Search

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.

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 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.

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.

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.