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This research represents a crucial step forward in the design and application of magnetized ternary hybrid nanofluids, paving the way for innovations in thermal management and medical treatment technologies. Optimization analysis of nanoscale heat transport for magnetized ternary hybrid bio nanofluid containing SiO2, TiO2, and Al2O3 nanoparticles over a three-dimensional wedge geometry is made in this article. Heat transport analysis is studied through thermal and joule heating effects and the ternary hybrid composition is chosen to leverage the combined thermal properties of the nanoparticles. Furthermore, detail streamlines of flow pattern are investigated for different physical parameters. Physical system is formulated with the system of Partial differential equation (PDEs) and it is processed with similarity transformation to convert it into system of ordinary differential equation (ODEs). Furthermore, Keller box scheme is applied to fetch its numerical solution and compared with finite element technique for validation and found smooth agreement.Temperature is increased with pressure gradient, shear strain and thermal radiation parameter. Magnitude of drag force is increasing with increasing Weissenberg number. For We = 0.2, 0.3, 0.4, 0.5, 0.6, skin friction increases in ternary nanofluid with 13 %,17 %, 21 %, 23 % and 26 % respectively. For β = 0.3, 0.4, 0.5, 0.6, 0.7, skin friction decreases in ternary nanofluid with 30 %,25 %, 20 %, 15 % and 10 % respectively.

Review games are considered a method to help students recall information, solidify learning, and enhance learning effectiveness. This study explores students’ experiences using games to review the topic “Acid - Base - pH - Oxide - Salt” in 8th -grade Science curriculum. The research methodology involved theoretical analysis, pedagogical experimentation, and surveying 308 students. Results indicate positive student responses regarding competence, immersion, flow, and positive impact. Additionally, the designed game set needs adjustments to increase the challenge for students. The study underscores the significance of implementing review games, enriching both theoretical and practical foundations for using games in teaching Science at secondary school.

Benney–Luke equation, the estimation of water wave propagation on the water’s surface, is significantly important in studying the tension of water waves in physics. This paper focuses on the Bilinear Neural Network method (BNNM) to find the solutions to the Benney–Luke equation. Using the Hirota bilinear operator, the Benney–Luke equation is transformed into a bilinear expression and establishes models of neurons. The method construction is straightforward, well-organized, and effective for finding various exact analytic solutions of the Benny–Luke equation consisting of one-soliton solutions, two-soliton solutions, one-soliton hyperbolic wave solutions, two-soliton hyperbolic wave solutions, mixed-soliton hyperbolic solutions, and mixed-multi hyperbolic solutions by choosing the appropriate test functions. The solutions are rigorously depicted in three dimensions to observe the mutable behavior.

In this study, we present some results on the preparation of a conical-shaped W-Cu composite by using the combination of the spark plasma sintering and subsequent spinning process. The experimental results demonstrated that the full density, fine grain and high hardness composite could be obtained. The relative density of the W-Cu composite after the spinning process increased up to 99.8% which is higher than that of the composite prepared by SPS processing (98.8%). Similarly, the microhardness of the composite after the spinning process is improved compared to the sample obtained after SPS processing. This was attributed to the grain size refinement and the increase of the dislocation density generated during the spinning process. Besides, the dependence of the microstructure and microhardness of the conical-shaped W-Cu composite on the positions of the cone was investigated in detail. As a result, the microstructure and microhardness of the cone were altered at various locations from the inside to the outside walls. This could be attributed to the difference in the interface bond strength between W and Cu matrix at different positions. The current work promises to be an innovative and encouraging approach to producing high-performance W-Cu composites for possible industrial applications and specially in shaped charge liners.

Herein, we investigated the effect of W content on the jet penetration performance of W-Cu shaped charge liners by using both simulation and experimental methods. The W-Cu composite liners were prepared directly by using spark plasma sintering (SPS) technique. Microstructural observations showed that W particles were uniformly dispersed within the Cu matrix. The relative density of W-Cu composites decreased slightly from 99.2% to 98.8% with an increase in the W content. The hardness of the W-Cu composite liner increased as increasing W content and reached the highest value of 209.2 HV for the composite reinforced by 60 wt.% W. Besides, the penetration depth increased and reached the maximum value of 80 mm for the composite liner containing 50 wt.% W which is improved by about 11% compared to pure Cu liner. According to simulation and experiment results, the penetration depth of the W-Cu composite liners exhibits a nearly identical trend. W-Cu composite liner containing 50 wt.% W remains the best performance compared to other composites. However, the experimental results are lower compared to the simulation results. This could be because the simulation procedure did not completely account for the actual test conditions.

IntroductionWith increased diagnostic capabilities and treatment modalities in the field of primary immunodeficiencies (PID), many pediatric patients survive beyond childhood and experience a change of care to the adult-oriented healthcare system. Unfortunately, the transition pathways for PID are less clearly defined, resulting in deterioration of quality of care in adulthood. Hence, this is the first regional study to address PID clinicians’ opinions on practices and challenges of transition care in 7 Southeast Asia (SEA) countries.MethodsWe adopted a cross-sectional study design through an online survey platform to enquire opinions of transition practices from expert representatives in 7 SEA countries.ResultsRegionally, 3 out 7 countries reported having no practice of transition care. Among cited challenges were reluctant adaptation by patients and caregivers to unfamiliarized adult healthcare systems, inadequate ratio of adult immunologists to patients and lack of facilities for transfer.Discussion and conclusionOur study provides evidence to advocate policy makers on the importance of standardized integration of transition practice towards betterment of transiting PID patients into adulthood.

Abstract Background To investigate the knowledge, attitudes, and practices of the healthcare professionals (HCPs) including physicians and nurses regarding dengue transmission, diagnosis and clinical classification using the warning signs of World Health Organization (WHO) 2009 classification. Results Out of 471 respondents from three countries, 80.9% of physicians and 74% of nurses did not receive previous training regarding the dengue infection. The majority of respondents could identify the primary dengue vector (86%), while only a third of HCPs knew the biting time of dengue mosquitoes. Only half of our respondents knew about immunity induced by serotypes; Moreover, half of our participants could determine the diagnostic tests. On the other hand, about 90% of the respondents took responsibility for talking to the patients about preventive measures. Our respondents also showed wide variations in definition of warning signs listed in the WHO 2009 classification. Multivariate analysis linked the impact of different cofactors including prior training on dengue infection, type of profession, frequency of taking care of dengue patients and country on how HCPs defined these warning signs. Conclusions This study could declare the variation in employing the warning signs listed in the WHO 2009 classification. We have figured that most of the HCPs did not take prior training on the dengue viral infection; Also, we found gaps in the knowledge regarding various topics in dengue fever. This paper recommends the gathering of efforts to establish the proper knowledge of dengue infection and the warning signs listed by the WHO.

Background Identifying patients at risk of dengue shock syndrome (DSS) is vital for effective healthcare delivery. This can be challenging in endemic settings because of high caseloads and limited resources. Machine learning models trained using clinical data could support decision-making in this context. Methods We developed supervised machine learning prediction models using pooled data from adult and paediatric patients hospitalised with dengue. Individuals from 5 prospective clinical studies in Ho Chi Minh City, Vietnam conducted between 12th April 2001 and 30th January 2018 were included. The outcome was onset of dengue shock syndrome during hospitalisation. Data underwent random stratified splitting at 80:20 ratio with the former used only for model development. Ten-fold cross-validation was used for hyperparameter optimisation and confidence intervals derived from percentile bootstrapping. Optimised models were evaluated against the hold-out set. Findings The final dataset included 4,131 patients (477 adults and 3,654 children). DSS was experienced by 222 (5.4%) of individuals. Predictors were age, sex, weight, day of illness at hospitalisation, indices of haematocrit and platelets over first 48 hours of admission and before the onset of DSS. An artificial neural network model (ANN) model had best performance with an area under receiver operator curve (AUROC) of 0.83 (95% confidence interval [CI], 0.76–0.85) in predicting DSS. When evaluated against the independent hold-out set this calibrated model exhibited an AUROC of 0.82, specificity of 0.84, sensitivity of 0.66, positive predictive value of 0.18 and negative predictive value of 0.98. Interpretation The study demonstrates additional insights can be obtained from basic healthcare data, when applied through a machine learning framework. The high negative predictive value could support interventions such as early discharge or ambulatory patient management in this population. Work is underway to incorporate these findings into an electronic clinical decision support system to guide individual patient management.

Aims Carpal tunnel syndrome (CTS) and low serum prealbumin concentration are common in maintenance hemodialysis patients. In this study, we focused on the association between low serum prealbumin levels and carpal tunnel syndrome in maintenance hemodialysis (MHD) patients using low-flux dialysis reuse. Materials and methods Serum prealbumin levels were assessed to determine the association between low serum prealbumin levels and CTS in 373 prevalent MHD patients (the mean age was 45 years old, hemodialysis duration was 46 months). The patients were divided into 2 groups: the CTS group with 44 patients and the non-CTS group with 329 patients. Results The prevalence of CTS was 11.8%. Serum prealbumin showed a good prognostic value to predict CTS in MHD patients using low-flux dialysis reuse (the Area Under the Curve = 0.841, p

Abstract Background A previous genome-wide association study identified 2 susceptibility loci for severe dengue at MICB rs3132468 and PLCE1 rs3740360 and further work showed these mutations to be also associated with less severe clinical presentations. The aim of this study was to determine if these specific loci were associated with laboratory features of dengue that correlate with clinical severity with the aim of elucidating the functional basis of these genetic variants. Methods This was a case-only analysis of laboratory-confirmed dengue patients obtained from 2 prospective cohort studies and 1 randomised clinical trial in Vietnam (Trial registration: ISRCTN ISRCTN03147572. Registered 24th July 2012). 2742 dengue cases were successfully genotyped at MICB rs3132468 and PLCE1 rs3740360. Laboratory variables were compared between genotypes and stratified by DENV serotype. Results The analysis showed no association between MICB and PLCE1 genotype and early viraemia level, platelet nadir, white cell count nadir, or maximum haematocrit in both overall analysis and in analysis stratified by serotype. Discussion The lack of an association between genotype and viremia level may reflect the sampling procedures within the included studies. The study findings mean that the functional basis of these mutations remains unclear. Trial registration ISRCTN ISRCTN03147572 . Registered 24th July 2012.

The use of biocidal agents is a common practice for protection against biofouling in biomass-rich environments. In this paper, oligohexamethyleneguanidine (OHMG) polymer, known for its biocidal properties, was further modified with para-aminosalicylic acid (PAS) to enhance its properties against microorganisms coated with a lipid membrane. The structure of the product was confirmed by 1H NMR, 13C NMR, and FTIR spectroscopy. The values of the minimum inhibitory concentration (MIC) against Mycobacterium smegmatis ATCC 607 and Pseudomonas chlororaphis 449 were found to be 1.40 and 1.05 μg/mL, respectively. The synthesized substance was used as an additive to the polymer matrix of the composite optical oxygen sensor material. A series of samples with different contents of OHMG-PAS was prepared using a co-dissolution method implying the fabrication of a coating from a solution containing both polymers. It turned out that the mutual influence of the components significantly affects the distribution of the indicator in the matrix, surface morphology, and contact angle. The optimal polymer content turned out to be wt.3%, at which point the water contact angle reaches almost 122°, and the fouling rate decreases by almost five times, which is confirmed by both the respiratory MTT assay and confocal microscopy with staining. This opens up prospects for creating stable and biofouling-resistant sensor elements for use in air tanks or seawater. [ABSTRACT FROM AUTHOR]

Due to low compressive strength and low compressive elastic modulus in comparison with these in tension, GFRP reinforcement is often used for bending elements and is rarely used for compressive structures. In this paper, the authors used finite element (FE) method based on Abaqus software to evaluate the axial load-carrying capacity of GFRP reinforced concrete (RC) columns under varying concrete grades, GFRP reinforcement ratios and tie configurations. The model of the specimens is developed using concrete damage plastic (CDP) model and linear elastic material model for GFRP bar. The consistence of the FE method is verified by the experimental results of a series of columns that tested by current authors. The analytical results show that the selected numerical method can accurately predict the behavior as well as the ultimate capacity of the columns. From simulation results, it is clear that the contribution of GFRP to the load-carrying capacity is considerable in columns with low concrete grades. While using higher concrete grades, the contribution of GFRP decrease, at concrete grade B60, contribution of GFRP is almost unimportant (2.74 %). Influence of tie spacing on load-bearing capacity of columns is also investigated. Accordingly, reducing tie spacing leads to increase load-carrying capacity. Based on study results, the authors recommend to limit tie spacing less than eight times of the GFRP bar diameter.

Penfluridol has robust antipsychotic efficacy and is a first-generation diphenylbutylpiperidine. Its effects last for several days after a single oral dose and it can be administered once a week to provide better compliance and symptom control. Recently; strong antitumour effects for penfluridol were discovered in various cancer cell lines; such as breast; pancreatic; glioblastoma; and lung cancer cells via several distinct mechanisms. Therefore; penfluridol has drawn much attention as a potentially novel anti-tumour agent. In addition; the anti-cancer effects of penfluridol have been demonstrated in vivo: results showed slight changes in the volume and weight of organs at doses tested in animals. This paper outlines the potential for penfluridol to be developed as a next-generation anticancer drug.

Many resource allocation problems can be modeled as a linear sum assignment problem (LSAP) in wireless communications. Deep learning techniques such as the fully-connected neural network and convolutional neural network have been used to solve the LSAP. We herein propose a new deep learning model based on the bidirectional long short-term memory (BDLSTM) structure for the LSAP. In the proposed method, the LSAP is divided into sequential sub-assignment problems, and BDLSTM extracts the features from sequential data. Simulation results indicate that the proposed BDLSTM is more memory efficient and achieves a higher accuracy than conventional techniques.