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This research addresses the complex challenge of recognizing hand gestures irrespective of the user's body posture, a crucial issue in medical treatment for people with speech impairments and human-machine interfaces where precise gesture interpretation is vital. The aim is to engineer an advanced hand gesture recognition system, effective across various body positions and camera viewpoints. A novel flexible camera arrangement was employed, integrating a CNN-Transformer hybrid model, leveraging the strengths of Convolutional Neural Networks and the self-attention mechanism of Transformers. Developed using Python and the PyTorch deep learning framework, the system focuses on sophisticated image processing techniques. A thorough literature review on gesture recognition systems and multi-view analysis was conducted to inform the development. The system demonstrated exceptional accuracy in recognizing hand gestures in diverse body postures and from multiple camera perspectives, significantly outperforming existing methods. It marked a significant advancement in decoding complex gestures, a key aspect for medical applications and intricate human-machine is primarily interactions. This beneficial for people with speech impairments, rehabilitation, and in human-machine interfaces, poised to revolutionize patient care and enhance interaction with advanced machinery and computer systems.

This study addresses the vulnerabilities of traditional monocular camera-based face recognition systems, emphasizing the need for improved security and reliability in biometric authentication under varying environmental conditions, lighting, and human poses. To counteract the risk of spoofing attacks using masks or static images, we introduce a multi-angle stereo camera system. This system is strategically designed to capture facial imagery from multiple perspectives, thereby enhancing depth perception and spatial accuracy, crucial for high-security authentication. Employing a novel image processing approach, the study integrates a Convolutional Neural Networks (CNN) with a simple Boolean operation to differentiate the landmarks detected on each camera. This method exploits CNN’s robust feature extraction capabilities and the effective usage of stereo camera, enabling precise detection and analysis of 3D facial landmarks. Such an approach significantly bolsters the system’s ability to differentiate between genuine faces and deceptive representations like masks or static images. Empirical results demonstrate that the stereo camera configuration substantially improves recognition accuracy, reducing both false positives and negatives, especially in controlled spoofing scenarios. The advanced 3D facial landmark detection further reinforces the system ’ s security. With its enhanced robustness and security, the developed system shows great potential for applications in areas requiring stringent identity verification, such as banking, public facilities, and smart home technologies.

In the manufacture of integrated circuits (ICs), copper is used primarily as the multilevel interconnect material, which is manufactured with a dual damascene technique utilizing chemical mechanical polishing (CMP) to planarize overburdened materials. However, there are many challenges for copper CMP technique to produce a surface with a superior planarity and local device surface finish with minimal dishing and erosion while achieving uniform copper blanket film under specific thickness. Considering these challenges, this study pioneered the development of a three-dimensional microstructural model for polishing pads, which is based on image processing algorithms to construct the porous feature structure of polishing pad in conjunction with generating a layer of surface asperities, allowing for an accurate assessment of the effect of downward pressure during CMP on the microstructure of polishing pads. Moreover, this study also develop the new calibration method based on finite element simulation method for determining the mechanism of material removal by abrasive particles as well as the passivation of thin copper blanket film in polishing slurry. Results of this study include not only investigations of the copper blanket wafer’s surface roughness after CMP process but also the development of a new methodology of calibrating the material removal rates (MRRs) validated through comparison with CMP experiments. These findings can be further applied for developing CMP process model, and for advanced applications.

Sanitary landfill is still considered as one of the most significant and least expensive methods of waste disposal. It is essential to consider environmental impacts while selecting a suitable landfill site. Thus, the site selection for sanitary landfill is a complex and time-consuming task needing an assessment of multiple criteria. In the present study, a decision support system (DSS) was prepared for selecting a landfill site in a growing urban region. This study involved two steps of analysis. The first step of analysis involved the application of spatial data to prepare the thematic maps and derive their weight. The second step employed a fuzzy multicriteria decision-making (FMCDM) technique for prioritizing the identified landfill sites. Thus, initially, the analytic hierarchy process (AHP) was used for weighting the selected criteria, while the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) was applied for addressing the uncertainty associated with decision-making and prioritizing the most suitable site. A case study was conducted in the city of Memari Municipality. The main goal of this study was the initial evaluation and acquisition of landfill candidate sites by utilizing GIS and the following decision criteria: (1) environmental criteria consisting of surface water, groundwater, land elevation, land use land cover, distance from urban residence and buildup, and distance from sensitive places; and (2) socioeconomic criteria including distance from the road, population density, and land value. For preparing the final suitability map, the integration of GIS layers and AHP was used. On output, 7 suitable landfill sites were identified which were further ranked using FTOPSIS based on expert’s views. Finally, candidate site-7 and site-2 were selected as the most suitable for proposing new landfill sites in Memari Municipality. The results from this study showed that the integration of GIS with the MCDM technique can be highly applied for site suitability. The present study will be helpful to local planners and municipal authorities for proposing a planning protocol and suitable sites for sanitary landfill in the near future.

Lung ultrasound (LUS) has proven high diagnostic accuracy for community-acquired pneumonia (CAP) in developed countries. However, its diagnostic performance in resource-limited settings with high pulmonary tuberculosis (TB) incidence is less established. Additionally, the role of LUS in monitoring CAP progression remains underexplored.ObjectivesTo validate the diagnostic performance, monitoring and prognostic utility of LUS for CAP in a high pulmonary TB incidence setting.DesignProspective single-centre cohort study.SettingPulmonary department of a tertiary hospital in Vietnam.ParticipantsA total of 158 patients suspected of having CAP were enrolled, with 136 (mean age 62 years, 72.8% male) included in the final analysis.InterventionsPatients underwent LUS and chest X-ray (CXR) within 24 hours of admission, with a follow-up LUS on days 5–8.Primary and secondary outcome measuresThe primary outcome was the diagnostic accuracy of LUS and CXR compared with discharge diagnosis. Secondary outcomes included the accuracy compared with CT scan results, changes in LUS parameters—consolidation size, number and Lung Ultrasound Score (LUSS)—and their association with in-hospital mortality.ResultsLUS demonstrated higher sensitivity than CXR (96.0% (95% CI 90.0% to 99.0%) vs 82.8% (95% CI 73.9% to 89.7%)). LUS specificity was 64.9% (95% CI 47.5% to 80.0%), compared with 54.1% (95% CI 36.9% to 70.5%) for CXR. The moderate specificity for LUS was due to sonographic-similar conditions, notably TB in 5.1% of patients. Consolidation size and numbers showed marginal resolution, while LUSS showed more pronounced decreases over time. The baseline LUSS showed limited discriminative ability for predicting mortality (area under the curve, AUC 0.65, 95% CI 0.55 to 0.75), while follow-up LUSS and changes in LUSS (ΔLUSS) demonstrated higher levels of discrimination (AUC 0.81 (95% CI 0.71 to 0.89) and 0.89 (95% CI 0.80 to 0.95), respectively). For each one-point increase in ΔLUSS, the odds of in-hospital mortality went up by 70% (p=0.002). An improved LUSS effectively ruled out mortality (negative predictive value 97.4%).ConclusionAlthough LUS is highly sensitive for diagnosing CAP, its specificity in TB-endemic regions warrants further caution. Serial LUS assessments, particularly monitoring LUSS changes, are valuable for tracking disease progression and prognostication, with increasing LUSS indicating potential clinical deterioration.

Electrical discharge machining (EDM) is a highly regarded method for producing ultra-precise mechanical parts. In this study, the process parameters of die-sinking EDM using copper electrodes and American Iron and Steel Institute (AISI) P20 tool steel workpieces are optimized for various output responses. The study surveys three input parameters, including Current (I), Pulse on Time (Ton), and Pulse Off Time (Toff). Some statistical methods, such as Taguchi and Analysis of Variance (ANOVA), are applied to find the optimal set of parameters for the output responses, consisting of Material Removal Rate (MRR), Electrode Wear Rate (EWR), and Surface Roughness (SR), and determine the most influential input factor. With the L9 Orthogonal Array (OA), the analytical results demonstrate the optimal parameter set for MRR is I = 6 A, Ton = 120 µs, and Toff = 30 µs, while those optimal values for EWR and SR are I = 2 A, Ton = 120 µs, and Toff = 90 µs and I = 2 A, Ton = 60 µs, and Toff = 30 µs, respectively. The study also indicates that input factor I has the most effect on the output responses, followed by Ton and Toff. Moreover, Grey relational analysis in the Taguchi method is also employed for multi-response optimization. The optimal parameter set for the three output factors is I = 6 A, Ton = 120 µs, and Toff = 60 µs, respectively. In this research, the microstructure and recast layer of the machined surfaces are investigated using optical microscopy as well.

Introduction: This study aimed to determine the incidence of lower genital infections and related factors in preterm premature rupture of membranes (PPROM) and preterm labor. Methodology: A case-control study was conducted on pregnant women who were admitted to the Hospital of Hue University of Medicine and Pharmacy, Vietnam between November 2017 and May 2019. Cases from 22 to 36 gestational weeks were included as group 1 (patients with preterm labor and intact membranes) or as group 2 (those with PPROM). The control group included women with singleton pregnancies who were matched on gestational age and recruited concurrently with the study cases. Gram stain was perfomed to identify Lactobacillus, Gardnerella, mobiluncus, Candida, and leucocytes. Trichomonas vaginalis was detected by wet mount. Cultures of vaginal secretions and aminotic fluid were performed to identify aerobic bacteria. Results: Bacterial vaginosis was higher in group 1 (28.9%) compared to control (11.4%). The incidence of isolated aerobic bacteria was 44.1% in group 2, 11.1% in group 1, and 12.7% in the control group (p < 0.001). Fungal infection was not shown to be a risk factor for preterm labor (p = 0.990), whereas, bacterial vaginosis was (OR = 3.16; 95%CI = 1.23-8.15; p = 0.016). Isolated aerobic bacteria were associated with premature rupture of membranes (OR = 5.45; 95%CI = 2.11-14.05; p < 0.001). Conclusions: Bacteria vaginosis increased the risk of preterm labor and preterm premature rupture of membranes. Isolated aerobic bacteria were related to PPROM, while fungal infection was not associated with preterm labor.

This study aimed to measure the preferences for mental health support among health professionals, their willingness to support the mental health of colleagues and associated factors. A descriptive cross-sectional study was performed from August to October 2022 within five hospitals located in Hanoi, Vietnam. A total of 244 health professionals participated in the study. Data on socio-economic status, health and COVID-19-related characteristics, Depression Anxiety Stress Scale (DASS-21); and preferences for mental health support services were collected by using a structured self-reported questionnaire. Multivariate logistic regression models were utilized to identify associated factors with the demand for mental support services. 13.9%, 17.1% and 8.6% reported having at least mild depression, anxiety and stress, respectively. There 13.9% did not seek any mental health support during the COVID-19 pandemic. The most common support included talking with friends (52.9%), family (50.8%), colleagues (47.6%) and using social networks/Internet (43.5%). There 31.1% had been aware of mental health services, but only 18.0% used this service at least once. Regarding preferences, 47.3% had a demand for mental support services, and the most preferred service was providing coping skills (25.9%), followed by skills to support others against mental problems (22.2%). Major sources of support included psychiatrists (34.4%), colleagues (29.1%) and family (27.9%). The main preferred channels for support included telephone/mobile phone (35.7%) and Internet (20.9%). Only 12.3% were willing to provide mental support for colleagues during the pandemic. Age, education, perceived mental health status, ever seeking any mental service, and DASS-21 depression score were associated with demand for mental support services. This study found a lack of awareness of mental health services for health professionals, as well as moderate levels of demand for this service in this population. Raising awareness and developing tailored mental health support services are important to enhancing the mental well-being of health professionals in Vietnam to prepare for the next pandemic.

Helicobacter pylori (H. pylori) infection is prevalent and has a rapidly increasing antibiotic resistance rate in Vietnam. Reinfection is quite common, and gastric carcinoma remains one of the most common malignancies, which is not uncommon to develop after successful eradication. The purpose of this consensus is to provide updated recommendations on the management of H. pylori infection in the country. The consensus panel consisted of 32 experts from 14 major universities and institutions in Vietnam who were invited to review the evidence and develop the statements using the Delphi method. The process followed the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. The consensus level was defined as ≥80% for agreement on the proposed statements. Due to the limited availability of high-quality local evidence, this consensus was also based on high-quality evidence from international studies, especially those conducted in other populations in the Asia–Pacific region. The panel finally reached a consensus on 27 statements after two voting rounds, which consisted of four sections (1) indications for testing and selection of diagnostic tests (2), treatment regimens, (3) post-treatment confirmation of H. pylori status, and (4) reinfection prevention methods and follow-up after eradication. Important issues that require further evidence include studies on third-line regimens, strategies to prevent H. pylori reinfection, and post-eradication follow-up for precancerous gastric lesions. We hope this consensus will help guide the current clinical practice in Vietnam and promote multicenter studies in the country and international collaborations.

The combination of in vitro culture and simulated gravity under clinostat 2D conditions was first applied to strawberry (Fragaria × ananassa Duch.) leaf to evaluate in vitro morphogenesis, antioxidant enzyme activity and accumulation of endogenous hormones. The subsequent growth and runner formation of clinostat 2D generated-plantlets in the greenhouse as compared to those with plantlets in the in vitro culture condition (control) were also examined. The results showed that the leaf explants (0.5 cm × 0.5 cm) cultured under clinostat 2D gave 1-week shoot regeneration and the growth was higher than that under control condition after 3, 4 and 6 weeks of culture. In addition, in shoots generated from explants under clinostat 2D condition antioxidant enzyme activities affected results such as increasing ascorbate peroxidase (APX), catalase (CAT), 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and reducing phenolic content compared with control conditions after 6 weeks of culture. The clinostat 2D derived-shoots showed higher levels of GA3, ABA, and KIN; meanwhile, the content of IAA, ZEA, SA and MEL showed opposite results compared to the control condition. In this study, the ratios between endogenous hormone groups were also different between the two conditions. The ratios of GA3/IAA and GA3/CYT (ZEA, KIN and 2iP) of clinostat 2D derived-shoots were 12 and 1.5 times higher, respectively, compared to those in the control condition. In contrast, the ratios of IAA/CYT and IAA/SA showed the opposite results (two times lower) after 6 weeks of culture. The growth of shoots and plantlets derived from both conditions showed no abnormalities. In addition, the 2D clinostat generated-plantlets resulted in acclimatization and runner formation that was better than in the control. The results of the study offer a promising new direction for combining in vitro culture and clinostat 2D conditions for plant breeding.Key messageIn vitro culture and clinostat 2D conditions were applied to study leaf morphogenesis and 3 clinostat 2D-derived subsequent growth strawberry plantlets 4 Morphogenesis of in vitro strawberry leaf cultured under clinostat 2D were compared to 5 those under in vitro culture 6 Subsequent growth and runner formation of clinostat 2D-derived plantlets grown in the 7 greenhouse.