. Traditional turbidity monitoring methods involve manual collection of water samples at set locations and times followed by laboratory analysis, which are labor intensive and time consuming. Fiber-optic measurement permits real-time, in-situ turbidity monitoring. But the current technology is based on plastic fibers, which suffer from high optical attenuation and hence are unsuitable for large-scale remote monitoring. In this paper, we report the demonstration of a fiber-optic turbidity sensor based on multi-mode glass fibers. The system uses a single fiber to both deliver laser light into the water sample and collect the back-scattered light for detection. A balanced-detection scheme is utilized to remove the common-mode noise to enhance the turbidity sensitivity. Highly linear turbidity responses are obtained and a turbidity resolution as low as 0.1 NTU is achieved. The test unit is also shown to have excellent reproducibility against repeated measurements and good stability against temperature changes. Turbidity measurement in real environmental matrices such as tap water and pond water is also reported with an assessment of the impact of flow rate. This work demonstrates the feasibility of future large scale distributed fiber-optic turbidity monitoring networks.

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.

Protein import into the endoplasmic reticulum (ER) is the first step in the biogenesis of about 10,000 different soluble and membrane proteins in humans. It involves co- or post-translational targeting of precursor polypeptides to the ER and their subsequent membrane insertion or translocation. So far, three pathways for ER targeting of precursor polypeptides plus four pathways for ER targeting of mRNAs were described. Typically, these pathways deliver their substrates to the Sec61 polypeptide-conducting channel in the ER membrane. Next, the precursor polypeptides are inserted into the ER membrane or translocated into the ER lumen, which may involve auxiliary translocation components, such as the TRAP and Sec62/Sec63 complexes, or auxiliary membrane protein insertases, such as EMC and the TMCO1 complex. Recently, the PEX19/PEX3-dependent pathway, which has a well-known function in targeting and inserting various peroxisomal membrane proteins into pre-existent peroxisomal membranes, was also found to act in targeting and, putatively, inserting monotopic hairpin proteins into the ER. These either remain in the ER as resident ER membrane proteins or are pinched off from the ER as components of new lipid droplets. Therefore, the question arose if this pathway may play a more general role in ER protein targeting, i.e. represents a fourth pathway for ER targeting of precursor polypeptides. Thus, we addressed the client spectrum of the PEX19/PEX3-dependent pathway in both PEX3-depleted HeLa cells and PEX3-deficient Zellweger patient fibroblasts by an established approach, which involves label-free quantitative mass spectrometry of the total proteome of depleted or deficient cells and differential protein abundance analysis. The negatively affected proteins included twelve peroxisomal proteins and two hairpin proteins of the ER, thus confirming two previously identified classes of putative PEX19/PEX3-clients in human cells. Interestingly, fourteen collagen-related proteins with signal peptides or N-terminal transmembrane helices and belonging to the secretory pathway were also negatively affected by PEX3-deficiency, which may suggest compromised collagen biogenesis as a hitherto unknown contributor to organ failures in the respective Zellweger patients.

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.

Deep learning has been introduced to single-image super-resolution (SISR) in the last decade. These techniques have taken over the benchmarks of SISR tasks. Nevertheless, most architectural designs necessitate substantial computational resources, leading to a prolonged inference time on embedded systems or rendering them infeasible for deployment. This paper presents a comprehensive survey of plausible solutions and optimization methods to address this problem. Then, we propose a pipeline that aggregates the latter in order to enhance the inference time without significantly compromising the perceptual quality. We investigate the effectiveness of the proposed method on a lightweight GAN-based perceptual-oriented model as a case study. The experimental results show that our proposed method leads to significant improvement in the inference time on both Desktop and Jetson Xavier NX, especially for higher resolution input sizes on the latter, thereby making it deployable in practice.

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.

Logistics industry has been found to be among the key sources of carbon emission. In Vietnam logistics industry, there is a considerable difference between the number of foreign and Vietnamese firms as well as the proportion of markets that they are taking. This study is to research the low-carbon emission measures conducted by domestic and foreign invested logistics service providers (LSPs) and compare the results of the two groups. Both qualitative and quantitative approaches are applied. Literatures in relevant fields are reviewed and expert opinions are taken for structuring a questionnaire which was later distributed to 279 LSPs, with 166 returned and 159 being valid for data calculation. The results imply that there are differences in extension of applications of low-carbon practices between foreign and domestic firms. Except for transport mode switch and energy-saving lighting, the other practices witness that adoption levels of foreign LSPs are higher than their counterparts, which is possibly thanks to their global operation, more comfortable capital resources and awareness level of green initiative necessity. In conclusion, a comparison between the application conducted by foreign-invested firms and domestic ones, which has not been investigated before, was made.

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.

This study was conducted to investigate the status of regional linkage in tourism development in in the Midlands and Northern Mountains of Vietnam. The data was collected from a survey of 755 people, including officials from State management bodies in charge of tourism, officials and staffs at tourism resorts, tourism firms, tourism scientists and tourists. In addition, we conducted 10 group discussions, interviewed 30 State tourism agency officials and tourism firms in the Midland and Mountainous provinces of Vietnam. The results show that tourism development in Vietnam in general and the Northwest region in particular is extremely fragmented, not yet forming a regional linkage; Regional and national tourism development programs are just formalistic. The main cause of the situation is the limited regional integration policy in Vietnam, the lack of appropriate regional governance mechanisms and inactive participation of the private sector in regional integration. Based on the findings, we propose a tourism sector linkage model; besides, policy implications are given for fulfilling the linkage policy in the Midlands and Northern Mountains area.

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.

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

Verticillium wilt is a soil borne disease caused by distinct vegetative compatibility groups (VCG) of the fungus Verticillium dahliae. Two V. dahliae isolates were recovered from symptomatic cot-ton plants in Australian cotton fields and were assigned to two distinct vegetative compatibility groups (VCGs). One corresponding to the defoliating (VCG 1A) and the other non-defoliating (VCG 2A) pathotypes of Verticillium, have been transformed with Red and Green Fluorescent protein genes, respectively. The transformants maintained their ability to infect cotton and both strains were observed to colonise the xylem vessels of cotton plants. Moreover, we observed that the cotton V. dahliae strains could also infect some sampled non-Gossypium species found in the Australian landscape. The fluorescently labelled strains of V. dahliae will allow us to gain a thorough understanding of the infection processes of this important pathogen.

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

Damage in concrete structures initiates as the growth of diffuse microcracks that is followed by damage localisation and eventually leads to structural failure. Weak changes such as diffuse microcracking processes are failure precursors. Identification and characterisation of these failure precursors at an early stage of concrete degradation and application of suitable precautionary measures will considerably reduce the costs of repair and maintenance. To this end, a reduced order multiscale model for simulating microcracking-induced damage in concrete at the mesoscale levelis proposed. The model simulates the propagation of microcracks in concrete using a two-scale computational methodology. First, a realistic concrete specimen that explicitly resolves the coarse aggregates in a mortar matrix was generated at the mesoscale. Microcrack growth in the mortar matrix is modelled using a synthesis of continuum micromechanics and fracture mechanics. Model order reduction of the two-scale model is achieved using clustering technique. Model predictions are calibrated and validated using uniaxial compression tests performed in the laboratory.

Recent prolonged dry periods and lack of irrigation water have severely affected the productivity of coffee farms’ in the Central Highlands of Vietnam. This paper analyzes the efficiency of irrigation water use for Robusta coffee (Coffea canephora) in Lam Dong province, Highlands, Vietnam. A Cobb-Douglas production function was used to determine coffee productivity’s response to the application of irrigation water and other production factors using data collected from 194 farmers while the Technical Efficiency (TE) and Irrigation Water Use Efficiency (IWUE) were analyzed using a Data Envelopment Analysis (DEA) model. The correlation of different factors to IWUE was determined using the Tobit model. The production function analysis using Cobb-Douglas shows that the volume of irrigation water, amount of working capital, labor and farm size significantly influence coffee productivity. It also shows that indigenous farmers are more efficient in utilizing irrigation water than the (mostly Kinh) migrant farmers. The Tobit result, on the other hand. indicates that farmers’ experience, education level, distance of farm to water source, security of access to water source, extension contact and credit access significantly affect IWUE. The study findings further suggest that mitigating water shortages in coffee farms require sub-regional and national policy support such as better access to credit and extension services, training, land management and household-level effort to improve farming practices, through the application of appropriate technologies and traditional knowledge.

S-adenosylmethionine (SAM) is considered to be a useful therapeutic agent for degenerative cartilage diseases, although its mechanism is not clear. We previously found that polyamines stimulate expression of differentiated phenotype of chondrocytes. We also found that cellular communication network factor 2 (CCN2) played a huge role in the proliferation and differentiation of chondrocytes. Therefore, we hypothesized that polyamines and CCN2 could be involved in the chondroprotective action of SAM. In this study, we initially found that exogenous SAM enhanced proteoglycan production but not cell proliferation in human chondrocyte-like cell line-2/8 (HCS-2/8) cells. Moreover, SAM enhanced gene expression of cartilage-specific matrix (aggrecan and type II collagen), Sry-Box transcription factor 9 (SOX9), CCN2 and chondroitin sulfate biosynthetic enzymes. Blockade of the methionine adenosyltransferase 2A (MAT2A) enzyme catalyzing intracellular SAM biosynthesis restrained the effect of SAM on chondrocytes. The polyamine level in chondrocytes was higher in SAM-treated culture than control culture. Additionally, alcian blue staining and RT-qPCR indicated that the effects of SAM on the production and gene expression of aggrecan were reduced by the inhibition of polyamine synthesis. These results suggest that the stimulation of polyamine synthesis and gene expression of chondrogenic differentiation factors, such as CCN2, account for the mechanism underlying the action of SAM on chondrocytes.

Ho Chi Minh City (HCMC), the most crowded city and economic hub of Viet Nam, has been experiencing land subsidence over the past decades. This effort aims to contribute the spatial distribution of subsidence in HCMC in its horizontal and vertical components using synthetic aperture radar interferometry (InSAR) time series. To this purpose, an advanced Persistent Scatterers and Distributed Scatterers (PSDS) InSAR technique was applied to two European Space Agency (ESA) Sentinel-1 datasets consisting of 96 ascending and 202 descending images, acquired from 2014 to 2020 over the HCMC area. A time series of 33 COSMO-SkyMed ascending images was also used for comparison. The combination of ascending and descending satellite passes is used to decompose the light of sight velocities into horizontal east-west and vertical components. Taking into account the presence of east-west horizontal motion, our findings indicate that the accuracy of the decomposed vertical velocity can be improved by up to 3 mm/year for Sentinel-1 data. The obtained results revealed that subsidence is most pronounced in the areas along the Sai Gon River, in the northwest-southeast axis, and in the southwest of the city, with a maximum value of 80 mm/yr, which is in accordance with the findings of the literature. The amplitude of east-west horizontal velocities is relatively small and large-scale eastward movement can be observed in the west of the city at a rate of 3-5 mm/yr. This confirmed that the displacement in Ho Chi Minh City area is mainly vertical downward. Together, these results reinforced the remarkable suitability of ESA's SAR Sentinel-1 for subsidence applications, even for non-European countries such as Vietnam and Southeast Asia.

The coastline in the Ca Mau and the Kien Giang provinces of the Vietnamese Mekong Delta has been severely eroded in recent decades. Pile-Rock Breakwaters (PRBW) are one of the most widely adopted structures for controlling shoreline erosion in this region. These structures are effective for wave energy dissipation, stimulating sediment accumulation, and facilitating the restoration of mangrove forests. These breakwaters are generally considered to be best-engineering practice however there is currently insufficient scientific evidence with regard to specific structural design aspects. This can lead to PRBW structures being compromised when deployed in the field. This study uses a physical model of a PRBW in a laboratory to investigate several design parameters, including crest width and working states (i.e. submerged, transition, and emerged), and investigates their relationship with the wave transmission coefficient, wave reflection coefficient, and wave energy dissipation. To investigate these relationships further, empirical formulas were derived for PRBWs under different sea states and crest widths to aid the design process. The results showed that PRBW width had a significant influence on the wave energy coefficients. The findings revealed that the crest width of the breakwater is inversely proportional to the wave transmission coefficient (K_t) under the emerged state. The crest width is also proportional to the wave reduction efficiency and wave energy dissipation in both working states (i.e., submerged and emerged states). The front wave disturbance coefficient (K_f) was found to be proportional to the wave reflection coefficient, and the wave height in front of the structure was found to increase by up to 1.4 times in the emerged state. The wave reflection coefficient requires special consideration to reduce the toe erosion in the structure. Lastly, empirical equations including linear and non-linear formulas were compared with previous studies for different classes of breakwaters. These empirical equations will be useful for understanding the wave transmission efficiency of PRBWs. The findings of this study provide important guidance for PRBW design in the coastal area of the Mekong Delta.

Accurately predicting the distance an object will travel to its destination is very important in various sports. Acceleration sensors as a means of real-time monitoring are increasingly gaining increasing attention in sports. Due to the low energy output and power density of Triboelectric Nanogenerators (TENGs), recent efforts have focused on developing various acceleration sensors. However, these sensors suffer from significant drawbacks of large size, complexity, high power input requirements, and high cost. Here, we described a portable and cost-effective real-time refreshable strategy design comprising a series of individually addressable and controllable units based on TENGs embedded in a flexible substrate. This results in a highly sensitive, low-cost, and self-powered acceleration sensor. Putting, which accounts for nearly half of the strokes played, is obviously an important component of the golf game. The developed acceleration sensor has an accuracy controlled within 5 %. The initial velocity and acceleration of the forward movement of a rolling golf ball after it is hit by a putter can be displayed, and the stopping distance quickly calculated and predicted in about 7 seconds. This research demonstrates the application of the portable TENG-based acceleration sensor, while paving the way for designing portable, cost-effective, scalable, and harmless ubiquitous self-powered acceleration sensors.

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.)

Nervous necrosis virus (NNV) has spread throughout the world, affecting more than 120 freshwater and marine fish species. While vaccination effectively prevents disease outbreaks, the difficulty of producing sufficient viruses using cell lines continues to be a significant disadvantage for producing inactivated vaccines. This study, therefore, explored the application of synthetic peptides as potential vaccine candidates for the prevention of NNV in Asian seabass (Lates calcarifer). Using the epitope prediction tool and molecular docking, three predicted immunogenic B cell epitopes (30-32 aa) derived from NNV coat protein were selected and synthesised, corresponding to amino acid positions 5 to 34 (P1), 133 to 162 (P2) and 181 to 212 (P3). All the predicted peptides interact with Asian sea bass’s MHC class II by docking. The antigenicity of these peptides was determined through ELISA and all peptides were able to react with NNV-specific antibodies. Subsequently, the immunogenicity of these synthetic peptides was investigated by immunisation of Asian seabass with individual peptides (30 μg/fish) and a peptide cocktail (P1+P2+P3, 10 μg each/fish) by intraperitoneal injection, followed by a booster dose at day 28 post-primary immunisation. There was a subset of immunised fish that were able to induce upregulation of CD4 in the head kidney and spleen. Importantly, antibodies derived from fish immunised with synthetic peptides reacted with whole NNV virions. Taken together, these findings indicate that synthetic linear peptides based on predicted B cell epitopes exhibited both antigenic and immunogenic properties, suggesting that they could be potential vaccine candidates for the prevention of NNV in fish.

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

Concrete is a heterogeneous material with a disordered material morphology that strongly governs the behavior of the material. In this contribution, we present a computational tool called the Concrete Mesostructure Generator (CMG) for the generation of ultra-realistic virtual concrete morphologies for mesoscale and multiscale computational modeling and simulation of concrete. Given an aggregate size distribution, realistic generic concrete aggregates are generated by a sequential reduction of a cuboid to generate a polyhedron with multiple faces. Thereafter, concave depressions are introduced in the polyhedron using gaussian surfaces. The generated aggregates are assembled into the mesostructure using a hierarchic random sequential adsorption algorithm. The virtual mesostructures are first calibrated using laboratory measurements of aggregate distributions. The model is validated by comparing the elastic properties obtained from laboratory testing of concrete specimens with the elastic properties obtained using computational homogenisation of virtual concrete mesostructures. Finally, a 3D-convolutional neural network is trained to directly generate elastic properties from voxel data.

Knee osteoarthritis is the most popular type of osteoarthritis that causes extreme pain in elderly. Currently there is no cure for osteoarthritis. To lessen clinical symptoms, glucosamine was suggested. The primary goal of our study is to evaluate the efficacy and safety of glucosamine from recent studies. Electronic databases such as PubMed, Scopus, Cochrane were used to assess RCT. From the beginning through March 2023, the papers were checked, and if they fulfilled the inclusion criteria, they were then examined. WOMAC and VAS scales were considered as main outcome measure. A total of 15 studies were selected. Global pain was significantly decreased in comparison to placebo, as measured by the VAS index, with an overall effect size SMD of -7.41 ([95% CI] 14.31, 0.51). The WOMAC scale confirmed that pain, stiffness, and physical function had improved, however the effects were insufficient. A statistical update also revealed that there were no reports of serious medication interactions or significant adverse events. To summarize, glucosamine is more effective than a placebo at reducing pain in knee osteoarthritis patients. In long-term treatment, oral glucosamine sulfate 1500 mg/day is believed to be well tolerated.

Ultrasonic measurements are used in civil engineering for structural health monitoring of concrete infrastructures. The late portion of the ultrasonic wavefield, the coda, is sensitive to small changes in the elastic moduli of the material. Coda Wave Interferometry (CWI) correlates these small changes in the coda with the wavefield recorded in intact, or unperturbed, concrete specimen to reveal the amount of velocity change that occurred. CWI has the potential to detect localised damages and global velocity reductions alike. In this study, the sensitivity of CWI to different types of concrete mesostructures and their damage levels is investigated numerically. Realistic numerical concrete models of concrete specimen are generated and damage evolution is simulated using the discrete element method. In the virtual concrete lab, the simulated ultrasonic wavefield is propagated from one transducer using a realistic source signal and recorded at a second transducer. Different damage scenarios reveal a different slope in the decorrelation of waveforms with the observed reduction in velocities in the material. Finally, the impact and possible generalizations of the findings are discussed and recommendations are given for a potential application of CWI in concrete at structural scale.

High costs for the repair of concrete structures can be prevented if damage at an early stage of degradation is detected and precautionary maintenance measures are applied. To this end, we use numerical wave propagation simulations to identify simulated damage in concrete using convolutional neural networks (CNN). Damage in concrete subjected to compression is modeled at the mesoscale using the discrete element method. Ultrasonic wave propagation simulation on the damaged concrete specimens are performed using the rotated staggered finite-difference grid method. The simulated ultrasonic signals are used to train a CNN based classifier capable of classifying three different damage stages (microcrack initiation, microcrack growth and microcrack coalescence leading to macrocracks). The performance of the classifier is improved by refining the dataset via an analysis of the averaged envelope of the signal. The classifier using the refined dataset has an overall accuracy of 90%.

Agricultural land fires have been linked to various and adverse impacts on ecosystems, food security and the agriculture sector. Understanding the patterns and drivers of agricultural land fires is essential for effective agricultural land fire management. The key objectives of this study were to (1) analyze the temporal and spatial patterns of agricultural land fires using satellite remote sensed data, (2) assess a range of environmental conditions that could drive the occurrence of agricultural land fires, (3) determine the best model for predicting agricultural land fires and (4) determine the relative contribution of each environmental condition variable on the best predictive model. We used both univariate and multivariate regressions for the fire prediction capability of four independent environmental conditions (fuel, weather, topographic and anthropogenic). Analysis of historical satellite data revealed that agricultural land fires were more frequent than forested land fires. Our analyses also revealed that fuel condition was the most important variable for predicting agricultural land fires followed by weather, topographic and anthropogenic conditions. This study provides a novel multivariate model for predicting agricultural land fires that harbors the potential to improve agricultural land fire management and reduce fire risk within the agricultural sector.

Australian bat lyssavirus (ABLV) is a rhabdovirus that circulates in four species of pteropid bats (ABLVp) and the yellow-bellied sheath-tailed bat (ABLVs) in mainland Australia. In the three confirmed human cases of ABLV, rabies illness preceded fatality. As with rabies virus (RABV), post-exposure prophylaxis (PEP) for potential ABLV infections consists of wound cleansing, ad-ministration of the rabies vaccine and injection of rabies immunoglobulin (RIG) proximal to the wound. Despite the efficacy of PEP, the inaccessibility of human RIG (HRIG) in the developing world and the high immunogenicity of equine RIG (ERIG) has led to consideration of human monoclonal antibodies (hmAbs) as a passive immunization option that offers enhanced safety and specificity. Using a recombinant vesicular stomatitis virus (rVSV) expressing the glycoprotein (G) protein of ABLVs and phage display, we identified two hmAbs, A6 and F11, which completely neutralize ABLVs/ABLVp, and RABV at concentrations ranging from 0.19-3.12 µg/mL and 0.39-6.25 µg/mL respectively. A6 and F11 recognize overlapping epitopes in the lyssavirus G protein, ef-fectively neutralizing phylogroup 1 lyssaviruses, while having little effect on phylogroup 2 and non-grouped diverse lyssaviruses. These results suggest A6 and F11 could be effective therapeutic and diagnostic tools for phylogroup 1 lyssavirus infections.