This study investigates the impact of macroprudential policies on ecological footprint (EF) in the top 11 largest countries. This study uses country-level panel data from these countries, covering the period from 1992 to 2020. Findings indicate that macroprudential policies alleviates ecological footprint in the sample. Macroprudential policies primarily reduce the ecological footprint before medium quantile (50%) while the environmental benefits of the policies end in the later quantiles. Moreover, environmental policy stringency (EPS) amplifies the positive influence of macroprudential policies on environmental sustainability. Estimate results stay the same with basic regression results in the post-global financial crisis (GFC) period while the impact is positive in the pre-GFC period. Finally, other robust tests validate the findings reported in basic regression model. This study suggests that governments should customize various types of macroprudential policies while also considering environmental concerns. The achievement of a sustainable environment can be facilitated by the combined effects of macroprudential policies and EPS.
In this work, the mixed multivariate T2 control chart's detailed performance evaluation based on PCA mix is explored. The control limit of the proposed control chart is calculated using the kernel density approach. Through simulation studies, the proposed chart's performance is assessed in terms of its capacity to identify outliers and process shifts. When 30% more outliers are included in the data, the proposed chart provides a consistent accuracy rate for identifying mixed outliers. For the balanced percentage of attribute qualities, misdetection happens because of the high false alarm rate. For unbalanced attribute qualities and excessive proportions, the masking effect is the key issue. The proposed chart shows the improved performance for the shift in identifying the shift in the process.
The issues of employment, social inequality, and resource scarcity can be effectively addressed through social entrepreneurship, contributing to the growing research interest on the formation of social entrepreneurial intention. Using the theory of planned behaviour, the current study examined the influence of selected key factors on social entrepreneurial intention among university students. Based on the cross-sectional quantitative research design, online survey was conducted, which involved 684 students and graduates from five universities in Southern China. The obtained results demonstrated the significant and positive influence of perceived values on sustainability, opportunity recognition competency, attitude towards entrepreneurship, subjective norms, and perceived behavioural control on social entrepreneurial intention. Additionally, attitude towards entrepreneurship partially mediated the relationships of risk-taking propensity, self-efficacy, and need for achievement on social entrepreneurial intention. The multi-group analysis results also showed that need for achievement and social entrepreneurial intention differed significantly between genders, which provides new ideas for future investigations into the impact of gender on social entrepreneurial intentions. Based on the findings of this study, it is crucial that university students are exposed to relevant courses or training to develop social entrepreneurship competencies and promote sustainable values. The findings of this study will provide policymakers with relevant policy guidelines and more effective theoretical support to achieve the goal of promoting social entrepreneurship among university students in a more resource-efficient and effective manner.
Adherence to scheduled physician screenings for renal function monitoring in patients with chronic kidney disease (CKD) or those at high risk remains suboptimal despite the endorsement of regular screenings by several clinical practice guidelines. Our study aims to assess the effectiveness of a point-of-care CKD screening program led by these pharmacists using the PICCOLO device while recognizing the unique position of community pharmacists in primary care. We conducted an 11-month prospective point-of-care interventional research study in the United Arab Emirates to evaluate the performance of a community pharmacist-led CKD screening program for high-risk patients. Six diverse community pharmacies were selected based on staff availability, patient volume, and their offered range of services. Eligible individuals with risk factors for CKD were identified during medication evaluations. The PICCOLO Comprehensive Metabolic Panel facilitated on-site blood analysis, delivering estimated Glomerular Filtration Rate (eGFR) results within 10 to 15 min. Data also included eGFR categories, demographic information, and insights into lifestyle and health habits collected through a questionnaire. Pharmacists conducted comprehensive medication reviews and offered referrals and lifestyle guidance as part of the program. The study encompassed a total of 400 patients, with an average age of 69 ± 13.4 years within the study cohort. Notably, 38.8% (155 individuals) of the 400 patients were found to have undiagnosed CKD stages 3-5. Univariate logistic regression analysis revealed a significant association between a higher incidence of CKD stages 3-5 and factors such as older age, a history of hypertension, vascular disease, and diabetes mellitus. In the multivariate regression model, age and a history of diabetes mellitus emerged as significant predictors of an elevated risk of CKD. This study sheds light on the viability and impact of CKD screening programs conducted by community pharmacists, particularly in detecting CKD stages 3-5. The findings have implications for healthcare policies, as they can influence the enhancement of early detection and management of CKD. Moreover, these insights may catalyze focused screening initiatives and strengthen collaboration between community pharmacies and healthcare systems to benefit patients at high risk of CKD.
T2DM is known to cause disturbances in glucose homeostasis and negative changes in the heart muscle, while aging and diabetes are recognized risk factors for CVD. Given this, our study aims to investigate a method for controlling and managing CVDs induced by T2DM in elderly populations. To achieve this, we categorized 40 rats into 5 groups, including HAD (n = 8), HA (n = 8), AD (n = 8), AHT (n = 8), and ADT (n = 8). The exercise protocol consisted of eight weeks of HIIT (three sessions per week) performed at 90-95% of maximal speed. Following cardiac tissue extraction, we assessed the levels of IGF-1, PI3K, and AKT proteins using Western blot technique, and analyzed the histopathological variations of the heart tissue using H&E, Sudan Black, and Masson's trichrome tissue staining. The histological findings from our study demonstrated that T2DM had a significant impact on the development of pathological hypertrophy and fibrosis in the heart tissue of elderly individuals. However, HIIT not only effectively controlled pathological hypertrophy and fibrosis, but also induced physiological hypertrophy in the AHT and ADT groups compared to the HA and AD groups. Results from Sudan Black staining indicated that there was an increase in lipid droplet accumulation in the cytoplasm of cardiomyocytes and their nuclei in the HA and AD groups, while the accumulation of lipid droplets decreased significantly in the AHT and ADT groups. In both the AHT group and the ADT group, a single HIIT session led to a reduction in collagen fiber accumulation and fibrotic frameworks. Our research also revealed that diabetes caused a significant elevation in the levels of IGF-1, PI3K, and AKT proteins, but after eight weeks of HIIT, the levels of these proteins decreased significantly in the training groups. Overall, our findings suggest that HIIT may be a suitable non-pharmacological approach for improving histological and physiological changes in elderly individuals with T2DM. However, we recommend further research to examine the impact of HIIT training on both healthy and diseased elderly populations.
Probiotics are a mixture of beneficial live bacteria and/or yeasts that naturally exist in our bodies. Recently, numerous studies have focused on the immunostimulatory effects of single-species or killed multi-species probiotic conditioned mediums on macrophages. This study investigates the immunostimulatory effect of commercially available active, multi-species probiotic conditioned medium (CM) on RAW264.7 murine macrophages. The probiotic CM was prepared by culturing the commercially available probiotic in a cell-culture medium overnight at 37 °C, followed by centrifugation and filter-sterilization to be tested on macrophages. The immunostimulatory effect of different dilution percentages (50%, 75%, 100%) of CM was examined using the MTT assay, proinflammatory cytokine (tumor necrosis factor TNF-alpha) production in macrophages, migration, and phagocytosis assays. For all the examined CM ratios, the percentages of cell viability were > 80%. Regarding the migration scratch, TNF-alpha and phagocytosis assays, CM demonstrated a concentration-dependent immunostimulatory effect. However, the undiluted CM (100%) showed a significant (p-value
The actual prevalence of diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D) in Malaysia is unknown. We aimed to determine the prevalence of DKD and its associated risk factors among T2D patients in Malaysia. An analytical cross-sectional study was conducted using the year 2022 clinical audit dataset from the National Diabetes Registry. DKD was defined as albuminuria, a decreased glomerular filtration rate, or both. Among 80,360 patients, 62.2% were female, 68.4% were Malay, and the mean age was 61.4 years. A total of 56.7% (95% CI 56.4-57.1%) of patients were found to have DKD. Increasing age, male sex, Malay ethnicity, longer duration of diabetes, overweight, obesity, hypertension, diabetic retinopathy, diabetic foot ulcer, nontraumatic lower-extremity amputation, ischaemic heart disease, stroke, insulin, higher numbers of antihypertensive agents, antiplatelet agents, poorer HbA1c control, higher systolic blood pressure, non-achievement of triglyceride target, and non-attainment of HDL-cholesterol goal were independent risk factors associated with DKD. Clinicians, program managers, and health policymakers should target modifiable factors to manage DKD and prevent its progression to end-stage kidney disease in Malaysia.
Many intrusion detection techniques have been developed to ensure that the target system can function properly under the established rules. With the booming Internet of Things (IoT) applications, the resource-constrained nature of its devices makes it urgent to explore lightweight and high-performance intrusion detection models. Recent years have seen a particularly active application of deep learning (DL) techniques. The spiking neural network (SNN), a type of artificial intelligence that is associated with sparse computations and inherent temporal dynamics, has been viewed as a potential candidate for the next generation of DL. It should be noted, however, that current research into SNNs has largely focused on scenarios where limited computational resources and insufficient power sources are not considered. Consequently, even state-of-the-art SNN solutions tend to be inefficient. In this paper, a lightweight and effective detection model is proposed. With the help of rational algorithm design, the model integrates the advantages of SNNs as well as convolutional neural networks (CNNs). In addition to reducing resource usage, it maintains a high level of classification accuracy. The proposed model was evaluated against some current state-of-the-art models using a comprehensive set of metrics. Based on the experimental results, the model demonstrated improved adaptability to environments with limited computational resources and energy sources.
Fins are widely used in many industrial applications, including heat exchangers. They benefit from a relatively economical design cost, are lightweight, and are quite miniature. Thus, this study investigates the influence of a wavy fin structure subjected to convective effects with internal heat generation. The thermal distribution, considered a steady condition in one dimension, is described by a unique implementation of a physics-informed neural network (PINN) as part of machine-learning intelligent strategies for analyzing heat transfer in a convective wavy fin. This novel research explores the use of PINNs to examine the effect of the nonlinearity of temperature equation and boundary conditions by altering the hyperparameters of the architecture. The non-linear ordinary differential equation (ODE) involved with heat transfer is reduced into a dimensionless form utilizing the non-dimensional variables to simplify the problem. Furthermore, Runge-Kutta Fehlberg's fourth-fifth order (RKF-45) approach is implemented to evaluate the simplified equations numerically. To predict the wavy fin's heat transfer properties, an advanced neural network model is created without using a traditional data-driven approach, the ability to solve ODEs explicitly by incorporating a mean squared error-based loss function. The obtained results divulge that an increase in the thermal conductivity variable upsurges the thermal distribution. In contrast, a decrease in temperature profile is caused due to the augmentation in the convective-conductive variable values.
The study addressed a significant gap in the profiling and understanding of the gut microbiota's influence on Malaysian Malay women with gestational diabetes mellitus (GDM). This prospective cohort study aimed to explore the intricate relationship between gut microbiota, dietary choices, and lifestyle factors among Malay women, both with and without GDM. The research specifically focused on participants during the second (T0) and third (T1) trimesters of pregnancy in Johor Bahru, Malaysia. In Part 1 of the study, a diverse pool of pregnant women at T0 was categorized into two groups: those diagnosed with GDM and those without GDM, with a total sample size of 105 individuals. The assessments encompassed demographic, clinical, lifestyle, and dietary factors at the T0 and T1 trimesters. Part 2 of the study delved into microbiome analysis, targeting a better understanding of the gut microbiota among the participants. Stool samples were randomly collected from 50% of the individuals in each group (GDM and non-GDM) at T0 and T1. The collected samples underwent processing, and 16s rRNA metagenomic analysis was employed to study the microbial composition. The results suggested an association between elevated body weight and glucose levels, poor sleep quality, lack of physical activity, greater intake of iron and meat, and reduced fruit consumption among women with GDM compared to non-GDM groups. The microbiome analysis revealed changes in microbial composition over time, with reduced diversity observed in the GDM group during the third trimester. The genera Lactiplantibacillus, Parvibacter, Prevotellaceae UCG001, and Vagococcus positively correlated with physical activity levels in GDM women in the second trimester. Similarly, the genus Victivallis exhibited a strong positive correlation with gravida and parity. On the contrary, the genus Bacteroides and Roseburia showed a negative correlation with omega-3 polyunsaturated fatty acids (PUFAs) in women without GDM in the third trimester. The study highlighted the multifaceted nature of GDM, involving a combination of lifestyle factors, dietary choices, and changes in gut microbiota composition. The findings emphasized the importance of considering these interconnected elements in understanding and managing gestational diabetes among Malaysian Malay women. Further exploration is essential to comprehend the mechanisms underlying this relationship and develop targeted interventions for effective GDM management.
The growing Human Immunodeficiency Virus (HIV) incidences and insufficient HIV knowledge among Malaysian late adolescents necessitate immediate attention to HIV prevention via education. This study aims to develop and validate an Information-Motivation-Behavioural skills (IMB) model-based education kit for adolescents, PREM-Kit, to educate on HIV prevention among Malaysian late adolescents. Utilizing the Analysis, Design, Development, Implementation, and Evaluation model, we conducted the study in three phases: needs assessment, development of PREM-Kit, and validation of PREM-Kit by applying the IMB model to map the PREM-Kit's contents. PREM-Kit, developed in Malay language, consisted of an infographic flip chart and videos. Five multi-disciplinary experts validated the PREM-Kit using the content validity index (CVI), and 13 end-users validated the PREM-Kit using the Malay version of the Patient Education Materials Assessment Tool for Printable and Audiovisual Materials. The infographic flip chart comprised three modules covering 15 topics, and an animated video accompanied each module. PREM-Kit achieved CVI scores of 1.0 and median scores of over 80% for understandability and actionability. Overall, the newly developed IMB model-based HIV education kit has good content validity, is simple to comprehend and apply, and is ready for testing its effectiveness in improving adolescents' knowledge, attitudes, and practices for HIV prevention.
In this cross-sectional investigation, the primary objective was to explore the correlation between the consumption of polyphenols and the likelihood of non-alcoholic fatty liver disease (NAFLD) in the adult population participating in the Hoveyzeh cohort. Data from the Hoveyzeh cohort study, part of the Persian Cohort Study, involving 10,009 adults aged 35-70, were analyzed. Exclusions were made for missing data, extreme energy intake, and liver cancer patients. Dietary habits were assessed using a food frequency questionnaire, and polyphenol intake was calculated using the Phenol Explorer database. Logistic regression analyses, adjusted for confounders, were performed to assess the relationship between polyphenol subclasses (total polyphenols, total flavonoids, phenolic acid, and lignin) and NAFLD. Among 9894 participants, those in the highest quintile of total polyphenol (OR 0.65, CI 0.5-0.84; P = 0.007), phenolic acid (OR 0.67, CI 0.52-0.86; P
Previous research has primarily focused on pre-processing parameters such as design, material selection, and printing techniques to improve the strength of 3D-printed prosthetic leg sockets. However, these methods fail to address the major challenges that arise post-printing, namely failures at the distal end of the socket and susceptibility to shear failure. Addressing this gap, the study aims to enhance the mechanical properties of 3D-printed prosthetic leg sockets through post-processing techniques. Fifteen PLA + prosthetic leg sockets are fabricated and reinforced with four materials: carbon fiber, carbon-Kevlar fiber, fiberglass, and cement. Mechanical and microstructural properties of the sockets are evaluated through axial compression testing and scanning electron microscopy (SEM). Results highlight superior attributes of cement-reinforced sockets, exhibiting significantly higher yield strength (up to 89.57% more than counterparts) and higher Young's modulus (up to 76.15% greater). SEM reveals correlations between microstructural properties and socket strength. These findings deepen the comprehension of 3D-printed prosthetic leg socket post-processing, presenting optimization prospects. Future research can focus on refining fabrication techniques, exploring alternative reinforcement materials, and investigating the long-term durability and functionality of post-processed 3D-printed prosthetic leg sockets.
Interval-valued q-rung orthopair fuzzy set (IVq-ROFS) is a powerful tool for dealing with uncertainty. In this paper, we first propose a new method for aggregating multiple IVq-ROFSs, which is easier to understand and implement in the multi-attribute group decision making process compared to current aggregation operators. Secondly, this paper introduces a new fuzzy entropy with parameters based on IVq-ROFS, which is highly flexible due to its adjustable parameters. Based on this, the IVq-ROFS-based attribute weight calculation method is proposed to obtain the objective weights of the attributes, which is more reasonable and objective than the existing methods. Then, for the dimensional differences between the three compromise scores in the original Combined Compromise Solution (CoCoSo) method, the enhanced compromise scores are proposed. These scores are obtained by normalizing the three dependent compromise scores, ensuring that they fall within the same range. Finally, a novel CoCoSo mothed on IVq-ROFS using the proposed fuzzy entropy and enhanced compromise scores is presented. The proposed method is highly adaptable and scalable, not limited to IVq-ROFS. The excellent performance and robustness of the proposed method are verified in sepsis diagnosis applications.
Literature has shown that simulated power production during conventional functional electrical stimulation (FES) cycling was improved by 14% by releasing the ankle joint from a fixed ankle setup and with the stimulation of the tibialis anterior and triceps surae. This study aims to investigate the effect of releasing the ankle joint on the pedal power production during FES cycling in persons with spinal cord injury (SCI). Seven persons with motor complete SCI participated in this study. All participants performed 1 min of fixed-ankle and 1 min of free-ankle FES cycling with two stimulation modes. In mode 1 participants performed FES-evoked cycling with the stimulation of quadriceps and hamstring muscles only (QH stimulation), while Mode 2 had stimulation of quadriceps, hamstring, tibialis anterior, and triceps surae muscles (QHT stimulation). The order of each trial was randomized in each participant. Free-ankle FES cycling offered greater ankle plantar- and dorsiflexion movement at specific slices of 20° crank angle intervals compared to fixed-ankle. There were significant differences in the mean and peak normalized pedal power outputs (POs) [F(1,500) = 14.03, p
The present research investigates the double-chain deoxyribonucleic acid model, which is important for the transfer and retention of genetic material in biological domains. This model is composed of two lengthy uniformly elastic filaments, that stand in for a pair of polynucleotide chains of the deoxyribonucleic acid molecule joined by hydrogen bonds among the bottom combination, demonstrating the hydrogen bonds formed within the chain's base pairs. The modified extended Fan sub equation method effectively used to explain the exact travelling wave solutions for the double-chain deoxyribonucleic acid model. Compared to the earlier, now in use methods, the previously described modified extended Fan sub equation method provide more innovative, comprehensive solutions and are relatively straightforward to implement. This method transforms a non-linear partial differential equation into an ODE by using a travelling wave transformation. Additionally, the study yields both single and mixed non-degenerate Jacobi elliptic function type solutions. The complexiton, kink wave, dark or anti-bell, V, anti-Z and singular wave shapes soliton solutions are a few of the creative solutions that have been constructed utilizing modified extended Fan sub equation method that can offer details on the transversal and longitudinal moves inside the DNA helix by freely chosen parameters. Solitons propagate at a consistent rate and retain their original shape. They are widely used in nonlinear models and can be found everywhere in nature. To help in understanding the physical significance of the double-chain deoxyribonucleic acid model, several solutions are shown with graphics in the form of contour, 2D and 3D graphs using computer software Mathematica 13.2. All of the requisite constraint factors that are required for the completed solutions to exist appear to be met. Therefore, our method of strengthening symbolic computations offers a powerful and effective mathematical tool for resolving various moderate nonlinear wave problems. The findings demonstrate the system's potentially very rich precise wave forms with biological significance. The fundamentals of double-chain deoxyribonucleic acid model diffusion and processing are demonstrated by this work, which marks a substantial development in our knowledge of double-chain deoxyribonucleic acid model movements.
Loratadine (LoR) is a highly lipophilic and practically insoluble in water, hence having a low oral bioavailability. As it is formulated as topical gel, it competitively binds with the receptors, thus reducing the side-effects. The objective of this study was to prepare LoR loaded nanosponge (LoR-NS) in gel for topical delivery. Nine different formulations of emulsion were prepared by solvent evaporation method with polyvinyl alcohol (PVA), ethyl cellulose (EC), and dichloromethane (DCM). Based on 32 Full Factorial Design (FFD), optimization was carried out by varying the concentration of LOR:EC ratio and stirring rate. The preparations were subjected for the evaluation of particle size (PS), in vitro release, zeta potential (ZP) and entrapment efficiency (EE). The results revealed that the NS dispersion was nanosized with sustained release profiles and significant PS. The optimised formulation was formulated and incorporated into carbopol 934P hydrogel. The formulation was then examined to surface morphological characterizations using scanning electron microscopy (SEM) which depicted spherical NS. Stability studies, undertaken for 2 months at 40 ± 2 °C/75 ± 5% RH, concluded to the stability of the formulation. The formulation did not cause skin irritation. Therefore, the prepared NS hydrogel proved to be a promising applicant for LoR as a novel drug delivery system (NDDS) for safe, sustained and controlled topical application.
Compact multi-rotor unmanned aerial vehicles (UAVs) can be operated in many challenging environmental conditions. In case the UAV requires certain considerations in designing like lightweight, efficient propulsion system and others depending upon the application, the hybrid UAV comes into play when the usual UAV types cannot be sufficient to meet the requirements. The propulsion system for the UAV was selected to be coaxial rotors because it has a high thrust-to-weight ratio and to increase the efficiency of the propulsion system, a unique propeller was proposed to achieve higher thrust. The proposed propeller was uniquely designed by analyzing various airfoil sections under different Reynolds's number using X-Foil tool to obtain the optimum airfoil section for the propellers. Since the design with duct increases efficiency, the Hybrid UAV presented in this paper has the modified novel convergent-divergent (C-D)-based duct which is a simplified model of a conventional C-D duct. The yawing and rolling maneuverings of the UAV could be achieved by the thrust vectoring method so that the design is simpler from a structural and mechanical perspective. The use of UAVs has risen in recent years, especially compact UAVs, which can be applied for applications like surveillance, detection and inspection, and monitoring in a narrow region of space. The design of the UAV is modeled in CATIA, and its further performance enactment factors are picked from advanced computational simulations relayed bottom-up approach. The predominant computational fluid dynamics (CFD) and fluid structure interaction (FSI) investigations are imposed and optimized through Computational Analyses using Ansys Workbench 17.2, which includes analysis of structural behaviour of various alloys, CFRP and GFRP based composite materials. From the structural analysis Titanium alloy came out to be the best performing materials among the others by having lower total deformation and other parameters such as normal and equivalent stress. The dynamics control response is obtained using MATLAB Simulink. The validations are carried out on the propeller using a thrust stand for CFD and on the duct through a high-jet facility for structural outcomes to meet the expected outcome.
This study presented a unique, miniaturised asymmetric interconnected vertical stripe (IVS) design for terahertz (THz) frequency applications. Therefore, this research aimed to achieve a frequency response of 0 to 10 THz using a 5 × 5 µm2 Silicon (Si) substrate material. Meanwhile, various parametric examinations were conducted to investigate variations in the performance. For example, the unit cell selection process was carefully examined by using various design structures and modifying the structure by adding split gaps and connecting bars between vertical stripes. Furthermore, the proposed sandwich structure design was used to compute the absorbance and reflectance properties. All the analytical examinations were executed utilising the Computer Simulation Technology (CST) 2019 software. The introduced IVS metamaterial exhibits negative index behaviour and has a single resonance frequency of 5.23 THz with an acceptable magnitude of - 24.38 dB. Additionally, the quadruple-layer IVS structure exhibits optimised transmission coefficient behaviour between 3 and 6 THz and 7 to 9 THz, respectively. However, the magnitude of the transmission coefficient increased with the number of material layers. Besides that, the absorbance study shows that using a quadruple-layer structure obtains unique and promising results. Overall, the proposed asymmetric IVS metamaterial design achieves the required performance by using a compact structure rather than extending the dimensions of the design.