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A robust optimal controller for the Ward-Leonard system in a wind turbine is used to meet the performance and stability requirements when the system parameters change. However, designing according to the robust optimal method often leads to a high-order controller. This study investigated the application of order reduction algorithms to simplify the controller and help it better meet the real control problem. Comparative evaluation of the order reduction controller methods showed that the second-order reduction controller according to Moore's balanced truncation algorithm was the most suitable to replace the higher-order controller. The step response quality of the system was better when using a second-order reduction controller than a higher-order controller.

Experiment data on isolated rat hearts shows that the transient behaviors after switching pacing intervals are very complicated with increasing, decreasing, and rebound of the contraction force. The strength of contraction in the heart muscle is strongly related to intracellular free Ca2+ mediated by an action potential. This behavior can be explained by calcium cycling inside the excitable cardiac myocytes coupled with their action potential. The previous and recently proposed models can only explain a short period of time after changing the pacing frequency. Our aim is to develop a simple feedback model based on the role of the enzyme CaMKII to describe the whole dynamic picture captured from experiments.

A majority of the patients with esophageal cancer (EC) suffer from dysphagia. Several endoscopic treatment options are available such as stent placement, argon plasma coagulation, and esophageal dilatation. This study aimed to map the use of endoscopic dysphagia relieving interventions and secondly investigate possible impact on survival.Data was collected at the Dept. of SurgeryTransplantation, Rigshospitalet, Denmark. Patients with non-curable EC referred from 2016 to 2019 were included. Type of dysphagia treatment, complications and the need for repeated treatments, and survival were registered.In the study, 601 patients were included. Forty-five percent were treated with an endoscopic procedure due to dysphagia (82% had a stent placed). The median time from diagnosis to intervention was 24 days. The overall complication rate was 35% (38% in the stent group and 20% in the non-stent group, p = 0.03) and 13% of the patients were readmitted due to a complication. After 26% of the procedures, a repeated treatment was required. Patients having an endoscopic intervention had a worsened survival prognosis compared with the patients in the non-intervention group (HR: 2.17, 95% CI: 1.80-2.61, p 0.001). In the sub analysis where only patients who had an intervention was included, a survival difference in favor of the non-stent group was found (HR: 0.61, 95% CI: 0.43-0.86, p = 0.005).In this cohort, the incidence of endoscopic procedures was high, complication rates were considerable, and many the patients required a second treatment. A survival difference was seen, where the patients who had a stent placed seemed to have the worst survival outcomes. However, the causal relationship is yet to be determined why the results must be interpreted carefully. New interventions and tailored approaches that may positively affect functional and long-term oncological outcomes are highly warranted and this should preferably be investigated in randomized clinical trials.

Particulate matter (PM) pollution has become a major problem worldwide, with significant adverse health impacts, but the climatology of annual variations in and the effect of climate change on PM levels are still not comprehensively evaluated. Here we show that the vertical motions of the East Asian winter and summer monsoons regulate the annual variation in PM over Taiwan. The PM pollution season starts and ends earlier during El Niño episodes than during La Niña episodes. Furthermore, the onset, active, break, revival, and retreat phases of the PM pollution lifecycle are innovatively defined. Our results demonstrate that the annual seasonal cycle dominates wintertime PM pollution climate development during the active phase with a minor modulation by El Niño and La Niña episodes, whereas October and March, the seasonal transition periods, are significantly modulated by these two episodes. The findings suggest a new dimension of PM pollution research—the lifecycle evolution effect.

Simulating wind turbine wakes with high accuracy is crucial for understanding their effects on nearby flow patterns and optimizing the design and operation of wind farms. However, current Large Eddy simulation (LES) models for this purpose often rely on highly idealized boundary layer conditions, which may not capture all relevant realistic processes. In this study, we present the development and application of a Simple Actuator Disc model for Large Eddy Simulation (SADLES) for simulating wakes in realistic conditions. SADLES was developed to utilize traditional thrust and power curves provided by turbine manufacturers, while also achieving an intermediate resolution of a few dozen meters to strike a balance between fidelity and computational cost. SADLES has been integrated into the Weather Research and Forecast (WRF) model, resulting in the WRF-SADLES system. Using this system, atmospheric conditions from ERA5 data were downscaled to a wake-enable scale of 40 m using a system of 5 nested domains. Selected transition events were simulated and the results were validated using real observations from the FINO1 meteorological mast and LiDAR data. Our WRF-SADLES approach represents a promising advancement in the simulation of wind turbine wakes and their impacts on surrounding flow fields.

Atmospheric conditions and instabilities affect directly the performance of modern large offshore wind farms and several offshore operations, particularly farther offshore in deep waters. However, our current knowledge regarding to the atmospheric processes over a wide range of spatiotemporal scales needs further improvements by the use of measurements, and sophisticated modelling of Marine Atmospheric Boundary Layer (MABL) processes relevant to the offshore wind energy. Processes like gravity waves, Open Convective Cells (OCCs), Low Level Jets (LLJs) affect both horizontal and vertical structures of MABL flow fields and the interactions between the ambient flow and offshore constructions. For example, LLJs are common physical processes over the Southern North Sea. These transient events occur during stably stratified atmosphere with jet cores at heights between 150 m and 300 m. Strong positive and negative shears are observed below and above the nose of LLJ (i.e a maxima in the vertical wind profile). Structure, timing, shape, and characteristics of LLJs influence the loads on turbines and the overall power generation of offshore wind parks. Therefore, precise modelling and measurement of these episodes are highly important.While advanced measurement systems such as LiDAR provides important information on formation and characteristics of LLJs, such measurements are sparse in time and space. On the other hand, modelling tools are sensitive in prediction of LLJ characteristics such as LLJ’s height, spatial position, and timing, the choice of initial and boundary conditions, and planetary boundary layer schemes used in the Numerical Weather Prediction models (NWPs). Predictive skills of these models can be enhanced through assimilation of available quality observational data with NWPs like Weather Research and Forecasting (WRF) model. In this study, we use the WRF model to model wind variability for a geographical area covering the FINO1 offshore meteorological met-mast and Alpha Ventus offshore wind park (in the Southern North Sea). We first examine the performance of WRF, with an appropriate configuration, in forecasting few LLJ events. We then apply a LiDAR-based data assimilation (for sometimes during 2015) and study how different DA techniques (namely observational nudging and 3DVAR) can improve the accuracy of wind forecasting and reduce the model uncertainity during the LLJ events.

Previous studies showed that interaction between the atmosphere and sea is very important for simulating offshore wind, due to the effects of sea waves on momentum, mass and energy exchanges. In numerical weather prediction models, this effect is typically represented by a parameter known as roughness length. However, many atmospheric models do not take into account the impact of waves on roughness length over the sea.In this study, we aimed to investigate the effects of waves on offshore wind simulation by applying some new roughness length formula in Weather Research and Forecasting (WRF) to consider wave characteristics in roughness length calculation. The simulations were compared with observations during some cases of misalignment and alignment of wind and wave directions at FINO1 station. We compared wind speed and wind power density of the simulated and observed data using met mast and lidar data.

The development of wind energy in recent years has made the representation of wind turbines in numerical models essential for wind resource and environmental assessment. In this study, we introduce a new wind turbine model, the Simple Actuator Disk for Large Eddy Simulation (SADLES), parameterized in the Weather Research and Forecast (WRF) model. Our goal is to perform realistic downscaling of large eddy simulation, so we integrated SADLES and the cell perturbation method as WRF modules and released the code as open-source for further research. We demonstrate the effectiveness of SADLES by comparing a large eddy simulation of a 5-MW wind turbine using the WRF-SADLES with the Parallelized Large-eddy simulation Model (PALM), showing that SADLES can simulate wind turbine wakes effectively at an intermediate resolution of a few dozen meters. Furthermore, we show the applicability of SADLES in wind farm assessment by downscaling the ERA5 reanalysis data to study turbine-to-turbine and farm-to-farm interactions for the Alpha Ventus wind farm. In our case study, due to the wind farm to the southwest, the ambient wind speed at Alpha Ventus is reduced by 14 % and the average turbine power is reduced by 35 %. SADLES provides a promising balance between computational efficiency and accuracy for wind turbine wake simulations and has potential applications in wind energy assessment and wind farm construction planning.

This multicentre prospective cohort study aimed to compare the accuracy of the PAASH, WFNS, and Hunt and Hess (H&H) scales in predicting the outcomes of adult patients with aneurysmal SAH presented to three central hospitals in Hanoi, Vietnam, from August 2019 to June 2021. Of 415 eligible patients, 32.0% had a 90-day poor outcome, defined as an mRS score of 4 (moderately severe disability) to 6 (death). The PAASH, WFNS and H&H scales all have good discriminatory abilities for predicting the 90-day poor outcome. There were significant differences in the 90-day mean mRS scores between grades I and II (p = 0.001) and grades II and III (p = 0.001) of the PAASH scale, between grades IV and V (p = 0.026) of the WFNS scale, and between grades IV and V (p

This article examines the factors influencing the teaching of critical thinking development for students by primary school teachers in northern mountainous areas of Vietnam. The 21 survey questions were designed via google form and sent to 128 primary school teachers in the mountainous northern region of Viet Nam. The exploratory factor analysis (EFA) method was used to analyze the study results. Research results show that there are six factors that influence primary school teachers' teaching to develop critical thinking for students: 1) Teaching skills develop critical thinking; 2) Teacher attitude; 3) The teacher's understanding of critical thinking; 4) The interest of the student's parents; 5) Influence from colleagues and managers; 6) Critical thinking assessment activities. The total variance extracted by these 6 factors explains 68.477% of the 21 observed variables. The results of this research can help primary school teachers in the mountainous north of Vietnam better understand what is needed to develop students' critical thinking and apply appropriate teaching methods to help students develop these skills.

In this paper, we prove that the multiplicative group of a unital non-commutative Leavitt path algebra $L_K(E)$ and Cohn path algebra $C_K(E)$ contain a non-cyclic free subgroup, provided $K$ is a non-absolute field. We also provide a description of the generators of free subgroups in term of the graph $E$. Finally, we determine multiplicative groups of Leavitt path algebras of some special types., Comment: 31 pages, 11 figures

Contains fulltext : 292710.pdf (Publisher’s version ) (Open Access) Heterozygous variants in GBA1, encoding glucocerebrosidase (GCase), are the most common genetic risk factor for Parkinson's disease (PD). Moreover, sporadic PD patients also have a substantial reduction of GCase activity. Genetic variants of SMPD1 are also overrepresented in PD cohorts, whereas a reduction of its encoded enzyme (acid sphingomyelinase or ASM) activity is linked to an earlier age of PD onset. Despite both converging on the ceramide pathway, how the combined deficiencies of both enzymes might interact to modulate PD has yet to be explored. Therefore, we created a double-knockout (DKO) zebrafish line for both gba1 (or gba) and smpd1 to test for an interaction in vivo, hypothesising an exacerbation of phenotypes in the DKO line compared to those for single mutants. Unexpectedly, DKO zebrafish maintained conventional swimming behaviour and had normalised neuronal gene expression signatures compared to those of single mutants. We further identified rescue of mitochondrial Complexes I and IV in DKO zebrafish. Despite having an unexpected rescue effect, our results confirm ASM as a modifier of GBA1 deficiency in vivo. Our study highlights the need for validating how genetic variants and enzymatic deficiencies may interact in vivo.

Sepsis is the most common cause of in-hospital deaths, especially from low-income and lower-middle-income countries (LMICs). This study aimed to investigate the mortality rate and associated factors from sepsis in intensive care units (ICUs) in an LMIC. We did a multicenter cross-sectional study of septic patients presenting to 15 adult ICUs throughout Vietnam on the 4 days representing the different seasons of 2019. Of 252 patients, 40.1% died in hospital and 33.3% died in ICU. ICUs with accredited training programs (odds ratio, OR: 0.309; 95% confidence interval, CI 0.122–0.783) and completion of the 3-h sepsis bundle (OR: 0.294; 95% CI 0.083–1.048) were associated with decreased hospital mortality. ICUs with intensivist-to-patient ratio of 1:6 to 8 (OR: 4.533; 95% CI 1.621–12.677), mechanical ventilation (OR: 3.890; 95% CI 1.445–10.474) and renal replacement therapy (OR: 2.816; 95% CI 1.318–6.016) were associated with increased ICU mortality, in contrast to non-surgical source control (OR: 0.292; 95% CI 0.126–0.678) which was associated with decreased ICU mortality. Improvements are needed in the management of sepsis in Vietnam such as increasing resources in critical care settings, making accredited training programs more available, improving compliance with sepsis bundles of care, and treating underlying illness and shock optimally in septic patients.

There are 19 currently recognized species of treeshrews in the genus Tupaia (Tupaiidae, Scandentia) with a majority of the taxa found in Southeast Asia. During our surveys in northeastern Vietnam, nine new specimens of Tupaia were collected from five different localities, including Lang Son and Ha Giang provinces and Cat Ba Island, Hai Phong City. Our molecular analysis reveals that the new population diverges from its closest congeners by at least 11.2% based on a fragment of the mitochondrial COI gene and 10.1% based on a fragment of the mitochondrial cytochrome b (Cyt b) gene. The distinction of the newly discovered population is also supported by significant differences compared to other species based on morphological analysis. As a result, a new species, Tupaia danghuyhuynhi sp. nov., was described based on morphological and molecular evidence.

The primary function of hybrid direct current circuit breakers (HCBs) is to quickly interrupt fault currents to protect high-voltage direct current (HVDC) systems. To enhance the reliability and stability of HVDC systems, optimal design of HCBs is required to minimize the peak fault current, interruption time, and recovery time. Therefore, this study develops a multi-objective genetic algorithm (MOGA)-based optimization model to identify the optimal parameters for HCBs. The MOGA model consists of three objective functions that provide trade-offs among reductions in the peak fault current, the interruption time, and the recovery time. The proposed algorithm is verified with a novel HCB topology using inverse current injection techniques. The performance of the HCB topology with the optimal parameters is validated in the MATLAB/Simulink environment. In addition, a comparison study between the optimal design of an HCB using the proposed algorithm and a typical HCB model is presented in this study to show the effectiveness of the proposed optimization method. Our simulation results show that the optimal parameter design of HCBs significantly reduces the magnitude of the peak fault current and operating time, thus maintaining the safe and stable operation of the entire system.

Background: Although men have a higher rate of stroke than women, it is not clear whether women have a worse outcome after adjusting for confounders such as vascular risk factors, age, stroke severity, and reperfusion therapy. We evaluated sex differences on 90-day functional outcomes after stroke in a multicenter study in Vietnam. Methods: We recruited patients presenting with ischemic or hemorrhagic stroke at 10 stroke centers in Vietnam for a period of 1 month from August 1, 2022, to August 31, 2022. We reviewed the patient’s clinical demographics, time from symptom onset to hospital admission, stroke classification, stroke subtype, stroke severity, characteristics of reperfusion therapy, and 90-day clinical outcome. We compared functional outcomes and predisposing factors at day 90 between men and women after an ischemic and hemorrhagic stroke. Poor outcome was defined as mRS 3-6. Results: There were 2,300 stroke patients included. Men accounted for 61.3% (1,410) of participants. Compared with men, women were older (67.7±13.9 vs. 63.7±13.3, P There was no difference in 90-day functional outcomes between sexes. Factors associated with poor outcomes included age ≥ 50 years (adjusted OR, aOR 1.75; 95% CI, 1.16 to 2.66), history of stroke (aOR 1.50; 95% CI, 1.15 to 1.96), large artery atherosclerosis (aOR 5.19; 95% CI, 3.90 to 6.90), and cardioembolism (aOR 3.21; 95% CI, 1.68 to 6.16). Factors associated with mortality in patients with acute ischemic stroke included a history of coronary artery disease (aOR 3.04; 95% CI, 1.03 to 8.92), large artery atherosclerosis (aOR 3.37; 95% CI, 2.11 to 5.37), and cardioembolism (aOR 3.15; 95%CI, 1.20 to 8.27). Conclusion: There were no sex differences in the clinical outcome of stroke and ischemic stroke in this prospective cohort of hospitalized Vietnamese patients

Background: Lipid alterations contribute to Alzheimer’s disease (AD) pathogenesis. Lipidomics studies could help systematically characterize such alterations and identify potential biomarkers. Objective: To identify lipids associated with mild cognitive impairment and amyloid-β deposition, and to examine lipid correlation patterns within phenotype groups Methods: Eighty plasma lipids were measured using mass spectrometry for 1,255 non-demented participants enrolled in the Mayo Clinic Study of Aging. Individual lipids associated with mild cognitive impairment (MCI) were first identified. Correlation network analysis was then performed to identify lipid species with stable correlations across conditions. Finally, differential correlation network analysis was used to determine lipids with altered correlations between phenotype groups, specifically cognitively unimpaired versus MCI, and with elevated brain amyloid versus without. Results: Seven lipids were associated with MCI after adjustment for age, sex, and APOE4. Lipid correlation network analysis revealed that lipids from a few species correlated well with each other, demonstrated by subnetworks of these lipids. 177 lipid pairs differently correlated between cognitively unimpaired and MCI patients, whereas 337 pairs of lipids exhibited altered correlation between patients with and without elevated brain amyloid. In particular, 51 lipid pairs showed correlation alterations by both cognitive status and brain amyloid. Interestingly, the lipids central to the network of these 51 lipid pairs were not significantly associated with either MCI or amyloid, suggesting network-based approaches could provide biological insights complementary to traditional association analyses. Conclusion: Our attempt to characterize the alterations of lipids at network-level provides additional insights beyond individual lipids, as shown by differential correlations in our study.

Background Burkholderia pseudomallei is a causative agent of melioidosis, a fatal infectious disease highly prevalent in the tropics where traditional medicinal plants are widely used for the treatment of various human ailments. In this study, we aimed to evaluate the in vitro antibacterial activity of common eligible herbs and medicinal plants against B. pseudomallei. Thermal and gastric stability, antibacterial spectrum, bactericidal activity, and cell cytotoxicity were also tested to verify the possible usage of these plants in the treatment of melioidosis. Results Eighteen eligible herbs and twenty-one medicinal plants were collected. Herb juices and aqueous plant samples extracted at different temperatures were prepared for antibacterial testing. A higher proportion of aqueous plant extracts (17/21; 80.9%) against B. pseudomallei was observed, in comparison with that of herb juices (8/18; 44.5%). Two herb juices and twelve aqueous plant extracts were selected for further tests. The juices of A. sativum and A. tuberosum decreased their antimicrobial activity when treated at higher temperatures whereas the aqueous plant extracts increased their antimicrobial activity when prepared at 70 and 100 °C. The herb juices showed a broader spectrum of antimicrobial activity than the aqueous plant extracts. All samples showed less cytotoxicity on the HT29, HepG2, and HEK293 cell lines. At the 2× minimal inhibitory concentration (MIC), aqueous extracts of Blechnum orientale, Breynia fruticose, Psidium guajava, Rhodomyrtus tomentosa, Rosa odorata, and Schima wallichii showed similar bactericidal activity to that of amoxicillin clavulanic acid. The antimicrobial activity of Mangifera indica, Punica granatum, and R. tomentosa remained under the stimulated gastric conditions. Conclusion Our data indicate that traditional medicinal plants prepared by decoction could be effectively used to treat melioidosis via the oral route. Further in vivo investigations are needed to explore other alternative therapies for the prevention and treatment of tested pathogenic bacterial species.

ObjectivesTo compare the accuracy of the SOFA and APACHE II scores in predicting mortality among ICU patients with sepsis in an LMIC.DesignA multicentre, cross-sectional study.SettingA total of 15 adult ICUs throughout Vietnam.ParticipantsWe included all patients aged ≥ 18 years who were admitted to ICUs for sepsis and who were still in ICUs from 00:00 hour to 23:59 hour of the specified study days (i.e., 9thJanuary, 3rdApril, 3rdJuly, and 9thOctober of the year 2019).Primary and secondary outcome measuresThe primary outcome was hospital all-cause mortality (hospital mortality). We also defined the secondary outcome as all-cause deaths in the ICU (ICU mortality).ResultsOf 252 patients, 40.1% died in hospitals, and 33.3% died in ICUs. SOFA (AUROC: 0.688 [95% CI: 0.618-0.758]; cut-off value ≥ 7.5; PAUROCAUROCAUROCAUROCConclusionsIn this study, SOFA and APACHE II scores were worthwhile in predicting mortality among ICU patients with sepsis. However, due to better discrimination for predicting ICU mortality, the SOFA was preferable to the APACHE II score in predicting mortality.Clinical trials registry – India: CTRI/2019/01/016898Strengths and limitations of this studyAn advantage of the present study was data from multi centres, which had little missing data.Due to the absence of a national registry of intensive care units (ICUs) to allow systematic recruitment of units, we used a snowball method to identify suitable units, which might have led to the selection of centres with a greater interest in sepsis management.Due to the study’s real-world nature, we did not make a protocol for microbiological investigations. Moreover, we mainly evaluated resources utilized in ICUs; therefore, the data detailing the point-of-care testing and life-sustaining treatments were not available. Additionally, to improve the feasibility of conducting the study in busy ICUs, we opted not to collect data on antibiotic resistance and appropriateness.Due to our independent variables (e.g., SOFA score that was greater than or equal to the cut-off value) that might be associated with primary outcome only measured upon ICU admission, the mixed-effects logistic regression model could not be used to predict discrete outcome variables measured at two different times, i.e., inside and outside the ICU settings.Although the sample size was large enough, the confidence interval was slightly wide (±6.03%), which might influence the normal distribution of the sample.

ObjectivesTo investigate the impact of intracerebral haematoma (ICH) on the outcomes and the factors related to an ICH in patients with aneurysmal subarachnoid haemorrhage (aSAH) in a low- and middle-income country.DesignA multicentre prospective cohort study.SettingThree central hospitals in Hanoi, Vietnam.ParticipantsThis study included all patients (≥18 years) presenting with aSAH to the three central hospitals within 4 days of ictus, from August 2019 to June 2021, and excluded patients for whom the admission Glasgow Coma Scale was unable to be scored or patients who became lost at 90 days of follow-up during the study.Outcome measuresThe primary outcome was ICH after aneurysm rupture, defined as ICH detected on an admission head CT scan. The secondary outcomes were 90-day poor outcomes and 90-day death.ResultsOf 415 patients, 217 (52.3%) were females, and the median age was 57.0 years (IQR: 48.0–67.0). ICH was present in 20.5% (85/415) of patients with aSAH. There was a significant difference in the 90-day poor outcomes (43.5% (37/85) and 29.1% (96/330); p=0.011) and 90-day mortality (36.5% (31/85) and 20.0% (66/330); p=0.001) between patients who had ICH and patients who did not have ICH. The multivariable regression analysis showed that systolic blood pressure (SBP) ≥140 mm Hg (adjusted odds ratio (AOR): 2.674; 95% CI: 1.372 to 5.214; p=0.004), World Federation of Neurosurgical Societies (WFNS) grades II (AOR: 3.683; 95% CI: 1.250 to 10.858; p=0.018) to V (AOR: 6.912; 95% CI: 2.553 to 18.709; pConclusionsIn this study, ICH was present in a substantial proportion of patients with aSAH and contributed significantly to a high rate of poor outcomes and death. Higher SBP, worse WFNS grades and ruptured MCA aneurysms were independently associated with ICH on admission.

To determine the optimal size of an energy storage system (ESS) in a fast electric vehicle (EV) charging station, minimization of ESS cost, enhancement of EVs’ resilience, and reduction of peak load have been considered in this article. Especially, the resilience aspect of the EVs is focused due to its significance for EVs during power outages. First, the stochastic load of the fast-charging station (FCS) and the resilience load of the EVs are estimated using probability distribution functions. This information is utilized to maintain the energy level in the ESS to ensure the resilience of EVs during power outages. Then, the annualized cost of the ESS is determined using the annual interest rate and lifetime of ESS components. Finally, the optimal ESS size is determined using the annualized ESS cost, penalty cost for buying power during peak hours, and penalty cost for resilience violations. Simulations along with sensitivity analysis of uncertainties (market price, arrival time of EVs, and the residual energy level of EVs), number of EVs in the FCS, and converter ratings are conducted. Simulation results have shown that increasing the penalty cost for peak intervals is a viable solution to decrease the peak load while controlling the cost of the FCS.

An effort-based reward approach is proposed in this article for the allocation of load shedding amount in interconnected microgrids. In this article, effort is defined as the relative contribution of a microgrid to the network with respect to its capacity. In contrast to the absolute contribution-based reward methods, where smaller microgrids are discriminated, the proposed effort-based reward method provides a fair chance for microgrids of all sizes. Historic data of efforts of each microgrid are recorded and an index (effort index) is formulated. The effort index is used as a measure to allocate load shedding to microgrids during emergencies, where microgrids with higher effort indices receive lesser load shedding and vice versa. Different weights are defined for efforts of microgrids depending on the operation mode of the network due to the difference in the importance of power sharing in each mode. In addition, a reward compensation algorithm is devised to mitigate gaining of benefits for longer times while making lesser contributions. The proposed method is realized by using a multiagent system in java agent development framework (JADE) via agent communication language messages. The performance of the proposed method is compared with existing load shedding allocation algorithms, i.e., proportional method, bankruptcy Talmud rule, and absolute contribution-based reward methods.

In the conventional operation of a wind farm (WF) system, the operation point of each wind turbine generator (WTG) is determined to capture maximum energy individually using maximum power point tracking (MPPT) algorithm. However, this operation strategy might not ensure the maximum output power of WF due to wake effect among WTGs. Therefore, this paper develops a multi-agent-based cooperative learning strategy among WTGs using deep reinforcement learning to enhance the overall efficiency of WF by minimizing the wake effect. WTG agents are learnable units and they interact with others as an extensive-form game based on a cooperative model to achieve a common goals (i.e. maximum output power of the WF). In this game, WTG agents carry out their actions sequentially and measure a common reward which is used to update the knowledge of all agents. During the training process, WTG agents use different deep neural networks (DNNs) to improve their actions for achieving the higher reward in the long run by optimizing the weights of DNNs in each learning step. After the training process, WTG agents are able to determine optimal set-points with different input information to minimize the wake effect and to maximize the output power of the WF. Moreover, an operation strategy for the entire WF system is proposed to ensure that the WF always complies with grid-code constraints from transmission system operators, including the requirement of limited power and reserve power. In order to show the effectiveness of the proposed method, a comparison between the results using the proposed method and the conventional MPPT method is also presented in different cases, and the results show that the proposed method can increase the output power of the WF in the range of 1.99% to 4.11% with different layouts.

The existing distributed operation schemes for microgrids lack the ability to determine the power selling to the grid during normal operation mode and are unable to provide service reliability to critical loads, during islanded operation mode. In order to overcome these issues, in this study, we have proposed a distributed operation method for both grid-connected and islanded modes of microgrids. Unlike the existing studies, where the utility grid is considered as a dispatchable generator, the bi-directional flow of power with the grid is considered in this study. Similarly, different load agents are considered for different priority loads to assure the service reliability to the critical loads during islanding. A two-step operation method is proposed for both grid-connected and islanded mode operations. During the first step, each agent in the network shares information with its neighboring agents to determine the total load and available renewable power in the network. Whereas, in the second step, each agent in the network determines the optimal operation points based on the local information received from the neighboring agents. Moreover, a modified cost function for the battery is also proposed in this study, which utilizes the information of market price and load to enhance the battery operation. A comparison is made between the centralized method, conventional distributed method, and the proposed distributed operation method. Simulation results have proved the effectiveness of the proposed method for realizing distributed operation for microgrids in both grid-connected and islanded modes.

$Q$ -learning-based operation strategies are being recently applied for optimal operation of energy storage systems, where, a $Q$ -table is used to store $Q$ -values for all possible state-action pairs. However, $Q$ -learning faces challenges when it comes to large state space problems, i.e., continuous state space problems or problems with environment uncertainties. In order to address the limitations of $Q$ -learning, this paper proposes a distributed operation strategy using double deep $Q$ -learning method. It is applied to managing the operation of a community battery energy storage system (CBESS) in a microgrid system. In contrast to $Q$ -learning, the proposed operation strategy is capable of dealing with uncertainties in the system in both grid-connected and islanded modes. This is due to the utilization of a deep neural network as a function approximator to estimate the $Q$ -values. Moreover, the proposed method can mitigate the overestimation that is the major drawback of the standard deep $Q$ -learning. The proposed method trains the model faster by decoupling the selection and evaluation processes. Finally, the performance of the proposed double deep $Q$ -learning-based operation method is evaluated by comparing its results with a centralized approach-based operation.

This work is funded by Vietnam National University HoChiMinh City (VNUHCM) under grant number B2020-18-02. This paper aims to study solvable-by-finite and locally solvable maximal subgroups of an almost subnormal subgroup of the general skew linear group GLn(D) over a division ring D. It turns out that in the case where D is non-commutative, if such maximal subgroups exist, then either it is abelian or [D : F] < ∞. Also, if F is an infinite field and n ≥ 5, then every locally solvable maximal subgroup of a normal subgroup of GLn(F) is abelian.

In this Pseudo-global Warming study, potential future changes in the Southeast Asia tropical cyclone (TC) exposure climatology are quantified. One hundred and seventeen landfalling TCs in the last 20 years are simulated with their current climate conditions and also with the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble perturbed conditions under the SSP2-4.5 and SSP3-7.0 climate change scenarios. Our simulations suggest that landfalling TCs are projected to be 8% more intense at landfall, 2.8% faster and have smaller sizes by the end of the 21st century under the SSP3-7.0 scenario. In addition, TC landfall locations shift northward with tracks extending further inland toward Laos and Thailand. In particular, TC exposures, wind and rainfall impacts significantly increase in the northern Philippines, Taiwan, southwestern coast of China, and northern Vietnam; and significantly decrease in the southern areas of Southeast Asia and the southeastern coast of China. publishedVersion

In the last century, conventional antibiotics have played a significant role in global healthcare. Antibiotics support the body in controlling bacterial infection and simultaneously increase the tendency of drug resistance. Consequently, there is a severe concern regarding the regression of the antibiotic era. Despite the use of antibiotics, host defence systems are vital in fighting infectious diseases. In fact, the expression of ribosomal antimicrobial peptides (AMPs) has been crucial in the evolution of innate host defences and has been irreplaceable to date. Therefore, this valuable source is considered to have great potential in tackling the antimicrobial resistance (AMR) crisis. Furthermore, the possibility of bacterial resistance to AMPs has been intensively investigated. Here, we summarize all aspects related to the multiple applications of ribosomal AMPs and their derivatives in combating AMR.

BACKGROUND: Spirulina platensis contains a large amount of chlorophylls, chlorophyll a, that are starting materials to synthesize functionalized chlorins. Chlorin e6 (Ce6) as well as its derivatives are second generation sensitizers using in photodynamic therapy (PDT) of various cancers. In this study, we transfer chlorophyll a of S. platensis to Ce6derivatives and determine their several applications. AIM: to evaluate the effects of Ce6 derivatives to treat cancer cells. METHODS: Ce6 trimethylester was created from methyl pheophorbide a2 in S. platensis provided by the Hidumi Company, Nghe An province, Viet Nam. Hela cells were incubated with Ce6 trimethylester and the irradiated with the diode laser dose of 1.2 J/cm2/min through the system of filters £ 650 nm. MTT assay and clonogenic assay were used to determine survival rate and cloning efficiency of cells. Antimicrobial effect of Ce6 trimethylester with halogen light were studied with Propionibacterium acnes VTCC 0218 and Staphylococcus aureus VTCC 0173. RESULTS: From dry biomass (700 g) of S. platensis, after extracting chlorophyll a and methanolysis, 4.2 g of methyl pheophorbide a was obtained. The reaction to give Ce6 trimethylester with 82% yield was performed with potassium hydroxide (KOH) in MeOH/THF/CHCl3. After irradiation with a 650 nm laser at 1.2 J, the cell viability in all samples decreased with Ce6 trimethylester treatment, the survival declining trend of Hela cells treated with Ce6 trimethylester were proportional when concentration of Ce6 trimethylester increased. The rate of colony formation was declined as the concentration of Ce6 trimethylester treated was increased. The growth of both S. aureus and P. acnes can be inactivated by Ce6 trimethylester PDT. The MIC99 value against P. acnes VTCC 0218 and S. aureus VTCC 0173 of Ce6 trimethylester with halogen light was 1.25 μg/ml. CONCLUSION: The Ce6 trimethylester from S. platensis cultivated in Viet Nam could be used as a potential photosentizer for photodynamic therapy for treatment of cancer and acne.

Background The simple scoring systems for predicting the outcome of sepsis in intensive care units (ICUs) are few, especially for limited-resource settings. Therefore, this study aimed to evaluate the accuracy of the quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) score in predicting the mortality of ICU patients with sepsis in Vietnam. Methods We did a multicenter cross-sectional study of patients with sepsis (≥18 years old) presenting to 15 adult ICUs throughout Vietnam on the specified days (i.e., 9th January, 3rd April, 3rd July, and 9th October) representing the different seasons of 2019. The primary and secondary outcomes were the hospital and ICU all-cause mortalities, respectively. The area under the receiver operating characteristic curve (AUROC) was calculated to determine the discriminatory ability of the qSOFA score for deaths in the hospital and ICU. The cut-off value of the qSOFA scores was determined by the receiver operating characteristic curve analysis. Upon ICU admission, factors associated with the hospital and ICU mortalities were assessed in univariable and multivariable logistic models. Results Of 252 patients, 40.1% died in the hospital, and 33.3% died in the ICU. The qSOFA score had a poor discriminatory ability for both the hospital (AUROC: 0.610 [95% CI: 0.538 to 0.681]; cut-off value: ≥2.5; sensitivity: 34.7%; specificity: 84.1%; PAUROC = 0.003) and ICU (AUROC: 0.619 [95% CI: 0.544 to 0.694]; cutoff value: ≥2.5; sensitivity: 36.9%; specificity: 83.3%; PAUROC = 0.002) mortalities. However, multivariable logistic regression analyses show that the qSOFA score of 3 was independently associated with the increased risk of deaths in both the hospital (adjusted odds ratio, AOR: 3.358; 95% confidence interval, CI: 1.756 to 6.422) and the ICU (AOR: 3.060; 95% CI: 1.651 to 5.671). Conclusion In our study, despite having a poor discriminatory value, the qSOFA score seems worthwhile in predicting mortality in ICU patients with sepsis in limited-resource settings. Clinical trial registration Clinical trials registry–India: CTRI/2019/01/016898

Pineapple is one of the most widespread crops in the world. High volume of pineapple leaf (PL) waste which is burnt directly on the farm or landfill site after harvest leads to negative impacts on the environment. However, PL residue can be considered an important potential source for renewable materials due to its significant cellulose content. As means to reduce waste and enhance cellulose-based materials, nanocellulose gains high attraction due to its special properties such as non-toxicity, biocompatibility, biodegradability, and 100 % environmental friendliness. Because of nanometer scale, nanocellulose becomes a promising material, which expresses high mechanical strength, extremely large surface area, good modifiability and results in various value-added applications, namely packaging, regenerative medicine, electronics, etc. Aiming to sustainability and feasibility, focusing on environmental-friendly resources like nanocellulose to generate high-value materials efficiently is one of the progressive actions. To summarize the common methods approached to utilize PL as raw materials to produce high-value engineering nanocellulose and its potential applications, this review focuses firstly on chemical and mechanical pre-treatment of PL to enrich cellulose content; secondly on the preparation of nanocellulose via conventional acid hydrolysis, enzymatic hydrolysis, and newly mechano-hydrolysis and its physicochemical properties as well as characteristic structure; finally on the sustainable applications of nanocellulose in production of renewable materials such as aerogel, hydrogel, nanocomposite, and other promising fields.

Transmission system operators impose several grid-code constraints on large-scale wind farms to ensure power system stability. These constraints may reduce the net profit of the wind farm operators due to their inability to sell all the power. The violation of these constraints also results in an imposition of penalties on the wind farm operators. Therefore, an operation strategy is developed in this study for optimizing the operation of wind farms using an energy storage system. This facilitates wind farms in fulfilling all the grid-code constraints imposed by the transmission system operators. Specifically, the limited power constraint and the reserve power constraint are considered in this study. In addition, an optimization algorithm is developed for optimal sizing of the energy storage system, which reduces the total operation and investment costs of wind farms. All parameters affecting the size of the energy storage systems are also analyzed in detail. This analysis allows the wind farm operators to find out the optimal size of the energy storage systems considering grid-code constraints and the local information of wind farms.

Background The prevalence of risk factors for poor outcomes from aneurysmal subarachnoid hemorrhage (SAH) varies widely and has not been fully elucidated to date in Vietnam. Understanding the risk and prognosis of aneurysmal SAH is important to reduce poor outcomes in Vietnam. The aim of this study, therefore, was to investigate the rate of poor outcome at 90 days of ictus and associated factors from aneurysmal SAH in the country. Methods We performed a multicenter prospective cohort study of patients (≥18 years) presenting with aneurysmal SAH to three central hospitals in Hanoi, Vietnam, from August 2019 to August 2020. We collected data on the characteristics, management, and outcomes of patients with aneurysmal SAH and compared these data between good (defined as modified Rankin Scale (mRS) of 0 to 3) and poor (mRS, 4–6) outcomes at 90 days of ictus. We assessed factors associated with poor outcomes using logistic regression analysis. Results Of 168 patients with aneurysmal SAH, 77/168 (45.8%) were men, and the median age was 57 years (IQR: 48–67). Up to 57/168 (33.9%) of these patients had poor outcomes at 90 days of ictus. Most patients underwent sudden-onset and severe headache (87.5%; 147/168) and were transferred from local to participating central hospitals (80.4%, 135/168), over half (57.1%, 92/161) of whom arrived in central hospitals after 24 hours of ictus, and the initial median World Federation of Neurological Surgeons (WFNS) grading score was 2 (IQR: 1–4). Nearly half of the patients (47.0%; 79/168) were treated with endovascular coiling, 37.5% (63/168) were treated with surgical clipping, the remaining patients (15.5%; 26/168) did not receive aneurysm repair, and late rebleeding and delayed cerebral ischemia (DCI) occurred in 6.1% (10/164) and 10.4% (17/163) of patients, respectively. An initial WFNS grade of IV (odds ratio, OR: 15.285; 95% confidence interval, CI: 3.096–75.466) and a grade of V (OR: 162.965; 95% CI: 9.975–2662.318) were independently associated with poor outcomes. Additionally, both endovascular coiling (OR: 0.033; 95% CI: 0.005–0.235) and surgical clipping (OR: 0.046; 95% CI: 0.006–0.370) were inversely and independently associated with poor outcome. Late rebleeding (OR: 97.624; 95% CI: 5.653–1686.010) and DCI (OR: 15.209; 95% CI: 2.321–99.673) were also independently associated with poor outcome. Conclusions Improvements are needed in the management of aneurysmal SAH in Vietnam, such as increasing the number of aneurysm repairs, performing earlier aneurysm treatment by surgical clipping or endovascular coiling, and improving both aneurysm repairs and neurocritical care.

Background: Intraventricular haemorrhage (IVH) patients with acute obstructive hydrocephalus (AOH) who require external ventricular drainage (EVD) are at high risk for poor outcomes. Intraventricular fibrinolysis (IVF) with low-dose recombinant tissue plasminogen activator (rtPA) can be used to improve patient outcomes. Here, we evaluated the impact of IVF on the risk of death and the functional outcomes in IVH patients with AOH. Methods: This prospective cohort study included IVH patients with hypertensive intracranial haemorrhage complicated by AOH who required EVD. We evaluated the risk of death and the functional outcomes at 1 and 3 months, with a specific focus on the impact of combined EVD with IVF by low-dose rtPA. Results: Between November 30, 2011 and December 30, 2014, 80 patients were included. Forty-five patients were treated with EVD alone (EVD group) and 35 received IVF (EVD+IVF group). The 30- and 90-day mortality rates were lower in the EVD+IVF group than in the EVD group (42.2 vs. 11.4%, p = 0.003, and 62.2 vs. 20%, p < 0.001, respectively). The Graeb scores were significantly lower in the EVD+IVF group than in the EVD group (p ≤ 0.001) during the first 3 days and on day 7 after assignment. The 30-day good functional outcome (modified Rankin Scale [mRS] score 0–3) was also higher in the EVD+IVF group than in the EVD group (6.7 vs. 28.6%, p = 0.008). However, the 90-day good functional outcome (mRS score 0–3) did not significantly increase in the EVD+IVF group (30.8% in the EVD group vs. 51.6% in the EVD+IVF group, p = 0.112). Conclusions: In our prospective observational study, EVD+IVF was associated with a lower risk of death in IVH patients. EVD+IVF improved the chance of having a good functional outcome at 1 month; however, this result was no longer observed at 3 months.

Microgrids are considered as a potential solution to deal with major power disruption events due to their ability of islanding and potential to sustain the penetration of renewables. In order to elaborate the role of microgrids in enhancing the resilience of power systems, a three-step analysis is carried out in this paper. In the first step, the general backgrounds of resilience in power systems are presented, which comprise of disaster modeling, resilience analysis methods, and resilience enhancement efforts by different regions. In the second step, the use of microgrids as a resilience resource is analyzed, where formation of microgrids, networked microgrids, and dynamic microgrids along with resiliency of multi-energy networks are explored. In the third step, the strategies utilized by microgrids for enhancing their resilience during major outage events are analyzed. These strategies include proactive scheduling, outage management, feasible islanding, and advanced operation strategies for reducing the impact of major disruptions. The classification of these operation strategies is based on the event occurrence and clearance times. In addition, the resilience strategies used by different types of microgrids, types of energy management systems, communication resilience, and resilience of individual components in microgrids are also analyzed. Finally, research gaps in the existing literature and future directions for improving the available resilience-oriented operation methods for enhancing the resilience of microgrids are presented.

This paper proposes a three-step internal trading strategy for optimal energy sharing among building microgrids (MGs) to minimize the operation cost of the entire system. In the first step, barter trading is performed to exchange energies among building MGs of the network. Building MGs having shortage of electricity and surplus of heat can pair with buildings having surplus of electricity and shortage of heat to exchange their energies. Then, the surplus/shortage energy is updated after carrying out the barter trading. In the second step, building MGs sell their remaining surplus energy to other building MGs that have shortage energy. In the third step, building MGs, which have lower generation cost than the external system and ability to increase their power generation, increase their power generation and trade with other building MGs. These three steps can increase the power sharing among building MGs and reduce the trading with the external systems, which results in reduced operation cost of the network. An additional internal market along with price signals is also presented to carry out the proposed internal trading strategy. The internal market provides a mechanism for trading energies among the building MGs of a combined cooling, heat and power (CCHP) system. A hierarchical energy management system (EMS), including building EMSs (BEMSs) and a community EMS (C-EMS) is developed to minimize the operation cost of the CCHP system. Moreover, a heat pipeline (HPL) system is applied for storing the surplus heat energy for fulfilling the shortage heat energy in the building MGs. By using the proposed strategy, total trading cost of CCHP system is reduced by 7.43% compared with the conventional operation strategy.

In wind farm (WF) systems, the set-points of wind turbine generators (WTGs) is determined by the wind farm operator. A change in the value of set-point in two consecutive intervals leads to power fluctuations in the WF system, i.e. power deviation. A large amount of power deviation may adversely affect the operation of the WF system. Therefore, this paper proposes a strategy for operation of a WF system to minimize the power deviation of WTGs during operation time. By using the proposed strategy, the change in set-points of WTGs is minimized and the output power of WTGs is therefore smoother and avoids unnecessary fluctuations. Several grid-code constraints are also considered for operation of the WF system. This ensures the WF system to operate in compliance with the requirements from transmission system operator. Besides, an additional strategy is also proposed to monitor all events in the WF system. Whenever an event occurs in the system, the set-points of WTGs are rescheduled considering the event. Therefore, the proposed operation strategy is also capable of handling events in the WF system. Finally, the simulation results with and without the proposed method are compared to show the effectiveness of the proposed method.

A resilience-oriented optimization strategy is proposed in this paper by considering feasible islanding in normal operation and survivability of critical loads during emergency period. A resilience index is proposed for assessing the capability of each microgrid to feed local critical loads during sudden power disruptions. Based on the values of the proposed resilience index, local optimization results are revised by changing the commitment status of dispatchable generators and energy storage elements. The uncertainties associated with renewable generations and loads are realized via robust optimization method. The adjustable power bounds, suggested by each microgrid for minimizing the operation cost of the network, are also revised through the proposed resilience index. In emergency mode, decision between feeding of lesser critical loads and battery charging along with a strategy for minimization of load curtailment during switching of scheduling windows is considered. These two considerations assure the survivability of critical loads during emergency period. Finally, an incremental cost consensus algorithm is used for optimal allocation of surplus power among the connected microgrids having unserved loads. Three different network topologies are considered in emergency mode for assessing the performance of the proposed approach.