Enhancing Amplification in Compliant Mechanisms: Optimization of Plastic Types and Injection Conditions.

This study surveys the impacts of injection parameters on the deformation rate of the injected flexure hinge made from ABS, PP, and HDPE. The flexure hinges are generated with different filling time, filling pressure, filling speed, packing time, packing pressure, cooling time, and melt temperature. The amplification ratio of the samples between different injection parameters and different plastic types is measured and compared to figure out the optimal one with a high amplification ratio. The results show that the relationship between the input and output data of the ABS, PP, and HDPE flexure hinges at different injection molding parameters is a linear relation. Changing the material or many injection molding parameters of the hinge could lead to a great impact on the hinge's performance. However, changing each parameter does not lead to a sudden change in the input and output values. Each plastic material has different optimal injection parameters and displacement behaviors. With the ABS flexure hinge, the filling pressure case has the greatest amplification ratio of 8.81, while the filling speed case has the lowest value of 4.81. With the optimal injection parameter and the input value of 105 µm, the ABS flexure hinge could create a maximum average output value of 736.6 µm. With the PP flexure hinge, the melt temperature case achieves the greatest amplification ratio of 6.73, while the filling speed case has the lowest value of 4.1. With the optimal injection parameter and the input value of 128 µm, the PP flexure hinge could create a maximum average output value of 964.8 µm. The average amplification ratio values of all injection molding parameters are 6.85, 5.41, and 4.01, corresponding to ABS, PP, and HDPE flexure hinges. Generally, the ABS flexure hinge has the highest amplification ratios, followed by the PP flexure hinge. The HDPE flexure hinge has the lowest amplification ratios among these plastic types. With the optimal injection parameter and the input value of 218 µm, the HDPE flexure hinge could create a maximum average output value of 699.8 µm. The results provide more insight into plastic flexure hinges and broaden their applications by finding the optimal injection parameters and plastic types.

MXene nanosheet-derived N, S-codoped graphene quantum dots for ultrasensitive and selective detection of 3-nitro-l-tyrosine in human serum.

3-Nitro-l-tyrosine (3NT) is an oxidative stress metabolite associated with neurodegenerative diseases such as Parkinson's disease and rheumatoid arthritis. In this study, the N, S-co-doped graphene quantum dots (NSGQDs) derived from nitrogen-doped Ti3C2Tx MXene nanosheet via the hydrothermal method in the presence of mercaptosuccinic acid was synthesized as an optical sensing probe to detect 3NT in human serum. Tetramethyl ammonium hydroxide, the nitrogen source and delamination agent, was used to prepare nitrogen-doped MXene nanosheets via one step at room temperature. The as-prepared NSGQDs are uniform with an average size of 1.2 ± 0.6 nm, and can be stable in aqueous solution for at least 90 d to serve as the fluorescence probe. The N atoms in N-MXene reduce the restacking and aggregation of MXene nanosheets, while the sulfur dopant in NSGQDs increases the quantum yield from 6.2 to 12.1 % as well as enhances the selectivity of 3NT over the other 12 interferences via coordination interaction with nitro group in 3NT. A linear range of 0.02-150 µM in PBS and 0.05-200 µM in human serum with a recovery of 97-108 % for 3NT detection is observed. Moreover, the limit of detection can be lowered to 4.2 and 7 nM in PBS and 1 × diluted human serum, respectively. Results obtained clearly indicate the potential application of the N-Ti3C2Tx derived NSGQD for effective detection of 3NT, which can open a window for the synthesis of doped GQDs via 2D MXene materials for ultrasensitive and selective detection of other biometabolites and biomarkers of neurodegenerative diseases in biological fluids.

Five undescribed aryltetralin lignans with cytotoxic activities from the fruits of Cleistanthus eberhardtii.

Five undescribed lignans, cleiseberharnins A-D (1-4), cleiseberharside A (5) were isolated from the fruits of Cleistanthus eberhartii (Phyllanthaceae), together with six known aryltetralin lignans, cleistantoxin (6), picroburseranin (7), neocleistantoxin (8), 7-hydroxypicropolygamain (9), cleisindoside D (10), and cleisindoside A (11). Their structures and relative configurations were established by analysis of HRESIMS and NMR data, and quantum chemical calculations of JH,H coupling constants. The absolute configurations of 1-5 were determined by analysis of their experimental CD spectra and comparison with calculated electronic circular dichroism (ECD) spectra. All compounds (1-11) were evaluated for their cytotoxicity against KB, MCF-7, HepG-2, and Lu-1 human cancer cell lines. Among the tested compounds, compounds 6 and 7 showed strong activity against KB, MCF7, HepG2 and Lu-1 cell lines with IC50 values in the range of 0.02-0.62 µM. Compound 1 showed activity against three cancer cell lines KB, HepG2, and Lu-1 with IC50 values of 6.98, 7.61 and 11.75 µM, respectively. Compound 2 exhibited a selective inhibition with moderate cytotoxicity against Lu-1 with IC50 value of 15.30 µM. Compounds 4, 5 and 9 showed moderate activity against the three cancer cell lines with IC50 values in the range of 8.73-19.70 µM.

Weld Line Strength of Polyamide Fiberglass Composite at Different Processing Parameters in Injection Molding Technique.

This study examines the impact of injection parameters on the weld line strength of the polyamide 6 and 30% fiberglass (PA6 + 30% FG) composite samples. The effects of filling time, packing time, packing pressure, melt temperature, and mold temperature on the ultimate tensile strength (UTS) and the elongation value of the weld line are investigated. The results reveal that the filling time factor has the lowest influence rate. On the contrary, the packing pressure has the most considerable value of UTS standard deviation, indicating that this factor has a high impact rate. The melt temperature factor has the highest elongation standard deviation, pointing out the strong impact of melt temperature on the elongation value. In reverse, the filling time factor has the lowest elongation standard deviation, showing the low impact of this factor on the elongation value. Increasing the mold temperature enhances the elongation value greatly because a higher temperature generates a better connection in the weld line area. Although the UTS value improves modestly when the mold temperature control system is used, the elongation result from the mold temperature parameter is better than expected. The UTS result from all parameters presents a minor deviation; therefore, it is lower than expected. The optimal strength result from artificial neural networks with genetic algorithm optimization is 85.1 MPa, which is higher than the best experiment result of 76.8 MPa. Scanning electron microscopy (SEM) results show that the interface between the fiberglass and the PA matrix has high adherence. The fracture surface is smooth, indicating that the PA6 + 30% FG composite sample has a high fragility level. The findings could help to increase the injection sample's weld line strength by optimizing the injection molding conditions.

Predicting Antibiotic Resistance in ICUs Patients by Applying Machine Learning in Vietnam.

Introduction: Artificial Intelligence (AI) and machine learning (ML) are used extensively in HICs to detect and control antibiotic resistance (AMR) in laboratories and clinical institutions. ML is designed to predict outcome variables using an algorithm to enable "machines" to learn the "rules" from the data. ML is increasingly being applied in intensive care units to identify AMR and to assist empiric antibiotic therapy. This study aimed to evaluate the performance of ML models for predicting AMR bacteria and resistance to antibiotics in two Vietnamese hospitals. Patients and Methods: A cross-sectional study combined with retrospective was conducted from 1st January 2020 to 30th June 2022. Five models were developed to predict antibiotic resistance of bacterial infections of ICU patients. Two datasets were prepared to predict AMR bacteria and antibiotics with ML models. The performance of the prediction models was evaluated by various indicators (sensitivity, specificity, precision, accuracy, F1-score, PRC, AuROC, and NormMCC) to determine the optimal time point for data selection. Python version 3.8 was used for statistical analyses. Results: The accuracy, F1-score, AuROC, and normMMC of LightGBM, XGBoost, and Random Forest models were higher than those of other models in both datasets. In both datasets 1 and 2, accuracy, F1-score, AuROC and normMCC of the XGBoost model were the highest among five models (from 0.890 to 1.000). Only Random Forest models had specificity scores higher than 0.850. High scores of sensitivity, accuracy, precision, F1-score, and normMCC indicated that the models were making accurate predictions for datasets 1 and 2. Conclusion: XGBoost, LightGBM, and Random Forest were the best-performed machine learning models to predict antibiotic resistance of bacterial infections of ICUs patients using the patients' EMRs.

Trajectory Strategy Effects on the Material Characteristics in the WAAM Technique.

The wire Arc Additive Manufacturing (WAAM) technique has evolved into a cutting-edge 3D printing technique. This study surveys the influences of trajectory on the characteristics of low-carbon steel samples generated by the WAAM technique. The results show that the grains in the WAAM samples are isotropic, with grain size numbers ranging from 7 to 12. Strategy 3, with a spiral trajectory, has the smallest grain size, while strategy 2, with a lean zigzag trajectory, has the largest. The variations in grain size are caused by differences in heat input and output during the printing process. The WAAM samples achieve a significantly higher UTS value than the original wire, demonstrating the WAAM technique's benefit. Strategy 3, with a spiral trajectory, achieves the highest UTS value, 616.5 MPa, 24% higher than the original wire. The UTS values of strategy 1 (horizontal zigzag trajectory) and strategy 4 (curve zigzag trajectory) are comparable. WAAM samples have significantly higher elongation values than the original wire, with only 22% elongation. The sample with the highest elongation value, 47.2%, was produced by strategy 3. Strategy 2 has an elongation value of 37.9%. The value of elongation is proportional to the value of UTS. WAAM samples have average elastic modulus values of 95.8 GPa, 173.3 GPa, 92.2 GPa, and 83.9 GPa, corresponding to strategies 1, 2, 3, and 4. Only a strategy 2 sample has a similar elastic modulus value to the original wire. All samples have dimples on the fracture surface, indicating that the WAAM samples are ductile. These fracture surfaces' equiaxial shape corresponds to the original microstructure's equiaxial shape. The results provide the optimal trajectory for the WAAM products is the spiral trajectory, while the lean zigzag trajectory gains only modest characteristics.

Conformal Cooling Channel Design for Improving Temperature Distribution on the Cavity Surface in the Injection Molding Process.

Mold heating is an essential process in plastic injection molding. Raising the temperature of the mold before injecting liquefied plastic can ease the mold-filling process. A cooling channel can be used to transport high-temperature fluids for this purpose, such as hot water or oil. This dual purpose is a cost-effective solution for heating the mold because the target temperature is easily achieved using this method. In addition, a conformal cooling channel (CCC) can provide more efficient mold heating than a straight cooling channel. This study used the response surface methodology to determine the optimum CCC shape for heat distribution in a mold, and the simulation results confirmed its optimization. The average temperature of the mold using a CCC was better than that using a straight cooling channel, and the heat zone was uniform across the mold surface.

Enhancing the Fatigue Strength of the Weld Line in Advanced Polymer Injection Molding: Gas-Assisted Mold Temperature Control for Thermoplastic Polyurethane (TPU) Composites.

This study presents an innovative approach to enhancing weld line strength in advanced polymer injection molding through applying gas-assisted mold temperature control, significantly increasing mold temperature beyond typical values observed in conventional processes. We investigate the effects of various heating times and frequencies on the fatigue strength of Polypropylene (PP) samples and the tensile strength of Acrylonitrile Butadiene Styrene (ABS) composite samples at different Thermoplastic Polyurethane (TPU) percentages and heating times. Using gas-assisted mold heating, mold temperatures exceeding 210 °C are achieved, which represents a significant advancement compared to the standard mold temperatures of less than 100 °C. As a result, the fatigue strength of the PP sample with mold heating at 15 s shows a remarkable increase of up to 5.4 times at 5 Hz compared to the sample without mold temperature control. Moreover, ABS/TPU blends with 15 wt.% TPU exhibit the highest ultimate tensile strength (UTS) value of 36.8 MPa, while blends with 30 wt.% TPU have the lowest UTS value of 21.3 MPa. This advancement demonstrates the potential for improved welding line bonding and fatigue strength in manufacturing. Our findings reveal that increasing the mold temperature before injection results in higher fatigue strength in the weld line, with the TPU percentage having a more significant influence on the mechanical properties of ABS/TPU blends than heating time. The results of this study contribute to a deeper understanding of advanced polymer injection molding and offer valuable insights for process optimization.

Influences of TPU Content on the Weld Line Characteristics of PP and ABS Blends.

This study aims to explore the effects of Thermoplastic Polyurethane (TPU) content on the weld line properties of Polypropylene (PP) and Acrylonitrile Butadiene Styrene (ABS) blends. In PP/TPU blends, increasing the TPU content results in a significant decrease in the PP/TPU composite's ultimate tensile strength (UTS) and elongation values. Blends with 10 wt%, 15 wt%, and 20 wt% TPU and pure PP outperform blends with 10 wt%, 15 wt%, and 20 wt% TPU and recycled PP in terms of UTS value. The blend with 10 wt% TPU and pure PP achieves the highest UTS value of 21.85 MPa. However, the blend's elongation decreases due to the poor bonding in the weld line area. According to Taguchi's analysis, the TPU factor has a more significant overall influence on the mechanical properties of PP/TPU blends than the recycled PP factor. Scanning electron microscope (SEM) results show that the TPU area has a dimple shape on the fracture surface due to its significantly higher elongation value. The 15 wt% TPU sample achieves the highest UTS value of 35.7 MPa in ABS/TPU blends, which is considerably higher than other cases, indicating good compatibility between ABS and TPU. The sample containing 20 wt% TPU has the lowest UTS value of 21.2 MPa. Furthermore, the elongation-changing pattern corresponds to the UTS value. Interestingly, SEM results present that the fracture surface of this blend is flatter than the PP/TPU blend due to a higher compatibility rate. The 30 wt% TPU sample has a higher rate of dimple area than the 10 wt% TPU sample. Moreover, ABS/TPU blends gain a higher UTS value than PP/TPU blends. Increasing the TPU ratio mainly reduces the elastic modulus of both ABS/TPU blends and PP/TPU blends. This study reveals the advantages and disadvantages of mixing TPU with PP or ABS to ensure that it meets the requirements of the intended applications.

Changes in QT Interval in Maintenance Hemodialysis Patients: Pre-Dialysis, One Hour after Initiation of Dialysis, and Post-Dialysis.

INTRODUCTION: This study aimed to evaluate the effects of dialysis on change of QT interval in pre-dialysis, 1 h after dialysis initiation, and post-dialysis period in patients on maintenance dialysis (MHD). METHODS: An observational prospective study was conducted, including 61 patients, on thrice-weekly MHD ≥3 months, and without acute diseases, at the Nephrology-Dialysis Department of a tertiary hospital in Vietnam. The exclusive criteria were atrial fibrillation, atrial flutter, branch block, prolonged QT recorded in medical history, and taking antiarrhythmic drugs lengthening QT interval before entering the study. Twelve-lead electrocardiographs and blood chemistries were done simultaneously before, 1 h after initiation, and after the dialysis session. RESULTS: The proportion of patients with prolonged QT interval increased significantly from 44.3% in pre-dialysis to 77% 1 h after dialysis initiation and 86.9% in post-dialysis session. Immediately after dialysis, the QT and QTc intervals on all 12 leads were significantly longer. Post-dialysis levels of potassium, chloride, magnesium, and urea decreased significantly from 3.97 (0.7), 98.6 (4.7), 1.04 (0.2), and 21.4 (6.1) to 2.78 (0.4), 96.6 (2.5), 0.87 (0.2), and 6.33 (2.8) mmol/L, respectively, whereas the calcium increased significantly from 2.19 (0.2) to 2.57 (0.2) mmol/L. There were significant differences in the potassium level at the dialysis initiation and its speed of reduction between the group without and with prolonged QT interval. CONCLUSIONS: There was an increased risk of prolonged QT interval in MHD patients regardless of the absence of the previous abnormal QT interval. Notably, this risk increased rapidly 1 h after the initiation of dialysis.

Influences of Material Selection, Infill Ratio, and Layer Height in the 3D Printing Cavity Process on the Surface Roughness of Printed Patterns and Casted Products in Investment Casting.

As 3D-printed (3DP) patterns are solid and durable, they can be used to create thin wall castings, which is complicated with wax patterns because of the wax's fragility and high shrinkage ratio. According to this study's experiment results, polylactic acid (PLA), polyvinyl butyral (PVB), and castable wax (CW) are suitable materials for preparing investment casting (IC) cavities. The results indicate that the casting product with the highest-quality surface is obtained using a cavity prepared using a CW-printed pattern. PLA- and PVB-printed patterns provide a good surface finish for casted products. In addition, the roughness of both the printed and casted surfaces increases as the printing layer height increases. The roughness of the casted surface varies from 2.25 µm to 29.17 µm. This investigation also considers the correlation between the infill ratio and mechanical properties of PLA-printed patterns. An increase in the infill ratios from 0% to 100% leads to a significant increase in the tensile properties of the PLA-printed pattern. The obtained results can be practically used.

3D hierarchical cobalt vanadate nanosheet arrays on Ni foam coupled with redox additive for enhanced supercapacitor performance.

Room-temperature synthesized 3D hierarchical cobalt vanadate (Co3V2O8) nanosheet arrays on Ni foam for use as supercapacitor electrode is presented. In a 3 M KOH electrolyte, the electrode exhibits a capacitance of 109.9 mA h g-1 (878.9 F g-1) at a current density of 1 A g-1. The capacitance is enhanced to 198.1 mA h g-1 (1584.5 F g-1) at 1 A g-1 through the addition of 0.05 M redox-additive K3[Fe(CN)6] into the KOH electrolyte. Furthermore, the Co3V2O8/activated carbon asymmetric supercapacitor cell with the advanced electrolyte outperforms most reported Co3V2O8-based electrodes with a remarkable energy density of 55.5 W h kg-1 at an 800 W kg-1 power density. Combining a facile synthetic strategy and excellent electrochemical performance, the obtained Co3V2O8 exhibits potential for practical application.

Study on the Fatigue Strength of Welding Line in Injection Molding Products under Different Tensile Conditions.

The fatigue performance of polypropylene (PP) at various amplitudes and frequencies on fatigue cycles under tensile test conditions is investigated in this study. The results show that increasing the frequency leads to a decrease in fatigue cycles due to increased cycle time. The decline rate can be divided into two stages, between 1 and 5 Hz. The first stage rapidly decreases fatigue performance as the frequency increases from 1 Hz to 2 Hz or 3 Hz. The second stage has a lower reduction rate, which occurs between 2 Hz or 3 Hz and 5 Hz due to the strengthening effect of increasing frequency. Furthermore, increasing the amplitude from 0.1 mm to 0.4 mm reduces the fatigue cycle due to the higher deformation rate. In summary, expanding both amplitude and frequency reduces the fatigue performance of the PP material. Moreover, according to the scanning electron microscope microstructure, increasing the frequency results in more microcracks in the polymer matrix.

Metal complexes of benzimidazole-derived as potential anti-cancer agents: synthesis, characterization, combined experimental and computational studies.

In this study, a series of 14 Cu (II), Zn (II), Ni (II) and Ag (I) complexes containing bis-benzimidazole derivatives were successfully designed and synthesized from 2-(1H-benzimidazole-2-yl)-phenol derivatives and corresponding metal salt solutions. The compound structures were identified by FT-IR, 1H-NMR, powder X-ray diffraction and ESI-MS analyses, and the presence of the metal in the complexes was confirmed by ultraviolet-visible spectroscopy and ICP optical emission spectrometry. Electronic structure calculations were also carried out to describe the detailed structures in addition to the electronic absorption spectra of the ligands. The cytotoxic activity of the complexes was evaluated against three human cancer cell lines: lung (A549), breast (MDA-MB-231) and prostate (PC3) cancer cells. All complexes inhibited anti-proliferative cancer cells better than free ligands, especially Zn (II) and Ag (I) complexes, which are most sensitive to MDA-MB-231 cells. In addition, showing the growth inhibition of three cancer cell lines with IC50 < 10.4 µM, complexes C1 , C3 and C14 could be considered potential multi-targeted anti-cancer agents.

CFD Analysis and Optimum Design for a Centrifugal Pump Using an Effectively Artificial Intelligent Algorithm.

In this study, we proposed a novel approach to improve centrifugal pump performance with regard to the pump head, pump efficiency, and power. Firstly, to establish constraints, an optimal numerical model that accounted for factors such as pump efficiency and the head was considered. The pump was designed, and an artificial intelligence algorithmic approach was applied to the pump before performing experiments. We considered a set of models by selecting the parameters of the centrifugal pump casing section area, the interference of the impeller, the volute tongue length, and the volute tongue angle. The weights of the factors of safety and displacement on the optimization indices were estimated. The matrix of the weights for the optimal process was less than 38% or greater than 62%. This approach guarantees a complicated multi-objective optimization problem. The results show that the centrifugal pump performances were improved.

Regulatory Crosstalk between Physiological Low O2 Concentration and Notch Pathway in Early Erythropoiesis.

Physiological low oxygen (O2) concentration (<5%) favors erythroid development ex vivo. It is known that low O2 concentration, via the stabilization of hypoxia-induced transcription factors (HIFs), intervenes with Notch signaling in the control of cell fate. In addition, Notch activation is implicated in the regulation of erythroid differentiation. We test here if the favorable effects of a physiological O2 concentration (3%) on the amplification of erythroid progenitors implies a cooperation between HIFs and the Notch pathway. To this end, we utilized a model of early erythropoiesis ex vivo generated from cord blood CD34+ cells transduced with shHIF1α and shHIF2α at 3% O2 and 20% O2 in the presence or absence of the Notch pathway inhibitor. We observed that Notch signalization was activated by Notch2R−Jagged1 ligand interaction among progenitors. The inhibition of the Notch pathway provoked a modest reduction in erythroid cell expansion and promoted erythroid differentiation. ShHIF1α and particularly shHIF2α strongly impaired erythroid progenitors' amplification and differentiation. Additionally, HIF/NOTCH signaling intersects at the level of multipotent progenitor erythroid commitment and amplification of BFU-E. In that, both HIFs contribute to the expression of Notch2R and Notch target gene HES1. Our study shows that HIF, particularly HIF2, has a determining role in the early erythroid development program, which includes Notch signaling.

Emission factors for Vietnamese beef cattle manure sun-drying and the effects of drying on manure microbial community.

Livestock manure and its management are significant sources of greenhouse gas (GHG). In most Southeast Asian countries, the current GHG emissions are estimated by the Intergovernmental Panel on Climate Change (IPCC) Tier 1 approach using default emission factors. Sun-drying is the dominant manure treatment in Vietnam, and in this study, we measured GHG emissions during manure drying using a chamber-based approach. Results show the emission factors for CH4 and N2O were 0.295 ± 0.078 g kg-1 volatile solids (VS) and 0.132 ± 0.136 g N2O-N kg-1 Ninitial, respectively. We monitored the total bacterial/archaeal community using 16S rRNA gene amplicon sequencing and measured the abundance of functional genes required for methanogenesis (mcrA), nitrification (amoA) and denitrification (nirK, nirS and nosZ) processes. Methane emission occurred only at the beginning of the drying process (days 1 to 3). The results of amplicon sequencing indicated that the relative abundance of methanogens also decreased during this period. Although some nitrification activity was detected, there was no significant N2O emission. These findings well describe the manure management system in south Vietnam and the GHG emission from this manure category, paving the way for higher Tier estimations using country-specific values.

Effects of reducing postprandial hyperglycemia and metabolism of acetate wheat starch on healthy mice

Abstract Recently, the acetate wheat starch (AWS) has been prepared by acetylation with an acetyl content of 2.42%, containing of rapidly digestible starch (RDS), slowly digestible starch (SDS) and resistant starch (RS) with 25.0%; 22.9% and 34.5%, respectively. In this study, this kind of starch was continuously evaluated with the postprandial blood glucose response and determined short-chain fatty acids (SCFAs) metabolized from AWS in the gastrointestinal tract of healthy mice by HPLC. The result showed that the mice fed with AWS exhibited a very limited increase in blood glucose level and remained stable for 2 hours after meals efficiently comparing with the control group fed with natural wheat starch (NWS). Simultaneously, the content of SCFAs produced in the caecum of the mice fed with AWS was significantly higher than mice fed with NWS, especially with acetic and propionic acids by 28% and 26%, respectively. Thus, AWS has shown to limit the postprandial hyperglycemia in mice effectively through the resistance to amylase hydrolysis in the small intestine. When going into the caecum, it is fermented to form SCFAs providing a part of energy for the body's activities, avoiding rotten fermentation causing digestive disorders which are inherent restrictions of normal high cellulose and fiber food.

Associated Factors with Perceived Fear of COVID-19 among Vietnamese Hospital Healthcare Workers during Fourth Wave of the COVID-19 Pandemic: Policy Implications for Interconnected and Social- and Personal-Based Health Support.

(1) Background: The present study measures the fear of COVID-19 among hospital healthcare workers and identifies several factors associated with increasing fear of COVID-19. (2) Methods: A cross-sectional, hospital-based survey was conducted on healthcare workforce recruited from the National Hospital of Tropical Diseases from 1 October 2021 and 20 October 2021. We selected the participants who have been directly involved in diagnosing, treating, or providing nursing care to patients with COVID-19. The primary data was collected via sending the invitation directly to the participants, utilizing structured self-completed questionnaires. The seven-item fear of COVID-19 scale was used to measure the data. The responses of 208 hospital healthcare workers were included in the final analysis. (3) Results: Total score of COVID-19 fear was 19.62 (SD = 5.22). The COVID-19 fear score of 7 items ranged from 2.38 (SD = 0.83) to 3.21 (SD = 0.96). The lowest and highest scores were the item 'My hands become clammy when I think about Corona' and the item 'I am most afraid of corona' was the highest, respectively. Linear regression of the COVID-19 fear showed that the factors positively correlated with the fear of COVID-19 among hospital healthcare workers were: being influenced by the community (p = 0.001), feeling at very high risk of COVID-19 (p = 0.03), and experiencing traumatic stress with an academic event (p = 0.042). (4) Conclusions: Although these findings merit further elaboration, these preliminary findings suggest relatively great fear of the COVID-19 pandemic among Vietnamese hospital healthcare workers and that social and personal connections are necessary for maintaining the mental wellbeing.

Optimal Design for Compliant Mechanism Flexure Hinges: Bridge-Type.

Compliant mechanisms' design aims to create a larger workspace and simple structural shapes because these mechanical systems usually have small dimensions, reduced friction, and less bending. From that request, we designed optimal bridge-type compliant mechanism flexure hinges with a high magnification ratio, low stress by using a flexure joint, and especially no friction and no bending. This joint was designed with optimal dimensions for the studied mechanism by using the method of grey relational analysis (GRA), which is based on the Taguchi method (TM), and finite element analysis (FEA). Grey relational grade (GRG) has been estimated by an artificial neural network (ANN). The optimal values were in good agreement with the predicted value of the Taguchi method and regression analysis. The finite element analysis, signal-to-noise analysis, surface plot, and analysis of variance demonstrated that the design dimensions significantly affected the equivalent stress and displacement. The optimal values of displacement were also verified by the experiment. The outcomes were in good agreement with a deviation lower than 6%. Specifically, the displacement amplification ratio was obtained as 65.36 times compared with initial design.