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Limaçon rotary machines are the heart of power generation systems, especially small- and micro-scale ones. These machines are the prime movers that play the main role in converting the potential energy to other useful forms of work, such as mechanical and/or electrical; the generated energy can also be stored in batteries or in the form of hydrogen. The focus of this paper is on the working of this limaçon technology, and the embodiments and mechanical drives to produce the unique motion of these machines. This paper will also discuss the related power-generating cycles and control schemes.

In Vietnam, diarrhea, especially persistent diarrhea, is one of the most common diseases in children, while a significant proportion of cases are negative with pathogens; thus, there is an urgent need to understand gut bacterial dysbiosis. In this study, bacteria in the fecal samples of five healthy and ten diarrheal children were separated from other residues, then adopted to extract their metagenomic DNA for evaluating their diversity based on V3 and V6–V8 regions and the 16S rRNA gene by PCR-RFLP and PCR-DGGE. As a result, bacterial metagenomic DNAs with high quality, quantity and diversity were successfully extracted using a GeneJET kit and a chemical protocol. A sequence analysis of 73 representative DNA fragments from gels indicated a remarkable bacterial dysbiosis in all groups of diarrhea. Viral diarrhea was characterized by extremely reduced bacterial diversity with the blossom of Bifidobacterium and Streptococcus. Streptococcus was also the most abundant in persistent diarrhea. Beneficial bacteria that may play a role in the self- rebalance in intestinal bacterial communities, such as Bifidobacterium, Lactobacillus, and Enterococcus, were seen in all diarrheal groups, while Bacteroides and Akkermansia muciniphila were seen in the healthy group but absent in the diarrheal groups. This study provides additional evidence for a relationship between intestinal bacterial dysbiosis and diarrhea in children, emphasizing an increase in Streptococcus.

Organic Rankine Cycle (ORC)–based small-scale power plants are becoming a promising instrument in the recent drive to utilize renewable sources and reduce carbon emissions. But the effectiveness of such systems is limited by the low efficiency of gas expanders, which are the main part of an ORC system. Limaçon-based expansion machines with a fast inlet control valve have great prospects as they could potentially offer efficiencies over 50%. However, the lack of a highly reliable and significantly fast control valve is hindering its possible application. In this paper, a push–pull solenoid valve is optimized using a stochastic optimization technique to provide a fast response. The optimization yields about 56–58% improvement in overall valve response. A performance comparison of the initial and optimized valves applied to a limaçon expander thermodynamic model is also presented. Additionally, the sensitivity of the valve towards a changing inlet pressure and expander rotor velocity is analyzed to better understand the effectiveness of the valve and provide clues to overall performance improvement.

In this work, an artificial neural network (ANN)-based model is proposed to describe the input–output relationships in a Limaçon-To-Circular (L2C) gas expander with an inlet valve. The L2C gas expander is a type of energy converter that has great potential to be used in organic Rankine cycle (ORC)-based small-scale power plants. The proposed model predicts the different performance indices of a limaçon gas expander for different input pressures, rotor velocities, and valve cutoff angles. A network model is constructed and optimized for different model parameters to achieve the best prediction performance compared to the classic mathematical model of the system. An overall normalized mean square error of 0.0014, coefficient of determination (R2) of 0.98, and mean average error of 0.0114 are reported. This implies that the surrogate model can effectively mimic the actual model with high precision. The model performance is also compared to a linear interpolation (LI) method. It is found that the proposed ANN model predictions are about 96.53% accurate for a given error threshold, compared to about 91.46% accuracy of the LI method. Thus the proposed model can effectively predict different output parameters of a limaçon gas expander such as energy, filling factor, isentropic efficiency, and mass flow for different operating conditions. Of note, the model is only trained by a set of input and target values; thus, the performance of the model is not affected by the internal complex mathematical models of the overall valved-expander system. This neural network-based approach is highly suitable for optimization, as the alternative iterative analysis of the complex analytical model is time-consuming and requires higher computational resources. A similar modeling approach with some modifications could also be utilized to design controllers for these types of systems that are difficult to model mathematically.

The aim of this paper is to compare the power measurement capabilities in millimetre- and sub-millimetre-wave frequency bands of several national metrology institutes and one research institute. The first comparison, in WR-6.5 waveguide (110 GHz to 170 GHz), involved NPL, TUBITAK UME and PTB. The second comparison, in WR-1.5 waveguide (500 GHz to 750 GHz), involved NPL, METAS, TUBITAK UME, LNE, WAT, GUM and VDI. Two types of travelling standards were used for these comparisons: a thermoelectric power sensor in the WR-6.5 band and a calorimetric power sensor in the WR-6.5 and WR-1.5 bands. The thermoelectric power sensor was characterised by the participants against their own standards and a generalised effective efficiency was calculated. The calorimetric power sensor operating in the WR-6.5 band was measured to observe its behaviour during the comparison and was also measured in the WR-1.5 band after being fitted with a suitable waveguide taper and used in conjunction with a frequency multiplier. The participants measured the output of the calorimetric power sensor and their own power sensor standard. A normalised power ratio method was used as a comparison parameter for the WR-1.5 band measurements. In addition, a pyroelectric power standard was used by METAS to measure absolute power, and a frequency of 650 GHz was used as a link between the absolute power and the power ratios. Finally, all but two of the measurement points compared between the participants achieved agreement in terms of En scores less than 1. For the first time, an interlaboratory comparison of power measurements at sub-millimetre frequencies has been performed and, overall, good agreement was achieved between the different laboratories.

Background: Primary amebic meningoencephalitis (PAM) caused by Naegleria fowleri is a rare and devastating infection of the central nervous system, often diagnosed late, due to its rapid progression and nonspecific symptoms. Case Presentation: We report one of the youngest documented pediatric Vietnamese cases of PAM in a 10-month-old girl from the Mekong Delta, Vietnam. The diagnosis was confirmed through multiplex real-time PCR (MPL-rPCR), microscopy, and sequencing. Clinical data were gathered retrospectively from medical records, and additional details were provided by the patient’s family. Treatment regimens, disease progression, and diagnostic challenges were reviewed and compared to existing literature. With intensive treatment, the child survived for 14 days, representing one of the longest reported pediatric PAM survival durations. No direct exposure to untreated freshwater or other typical risk factors for Naegleria fowleri infection was identified, underscoring the unique epidemiological nature of this case. MPL-rPCR enabled timely detection of the pathogen and demonstrated its utility in resource-limited settings. Conclusions: This case highlights the critical need for rapid, accessible diagnostic tools such as MPL-rPCR, particularly in resource-constrained environments where traditional diagnostics may not be feasible. It also emphasizes the importance of international collaboration and investment in cost-effective diagnostics and novel therapeutic strategies. The geographical expansion of PAM due to climate change further underscores the urgency of these measures to improve health outcomes in vulnerable populations.

The hemoflagellate parasite Trypanosoma rangeli is transmitted by triatomine kissing bugs and may co-infect humans together with its Chagas disease-causing congener T. cruzi. Using real-time quantitative polymerase chain reaction (RT-qPCR) and antimicrobial assays, we studied (i) the temporal and spatial distribution of T. rangeli in common bed bugs, Cimex lectularius, following oral ingestion and hemocoelic injection of T. rangeli, and (ii) the immune responses of bed bugs induced by T. rangeli infections. Irrespective of infection mode, no live T. rangeli were present in the bed bugs’ hemolymph, salivary glands, or feces. On day 1 following infection, the bed bugs strongly upregulated the antimicrobial peptide CL-defensin. Following hemocoelic injection of T. rangeli, live parasites were absent in any bed bug tissues examined throughout the 10-day study period. The ingestion of T. rangeli-infected blood had no significant effect on bed bug survival. Our findings indicate that bed bugs disable the development of T. rangeli within their body, in stark contrast to triatomine kissing bugs, which allow the development and transmission of T. rangeli. Our findings help unravel the intricate relationships between bed bugs and trypanosomes, and they contribute to our understanding of vector biology.

The problem of calibrating phased array antennas in a noisy environment using an autocorrelation algorithm is investigated and a mathematical model of the autocorrelation calibration method is presented. The proposed calibration system is based on far-field scanning of the phased array antenna in an environment with internal noise and external interference. The proposed method is applied to a phased array antenna and compared with traditional rotating-element electric-field vector methods, which involve identifying the maximum and minimum vector–sum points (REVmax and REVmin, respectively). The proposed calibration system is verified for a phased array antenna at 3 GHz. Experimental verification of the mathematical model of the proposed method demonstrates that the autocorrelation method is more accurate than the rotating-element electric-field vector methods in determining the amplitude and phase shifts. The measured peak gain of the combined beam in the E-plane increased from 7.83 to 8.37 dB and 3.57 to 4.36 dB compared to the REVmax and REVmin methods, respectively, and the phase error improved from 47° to 55.48° and 19.43° to 29.16°, respectively. The proposed method can be considered an effective solution for large-scale phase calibration at both in-field and in-factory levels, even in the presence of external interference.

Overhead transmission line insulators are non-conductive materials that separate conductors from grounded transmission towers. Once in operation, they frequently experience environmental pollution and electrical or mechanical stress. Since adverse operational conditions can lead to insulation failure, regular inspections are essential to prevent power outages. To this end, this paper proposes a novel technique based on deep convolutional neural networks (CNNs) to classify high-voltage insulator surface conditions based on their image. Successful applications of CNNs in computer vision have led to several pretrained architectures for image classification. To use these pretrained models, a practitioner typically fine-tunes and selects one final model via a model selection stage and discards all other models. In contrast with many existing studies that use such a “winner-takes-all” approach, here, we identify the best subset of seven popular pretrained CNN architectures that are combined by soft voting to form an ensemble classifier. From a machine learning (ML) perspective, this focus is warranted because the convolutional base of each pretrained architecture operates as a feature extractor and an ensemble of them works as a combination of various feature extraction rules. Our numerical experiments demonstrate the advantage of the identified ensemble model to individual pretrained architectures.

A new autonomous underwater vehicle (AUV) has high maneuverability near the bottom and a direction turnaround ability, called the autonomous underwater helicopter (AUH). This paper numerically investigates the hydrodynamic performance of the AUH. A Reynolds-Averaged Navier–Stokes (RANS) equation, a computational fluid dynamics (CFD) technique, is applied to analyze the AUH’s behavior. Investigations of the AUH’s hydrodynamic characteristics become more obvious with a service speed in the range of 0.4–1.2 m/s. For the same velocity condition, the resistance of the AUH increases, and the irregular eddy at the rear of the AUH expands with changes in the angles of attack and the length/height ratio. Essential design characteristics including pressure, velocity distribution, and velocity streamlines are shown and analyzed. These insights can be used as a guideline to reduce drag force and optimize the AUH profile for future designs. It has great potential for improving the AUH’s control algorithms.

The ever-growing concerns about global warming and the rapid depletion of fossil fuels have triggered a rising interest in the research for cleaner, more efficient, and cost-effective energy generation. Organic Rankine cycle systems have immense potential to become a strong alternative to conventional methods of energy generation. However, such systems’ efficiency is limited by the performance of the incorporated gas expanders or prime movers. Conventional gas expanders often utilize ports or cam-operated valves. Ported expanders offer limited efficiency and controllability and produce high emissions, causing a large amount of heated and compressed gas to be wasted. Cam-operated valves, in contrast, increase expansion performance compared to ported expanders; however, they have no variability and adaptability to changes in system parameters such as gas pressure, temperature, dryness fraction, and load variation, to name a few. On a positive note, this issue can be addressed by adopting a variable timing and fast-operating, control valve with an accurate and adaptive control mechanism at the expander inlet. A properly designed and controlled valve can greatly improve the system performance of gas expanders and pave the way for an efficient low-cost alternative energy generation. This manuscript provides a comparative review of recent progress on the design, modeling, optimization, and control aspects of valves for gas expanders. A clear pathway on the scope of further development is also drawn based on the present state of the art.

There are various types of sharing economy services, such as ride-sharing and shared-taxi rides. Motivated by these services, we consider a single-server queue in which customers probabilistically select the type of service, that is, the single service or batch service, or other services (e.g., train). In the proposed model, which is denoted by the M+M(K)/M/1 queue, we assume that the arrival process of all the customers follows a Poisson distribution, the batch size is constant, and the common service time (for the single- and batch-service customers) follows an exponential distribution. In this model, the derivation of the sojourn time distribution is challenging because the sojourn time of a batch-service customer is not determined upon arrival but depends on single customers who arrive later. This results in a two-dimensional recursion, which is not generally solvable, but we made it possible by utilizing a special structure of our model. We present an analysis using a quasi-birth-and-death process, deriving the exact and approximated sojourn time distributions (for the single-service customers, batch-service customers, and all the customers). Through numerical experiments, we demonstrate that the approximated sojourn time distribution is sufficiently accurate compared to the exact sojourn time distributions. We also present a reasonable approximation for the distribution of the total number of customers in the system, which would be challenging with a direct-conventional method. Furthermore, we presented an accurate approximation method for a more general model where the service time of single-service customers and that of batch-service customers follow two distinct distributions, based on our original model.

This paper introduces a novel technology for the monolithic integration of GaN-based vertical and lateral devices. This approach is groundbreaking as it facilitates the drive of high-power GaN vertical switching devices through lateral GaN HEMTs with minimal losses and enhanced stability. A significant challenge in this technology is ensuring electrical isolation between the two types of devices. We propose a new isolation method designed to prevent any degradation of the lateral transistor’s performance. Specifically, high voltage applied to the drain of the vertical GaN power FinFET can adversely affect the lateral GaN HEMT’s performance, leading to a shift in the threshold voltage and potentially compromising device stability and driver performance. To address this issue, we introduce a highly doped n+ GaN layer positioned between the epitaxial layers of the two devices. This approach is validated using the TCAD-Sentaurus simulator, demonstrating that the n+ GaN layer effectively blocks the vertical electric field and prevents any depletion or enhancement of the 2D electron gas (2DEG) in the lateral GaN HEMT. To our knowledge, this represents the first publication of such an innovative isolation strategy between vertical and lateral GaN devices.

Vibration-assisted machining, known as hybrid processing technology, offers several benefits over conventional machining methods. However, developing mechanical structure designs to generate a non-resonant frequency source remains challenging. The objective of this study is to propose a novel design for an XY flexure positioner by combining the pseudo-rigid-body model with the Lagrange technique, finite element analysis and Crayfish optimization algorithm. Firstly, the mechanism was designed by combining a hybrid amplifier and parallel driving mechanism integrated with right circular hinges to increase the natural frequency and precision for potential application to VAM CNC milling. Then, the analytical model was established by the pseudo-rigid-body and Lagrange method. Next, the theoretical result was verified by finite element analysis. The first natural frequency results of theory and FEM methods were found at 990.74 Hz and 1058.5 Hz, respectively. The error between the two methods was 6.4%, demonstrating a reliable modeling approach. Based on the analytical equations, the Crayfish optimization algorithm was utilized for optimizing the main design variables of the mechanism. Next, the prototype was fabricated. The results showed that the experimental and simulated frequencies were 1127.62 Hz and 1216.6 Hz, with an error between the two methods of 7.31%. Finally, the workpiece was installed on the prototype and a real vibration-assisted CNC milling process was carried out in the frequency range [700 Hz, 1000 Hz]. The best surface roughness of the specimen was achieved at a frequency of 900 Hz with a Ra of 0.287 µm. This demonstrates that the proposed XY mechanism is an effective structure for generating a non-resonant frequency source for vibration-assisted machining.

Density functional theory and a semi-empirical quantum chemical approach were used to evaluate the photocatalytic efficiency of ceria (CeO2) combined with reduced graphene oxide (rGO) and graphene (GP) for degrading methylene blue (MB). Two main aspects were examined: the adsorption ability of rGO and GP for MB, and the separation of photogenerated electrons and holes in CeO2/rGO and CeO2/GP. Our results, based on calculations of the adsorption energy, population analysis, bond strength index, and reduced density gradient, show favorable energetics for MB adsorption on both rGO and GP surfaces. The process is driven by weak, non-covalent interactions, with rGO showing better MB adsorption. A detailed analysis involving parameters like fractional occupation density, the centroid distance between molecular orbitals, and the Lewis acid index of the catalysts highlights the effective charge separation in CeO2/rGO compared to CeO2/GP. These findings are crucial for understanding photocatalytic degradation mechanisms of organic dyes and developing efficient photocatalysts.

Despite recent advancements in cancer immunotherapy, many patients with gliomas and glioblastomas have yet to experience substantial therapeutic benefits. Modulating the tumor microenvironment (TME) of gliomas, which is typically “cold”, is crucial for improving treatment outcomes. Clinical tumor specimens obtained post-immunotherapy provide invaluable insights. However, access to such post-immunotherapy samples remains limited, even in clinical trials, as tumor tissues are often collected only at tumor relapse. Recent studies of neoadjuvant immunotherapy provided important insights by incorporating surgical resections of post-treatment tumors. Moreover, pre-surgical immunotherapies are increasingly integrated into clinical trial designs to evaluate treatment efficacy. These investigations reveal critical information, particularly regarding the delivery success of therapeutic agents, the expansion and persistence of immune products, and the cellular and molecular changes induced in the TME. In this review, we assess the findings on post-treatment tumor specimens obtained from recent immunotherapy clinical trials on gliomas, highlight the importance of these samples for understanding therapeutic impacts, and discuss proactive investigation approaches for future clinical trials.

This study examines the effects of urbanization on household health expenditure. Using a unique bi-annually household-level dataset from 2012–2016 from Vietnam, we obtain key findings as follows. To mitigate possible endogeneity concerns, we utilize a two-stage least squares regression (2SLS) approach, employing the development of information and communication (ICT) infrastructure at the province level as an instrumental variable (IV). The key findings can be summarized as follows. First, urbanization significantly reduces Vietnamese households’ inpatient and outpatient health expenses. Second, the self-treatment expenses of households increase as the process of urbanization advances. In addition, we perform various robustness checks, encompassing different measures of urbanization, the use of lag of urbanization as an additional IV, and the plausible exogenous IV. The outcomes derived from these rigorous sensitivity analyses substantiate the reliability and consistency of our key results. Finally, we propose different ways to explain these results, including health insurance expenses and household income.

A novel compact 2-DOF compliant positioner is developed for the purpose of achieving good characteristics such as high natural frequency, high displacement amplification ratio, good linear motion, and compact structure based on its symmetrical structure. To be specific, the developed stage is proposed according to an advanced six-lever displacement amplifier arranged at an inclination angle of the rigid bar utilizing right circular hinges and a parallel guiding mechanism with integrated flexure leaf hinges to attain the above-mentioned characteristics and reduce the decoupling mobility error. First, to quickly assess the initial quality response, an integration method of kinetostatic analysis, the Lagrange method, and finite element analysis was applied to evaluate and verify the quality characteristic of the stage. The experimental result showed that the error between the analytical method and the FEA method was 1.3%, which was relatively small and reliable for quickly assessing the primary quality response of the proposed positioner. Next, to boost the important output characteristics of the developed positioner, the integration approach of the response surface method and NSGA-II algorithm was utilized to find the optimal design variables. Finally, a prototype was manufactured based on the CNC milling method to validate the experimental and FEA analysis results. The attained results show that the optimal results of safety factor and output displacement were 2.4025 and 248.9 µm. Moreover, the FEA verification results were 2.4989 and 242.16 µm, with errors for safety factor and output displacement between the optimal result and the FEA result of 3.86% and 2.78%, respectively. In addition, the simulation and experimental results of the first natural frequency were 371.83 Hz and 329.59 Hz, respectively, and the error between the FEA result and experimental result for the first natural frequency was 11.36%. Furthermore, the achieved results show that the relationship between input displacement and output displacement of the experimental result and the FEA result of the developed structure achieved a good linear connection. These results suggest that the proposed positioner will be a potential structure employed in precise positioning systems and nanoindentation testing positioning systems for checking bio-specimens’ behaviors.

As the utilization of wind power systems continues to increase, reducing overall system inertia, there is a consequential negative impact on the power system’s ability to regulate frequency. Consequently, this study focuses on examining the fast-frequency regulation in high penetration of wind power, especially doubly fed induction generators—the most commonly installed wind turbine type, and an energy storage system installed in the wind farm. This study proposes a coordinated control of wind turbine generators and battery energy storage systems that provides fast-frequency regulation to the system while simultaneously ensuring the safety of the battery. Firstly, the fast-frequency regulation capability of the wind turbine will be studied. Secondly, primary frequency control of the battery energy storage system considering adaptive droop control based on state of charge is proposed to prevent both over-charging and over-discharging of the battery. Finally, this study proposed a coordinated fast-frequency regulation approach for the hybrid wind-storage system, which is evaluated under various wind speed scenarios. This approach involves a detailed analysis of the operational characteristics of the wind turbine generators to ensure optimal performance. The proposed method is validated through simulation using a MATLAB model of the wind-storage system, and comparative results with alternative control methods confirm the effectiveness of the proposed approach in raising the frequency nadir and avoiding the secondary frequency dip.

Introduction: Autoimmune bullous dermatoses (ABD) represent a heterogeneous group of blistering disorders that may be debilitating with high morbidity. Clinical, histological, and direct immunofluorescence (DIF) studies are essential in establishing an accurate diagnosis of ABD, which is essential for its clinical management. Our study objective was to perform a systematic evaluation of ABD cases in a patient population at an academic medical center in Ho Chi Minh City, Vietnam, and determine the degree of concordance of clinical, histological, and DIF findings in ABD. Methodology: A systematic retrospective cross-sectional study was performed on 92 patients diagnosed with ABD by clinical, histological, and DIF studies at the University of Medicine and Pharmacy in Ho Chi Minh City, Vietnam, between September 2019 and September 2021. The clinical histories, H and E stained tissue sections, and DIF stains were evaluated by pathologists at the University of Medicine and Pharmacy. Results: ABD was evaluated as a whole and subdivided into an intraepidermal blister subgroup and a subepidermal blister subgroup. The analysis of paired diagnostic methods (clinical, histological, and DIF) for concordance with the final diagnosis was performed and showed that there were no statistically significant differences between the paired methods (McNemar’s test, p > 0.05). There was moderate concordance between the clinical, histological, and DIF diagnoses among all ABD cases (Brennan-Prediger coefficient Kappa test, κBP = 0.522, CI = 0.95). In the intraepidermal blister subgroup, the diagnostic accuracies of the histology and DIF stains were comparable to each other, and both were more accurate than a clinical diagnosis alone. In the subepidermal blister subgroup, there was no statistically significant difference in each pair of the three diagnostic methods (clinical, histological, and DIF) (McNemar’s test, p > 0.05). The concordance between the clinical, histological, and DIF diagnoses was high for the intraepidermal blister subgroup (Kappa test, κBP = 0.758, CI = 0.95). However, the concordance between the clinical, histological, and DIF diagnoses was slight for the subepidermal blister subgroup (Kappa test, κBP = 0.171, CI = 0.95). Conclusion: Histological evaluation is highly accurate in the diagnosis of the intraepidermal blister subgroup, but it is not as accurate in the diagnosis of the subepidermal blister subgroup in the Vietnamese patient cohort in which clinical, histological, and DIF studies were performed. DIF stains are a crucial diagnostic tool for ABD in this patient population.

Renewable energy-based compact energy-generation systems based on the organic Rankine cycle (ORC) can be employed to meet the ever-growing thirst for affordable and clean energy. The overall performance and effectiveness of ORC systems are constrained by the low efficiency of the gas expander, specifically the positive displacement expander, which is responsible for energy conversion from the working fluid. This low-efficiency scenario can be significantly improved by employing a control valve to regulate and restrict the flow of the working fluid into the expander. A control valve can effectively curve the loss of costly compressed and energized working fluids by allowing them to expand in the expander chamber before discharging through the outlet port. They can thus be used to regulate the amount of energy yield and output power. In this work, two direct drive rotary valves (DDRVs) operated by a stepper motor (SM-DDRV) and rotary solenoid (RS-DDRV) are suggested, and the behavior of the valves is examined. The effect of friction and temperature on the valve response is also studied. Additionally, the effect of inlet control valves on the overall system performance of the limaçon expander is assessed. Thermodynamic properties such as the isentropic efficiency and filling factor are also computed. The effect of leakage due to valve response delay is analyzed at different inlet pressures. The performance indices are compared to the expander performance without any inlet valve. The SM-DDRV setup results in a 14.86% increase in isentropic efficiency and a 220% increase in the filling factor, whereas the RS-DDRV performs moderately with a 2.58% increase in isentropic efficiency and an 80% increase in the filling factor compared to a ported expander. The SM-DDRV provides better performance indices compared to the RS-DDRV and without valve setups. However, the performance of the limaçon expander with the SM-DDRV is sensitive to the inlet pressure and degrades at higher pressure. Overall, the valves proposed in this work present key insights into improving the performance characteristics of gas expanders of ORC systems.

Utilizing data from the 2016 Vietnam Household Living Standard Survey, we undertake an empirical investigation into the influence of energy poverty on the health expenditure of Vietnamese households. Employing a double-hurdle model, our empirical findings reveal a negative relationship between energy poverty and health expenditure. Specifically, our results indicate that for each incremental unit increase in energy poverty, there is a substantial reduction of 42.5 percentage points in the overall health expenditure of the households. Furthermore, as energy poverty deepens, we observe declines of 24.6 percentage points and 45.5 percentage points in the expenses incurred for inpatient/outpatient care and self-treatment, respectively. To validate the robustness of our results, we conduct several sensitivity analyses, including propensity score matching, double/debiased machine learning. Across all these methods, our findings consistently underscore the significant and persistent adverse impact of energy poverty on the examined outcome variables. Additionally, to examine the underlying pathways, we conduct a structural equation modeling analysis and find that the relationship between energy poverty and health expenses is mediated by household hospitalization and expenditures on essential items, such as food and daily necessities.

This study introduced a novel control approach based on fuzzy logic control (FLC) to enhance the frequency regulation capacity of variable-speed wind turbines (VSWTs). The proposed method integrates FLC within droop and inertia control loops. Real-time measurements of the system frequency and the rate of change of frequency (ROCOF) serve as inputs to the FLC, enabling the method to improve the frequency response by VSWTs. In addition, the method employs FLC for pitch angle frequency control, optimizing reserve power for frequency regulation under varying wind speed levels. The innovative aspect of this study lies in the simultaneous application of FLC to pitch angle frequency control and droop/inertia control, leading to the enhanced frequency regulation capability of VSWTs and smoother operation across a range of wind speeds. Compared with traditional methods, the proposed approach provides a comprehensive and effective solution to the challenges associated with frequency regulation in VSWTs. Through simulations across different wind speed scenarios, the proposed control method demonstrated the best performance among various mature methods, highlighting the efficacy of the proposed method on the frequency regulation of VSWTs under different wind speeds. This study’s findings highlight the potential of the proposed FLC-based method to optimize frequency regulation and contribute to more reliable and efficient wind energy systems.

Objective: This study aims to evaluate the safety and immunogenicity of the SKYVaricella vaccine in healthy Vietnamese children aged 12 months to 12 years. Methods: This open-label, single-arm study involved 201 children divided into two groups: 60 children aged 12 months to 5 years and 141 children aged 6 to 12 years. Safety was assessed through immediate reactions, solicited adverse events within 7 days, and unsolicited events up to Day 42. Immunogenicity was evaluated by seroconversion rates (SCR) and geometric mean titer (GMT) increments using fluorescent antibody-to-membrane antigen (FAMA) on the day of vaccination (D0) and 42 days after vaccination (D42). Results: All participants completed the follow-up. Immediate adverse events included pain (8.0%), redness (8.0%), and swelling (20.9%) at the injection site. Within 7 days, pain (17.9%) and swelling (12.4%) were mild and self-resolving. Unsolicited adverse events were infrequent and mild. Both age groups achieved 100% SCR. GMT of varicella-zoster virus antibodies increased from 1.37 (SD 1.97) at D0 to 18.02 (SD 2.22) at D42, a 13.12-fold rise. No Grade 3 adverse events were observed. Conclusion: The SKYVaricella vaccine shows a robust immunogenic response and favorable safety profile in Vietnamese children aged 12 months to 12 years. These findings endorse its potential inclusion in pediatric vaccination programs as a reliable preventive option against varicella.

We have designed an excellent visible-light-driven and high-performance photocatalyst with a Ag-Cu2O-ZnO nanowire heterostructure in our work by combining the hydrothermal approach with plasma–liquid technology. The structural and morphological characteristics and optical properties of the samples were evaluated using X-ray diffraction, field-emission scanning electron microscopy, and spectrophotometry, respectively. The results show that the Ag nanoparticles are mainly positioned on the Cu2O nanoclusters compared with the ZnO nanowire surface, forming broccoli-like Ag-Cu2O nanoclusters during the Ar gas plasma treatment process in an aqueous solution. The diameter of the Ag/Cu2O nanoclusters ranges from 150 to 180 nm. The Ag-Cu2O-ZnO nanowires exhibited improved photocatalytic performance, decomposing approximately 98% methyl orange dye in 30 min. This is a consequence of the synergistic interactions between the p-n heterojunction formed at the Cu2O-ZnO interfaces and the localized surface plasmon resonance (LSPR) effect of the Ag nanoparticles, which broaden the visible light absorption range and effectively separate the photogenerated charge carriers.

The postharvest preservation of Ngoc Linh ginseng (NL ginseng) is essential to retain its quality and sensory values for prolonged storage. In this study, the efficacy of NL ginseng preservation by coating chitosan derivatives in combination with polyvinyl alcohol (PVA) solutions was investigated under refrigeration conditions (~3 °C; ~40% RH) for 56 days. The effect of the chitosan–based solutions, including N,O–carboxymethyl chitosan (NOCC), chitosan oligomer saccharide (COS), or chitosan (CS), and the blend solutions (NOCC–PVA or COS–PVA) on the coated NL ginsengs was observed during storage. The pH values, viscosity, and film-forming capability of the coating solutions were determined, while the visual appearance, morphology, and mechanical properties of the films formed on glass substrates as a ginseng model for coating were also observed. The appearance, skin lightness, weight loss, sensory evaluation, total saponin content (TSC), total polyphenol content (TPC), and total antioxidant capacity (TAC) of the coated NL ginsengs were evaluated. The findings showed that the observed values of the coated NL ginsengs were better than those of the non-coated samples, with the exception of the COS–coated samples, which had completely negative results. Furthermore, the NOCC–PVA solution exhibited a better preservation effect compared with the COS–PVA one based on the observed indices, except for TPC and TAC, which were not impacted by the coating. Notably, the optimal preservation time was determined to be 35 days. This study presents promising preservation technology using the coating solution of NOCC–PVA, harnessing the synergistic effect of pH 7.4 and the form–firming capacity, to maintain the shelf life, medicinal content, and sensory attributes of NL ginseng.

Positive displacement compressors are essential in many engineering systems, from domestic to industrial applications. Many studies have been devoted to providing more insights into the workings and proposing solutions for performance improvements of these machines. This study aims to present a systematic review of published research on positive displacement compressors of various geometrical structures. This paper discusses the literature on compressor topics, including leakage, heat transfer, friction and lubrication, valve dynamics, port characteristics, and capacity control strategies. Moreover, the current status of the application of machine learning methods in positive displacement compressors is also discussed. The challenges and opportunities for future work are presented at the end of the paper.

Eclipta prostrata L. (EPL), a medicinal plant, is widely utilized in the central highlands of Vietnam. This study aims to assess the chemical profile and potential medical effects of an EPL extract rich in flavonoids. A total of 36 secondary metabolites were identified from the EPL extract through GC-MS and UHPLC-UV analysis. Among them, 15 volatile compounds and several phenolic and flavonoid chemicals, including salicylic acid, epicatechin gallate, isovitexin, and apigetrin, were reported in EPL extract for the first time. This herbal extract demonstrated moderate inhibition against α-amylase and α-glucosidase, and high anti-oxidant and anti-acetylcholinesterase activities (IC50 = 76.8 ± 0.8 μg/mL). These promising attributes can be likely attributed to the high levels of major compounds, including wedelolactone (1), chlorogenic acid (3), epicatechin gallate (6), salicylic acid (8), isovitexin (9), apigetrin (11), and myricetin (12). These findings align with the traditional use of EPL for enhancing memory and cognitive function, as well as its potential benefits in diabetes management. The results of the molecular docking study reveal that the major identified compounds (1, 6, 9, and 11) showed a more effective acetylcholinesterase inhibitory effect than berberine chloride, with good binding energy (DS values, −12.3 to −14.3 kcal/mol) and acceptable values of RMSD (1.02–1.67 Å). Additionally, almost all the identified major compounds exhibited good ADMET properties within the required limits.

This study presents an approach for calculating the stress and deformation increase in the modulation of magnetically geared machines using a mathematical method. An analytical method is employed to obtain the magnetic force density acting on the modulation components. Afterward, the proposed mathematical method predicts the mechanical characteristics. The 9 slots/32 poles/19 modulations model was evaluated via a comparison with the finite element method simulation.

Various transportation services exist, such as ride-sharing or shared taxis, in which customers receive services in a batch of flexible sizes and share fees. In this study, we conducted an equilibrium analysis of a variable batch service model in which customers who observe no waiting customers in an incomplete batch can strategically select a batch size to maximize the individual utilities. We formulated this model as a three-dimensional Markov chain and created a book-type transition diagram. To consider the joining/balking dilemma of customers for this model, we proposed an effective algorithm to construct a necessary and sufficient size of state space for the Markov chain provided that all customers adopt the threshold-type equilibrium strategy. Moreover, we proved that the best batch size is a non-decreasing function for i if the reward for the completion of batch service with size l is an increasing function of l assuming that a tagged customer observes i complete batches in the system upon arrival; in other words, the fee decreases as the batch becomes larger. We then derive several performance measures, such as throughput, social welfare, and monopolist’s revenue. Throughout the numerical experiment, a comparison between the present variable batch service model and regular batch service model in which customers were served in a constant batch, was discussed. It was demonstrated that the three performance measures can be optimized simultaneously in the variable batch service model, as long as the fee was set relatively high.

Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social interaction/communication, restricted interests, and repetitive behaviors. Recent discussions have emerged worldwide regarding the heterogeneity around presentation/etiology and comorbidities. This study aimed to determine the frequency and characteristics of comorbidities among children diagnosed with ASD in Manitoba and to evaluate differences in presentation between those with and without medical comorbidities. We conducted a retrospective chart review of >1900 electronic charts at the only publicly funded referral site for children ≤6 years requiring evaluation for ASD in Manitoba. All children aged 0–6 years diagnosed with ASD at this site between May 2016 and September 2021 were identified. χ2 and t-tests were used to compare groups. Of the total of 1858 children identified, 1452 (78.1%) were boys, 251 (13.5%) were prematurely born, and 539 (29.0%) had ≥1 medical comorbidity. Global developmental delay (GDD) was diagnosed in 428 (23.0%). The age of referral and diagnosis did not differ between groups. Comorbidities were more common among premature children (16.0% vs. 12.5%, p: 0.005) and children with comorbid GDD (34.9% vs. 18.2%, p < 0.001). Neurological comorbidities were most common (37.1%). No sex difference in the overall presence of comorbidities was found (boys = 77.1% vs. 78.5%, p: 0.518); however, girls had a higher incidence of neurological comorbidities, e.g., cerebral palsy, seizures, hypotonia (14.8% vs. 9.64%, p: 0.009), as well as genetic comorbidities (4.92% vs. 2.75%, p: 0.04). The high rates of associated neurological conditions, GDD, and prematurity add heterogeneity to this group leading to potential difficulties with prognosis and service allocation. Primary vs. secondary ASD can be a way of separating individuals based on relevant medical comorbidities.

The aim of this study is to develop a physical model and investigate the bactericidal effect of an automated hand-washing system through numerical computation, which is essential in areas affected by COVID-19 to ensure safety and limit the spread of the pandemic. The computational fluid dynamics approach is used to study the movement of the solution inside the hand-washing chamber. The finite element method with the k-ε model is applied to solve the incompressible Navier–Stokes equations. The numerical results provide insights into the solution’s hydrodynamic values, streamlines, and density in the two cases of with a hand and without a hand. The pressure and mean velocity of the fluid in the hand-washing chamber increases when the inlet flow rates increase. When the hand-washing chamber operates, it creates whirlpools around the hands, which remove bacteria. In addition, the liquid inlet flow affects the pressure in the hand-washing chamber. The ability to predict the hydraulic and cleaning performance efficiencies of the hand-washing chamber is crucial for evaluating its operability and improving its design in the future.

Background: Mixing vaccines was proposed as a solution to tackle supply chain interruptions during the crisis of the COVID-19 pandemic. This study aimed to investigate the safety of mixing COVID-19 vaccines for a booster dose in Hanoi, Vietnam. Method: A cross-sectional study was conducted via a telephone-based interview to identify the adverse events following COVID-19 vaccination among 719 participants in Hanoi, Vietnam. Results: In total, 45.76% of participants experienced at least one adverse event following two doses of the COVID-19 vaccine. Most of the adverse events were local effects with mild symptoms such as fever, headache, muscle pain, and/or pain at the site. In general, matching two doses in the same vaccines was not associated with the adverse events as compared to mixing vaccines (OR = 1.43, 96%CI: 0.93–2.2), except matching two doses of Pfizer (OR = 2.25, 95%CI: 1.33–3.82). Conclusion: The findings of this study suggest the overall safety of mixed vaccination. In light of the vaccine shortage, mixing vaccinations for COVID-19 prevention is a good solution. Further studies with larger cohorts and investigating immunity following mixing vaccines are needed to elucidate the mechanism.

Pseudomonas aeruginosa is a difficult-to-treat pathogen that is frequently involved with chronic wound infections. Here, we conducted a literature search of world-wide studies published between 2005 and 2022 that described the microbiological profiles of chronic wound infections. For each continent, a hierarchy of pathogens was created to define the organisms that were most frequently isolated in each region. Except for South America, P. aeruginosa was the second most common organism in each major continent, with Staphylococcus aureus being the most abundant pathogen overall. When individual countries were evaluated, P. aeruginosa was the most frequently isolated organism in several Southeast Asia nations including India and Malaysia. P. aeruginosa was less commonly isolated from diabetic foot infections in North America, Europe, and Africa in comparison to other types of chronic wound infections. Additionally, the Levine wound swab technique may be a quick and painless way to isolate P. aeruginosa from wound infections, but the isolation of P. aeruginosa does not seem to be an informative predictor of the patient’s clinical course. A multivariate risk assessment that accounts for the regional frequency of P. aeruginosa isolation may be an appropriate way to guide empiric management of chronic wound infections.

This paper considers a tandem queueing network with a Poisson arrival process of incoming calls, two servers, and two infinite orbits by the method of asymptotic analysis. The servers provide services for incoming calls for exponentially distributed random times. Blocked customers at each server join the orbit of that server and retry to enter the server again after an exponentially distributed time. Under the condition of low retrial rates, we prove that the joint stationary distribution of scaled numbers of calls in the orbits weakly converges to a two-variable Normal distribution.

Nowadays, virus pandemics have become a major burden seriously affecting human health and social and economic development. Thus, the design and fabrication of effective and low-cost techniques for early and accurate virus detection have been given priority for prevention and control of such pandemics. Biosensors and bioelectronic devices have been demonstrated as promising technology to resolve the major drawbacks and problems of the current detection methods. Discovering and applying advanced materials have offered opportunities to develop and commercialize biosensor devices for effectively controlling pandemics. Along with various well-known materials such as gold and silver nanoparticles, carbon-based materials, metal oxide-based materials, and graphene, conjugated polymer (CPs) have become one of the most promising candidates for preparation and construction of excellent biosensors with high sensitivity and specificity to different virus analytes owing to their unique π orbital structure and chain conformation alterations, solution processability, and flexibility. Therefore, CP-based biosensors have been regarded as innovative technologies attracting great interest from the community for early diagnosis of COVID-19 as well as other virus pandemics. For providing precious scientific evidence of CP-based biosensor technologies in virus detection, this review aims to give a critical overview of the recent research related to use of CPs in fabrication of virus biosensors. We emphasize structures and interesting characteristics of different CPs and discuss the state-of-the-art applications of CP-based biosensors as well. In addition, different types of biosensors such as optical biosensors, organic thin film transistors (OTFT), and conjugated polymer hydrogels (CPHs) based on CPs are also summarized and presented.

Alzheimer’s disease (AD) is the most common form of dementia, which is recorded as a global health issue. Natural acetylcholinesterase inhibitors (AChEIs) are considered a helpful therapy for the management of symptoms of patients with mild-to-moderate AD. This work aimed to investigate and characterize Euonymus laxiflorus Champ. (ELC) as a natural source of AChEIs compounds via in vitro and virtual studies. The screening parts used, including the leaves, heartwood, and trunk bark of ELC, revealed that the trunk bark extract possessed the highest activity, phenolics and flavonoid content. The in vitro anti-Alzheimer activity of ELC trunk bark was notably reclaimed for the first time with comparable effect (IC50 = 0.332 mg/mL) as that of a commercial AChEI, berberine chloride (IC50 = 0.314 mg/mL). Among various solvents, methanol was the most suitable to extract ELC trunk bark with the highest activity. Twenty-one secondary metabolites (1–21) were identified from ELC trunk bark extract, based on GCMS and UHPLC analyses. Of these, 10 volatile compounds were identified from this herbal extract for the first time. One phenolic (11) and seven flavonoid compounds (15–21) were also newly found in this herbal extract. Of the identified compounds, chlorogenic acid (11), epigallocatechin gallate (12), epicatechin (13), apigetrin (18), and quercetin (20) were major compounds with a significant content of 395.8–2481.5 μg/g of dried extract. According to docking-based simulation, compounds (11–19, and 21) demonstrated more effective inhibitory activity than berberine chloride, with good binding energy (DS values: −12.3 to −14.4 kcal/mol) and acceptable RMSD values (0.77–1.75 Å). In general, these identified compounds processed drug properties and were non-toxic for human use, based on Lipinski’s rule of five and ADMET analyses.

P-type layered oxides recently became promising candidates for Sodium-ion batteries (NIBs) for their high specific capacity and rate capability. This work elucidated the structure and electrochemical performance of the layered cathode material NaxMn0.5Co0.5O2 (NMC) with x~1 calcined at 650, 800 and 900 °C. XRD diffraction indicated that the NMC material possessed a phase transition from P3- to P2-type layered structure with bi-phasic P3/P2 at medium temperature. The sodium storage behavior of different phases was evaluated. The results showed that the increased temperature improved the specific capacity and cycling stability. P2-NMC exhibited the highest initial capacity of 156.9 mAh·g−1 with capacity retention of 76.2% after 100 cycles, which was superior to the initial discharge capacity of only 149.3 mAh·g−1 and severe capacity fading per cycle of P3-NMC, indicating high robust structure stability by applying higher calcination temperature. The less stable structure also contributed to the fast degradation of the P3 phase at high current density. Thus, the high temperature P2 phase was still the best in sodium storage performance. Additionally, the sodium diffusion coefficient was calculated by cyclic voltammetry (CV) and demonstrated that the synergic effect of the two phases facile the sodium ion migration. Hard carbon||P2-NMC delivered a capacity of 80.9 mAh·g−1 and 63.3% capacity retention after 25 cycles.

Several studies have been conducted on scaling limits for Markov-modulated infinite-server queues. To the best of our knowledge, most of these studies adopt an approach to prove the convergence of the moment-generating function (or characteristic function) of the random variable that represents a scaled version of the number of busy servers and show the weak law of large numbers and the central limit theorem (CLT). In these studies, an essential assumption is the finiteness of the phase process and, in most of them, the CLT for the number of busy servers conditional on the phase (or the joint states) has not been considered. This paper proposes a new method called the moment approach to address these two limitations in an infinite-server batch service queue, which is called the M/MX/∞ queue. We derive the conditional weak law of large numbers and a recursive formula that suggests the conditional CLT. We derive series expansion of the conditional raw moments, which are used to confirm the conditional CLT by a symbolic algorithm.

In this work, the physical and the electrical properties of vertical GaN Schottky diodes were investigated. Cathodo-luminescence (CL), micro-Raman spectroscopy, SIMS, and current-voltage (I-V) measurements were performed to better understand the effects of physical parameters, for example structural defects and doping level inhomogeneity, on the diode electrical performances. Evidence of dislocations in the diode epilayer was spotted thanks to the CL measurements. Then, using 2D mappings of the E2h and A1 (LO) Raman modes, dislocations and other peculiar structural defects were observed. The I-V measurements of the diodes revealed a significant increase in the leakage current with applied reverse bias up to 200 V. The combination of physical and electrical characterization methods indicated that the electrical leakage in the reverse biased diodes seems more correlated with short range non-uniformities of the effective doping than with strain fluctuation induced by dislocations.

Of particular interest within fifth generation (5G) cellular networks are the typical levels of radiofrequency (RF) electromagnetic fields (EMFs) emitted by ‘small cells’, low-power base stations, which are installed such that both workers and members of the general public can come in close proximity with them. In this study, RF-EMF measurements were performed near two 5G New Radio (NR) base stations, one with an Advanced Antenna System (AAS) capable of beamforming and the other a traditional microcell. At various positions near the base stations, with distances ranging between 0.5 m and 100 m, both the worst-case and time-averaged field levels under maximized downlink traffic load were assessed. Moreover, from these measurements, estimates were made of the typical exposures for various cases involving users and non-users. Comparison to the maximum permissible exposure limits issued by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) resulted in maximum exposure ratios of 0.15 (occupational, at 0.5 m) and 0.68 (general public, at 1.3 m). The exposure of non-users was potentially much lower, depending on the activity of other users serviced by the base station and its beamforming capabilities: 5 to 30 times lower in the case of an AAS base station compared to barely lower to 30 times lower for a traditional antenna.

This paper investigates the role of board characteristics in the relationship between tax avoidance behavior and corporate risk tolerance to elucidate the importance of corporate governance mechanisms. The applied methodology is System-GMM for 334 listed corporations in Vietnam from 2008 to 2020 to avoid endogenous problems in our models. The main findings are that higher (lower) corporate risk-taking is related to higher (lower) corporate tax avoidance if the size of the board of directors and the supervisory board are larger (lower) than six and three members, respectively. Furthermore, if the board independence ratio is lower than 48.63%, an increase in corporate risk-taking leads to increased tax avoidance. Our results support the argument that the influence of corporate risk-taking on tax avoidance behavior is governed by governance structure. Therefore, the practical implications will be towards building the optimal governance mechanism for enterprises in Vietnam.

Kombucha, one of the ordinary fermented beverages consumed worldwide, is produced by fermenting tea and sugar with a symbiotic culture of bacteria and yeasts or so-called SCOBY. Kombucha can be made from different types of tea, such as black, green, white, red, and oolong teas, yielding various health benefits and properties. Several species of bacteria and yeasts are involved in the fermentation process, which generates many beneficial compounds, such as polyphenols, organic acids, amino acids, vitamins, minerals, organic nitrogens, and hydrolytic enzymes, which have significant health effects and therapeutic properties, such as antioxidant, anti-inflammatory, anticancer, and antimicrobial properties. This review describes recent research on kombucha fermentation, the microbial community in SCOBY, the chemical composition of kombucha, and its health benefits. The adverse effects and prospects of kombucha production were also discussed.

The application of chest X-ray imaging for early disease screening is attracting interest from the computer vision and deep learning community. To date, various deep learning models have been applied in X-ray image analysis. However, models perform inconsistently depending on the dataset. In this paper, we consider each individual model as a medical doctor. We then propose a doctor consultation-inspired method that fuses multiple models. In particular, we consider both early and late fusion mechanisms for consultation. The early fusion mechanism combines the deep learned features from multiple models, whereas the late fusion method combines the confidence scores of all individual models. Experiments on two X-ray imaging datasets demonstrate the superiority of the proposed method relative to baseline. The experimental results also show that early consultation consistently outperforms the late consultation mechanism in both benchmark datasets. In particular, the early doctor consultation-inspired model outperforms all individual models by a large margin, i.e., 3.03 and 1.86 in terms of accuracy in the UIT COVID-19 and chest X-ray datasets, respectively.

Non-alcoholic steatohepatitis (NASH) is a leading cause of chronic liver disease with limited treatment options. The widely distributed plant Aloe vera has shown protective effects against NASH in animals, yet the precise mechanism remains unknown. In this study, we investigated the potential mechanisms underlying the anti-NASH effects of Aloe vera using a network pharmacology and molecular docking approach. By searching online databases and analyzing the Gene Expression Omnibus dataset, we obtained 260 Aloe vera–NASH common targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the common targets were strongly associated with the key pathological processes implicated in NASH, including lipid and glucose metabolism, inflammation, apoptosis, oxidative stress, and liver fibrosis. Four core proteins, AKT serine/threonine kinase 1 (AKT1), tumor necrosis factor alpha (TNFα), transcription factor c-Jun, and tumor suppressor protein p53, were identified from compound–target–pathway and protein–protein interaction networks. Molecular docking analysis verified that the active ingredients of Aloe vera were able to interact with the core proteins, especially AKT1 and TNFα. The results demonstrate the multi-compound, multi-target, and multi-pathway mechanisms of Aloe vera against NASH. Our study has shown the scientific basis for further experiments in terms of the mechanism to develop Aloe vera-based natural products as complementary treatments for NASH. Furthermore, it identifies novel drug candidates based on the structures of Aloe vera’s active compounds.