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Lentic waters are biogeochemical reactors, producing and receiving carbon (C) originally fixed by the terrestrial and aquatic biosphere, which is then buried in sediments or respired back to the atmosphere in the forms of carbon dioxide (CO2) and one of the more potent greenhouse gas (GHG) methane (CH4). Additionally, lakes serve as archives of terrestrial and aquatic carbon processes within their sediments, enabling the reconstruction of historical changes spanning thousands of years. These changes encompass alterations in land cover, indicated by pollen records, soil carbon erosion and shifts in lake productivity resulting from changes in land use and climate. Both the burial of C in lakes and the emissions of GHGs are recognised as important components of Earth's climate system, yet they remain poorly understood and constrained due to inadequate quantities and qualities of observations. In the case of GHG emissions from lakes, observations are often sporadic, failing to capture the significant spatial and temporal variations in emissions across diverse lentic systems. To address this challenge, process-based models that incorporate the interconnected biogeochemical processes occurring within lakes and their watersheds would arguably be the best tool to extrapolate from site-level observations to regional and finally global scales, to quantify the anthropogenic impact on these fluxes and to reconstruct long-term shifts in emissions and burial due to changes in land cover and climate. However, the development and evaluation of such models is hampered by the lack of observations in sufficient quality. In this project, we bring together a unique consortium of specialists in aquatic ecology, biogeochemistry, palynology, sedimentology and modelling of terrestrial and aquatic biogeochemistry. This project will put forth a national programme of systematic, long-term observations of lake GHG and C cycling processes of unmet detail, consistency and quality. First, at 40 pilot sites spanning typological and environmental gradients, there will be a comprehensive data acquisition endeavour to evaluate biological processes and mesological factors influencing the sequestration or recycling of organic carbon. This effort will be complemented with a synthesis of existing data (WP1). Second, based on well-dated sediment records, which include both newly-acquired and synthesised existing data, variability of lake C burial and their climate and land-use controls will be reconstructed over the past 150 years (WP2). For 15 of these pilot sites, reconstruction will go back until the mid-Holocene (5,000 years BP), allowing us to shed light on the anthropogenic perturbation of the C cycle in this earlier part of human history, which is commonly excluded from this type of research due to lack of information. The activities of these first two WPs will result in an open-source national database, guaranteeing valorisation of our research far beyond this project. In WP3, we will use the land surface model (LSM) ORCHIDEE C-lateral to assess C cycling in the terrestrial biosphere and the mobilisation of biospheric C into lakes, which is possible due to an explicit representation of soil C leaching and erosion processes and a downscaling scheme permitting us to assess C exports from watersheds at sub-grid scale. While LSMs are used to assess evolution of biospheric C budgets from the beginning of the Industrial Period, we will use it to hindcast the evolution since the mid-Holocene, using lake sediment records for model validation. Moreover, we will develop a new process-based lake C model supported by the database established in WPs 1 and 2, which we will couple to ORCHIDEE C-lateral to simulate lake C burial and GHG emissions in response to climate and processes in the lake watershed. This model set-up will first be used to better constrain contemporary large-scale lake GHG emissions and to disentangle the anthropogenic perturbation of these fluxes from the natural background flux. These estimates will be revolutionary, as they will allow attributing part of lake GHG emissions to anthropogenic emissions for national GHG budget reporting. Then, these models will be emulated to reconstruct evolution of lake GHG budgets and C budgets of the whole lake watershed since the mid-Holocene. While simulations will first be performed at the scales of France and Europe, the development of international partnerships to implement observations from other biomes (WP4) will finally support simulations at the global scale.

Abstract Freshwater algae exhibit complex dynamics, particularly in meso-oligotrophic lakes with sudden and dramatic increases in algal biomass following long periods of low background concentration. While the fundamental prerequisites for algal blooms, namely light and nutrient availability, are well-known, their specific causation involves an intricate chain of conditions. Here we examine a recent massive Uroglena bloom in Lake Geneva (Switzerland/France). We show that a certain sequence of meteorological conditions triggered this specific algal bloom event: heavy rainfall promoting excessive organic matter and nutrients loading, followed by wind-induced coastal upwelling, and a prolonged period of warm, calm weather. The combination of satellite remote sensing, in-situ measurements, ad-hoc biogeochemical analyses, and three-dimensional modeling proved invaluable in unraveling the complex dynamics of algal blooms highlighting the substantial role of littoral-pelagic connectivities in large low-nutrient lakes. These findings underscore the advantages of state-of-the-art multidisciplinary approaches for an improved understanding of dynamic systems as a whole.

Abstract BackgroundThe Primary Trauma Care (PTC) course was originally developed to instruct health care workers in the management of patients with severe injuries in low- and middle-income countries (LMICs) with limited medical resources. PTC has now been taught for more than 25 years. Many studies have demonstrated that the 2-day PTC workshop is useful and informative to frontline health staff and has helped improve knowledge and confidence in trauma management; however, there is little evidence of the effect of the course on changes in clinical practice. The Kirkpatrick model (KM) and the knowledge, attitude, and practice (KAP) model are effective methods to evaluate this question. ObjectiveThe aim of this study was to investigate how the 2-day PTC course impacts the satisfaction, knowledge, and skills of health care workers in 2 Vietnamese hospitals using a conceptual framework incorporating the KAP model and the 4-level KM as evaluation tools. MethodsThe PTC course was delivered over 2 days in the emergency departments (EDs) of Thanh Hoa and Ninh Binh hospitals in February and March 2022, respectively. This study followed a prospective pre- and postintervention design. We used validated instruments to assess the participants’ satisfaction, knowledge, and skills before, immediately after, and 6 months after course delivery. The Fisher exact test and the Wilcoxon matched-pairs signed rank test were used to compare the percentages and mean scores at the pretest, posttest, and 6-month postcourse follow-up time points among course participants. ResultsA total of 80 health care staff members attended the 2-day PTC course and nearly 100% of the participants were satisfied with the course. At level 2 of the KM (knowledge), the scores on multiple-choice questions and the confidence matrix improved significantly from 60% to 77% and from 59% to 71%, respectively (PPP ConclusionsThe PTC course undertaken in 2 local hospitals in Vietnam was successful in demonstrating improvements at 3 levels of the KM for ED health care staff. The improvements in the confidence matrix and scenarios checklist were maintained for at least 6 months after the course. PTC courses should be effective in providing and sustaining improvement in knowledge and trauma care practice in other LMICs such as Vietnam.

Kien Xuan Nguyen,1,&ast; Tien Viet Tran,2 Thuan Duc Nghiem,3 Tuan Ngoc Tran,1 Thang Ba Ta,4 Ba Van Nguyen,5 Tuan Dinh Le,6,&ast; Son Tien Nguyen,6 Kien Trung Nguyen,7 Hoa Trung Dinh,8 Dinh Cong Pho,9 Toan Nguyen Duy,10,&ast; Pham Quoc Toan11 1Department of Military Medical Command and Organization, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 2Department of Infectious Diseases, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 3Department of Otolaryngology, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 4Respiratory Center, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 5Department of Oncology, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 6Department of Rheumatology and Endocrinology, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 7Center of Hematology and Blood Transfusion, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 8Department of Requested Treatment, National Hospital of Endocrinology, Hanoi, Vietnam; 9Department of Military Science, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 10Cardiovascular Center, Military Hospital 103, Vietnam Medical Military University, Hanoi, 10000, Vietnam; 11Department of Nephrology, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam&ast;These authors contributed equally to this workCorrespondence: Pham Quoc Toan, Department of Nephrology, Military Hospital 103, Vietnam Military Medical University, 160 Phung Hung Street, Phuc La Ward, Ha Dong District, Hanoi, Vietnam, Email toannephro@gmail.comIntroduction: Metacognition plays an essential role in competency-based medical education. Metacognitive skills consist of knowledge and regulation metacognition. This study was conducted to investigate the metacognition of undergraduate students and its correlation with students’ academic performance.Methods: The metacognitive skills inventory comprised 52 binary-scale items administered to 202 Vietnam Military Medical University medical students. The entire semester and clinical results were used to measure their academic performance.Results: Medical students’ total metacognitive awareness score was high (median 0.8). The median metacognitive knowledge score was significantly lower than the metacognitive regulation score (0.7 vs 0.8, respectively). The participants with a total metacognition score ≥ 0.8 had significantly higher academic results (full semester exam results of 7.4 and clinical exam of 7.5). The group of participants in the military, having sports habits and usually searching academic documents in English, had a higher proportion of total metacognitive awareness score ≥ 0.8 than the group without these above characteristics (with the percentages of 53.3%, 59%, and 64.3%, respectively; p < 0.05). The number of books read by participants with a total metacognitive awareness score ≥ 0.8 was significantly higher than those with a total metacognitive awareness score < 0.8 (3.5 compared to 2.4 books).Conclusion: Metacognitive awareness of Vietnam Military Medical University medical students was likely to be high. A high score of metacognitive awareness could predict high academic performance. Being a military student, playing sports, reading books, and searching English documents were predictors of better metacognitive awareness.Keywords: metacognition, medical student, metacognitive awareness, academic performance

Han Thi Ngoc Le,1,&ast; Kien Xuan Nguyen,2,&ast; Toan Duy Nguyen,1 Ho Quang La,3 Xuan Thanh Nguyen,4 Dung Tien Le,5 Huy Quoc Pham,5 Khai Xuan Nguyen,6 Hiep Hoang Nguyen,7 Viet Van Pham,6 Cong Van Pham,5 Dinh Cong Pho,8 Binh Nhu Do,8 Tien Viet Tran,9 Son Tien Nguyen,10 Tuan Dinh Le,10,&ast; Thuc Cong Luong1 1Cardiovascular Center, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 2Department of Military Medical Command and Organization, Vietnam Medical Military University, Hanoi, 10000, Vietnam; 3Hospital Quality Control Division, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 4Senior Officer Department, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 5Intensive Care, Emergency and Poison Control Center, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 6Interventional Radiology Department, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 7Field Internal Medicine Center, Military Hospital 103, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 8Department of Military Science, Vietnam Military Medical University, Hanoi, 10000, Vietnam; 9Department of Infectious Diseases, Military Hospital 103, Vietnam Medical Military University, Hanoi, 10000, Vietnam; 10Department of Rheumatology and Endocrinology, Vietnam Military Hospital 103, Medical Military University, Hanoi, 10000, Vietnam&ast;These authors contributed equally to this workCorrespondence: Thuc Cong Luong, Cardiovascular Center, Military Hospital 103, Vietnam Military Medical University, 160 Phung Hung Street, Phuc La Ward, Ha Dong District, Hanoi, Vietnam, Email luongcongthuc@vmmu.edu.vnBackground: Personal protective equipment (PPE), an essential shield to protect healthcare workers (HCWs) during the COVID-19 pandemic, has been reported to affect their heart rate variability (HRV).Objective: To investigate the changes of very short-term heart rate variability in HCWs after three hours of wearing PPE to treat COVID-19 patients at different working times and intensities, and related factors.Methods: Sixty-five healthy HCWs were enrolled at the Number 2 Infectious Field Hospital (formed by Military Hospital 103), Vietnam. Two-minute 12-lead electrocardiograms were recorded before wearing and after removing PPE.Results: After three hours of wearing PPE, the mean heart rate of HCWs increased (p = 0.048) meanwhile, the oxygen saturation decreased significantly (p = 0.035). Standard deviation of all normal to normal intervals (SDNN), mean intervals RR (mean NN), and root mean square successive difference (rMSSD) after wearing PPE was also reduced significantly. SDNN, Mean NN, and rMSSD decreased as the working intensity increased (as in mild, moderate, and severe patient departments). In univariate regression analysis, logSDNN, logmean NN and logrMSSD were positively correlated with SpO2 and QT interval (r = 0.14, r = 0.31, r = 0.25; r = 0.39, r = 0.77, r = 0.73, respectively) and were negatively correlated with ambient temperature inside PPE (r = − 0.41, r = − 0.405, r = − 0.25, respectively) while logmean NN and log rMSSD were negatively correlated with diastolic blood pressure (r = − 0.43, r = − 0.39, respectively). In multivariable regression analysis, logSDNN and logmean NN were negatively correlated to ambient temperature inside PPE (r = − 0.34, r = − 0.18, respectively).Conclusion: Time-domain heart rate variability decreased after wearing PPE. Time-domain HRV parameters were related to ambient temperature inside PPE, diastolic blood pressure, QT interval, and SpO2.Keywords: cardiovascular disorders, cardiovascular change, heart rate variability, personal protective equipment, healthcare workers, COVID-19

Recent advancements in optical wavefront shaping have brought multimode fibers (MMFs) into the spotlight as potential contenders for long-haul communication, positioning them as promising substitutes to single-mode fibers. MMFs offer greater data rates, countering the impending congestion of fiber-based networks. Additionally, their suitability for single fiber endoscope procedures presents them as compelling alternatives for minimally invasive endoscopy, providing information comparable to, if not surpassing, current cutting-edge technology. However, the complex modal behavior of light in MMFs hinders the implementation of these promising applications. Hence, precise modal excitation and control are crucial for improving the transmission of structured light in MMFs. This study introduces a groundbreaking approach that achieves the retrieval of the transmission matrix in a single step, thereby facilitating coherent light propagation through highly dispersive MMFs. By combining iterative phase retrieval algorithms with the measurement of phase shifts between experimentally established focal points, potential arbitrary interference control is enabled, leading to effective phase correction. The efficacy of our method is validated through the successful transmission of diverse structured light beams, including Laguerre–Gauss and Hermite–Gaussian types, as well as handwritten characters via MMF. The examination of structured light is simplified using an off-axis holographic technique that accurately captures both intensity and phase information. These results hold significant potential, paving the way for major advancements in long-distance communication and minimally invasive medical procedures, thereby transforming the telecommunications and healthcare sectors.

Kien Xuan Nguyen,1,&ast; Tien Bui Minh,2,&ast; Hoa Trung Dinh,3,4 Tien Viet Tran,5 Tuan Dinh Le,5,&ast; Nga Phi Thi Nguyen,6 Thi Thanh Hoa Tran,3 Trinh Hien Vu,3 Lan Ho Thi Nguyen,3 Kien Trung Nguyen,2 Nguyen Huy Thong,6 Khanh Do,6 Trung Kien Nguyen,7 Hung Nguyen Dao,8 Son Tien Nguyen6,&ast; 1Department of Military Medical Command and Organization, Vietnam Medical Military University, Ha Noi, Vietnam; 2Department of Obstetrics and Gynecology, Thai Binh University of Medicine and Pharmacy, Thai Binh, Vietnam; 3Department of Requested Treatment, National Hospital of Endocrinology, Ha Noi, Vietnam; 4National Hospital of Endocrinology, Ha Noi, Vietnam; 5Department of Infectious Diseases, Military Hospital 103, Vietnam Medical Military University, Hanoi, Vietnam; 6Department of Rheumatology and Endocrinology, Military Hospital 103, Vietnam Military Medical University, Ha Noi, Vietnam; 7Hematology and Blood Transfusion Center, Military Hospital 103, Vietnam Military Medical University, Ha Noi, Vietnam; 8Department of Obstetrics and Gynecology, Military Hospital 103, Vietnam Military Medical University, Ha Noi, Vietnam&ast;These authors contributed equally to this workCorrespondence: Son Tien Nguyen, Department of Rheumatology and Endocrinology, Military Hospital 103, Vietnam Military Medical University, 160 Phung Hung Street, Phuc La Ward, Ha Dong District, Hanoi City, Vietnam, Email ntson4879@gmail.comIntroduction: Chronic low-grade inflammation (LGI) plays a role in the pathogenesis of gestational diabetes mellitus (GDM). LGI, on the one hand, promotes insulin resistance and at the same time, affects fetal development. The study aimed to use clinically feasible means to evaluate the association between maternal LGI and maternal insulin resistance and fetal growth indices by ultrasound in the third trimester.Methods: A crossectional and descriptive study on 248 first-time diagnosed GDM in Vietnam.Results: Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte (PLR) indices were significantly higher in GDM than in normal glucose-tolerant pregnancies (p = 0.048 and 0.016, respectively). GDM with LGI witnessed significantly higher systolic blood pressure, BMI, HbA1c, and significantly lower quantitative Insulin Sensitivity Check Index (QUICKI) than those without LGI. After adjusting for maternal BMI, fasting plasma glucose (FPG), age, and parity, C-reactive protein (CRP) was positively correlated with HOMA2-IR (B=0.13, p< 0.01) and Mathews index (B=0.29, p< 0.01). Regarding fetal characteristics, LGI was associated with fetal growth indices in the third trimester of GDM. NLR was negatively correlated with estimated fetal weight (EFW) (B=− 64.4, p< 0.05) after adjusting for maternal BMI and FPG. After adjusting for maternal BMI, FPG, age, and parity, PLR was negatively correlated with biparietal diameter (B=− 0.02, p< 0.01) and abdominal circumference (AC) (B=− 0.16, p< 0.05), and EFW (B=− 1.1, p< 0.01), and head circumference (HC) (B=− 0.06, p< 0.01); CRP was negatively correlated with AC (B=− 0.16, p< 0.001), EFW (B=− 85.3, p< 0.001), and HC (B=− 5.0, p< 0.001).Conclusion: In the third trimester, LGI was associated with maternal glucose and insulin resistance in GDM. Moreover, LGI was associated with fetal characteristics in ultrasonic images. There were negative correlations between LGI and fetal developmental characteristics.Keywords: gestational diabetes mellitus, low-grade inflammation, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, fetal ultrasound parameters

Thanh Xuan Nguyen,1,2 Huyen Thi Thanh Vu,1,2 Tuan Nguyen,3– 6 Adrian Esterman,5 Luc Viet Tran,1,2 Janani Thillainadesan,7,8 Vasikaran Naganathan,7,8 Henry Brodaty,9 Anh Trung Nguyen1,2 1Scientific Research Department, National Geriatric Hospital, Hanoi, 10000, Vietnam; 2Department of Geriatrics, Hanoi Medical University, Hanoi, 10000, Vietnam; 3Division of Social Gerontology, National Ageing Research Institute, Parkville, VIC, 3050, Australia; 4School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC, 3122, Australia; 5UniSA Clinical & Health Sciences, University of South Australia, Adelaide, SA, 5001, Australia; 6Health Strategy and Policy Institute, Ministry of Health of Vietnam, Hanoi, 10000, Vietnam; 7Department of Geriatric Medicine and Centre for Education and Research on Ageing (CERA), Concord Hospital, Sydney, NSW, Australia; 8Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia; 9Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, UNSW, Sydney, NSW, AustraliaCorrespondence: Thanh Xuan Nguyen, Scientific Research Department, National Geriatric Hospital, 1A, Phuong Mai, Dong Da, Hanoi, 10000, Vietnam, Tel +84 983277646, Email xuanthanhbmlk@hmu.edu.vnBackground: Multidomain interventions have been shown to be effective in improving cognition, quality of life, reducing neuropsychiatric symptoms and delaying progression of functional impairment or disability in dementia patients. To investigate the multidomain intervention in other populations and diverse cultural and geographical settings, this pilot study will assess the feasibility of a multidomain intervention for older people with dementia in nursing homes in Vietnam.Methods: Participants will be randomized into two equal groups, to receive either a multidomain intervention (intervention group) or regular health advice (control group). The intervention will include physical, cognitive, and social interventions as well as management of metabolic and vascular risk factors. We will hypothesize that the multidomain intervention will be feasible in Vietnam, and participants who receive the intervention will show improvement in quality of life, behaviors, functional ability, cognitive function, sleep, and in reduction of falls, use of healthcare services, and death rate compared to those in the control group during the 6 months intervention period and after the 6 months extended follow-up.Discussion: This is the first study to evaluate the feasibility of a multidomain intervention program for older people with dementia in nursing homes in Vietnam. The results from the trial will inform clinicians and the public of the possibility of comprehensive treatment beyond simply drug treatments for dementia. This paves the way for further studies to evaluate the long-term effects of multidomain interventions in dementia patients. Furthermore, the research results will provide information on the effectiveness of multidomain interventions which will inform policy development on dementia.Trial Registration: The trial is registered with ClinicalTrials.gov identifier: NCT04948450 on 02/07/2021.Keywords: dementia, multidomain, intervention, feasibility

Rapid antigen testing (RAT) is a cost-effective and time-efficient method of identifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and therefore a critical part of infection control strategies. There is no published evidence evaluating the use of RAT during the Omicron wave of the COVID-19 pandemic for asymptomatic patients or its performance between waves. All patients presenting to an Emergency Department over a two-week period without COVID-19 symptoms were screened for SARS-CoV-2 using both the Abbott Panbio RAT as well as the gold standard reverse transcriptase real-time polymerase chain reaction (PCR). The Abbott Panbio RAT sensitivity was 13% (95% CI 0.028, 0.336) for asymptomatic patients. The use of this test in asymptomatic patients during the Omicron wave had a statistically significant reduction in sensitivity compared with two reports of the same test in previous waves (13% vs. 86%, p < 0.0001; 13% vs. 83%, p < 0.0001). As SARS-CoV-2 continues to mutate, the sensitivity of RATs are altered and needs to be continually re-evaluated for each variant of concern if they are to be used as part of an infection control strategy.

Opioid prescribing and dispensing from emergency departments is a noteworthy issue given widespread opioid misuse and diversion in many countries, contributing both physical and economic harm to the population. High patient numbers and the stochastic nature of acute emergency presentations to emergency departments (EDs) introduce challenges for prescribers who are considering opioid stewardship principles. This study investigated the effect of changes to electronic prescribing software on prescriptions with an auto-populated quantity of oxycodone immediate release (IR) from an Australian tertiary emergency department following the implementation of national recommendations for reduced pack sizes. A retrospective review of oxycodone IR prescriptions over two six-month periods between 2019 and 2021 was undertaken, either side of a software adjustment to reduce the default quantities of tablets prescribed from 20 to 10. Patient demographic details were collected, and prescriber years of practice calculated for inclusion in linear mixed effects regression modelling. A reduction in the median number of tablets prescribed per prescription following the software changes (13.5 to 10.0, p < 0.001) with little change in the underlying characteristics of the patient or prescriber populations was observed, as well as an 11.65% reduction in the total number of tablets prescribed. The prescriber’s years of practice, patient age and patient sex were found to influence increased prescription sizes. Reduced quantity of oxycodone tablets prescribed was achieved by alteration of prescribing software prefill parameters, providing further evidence to support systems-based policy interventions to influence health care providers behaviour and to act as a forcing function for prescribers to consider opioid stewardship principles.

Background: The B-type rafkinase (BRAF) V600E gene mutation plays an important role in the pathogenesis, diagnosis, and prognosis of thyroid carcinoma. This study was conducted to investigate the rate of the BRAF V600E mutation, the relationships between the BRAF V600E gene mutation and some immunohistochemical markers, and recurrence rate in patients with differentiated thyroid cancer. Method: The study was conducted by a descriptive and longitudinal follow-up method on 102 thyroid carcinoma patients at 103 Military Hospital, Hanoi, Vietnam. All patients were identified with the BRAF V600E gene mutation by real-time polymerase chain reaction. Results: The rate of BRAF V600E gene mutation in patients with thyroid cancer was 60.8%. Patients with BRAF V600E gene mutation had a significantly higher rate of positive cyclooxygenase 2 (COX-2) and Ki67 markers than those without the mutation (COX-2: odds ratio [OR] = 2.93; 95% confidence interval [CI] = 1.27-6.74, P = .011; Ki67: OR = 3.41; 95% CI = 1.31-8.88, P = .01). A statistically significant relationship was identified between the rate of BRAF V600E mutation and the rate of positive Hector Battifora mesothelial 1 (HBME-1) (B = −1.040; P = .037) and COX-2 (B = −1.123; P = .023) markers. The recurrence rate in patients with BRAF V600E gene mutation was significantly higher than that in those without the mutation ( P = .007). The mean of the recurrence time of patients with BRAF V600E mutation was significantly lower than that in those without the mutation ( P = .011). Conclusions: A high prevalence of BRAF V600E gene mutation was found in thyroid carcinoma patients. The rates of positive HBME-1, COX-2, and Ki67 markers were significantly correlated to BRAF V600E gene mutation. Patients with BRAF V600E gene mutation showed a significantly higher relapse rate and earlier relapse time than those without the mutation.

Son Tien Nguyen,1,&ast; Tien Bui Minh,2,&ast; Hoa Trung Dinh,3,4 Tuan Dinh Le,1 Nga Phi Thi Nguyen,1 Thi Thanh Hoa Tran,3 Trinh Hien Vu,3 Thuc Luong Cong,5 Lan Ho Thi Nguyen,3 Phuong Tuan Pham,3,4 Tien Viet Tran,6 Kien Xuan Nguyen7 1Department of Rheumatology and Endocrinology, Military Hospital 103, Vietnam Military Medical University, Ha Noi, Vietnam; 2Department of Obstetrics and Gynecology, Thai Binh University of Medicine and Pharmacy, Thai Binh, Vietnam; 3Department of Requested Treatment, National Hospital of Endocrinology, Ha Noi, Vietnam; 4National Hospital of Endocrinology, Ha Noi, Vietnam; 5Cardiovascular Center, Military Hospital 103, Vietnam Medical Military University, Ha Noi, Vietnam; 6Department of Infectious Diseases, Military Hospital 103, Vietnam Medical Military University, Hanoi, 10000, Vietnam; 7Department of Military Medical Command and Organization, Vietnam Medical Military University, Ha Noi, Vietnam&ast;These authors contributed equally to this workCorrespondence: Kien Xuan Nguyen, Department of Military Medical Command and Organization, Vietnam Military Medical University, 160 Phung Hung Street, Phuc La Ward, Ha Dong District, Hanoi city, Vietnam, Email nguyenxuankien@vmmu.edu.vnIntroduction: Cortisol is proven to play a crucial role in hyperglycemia and fetal development in gestational diabetes mellitus (GDM). This research aims to investigate the relationship between maternal serum cortisol and insulin resistance indices and fetal ultrasound characteristics in women with GDM.Methods: A cross-sectional and descriptive study on 144 GDM in Vietnam from January 2015 to December 2020. Serum cortisol was measured using electrochemiluminescence immunoassay at 8 a.m. on the examination day in the vicinity of the 24th gestational week. Fetal ultrasound was performed by an experienced person who was blind to the study.Results: The mean cortisol level in the GDM group was 627.04 nmol/L. Serum cortisol levels positively correlated with abdominal circumference (AC), fasting plasma glucose (FPG), insulin, triglycerides, HOMA2-IR, and Mathew indices (with r of 0.18, 0.22, 0.18, 0.17, 0.18, and 0.22, respectively). Serum cortisol levels negatively correlated with QUICKI and McAuley indices (with r of − 0.19 and − 0.21), respectively. In a univariate linear regression, maternal serum cortisol positively correlated with fetal AC, head circumference (HC), and biparietal diameter (BPD) (with r of 0.21; 0.23; and 0.25, respectively). In a multivariate linear regression analysis, cortisol positively correlated with fetal AC, HC, and BPD after adjusting to maternal McAuley index.Conclusion: Serum cortisol levels in GDM correlated with fasting blood glucose, triglycerides, and insulin resistance. Besides, serum cortisol levels in GDM positively correlated with fetal development.Keywords: gestational diabetes mellitus, serum cortisol, insulin resistance indices, fetal ultrasound parameters

We present two datasets composed of high frequency sensors data, vertical in situ profiles and laboratory chemical analysis data, acquired during two different aquatic mesocosm experiments performed at the OLA (“Long-term observation and experimentation for lake ecosystems”) facility at the UMR CARRTEL in Thonon les Bains, on the French shore of Lake Geneva. The DOMLAC experiment lasted 3 weeks (4-21 October 2021) and aimed to simulate predicted climate scenarios (i.e. extreme events such as storms and floods) by reproducing changes in quality and composition of lake subsidies and runoff by increased inputs of terrestrial organic matter. The PARLAC experiment lasted 3 weeks (5-23 September 2022) and aimed to simulate turbid storms by light reduction.The experimental setup consisted of nine inland polyester laminated tanks (2.1 m length, 2.1 m width and 1.1 m depth) with a total volume of approximately 4000 L and filled with water directly supplied from the lake at 4m depth. Both experimental design included three treatments each replicated three times. The DOMLAC experiment involved a control treatment (no treatment applied) and two treatments simulating allochthonous inputs from two different dissolved organic matter (DOM) extract from peat moss Sphagnum sp. (Peat-Moss treatment) and Phragmites australis (Phragmite treatment). The PARLAC experiment involved a control treatment (no treatment applied) and two treatments simulating two different intensity of light reduction. In the Medium treatment transmitted light was reduced to 70% and in the High treatment transmitted light was reduced to 15%.The datasets are composed of: 1. In situ measures from automated data loggers of temperature, conductivity, dissolved oxygen and CO2 acquired every 5 minutes at 0.1, 0.5 and 1 m depth (DOMLAC) and 0.5m (PARLAC) for the entire period of the experiment. 2. In situ profiles (0-1 m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation) acquired twice a week during the experiment. 3. In situ measures of light spectral UV/VIS/IR irradiance (300-950 nm wavelength range) taken in the air and at 0, 0.5 and 1 m twice a week on the same day of the profiles at point 2. 4. Laboratory chemical analysis of integrated samples taken twice a week on the same day of the in situ profiles at point 2 and 3 of conductivity, pH, total alkalinity, NO3, total and particulate nitrogen (Ntot, Npart), PO4, total and particulate phosphorus (Ptot, Ppart), total and particulate organic carbon (TOC, POC), Ca, K, Mg, Na, Cl, SO4 and SiO2. Only for DOMLAC also analyses of NH4, NO2 and dissolved organic carbon (DOC). 5. Laboratory analysis of pigments (Chla, Chlc, carotenoids, phaeopigments) extracted from samples collected at point 4. 6. Only for DOMLAC, specific absorbance on the range 600-200nm of DOM (i.e.

Mountain biking is growing in participation but carries risk for severe injury and burden on health systems. Little is known about the impact of these injuries on emergency medical services, definitive healthcare, and factors contributing to accidents. This review aimed to determine the health service impacts of severe mountain bike trauma and risk factors, with a view to understanding critical gaps and needs. A systematic online search was conducted using the databases PubMed and MEDLINE complete and grey literature relating to mountain bike injury since the databases’ inception to July 2023. The results show that although mountain biking has relatively high injury rates that are increasing, the impacts on health services were rarely documented, with some evidence indicating that even small increases in injuries from race events can overwhelm local health services. Severe injuries were more common in downhill disciplines. However, the definitions of what constitutes severe injury were variable. Severe injuries were more common in downhill disciplines, influenced by the rider skill level, demographics, participation in competitive events, trail design, environmental factors, and healthcare availability. Further research in these areas is needed, along with the more consistent reporting of injury severity.

BackgroundDespite significant improvement in the last decade, road trauma remains a substantial contributor to deaths in Vietnam. The COVID-19 pandemic necessitated public health measures that had an unforeseen benefit on road trauma in high-income countries. We investigate if this reduction was also seen in a low- to middle-income country like Vietnam. ObjectiveOur aim was to investigate how the COVID-19 pandemic and the government policies implemented in response to it impacted road trauma fatalities in Vietnam. We also compared this impact to other government policies related to road trauma implemented in the preceding 14 years (2007-2020). MethodsCOVID-19 data were extracted from the Vietnamese Ministry of Health database. Road traffic deaths from 2007 to 2021 were derived from the Vietnamese General Statistical Office. We used Stata software (version 17; StataCorp) for statistical analysis. Poisson regression modeling was used to estimate trends in road fatality rates based on annual national mortality data for the 2007-2021 period. The actual change in road traffic mortality in 2021 was compared with calculated figures to demonstrate the effect of COVID-19 on road trauma fatalities. We also compared this impact to other government policies that aimed to reduce traffic-related fatalities from 2007 to 2020. ResultsBetween 2007 and 2020, the number of annual road traffic deaths decreased by more than 50%, from 15.3 to 7 per 100,000 population, resulting in an average reduction of 5.4% per annum. We estimated that the road traffic mortality rate declined by 12.1% (95% CI 8.9-15.3%) in 2021 relative to this trend. The actual number of road trauma deaths fell by 16.4%. This reduction was largely seen from August to October 2021 when lockdown and social distancing measures were in force. ConclusionsIn 2021, the road traffic–related death reduction in Vietnam was 3 times greater than the trend seen in the preceding 14 years. The public health response to the COVID-19 pandemic in Vietnam was associated with a third of this reduction. It can thus be concluded that government policies implemented to address the COVID-19 pandemic resulted in a 4.3% decrease in road traffic deaths in 2021. This has been observed in high-income countries, but we have demonstrated this for the first time in a low- and middle-income country.

Overuse of computed tomography pulmonary angiograms (CTPAs) for diagnosis of pulmonary embolism (PE) has been recognised as an issue for over ten years, with Choosing Wisely Australia recommending that CTPAs only be ordered if indicated by a clinical practice guideline (CPG). This study aimed to explore the use of evidence-based practice within regional Tasmanian emergency departments in relation to CTPA orders by determining whether CTPAs were ordered in accordance with validated CPGs. We conducted a retrospective medical record review of all patients who underwent CTPA across all public emergency departments in Tasmania between 1 August 2018 and 31 December 2019 inclusive. Data from 2758 CTPAs across four emergency departments were included. PE was reported in 343 (12.4%) of CTPAs conducted, with yield ranging from 8.2% to 16.1% between the four sites. Overall, 52.1% of participants had neither a CPG documented, nor a D-dimer conducted before their scan. A CPG was documented before 11.8% of scans, while D-dimer was conducted before 43% of CTPAs. The findings presented in this study indicate that Tasmanian emergency departments are not consistently ‘Choosing Wisely’ when investigating PE. Further research is required to identify explanations for these findings.

The work presented in this paper deals with a proactive network monitoring for security and protection of computing infrastructures. We provide an exploitation of an intelligent module, in the form of a as a machine learning application using deep learning modeling, in order to enhance functionality of intrusion detection system supervising network traffic flows. Currently, intrusion detection systems work well for network monitoring in near real-time and they effectively deal with threats in a reactive way. Deep learning is the emerging generation of artificial intelligence techniques and one of the most promising candidates for intelligence integration into traditional solutions leading to quality improvement of the original solutions. The work presented in this paper faces the challenge of cooperation between deep learning techniques and large-scale data processing. The outcomes obtained from extensive and careful experiments show the applicability and feasibility of simultaneously modelled multiple monitoring channels using deep learning techniques. The proper joining of deep learning modelling with scalable data preprocessing ensures high quality and stability of model performance in dynamic and fast-changing environments such as network traffic flow monitoring.

In this paper we propose a distributed architecture to provide machine learning practitioners with a set of tools and cloud services that cover the whole machine learning development cycle: ranging from the models creation, training, validation and testing to the models serving as a service, sharing and publication. In such respect, the DEEP-Hybrid-DataCloud framework allows transparent access to existing e-Infrastructures, effectively exploiting distributed resources for the most compute-intensive tasks coming from the machine learning development cycle. Moreover, it provides scientists with a set of Cloud-oriented services to make their models publicly available, by adopting a serverless architecture and a DevOps approach, allowing an easy share, publish and deploy of the developed models.

[This corrects the article DOI: 10.1371/journal.pone.0251194.].

The study presented in this work deals with environmental and compute-intensive applications and their operational management aimed to achieve maximum effectiveness on high-performance systems. These applications, mainly compute-intensive modeling and simulations, are often required to deliver accurate forecasts having far-reaching effects on many facets of our society. The extreme growing amounts of observational data, along with remarkable advances in computing power and technology significantly improve the ability to model and simulate challenging issues. However, it is well known that designing, implementing as well as deploying such high-fidelity applications intended for running on compute systems is still time-consuming and challenging work for domain experts. In this study, we show that it is a systematic process requiring an expertise and skills in the scientific domain of interest, mathematics, and computer science. The study outcomes present and analyze successful benefits of high computational power for compute-intensive applications especially in the environmental domain.

This dataset complement a previously published dataset [1] and corresponds to the physico-chemical parameters data series produced during the MESOLAC experimental project [2]. The presented dataset is composed of: 1. In situ profiles (0–3m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation). 2. In situ measurements of light spectral UV/VIS/IR irradiance (300–950 nm wavelength range) taken at 0, 0.25, 0.5, 1, 1.5, 2 and 2.5m. 3. Laboratory chemical analysis of samples collected at 0 and 2 m (conductivity, pH, total alkalinity, NH4, NO2, NO3, total and particulate nitrogen (Ntot, Npart), PO4, total and particulate phosphorus (Ptot, Ppart), total, organic particulate and total particulate carbon (Ctot, Cpart-org, Cpart-tot), Cl, SO4, SiO2. 4. Laboratory analysis of pigments extracted from samples collected at 0 and 2 m (Chla, Chlc, carotenoids, phaeopigments).The experimental design is the same as in Tran-Khac et al [1]. Briefly, it consisted of nine pelagic mesocosms (about 3000 L, 3m depth) deployed in July 2019 in Lake Geneva near the shore of Thonon les Bains (France) aiming to simulate predicted climate scenarios (i.e. extreme events) and assess the response of planktonic communities, ecosystem functioning and resilience.During the experiment, physical parameters were measured twice a week. At the same time, samples were collected at 0 and 2m of depth for subsequent chemical laboratory analyses. These data are presented in the dataset file, ordered by sampling event (numbered from S1 to S8), treatment (Control-C, High-H and Medium-M) and replicates (1 to 3). For each sampling point the measured parameters are listed in columns, missing data and values below the detection limit are marked as NA (not available).This data set aims to contribute to the understanding of the effect of environmental forcing on lake physico-chemical characteristics (such as temperature, oxygen and nutrient concentration) under simulated intense weather events. To a broader extent, the presented data can be used for a wide variety of applications, including monitoring of a large peri-alpine lake functioning under environmental stress and being included in further meta-analysis to generalise the effect of climate change on large lakes. The two complementary dataset differ in the acquired data and methods, temporal and spatial resolution. They complete each other in terms of physico-chemical characterization of the experimental treatments and together can allow comparison of the two different monitoring strategies (continuous vs punctual) during in situ experimental manipulations.

Computational reproducibility is a corner stone for sound and credible research. Especially in complex statistical analyses-such as the analysis of longitudinal data-reproducing results is far from simple, especially if no source code is available. In this work we aimed to reproduce analyses of longitudinal data of 11 articles published in PLOS ONE. Inclusion criteria were the availability of data and author consent. We investigated the types of methods and software used and whether we were able to reproduce the data analysis using open source software. Most articles provided overview tables and simple visualisations. Generalised Estimating Equations (GEEs) were the most popular statistical models among the selected articles. Only one article used open source software and only one published part of the analysis code. Replication was difficult in most cases and required reverse engineering of results or contacting the authors. For three articles we were not able to reproduce the results, for another two only parts of them. For all but two articles we had to contact the authors to be able to reproduce the results. Our main learning is that reproducing papers is difficult if no code is supplied and leads to a high burden for those conducting the reproductions. Open data policies in journals are good, but to truly boost reproducibility we suggest adding open code policies.

The objective of the study is to identify the characteristics of school administrators, teachers, and students in the 4.0 educational context. The study used research method from a qualitative perspective, using a basic qualitative research model. The study participants consisted of 10 lecturers selected according to the snowball method. The study data were collected through a semi-structured interview. Content analysis techniques will be used to analyze the data. We hope that the Education 4.0 revolution can be realized in Vietnamese education system. As a result, open access, personal education, idea transformation, digital integration into education, open learning environments, lifelong learning, discovery education, and multidisciplinary education are the main components of educations 4.0. It has been found that the key qualities expected from the students of Education 4.0 are interpersonal skills, technology skills, study skills, and personal style. The main qualities expected from the teachers in educations 4.0 are technology skills, instructional skills, lifelong learning skills, and personal style. Finally, the main qualities expected from school administrators in Education 4.0 are instructional skills, technology skills, learning skills.

Computed tomography pulmonary angiography (CTPA) has become the most widely used technique for diagnosis or exclusion of a pulmonary embolism (PE). It has been suggested that overuse of this imaging type may be prevalent, especially in emergency departments (EDs). The purpose of this literature review was to explore the use of CTPAs in EDs worldwide. A review following PRISMA guidelines was completed, with research published between September 2010 and August 2020 included. Five key topics emerged: use of CTPAs; explanations for overuse; use of D-dimer; variability in ordering practices between clinicians; and strategies to reduce overuse. This review found that CTPAs continue to be overused in EDs, leading to superfluous risks to patients. Published studies identify that while clinical practice guidelines (CPGs) have a strong effect on reducing unnecessary CTPAs with no significantly increased risk of missed diagnosis, the adoption of these tools by ED clinicians has remained low. This literature review highlights the need for further research into why CTPAs continue to be overused within EDs and why clinicians are hesitant to use CPGs in the clinical setting. Moreover, investigations into other potential strategies that may combat the overuse of this diagnostic tool are essential to reduce potential harm.

This dataset corresponds to a data series produced from automated data loggers during the MESOLAC experimental project. Nine pelagic mesocosms (about 3000 L, 3 m depth) were deployed in July 2019 in Lake Geneva near the shore of Thonon les Bains (France), simulating predicted climate scenarios (i.e. intense weather events) by applying a combination of forcing. The design consisted of three treatments each replicated three times: a control treatment (named C – no treatment applied) and two different treatments simulating different intensities of weather events. The high intensity treatment (named H) aimed to reproduce short and intense weather events such as violent storms. It consisted of a short-term stress applied during the first week, with high pulse of dissolved organic carbon (5x increased concentration, i.e. total DOC ∼ 6 mg L−1), transmitted light reduced to 15% and water column manual mixing. The medium intensity treatment (named M) simulated less intense and more prolonged exposures such as during flood events. It was maintained during the 4 weeks of the experiment and consisted of 1.5x increased concentration of dissolved organic carbon (i.e. total DOC ∼ 2 mg L−1), 70% transmitted light and water column manual mixing. Automated data loggers were placed for the entire period of the experiment in the mesocosms and in the lake for comparison with natural conditions. Temperature, conductivity, dissolved oxygen and CO2 were monitored every 15 min at different depths (0.15, 0.25, 1 and 2 m).This data set aims to contribute our understanding of the effect of environmental forcing on lake ecosystem processes (such as production, respiration and CO2 exchange) under simulated intense weather events and the ability of the planktonic community to recover after perturbation. To a broader extent, the presented data can be used for a wide variety of applications, including monitoring of lake community functioning during a period of high productivity on a large peri-alpine lake and being included in further meta-analysis aiming at generalising the effect of climate change on large lakes.

Background: Hypertension (HTN) significantly contributes to global disease burden, and its prevalence varies amongst different countries and regions. This work is aimed to characterize the hypertensive prevalence and identify risk factors for HTN among the residents in five locations (four communes and one town) of Moc Chau district (Son La province, Vietnam). Methods: A cross-sectional study with a cross-sectional methodology was done in selected places from August 2018 to December 2018. We interviewed 197 participants aged equal to or more than 18 years old and measured their blood pressure (BP). Univariate and multivariate logistic regression were applied. Results: The overall HTN prevalence of 30.0% was recorded. The differences of HTN prevalence rates were seen by several characters including age groups (p

Lakes are essential ecosystems that provide a large number of ecosystem services whose quality is strongly impacted by human pressures. Optimal uses of lakes require adapted management practices which in turn rely on physico-chemical and biological monitoring. Long-term ecological monitoring provides large sets of environmental data. When such data are available, they have to be associated to metadata and to be stored properly to be accessible and useable by the scientific community. We present a data informatics system accessible to anyone who requests it. Maintained online since 2014 (https://si-ola.inrae.fr), it is originated from the Observatory on LAkes (OLA). It contains long-term data from 4 peri-alpine lakes (Lakes Aiguebelette, Annecy, Bourget, Geneva/Léman) and 24 high-altitude lakes of the northern French Alps. We describe the generated long-term data series, the data type, the methodologies and quality control procedures, and the information system where data are made accessible. Data use is allowed under the condition of providing reference to the original source. We show here how such a platform clearly enhances data sharing and scientific collaboration. Various studies referring to these data are regularly published in peer-reviewed journals; providing in fine a better understanding of lakes’ ecosystems functioning under local and global pressures.

Summary: Junctophilin-2 (JPH2) is a structural calcium (Ca2+) handling protein, which approximates the cardiomyocyte transverse tubules (TTs) to the sarcoplasmic reticulum. This facilitates communication of the voltage-gated Ca2+ channel and the ryanodine receptor RyR2. A human patient with hypertrophic cardiomyopathy was positive for a JPH2 mutation substituting alanine-405âlocated within the alpha helix domainâwith a serine (A405S). Using a novel mouse echocardiography plane, we found that mice bearing this JPH2 mutation developed increased subvalvular septal thickness. Cardiomyocytes from the septa of these mice displayed irregular TTs and abnormal Ca2+ handling including increased SERCA activity. Key Words: calcium, hypertrophic cardiomyopathy, junctophilin-2, magnetic resonance imaging

Scientific research is the important task of lecturers in universities. However, university lecturers often struggle to balance research and teaching and focus more on teaching than research. In addition, the motivation for lecturers to do research is a little. This article surveys lecturers at some universities in Vietnam to find the factors that motivate lecturers to do science. The motivating factors include intrinsic factors (creativity, passion…), extrinsic factors (financial, promotion ..), and barriers to the scientific research activities of lecturers. Research results show that intrinsic and extrinsic factors positively impact the scientific research activities of lecturers, and the barrier factors negatively affect the research activities of lectures. Based on the research results, the authors make some suggestions to strengthen further the research activities of lecturers at universities in Vietnam.

Flood forecasting using numerical weather models is a computationally-intensive and complex task requiring cooperation of many experts in different areas. To enable this cooperation in a comfortable way, a part of the CrossGrid project is aimed towards developing a flood-forecasting, Grid-based environment. This Problem Solving Environment (PSE) consists mainly of a set of coupled simulation models, a storage system for configuration files, model codes and datasets, a WWW portal with collaboration tools and a powerful Computational Grid, provided by the partners in the CrossGrid project. This paper describes prototype of this PSE, targeting mainly the copled simulation models (simulation cascade), the portal and the Virtual Organization supposed to use the system.

We present one of the meteorological and hydrological experiments performed inthe FP7 project ADMIRE. It serves as an experimental platform for hydrologists,and we have used it also as a testing platform for a suite of advanced dataintegration and data mining (DMI) tools, developed within ADMIRE. The ideaof ADMIRE is to develop an advanced DMI platform accessible even to userswho are not familiar with data mining techniques. To this end, we have designeda novel DMI architecture, supported by a set of software tools, managed by DMIprocess descriptions written in a specialized high-level DMI language calledDISPEL, and controlled via several different user interfaces, each performinga different set of tasks and targeting different user group.

Background After nearly a decade, Vietnam’s basic midwifery competency standards need to be updated to effectively implement midwives, enhance the quality of midwifery human resources to meet the requirements of integration of countries in the region and around the world. This study aims to develop the competency standards for midwifery in Vietnam by using a Delphi process. Methods The draft midwifery competency standard was initially developed based on a literature review. Midwives and professionals working with midwives completed a two-round Delphi survey to evaluate the relevance of standards of competence on a four-point Likert scale. The criteria with consensus of under 80% were revised and included in the second round. 75 participants were in the first round and 72 participants were in the second round. Phase 3 was led by the Ministry of Health to finalize the consensus on the midwifery competency standards in Vietnam. Results The research results indicated that midwifery competency was mostly rated as quite relevant or higher (over 80%). Some standards were removed, and some were included in the second round of the Delphi process. The final competency standards were issued with 4 areas (midwifery professional practice; care management; midwifery management; professional development), 11 standards and 44 criteria; along with the general skills of midwifery. Conclusions The study developed a midwifery competency standard in Vietnam. These competency standards are consistent with the perceptions of the International Confederation of Midwives and the domestic midwifery context. The higher education institutions, employers, policy makers and midwives themselves benefit from this developed midwifery competency standards. Future research needs to be conducted to validate midwifery competency standards in clinical settings for further responses.

In this paper, we will present an abstraction layer for cloud computing, which intends to simplify the manipulation with virtual machines in clouds for easy and controlled development and deployment of cloud services. It also ensures interoperability between different cloud infrastructures and allows developers to create cloud appliances easily via inheritance mechanisms.

We present one of the meteorological and hydrological experiments performed in the FP7 project ADMIRE. It serves as an experimental platform for hydrologists, and we have used it also as a testing platform for a suite of advanced data integration and data mining (DMI) tools, developed within ADMIRE. The idea of ADMIRE is to develop an advanced DMI platform accessible even to users who are not familiar with data mining techniques. To this end, we have designed a novel DMI architecture, supported by a set of software tools, managed by DMI process descriptions written in a specialized high-level DMI language called DISPEL, and controlled via several different user interfaces, each performing a different set of tasks and targeting different user group.

Background: After nearly a decade, Vietnam’s basic midwifery competency standards need to be updated to effectively implement midwives, enhance the quality of midwifery human resources to meet the requirements of integration of countries in the region and around the world. This study aims to develop the competency standards for midwifery in Vietnam by using a Delphi process. Methods: The draft midwifery competency standard was initially developed based on a literature review. Midwives and professionals working with midwives completed a two-round Delphi survey to evaluate the relevance of standards of competence on a four-point Likert scale. The criteria with consensus of under 80% were revised and included in the second round. 75 participants were in the first round and 72 participants were in the second round. Phase 3 was led by the Ministry of Health to finalize the consensus on the midwifery competency standards in Vietnam. Results: The research results indicated that midwifery competency was mostly rated as quite relevant or higher (over 80%). Some standards were removed, and some were included in the second round of the Delphi process. The final competency standards were issued with 4 areas (midwifery professional practice; care management; midwifery management; professional development), 11 standards and 44 criteria; along with the general skills of midwifery. Conclusions: The study developed a midwifery competency standard in Vietnam. These competency standards are consistent with the perceptions of the International Confederation of Midwives and the domestic midwifery context. The higher education institutions, employers, policy makers and midwives themselves benefit from this developed midwifery competency standards. Future research needs to be conducted to validate midwifery competency standards in clinical settings for further responses.