Childhood Acute Poisoning at Haiphong Children\u27s Hospital: A 10-Year Retrospective Study

INTRODUCTION: Children are most often harmed by acute poisoning, which may cause disability or even death. This demonstrates the critical necessity for epidemiologic studies specific to each nation and area since they aid in developing plans for the prevention of acute poisoning. There are no data or outdated data on acute poisoning in children in Vietnam. This research would partly fill this existing gap and compare the trend with other places across the globe. METHODS: A retrospective study was conducted in the 10-year period from 2012 to 2021 in Haiphong Children\u27s Hospital, Vietnam. RESULTS: There were 771 children hospitalized due to acute poisoning. Children in the 1-5-year-old group accounted for the highest rate, at 506 (65.6%). The mean age was 4.5 ± 4.1 years old. The male-to-female ratio was 1.2/1. Nonpharmaceutical chemicals were the most common agent in 331 cases (42.9%), including cleaning products 63 (19.0%), rat poison 60 (18.1%), and petrol 42 (12.7%). Medications were the second most common agent in 290 cases (37.6%), mostly paracetamol 60 (20.7%) and sedatives 40 (13.8%). There were 633 (82.1%) children exposed to poisons unintentionally. CONCLUSION: Children between the ages of 1 and 5 are more likely to be exposed to harmful substances. The most common agents were nonpharmaceutical chemicals followed by pharmaceuticals. Most incidents were inadvertent. Finally, our research may provide insights that public health authorities might use to plan practical actions

Robust Adaptive Cerebellar Model Articulation Controller for 1-DOF Nonlaminated Active Magnetic Bearings

This paper presents a robust adaptive cerebellar model articulation controller (RACMAC) for 1-DOF nonlaminated active magnetic bearings (AMBs) to achieve desired positions for the rotor using a robust sliding mode control based. The dynamic model of 1-DOF nonlaminated AMB is introduced in fractional order equations. However, it is challenging to design a controller based on the model\u27s parameters due to undefined components and external disturbances such as eddy current losses in the actuator, external disturbance, variant parameters of the model while operating. In order to tackle the problem, RACMAC, which has a cerebellar model to estimate nonlinear disturbances, is investigated to resolve this problem. Based on this estimation, a robust adaptive controller that approximates the ideal and compensation controllers is calculated. The online parameters of the neural network are adjusted using Lyapunov\u27s stability theory to ensure the stability of system. Simulation results are presented to demonstrate the effectiveness of the proposed controller.The simulation results indicate that the CMAC multiple nonlinear multiple estimators are close to the actual nonlinear disturbance value, and the effectiveness of the proposed RACMAC method compared with the FOPID and SMC controllers has been studied previously

Active disturbance rejection control-based anti-coupling method for conical magnetic bearings

Conical-shape magnetic bearings are currently a potential candidate for various magnetic force-supported applications due to their unique geometric nature reducing the number of required active magnets. However, the bearing structure places control-engineering related problems in view of underactuated and coupling phenomena. The paper proposes an Adaptive Disturbance Rejection Control (ADRC) for solving the above-mentioned problem in the conical magnetic bearing. At first, virtual current controls are identified to decouple the electrical sub-system, then the active disturbance rejection control is employed to eliminate coupling effects owing to rotational motions. Comprehensive simulations are provided to illustrate the control ability

MARITIME SECURITY POLICY OF INDIA IN EARLY 21ST CENTURY: VIETNAM’S PERCEPTION OF ITS IMPLICATION ON THE ASIA-PACIFIC REGION

Since the early 21st century, the Asia-Pacific has become a dynamic region of development by some powerful countries in the world such as the United States (US), India, China, and Russia. Thus, the issue of ensuring maritime security to develop sea trade plays a central role in the strategies of these countries. From India’s perspective, maritime security in the Indian Ocean – Pacific Ocean is a deciding factor in the development, affirming its position and creating a balance of power in the country in comparison with other countries in the region. Nevertheless, the developed sea trade of India has faced challenges from various countries including the US, and China. Therefore, India has promoted a cooperative relationship with Vietnam to guarantee maritime security for Indian traders in the region. This paper aims to provide general information about maritime security as well as to determine and estimate India’s maritime security strategies. Additionally, it will present the role of Vietnam in India’s maritime security policies. The findings show that both nations, India and Vietnam have adequate backup strategies, which is the foundation for developing sea trade sustainability. Furthermore, India and Vietnam will play an increasingly strong role in the Asia-Pacific in the future.

Liquid pumping and mixing by PZT synthetic jet

In this paper, a PZT synthetic jet that can function as both an efficient pumping and mixing device is developed. Compare with the conventional design where the practice of controlling the internal flow is undertaken by microvalves structure, this approach promotes the durability and allows the device to work with different liquids at high Reynold number without losing of backflow from the diffuser, therefore provides efficient mixing. The pumping performance is applicable for commercialized counterparts while the homogeneous medium was obtained at downstream in the experiments, which was further confirmed by simulation. Notably, the chaotic mixing feature of the device is also applicable for immiscible liquids with the micro-droplet formation result at the outlet

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

Associations of Underlying Health Conditions With Anxiety and Depression Among Outpatients: Modification Effects of Suspected COVID-19 Symptoms, Health-Related and Preventive Behaviors

Objectives: We explored the association of underlying health conditions (UHC) with depression and anxiety, and examined the modification effects of suspected COVID-19 symptoms (S-COVID-19-S), health-related behaviors (HB), and preventive behaviors (PB).Methods: A cross-sectional study was conducted on 8,291 outpatients aged 18–85 years, in 18 hospitals and health centers across Vietnam from 14th February to May 31, 2020. We collected the data regarding participant's characteristics, UHC, HB, PB, depression, and anxiety.Results: People with UHC had higher odds of depression (OR = 2.11; p < 0.001) and anxiety (OR = 2.86; p < 0.001) than those without UHC. The odds of depression and anxiety were significantly higher for those with UHC and S-COVID-19-S (p < 0.001); and were significantly lower for those had UHC and interacted with “unchanged/more” physical activity (p < 0.001), or “unchanged/more” drinking (p < 0.001 for only anxiety), or “unchanged/healthier” eating (p < 0.001), and high PB score (p < 0.001), as compared to those without UHC and without S-COVID-19-S, “never/stopped/less” physical activity, drinking, “less healthy” eating, and low PB score, respectively.Conclusion: S-COVID-19-S worsen psychological health in patients with UHC. Physical activity, drinking, healthier eating, and high PB score were protective factors

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks