Irritable bowel syndrome (IBS) is frequently linked with coexisting mental illnesses. Our previous study discovered that 32.1% of IBS patients had subthreshold depression (SD), placing them at higher risk of developing major depression. Gut microbiota modulation through psychobiotics was found to influence depression via the gut-brain axis. However, the efficacy of lessening depression among IBS patients remains ambiguous. The study's aim was to investigate the roles of cultured milk drinks containing 109 cfu Lactobacillus acidophilus LA-5 and Lactobacillus paracasei L. CASEI-01 on depression and related variables among IBS participants with SD. A total of 110 IBS participants with normal mood (NM) and SD, were randomly assigned to one of four intervention groups: IBS-NM with placebo, IBS-NM with probiotic, IBS-SD with placebo, and IBS-SD with probiotic. Each participant was required to consume two bottles of cultured milk every day for a duration of 12 weeks. The following outcomes were assessed: depression risk, quality of life, the severity of IBS, and hormonal changes. The depression scores were significantly reduced in IBS-SD with probiotic and placebo from baseline (p
Maintaining a power balance between generation and demand is generally acknowledged as being essential to maintaining a system frequency within reasonable bounds. This is especially important for linked renewable-based hybrid power systems (HPS), where disruptions are more likely to occur. This paper suggests a prominent modified "Fractional order-proportional-integral with double derivative (FOPIDD2) controller" as an innovative HPS controller in order to navigate these obstacles. The recommended control approach has been validated in power systems including wind, reheat thermal, solar, and hydro generating, as well as capacitive energy storage and electric vehicle. The improved controller's performance is evaluated by comparing it to regular FOPID, PID, and PIDD2 controllers. Furthermore, the gains of the newly structured FOPIDD2 controller are optimized using a newly intended algorithm terms as squid game optimizer (SGO). The controller's performance is compared to benchmarks such as the grey wolf optimizer (GWO) and jellyfish search optimization. By comparing performance characteristics such as maximum frequency undershoot/overshoot, and steadying time, the SGO-FOPIDD2 controller outperforms the other techniques. The suggested SGO optimized FOPIDD2 controller was analyzed and validated for its ability to withstand the influence of power system parameter uncertainties under various loading scenarios and situations. Without any complicated design, the results show that the new controller can work steadily and regulate frequency with an appropriate controller coefficient.
In the dynamic world of fashion, high-heeled footwear is revered as a symbol of style, luxury and sophistication. Yet, beneath the facade of elegance of classy footwear lies the harsh reality of discomfort and pain. Thus, this study aims to investigate the influence of wearing high-heeled shoes on the sensation of pain across different body regions over a period of 6 h. It involved fifty female participants, all habitual wearers of high-heeled shoes, aged between 20 and 30 years. Each participant kept a record of their perceptions of pain and discomfort every hour for a total of 6 h using a 0-10 pain scale with 0 indicating no pain and 10 indicating severe pain. The findings reveal a progressive rise in pain throughout wear, with the most intense pain reported in the back, calcaneus, and metatarsals. The analysis shows that after approximately 3.5 h, participants experience significant increases in pain levels. However, the relationship between heel height and pain is not linear. It appears that a heel height of 7.5 cm is the threshold where overall body pain becomes significant. The study suggests that a duration of 3.5 h of wear and a heel height of 7.5 cm serve as critical points to decrease overall body pain. Moreover, beyond this heel height, knee pain diminishes compared to other body areas possibly due to the shift towards a more neutral posture. The study findings, coupled with the recommendations, can assist footwear designers in crafting not only stylish but also comfortable shoes.
The development of novel antioxidant compounds with high efficacy and low toxicity is of utmost importance in the medicine and food industries. Moreover, with increasing concerns about the safety of synthetic components, scientists are beginning to search for natural sources of antioxidants, especially essential oils (EOs). The combination of EOs may produce a higher scavenging profile than a single oil due to better chemical diversity in the mixture. Therefore, this exploratory study aims to assess the antioxidant activity of three EOs extracted from Cymbopogon flexuosus, Carum carvi, and Acorus calamus in individual and combined forms using the augmented-simplex design methodology. The in vitro antioxidant assays were performed using DPPH and ABTS radical scavenging approaches. The results of the Chromatography Gas-Mass spectrometry (CG-MS) characterization showed that citral (29.62%) and niral (27.32%) are the main components for C. flexuosus, while D-carvone (62.09%) and D-limonene (29.58%) are the most dominant substances in C. carvi. By contrast, β-asarone (69.11%) was identified as the principal component of A. calamus (30.2%). The individual EO exhibits variable scavenging activities against ABTS and DPPH radicals. These effects were enhanced through the mixture of the three EOs. The optimal antioxidant formulation consisted of 20% C. flexuosus, 53% C. carvi, and 27% A. calamus for DPPHIC50. Whereas 17% C. flexuosus, 43% C. carvi, and 40% A. calamus is the best combination leading to the highest scavenging activity against ABTS radical. These findings suggest a new research avenue for EOs combinations to be developed as novel natural formulations useful in food and biopharmaceutical products.
Tucker decomposition is widely used for image representation, data reconstruction, and machine learning tasks, but the calculation cost for updating the Tucker core is high. Bilevel form of triple decomposition (TriD) overcomes this issue by decomposing the Tucker core into three low-dimensional third-order factor tensors and plays an important role in the dimension reduction of data representation. TriD, on the other hand, is incapable of precisely encoding similarity relationships for tensor data with a complex manifold structure. To address this shortcoming, we take advantage of hypergraph learning and propose a novel hypergraph regularized nonnegative triple decomposition for multiway data analysis that employs the hypergraph to model the complex relationships among the raw data. Furthermore, we develop a multiplicative update algorithm to solve our optimization problem and theoretically prove its convergence. Finally, we perform extensive numerical tests on six real-world datasets, and the results show that our proposed algorithm outperforms some state-of-the-art methods.
Predicting the course of kidney disease in individuals with both type 1 and type 2 diabetes mellitus (DM) is a significant clinical and policy challenge. In several regions, DM is now the leading cause of end-stage renal disease. The aim of this study to identify both modifiable and non-modifiable risk factors, along with clinical markers and coexisting conditions, that increase the likelihood of stage 3-5 chronic kidney disease (CKD) development in individuals with type 2 DM in the United Arab Emirates (UAE). This was a single-center retrospective cohort study based on data derived from electronic medical records of UAE patients with DM who were registered at outpatient clinics at Tawam Hospital in Al Ain, UAE, between January 2011 and December 2021. Type 2 DM patients aged ≥ 18 years who had serum HbA1c levels ≥ 6.5% were included in the study. Patients with type 1 DM, who had undergone permanent renal replacement therapy, who had under 1 year of follow-up, or who had missing or incomplete data were excluded from the study. Factors associated with diabetic patients developing stage 3-5 CKD were identified through Cox regression analysis and a fine and gray competing risk model to account for competing events that could potentially hinder the development of CKD. A total of 1003 patients were recruited for the study. The mean age of the study cohort at baseline was 70.6 ± 28.2 years. Several factors were found to increase the risk of developing stage 3-5 CKD: advancing age (HR 1.005, 95% CI 1.002-1.009, p = 0.026), a history of hypertension (HR 1.69, 95% CI 1.032-2.8, p = 0.037), a history of heart disease (HR 1.49, 95% CI 1.16-1.92, p = 0.002), elevated levels of serum creatinine (HR 1.006, 95% CI 1.002-1.010, p = 0.003), decreased levels of estimated glomerular filtration rate (eGFR) (HR 0.943, 95% CI, 0.938-0.947; p
The aim of this study was to investigate relationships between changes in training practices and human development index (HDI) levels, and identify strategies employed by athletes who consistently maintained their training quantity during the first 100 days of the COVID-19 pandemic. A total of 10,074 athletes (5290 amateur and 4787 professional athletes from 121 countries) completed an online survey between 17 May to 5 July 2020. We explored their training practices, including specific questions on training frequency, duration and quantity before and during lockdown (March-June 2020), stratified according to the human development index (HDI): low-medium, high, or very high HDI. During the COVID-19 lockdown, athletes in low-medium HDI countries focused on innovative training. Nevertheless, women and amateur athletes experienced a substantial reduction in training activity. Performance-driven athletes and athletes from higher HDI indexed countries, were likely to have more opportunities to diversify training activities during lockdowns, facilitated by the flexibility to perform training away from home. Factors such as lockdown rules, socioeconomic environment, and training education limited training diversification and approaches, particularly in low-medium and high HDI countries. Athletes (amateurs and professionals) who maintained the quantity of training during lockdown appeared to prioritize basic cardiovascular and strength training, irrespective of HDI level. Modifying training and fitness programs may help mitigate the decrease in training activities during lockdowns. Customized training prescriptions based on gender, performance, and HDI level will assist individuals to effectively perform and maintain training activities during lockdowns, or other challenging (lockdown-like) situations.
Extraction of lignin via green methods is a crucial step in promoting the bioconversion of lignocellulosic biomasses. In the present study, utilisation of natural deep eutectic solvent for the pretreatment of kenaf fibres biomass is performed. Furthermore, extracted lignin from natural deep eutectic solvent pretreated kenaf biomass was carried out and its comparative study with commercial lignin was studied. The extracted lignin was characterized and investigated through Infrared Fourier transform spectroscopy, X-ray Diffraction, thermogravimetric analysis, UV-Vis spectroscopy, and scanning electron microscopy. FTIR Spectra shows that all samples have almost same set of absorption bands with slight difference in frequencies. CHNS analysis of natural deep eutectic solvent pretreated kenaf fibre showed a slight increase in carbon % from 42.36 to 43.17% and an increase in nitrogen % from - 0.0939 to - 0.1377%. Morphological analysis of commercial lignin shows irregular/uneven surfaces whereas natural deep eutectic solvent extracted lignin shows smooth and wavy surface. EDX analysis indicated noticeable peaks for oxygen and carbon elements which are present in lignocellulosic biomass. Thermal properties showed that lignin is constant at higher temperatures due to more branching and production of extremely condensed aromatic structures. In UV-VIS spectroscopy, commercial lignin shows slightly broad peak between 300 and 400 nm due to presence of carbonyl bond whereas, natural deep eutectic solvent extracted lignin does not show up any peak in this range. XRD results showed that the crystallinity index percentage for kenaf and natural deep eutectic solvent treated kenaf was 70.33 and 69.5% respectively. Therefore, these innovative solvents will undoubtedly have significant impact on the development of clean, green, and sustainable products for biocatalysts, extraction, electrochemistry, adsorption applications.
Agriculture plays a pivotal role in the economic development of a nation, but, growth of agriculture is affected badly by the many factors one such is plant diseases. Early stage prediction of these disease is crucial role for global health and even for game changers the farmer's life. Recently, adoption of modern technologies, such as the Internet of Things (IoT) and deep learning concepts has given the brighter light of inventing the intelligent machines to predict the plant diseases before it is deep-rooted in the farmlands. But, precise prediction of plant diseases is a complex job due to the presence of noise, changes in the intensities, similar resemblance between healthy and diseased plants and finally dimension of plant leaves. To tackle this problem, high-accurate and intelligently tuned deep learning algorithms are mandatorily needed. In this research article, novel ensemble of Swin transformers and residual convolutional networks are proposed. Swin transformers (ST) are hierarchical structures with linearly scalable computing complexity that offer performance and flexibility at various scales. In order to extract the best deep key-point features, the Swin transformers and residual networks has been combined, followed by Feed forward networks for better prediction. Extended experimentation is conducted using Plant Village Kaggle datasets, and performance metrics, including accuracy, precision, recall, specificity, and F1-rating, are evaluated and analysed. Existing structure along with FCN-8s, CED-Net, SegNet, DeepLabv3, Dense nets, and Central nets are used to demonstrate the superiority of the suggested version. The experimental results show that in terms of accuracy, precision, recall, and F1-rating, the introduced version shown better performances than the other state-of-art hybrid learning models.
Hypertension (HPT) is the leading modifiable risk factor for cardiovascular diseases and premature death worldwide. Currently, attention is given to various dietary approaches with a special focus on the role of micronutrient intake in the regulation of blood pressure. This study aims to measure the dietary intake of selected minerals among Malaysian adults and its association with HPT. This cross-sectional study involved 10,031 participants from the Prospective Urban and Rural Epidemiological study conducted in Malaysia. Participants were grouped into HPT if they reported having been diagnosed with high blood pressure [average systolic blood pressure (SBP)/average diastolic blood pressure (DBP) ≥ 140/90 mm Hg]. A validated food frequency questionnaire (FFQ) was used to measure participants' habitual dietary intake. The dietary mineral intake of calcium, copper, iron, magnesium, manganese, phosphorus, potassium, sodium, and zinc was measured. The chi-square test was used to assess differences in socio-demographic factors between HPT and non-HPT groups, while the Mann-Whitney U test was used to assess differences in dietary mineral intake between the groups. The participants' average dietary intake of calcium, copper, iron, magnesium, manganese, phosphorus, potassium, selenium, sodium, and zinc was 591.0 mg/day, 3.8 mg/day, 27.1 mg/day, 32.4 mg/day, 0.4 mg/day, 1431.1 mg/day, 2.3 g/day, 27.1 µg/day, 4526.7 mg/day and 1.5 mg/day, respectively. The intake was significantly lower among those with HPT than those without HPT except for calcium and manganese. Continuous education and intervention should be focused on decreasing sodium intake and increasing potassium, magnesium, manganese, zinc, and calcium intake for the general Malaysian population, particularly for the HPT patients.
Despite the high efficacy and safety demonstrated in clinical trials, COVID-19 booster vaccination rates in Malaysia remain below 50% among the general public. This study explores the factors influencing public acceptance of the COVID-19 booster vaccine among the Malaysian population. The questionnaire included variables on sociodemographics, knowledge, and the Health Belief Model (HBM) constructs. Based on the Chi-squared test of contingencies, a t-test and multivariate logistic regression analysis on 411 collected responses, the findings revealed that older participants, individuals of Chinese ethnicity, and those with higher education levels and incomes were more willing to accept booster vaccinations. The analysis further identified perceived susceptibility, perceived severity and perceived barriers as significant predictors influencing booster vaccination acceptance rates. Healthcare policymakers may consider targeting interventions to diminish the obstacles associated with booster vaccinations. These intervention strategies include implementing health intervention programmes, such as public health awareness initiatives, to raise awareness of the risks and severity of COVID-19, ultimately encouraging higher uptake of booster vaccines.
Preplaced aggregate concrete (PAC) also known as two-stage concrete (TSC) is widely used in construction engineering for various applications. To produce PAC, a mixture of Portland cement, sand, and admixtures is injected into a mold subsequent to the deposition of coarse aggregate. This process complicates the prediction of compressive strength (CS), demanding thorough investigation. Consequently, the emphasis of this study is on enhancing the comprehension of PAC compressive strength using machine learning models. Thirteen models are evaluated with 261 data points and eleven input variables. The result depicts that xgboost demonstrates exceptional accuracy with a correlation coefficient of 0.9791 and a normalized coefficient of determination (R2) of 0.9583. Moreover, Gradient boosting (GB) and Cat boost (CB) also perform well due to its robust performance. In addition, Adaboost, Voting regressor, and Random forest yield precise predictions with low mean absolute error (MAE) and root mean square error (RMSE) values. The sensitivity analysis (SA) reveals the significant impact of key input parameters on overall model sensitivity. Notably, gravel takes the lead with a substantial 44.7% contribution, followed by sand at 19.5%, cement at 15.6%, and Fly ash and GGBS at 5.9% and 5.1%, respectively. The best fit model i.e., XG-Boost model, was employed for SHAP analysis to assess the relative importance of contributing attributes and optimize input variables. The SHAP analysis unveiled the water-to-binder (W/B) ratio, superplasticizer, and gravel as the most significant factors influencing the CS of PAC. Furthermore, graphical user interface (GUI) have been developed for practical applications in predicting concrete strength. This simplifies the process and offers a valuable tool for leveraging the model's potential in the field of civil engineering. This comprehensive evaluation provides valuable insights to researchers and practitioners, empowering them to make informed choices in predicting PAC compressive strength in construction projects. By enhancing the reliability and applicability of predictive models, this study contributes to the field of preplaced aggregate concrete strength prediction.
The EQ-5D is a common generic tool used in clinical trials and economic evaluations to evaluate the health-related quality of life as a proxy of health outcomes. To date, studies using EQ-5D-5L to evaluate the health status of cancer patients remain scarce in Malaysia. In this study, EQ-5D-5L dimensions, EQ-5D-5L index, and EQ-VAS scores were applied to assess the health status of Malaysian cancer patients. A cross-sectional study was conducted March-December 2022 to collect data relevant to the EQ-5D-5L valuation of health status via the Research Electronic Data Capture (REDCap) platform. Respondents rated their health states using EQ-5D-5L and EQ-VAS. Among the 235 respondents, the mean EQ-5D-5L index and EQ-VAS score were 0.76 (SD 0.223) and 81.06 (SD 16.36). Most of the patients reported some problems in the pain/discomfort and anxiety/depression dimensions. The level of education, stage of cancer, and comorbidity were significantly associated with better health status on EQ-5D-5L (p
Pedestrian safety, particularly for children, relies on well-designed pathways. Child-friendly pathways play a crucial role in safeguarding young pedestrians. Shared spaces accommodating both vehicles and walkers can bring benefits to pedestrians. However, active children playing near these pathways are prone to accidents. This research aims to develop an efficient method for planning child-friendly pedestrian pathways, taking into account community development and the specific needs of children. A mixed-methods approach was employed, utilizing the Datang community in Guangzhou, China, as a case study. This approach combined drawing techniques with GIS data analysis. Drawing methods were utilized to identify points of interest for children aged 2-6. The qualitative and quantitative fuzzy analytic hierarchy process assessed factors influencing pathway planning, assigning appropriate weights. The weighted superposition analysis method constructed a comprehensive cost grid, considering various community elements. To streamline the planning process, a GIS tool was developed based on the identified factors, resulting in a practical, child-friendly pedestrian pathway network. Results indicate that this method efficiently creates child-friendly pathways, ensuring optimal connectivity within the planned road network.
This study intended to explore the neuropsychological ramifications in childhood acute lymphoblastic leukemia (ALL) survivors in Malaysia and to examine treatment-related sequelae. A case-control study was conducted over a 2-year period. Seventy-one survivors of childhood ALL who had completed treatment for a minimum of 1 year and were in remission, and 71 healthy volunteers were enlisted. To assess alertness (processing speed) and essential executive functioning skills such as working memory capacity, inhibition, cognitive flexibility, and sustained attention, seven measures from the Amsterdam Neuropsychological Tasks (ANT) program were chosen. Main outcome measures were speed, stability and accuracy of responses. Mean age at diagnosis was 4.50 years (SD ± 2.40) while mean age at study entry was 12.18 years (SD ± 3.14). Survivors of childhood ALL underperformed on 6 out of 7 ANT tasks, indicating poorer sustained attention, working memory capacity, executive visuomotor control, and cognitive flexibility. Duration of treatment, age at diagnosis, gender, and cumulative doses of chemotherapy were not found to correlate with any of the neuropsychological outcome measures. Childhood ALL survivors in our center demonstrated significantly poorer neuropsychological status compared to healthy controls.
This research aims to elucidate the relationship between circular design strategies (CDS) and the economic sustainability of construction projects (ESCP), examining the mediating role of organizational culture (OC). Motivated by the imperative to develop a sustainable circular economy (CE) model in the building industry, our study focuses on a crucial dimension of CE processes. Specifically, we investigate how construction firms' organizational values shape their pursuit of desired economic outcomes within CE theory. Through a comprehensive analysis of 359 responses from a cross-sectional survey of Chinese construction firms employing Partial Least Squares-Structural Equation Modeling (PLS-SEM), our findings reveal a positive albeit weakly impactful association between CDS and ESCP. Simultaneously, OC is identified as a factor detrimental to ESCP. Notably, this study unveils the influential roles of hierarchical culture (HC) and group culture (GC) in shaping the current state of ESCP in China. Emphasizing the significance of CDS, we propose that contract administrators proactively reposition their organizations to adopt strategies conducive to achieving the necessary economic output for construction projects. The originality aspect lies in this research contributes to the existing body of knowledge by offering empirical insights into the theoretical framework, marking the first such empirical study in northern China. We conclude by critically examining research outcomes and limitations while providing insightful recommendations for future research to foster sustainable construction practices in the Chinese context.
SAG21/LEA5 is an unusual late embryogenesis abundant protein in Arabidopsis thaliana, that is primarily mitochondrially located and may be important in regulating translation in both chloroplasts and mitochondria. SAG21 expression is regulated by a plethora of abiotic and biotic stresses and plant growth regulators indicating a complex regulatory network. To identify key transcription factors regulating SAG21 expression, yeast-1-hybrid screens were used to identify transcription factors that bind the 1685 bp upstream of the SAG21 translational start site. Thirty-three transcription factors from nine different families bound to the SAG21 promoter, including members of the ERF, WRKY and NAC families. Key binding sites for both NAC and WRKY transcription factors were tested through site directed mutagenesis indicating the presence of cryptic binding sites for both these transcription factor families. Co-expression in protoplasts confirmed the activation of SAG21 by WRKY63/ABO3, and SAG21 upregulation elicited by oligogalacturonide elicitors was partially dependent on WRKY63, indicating its role in SAG21 pathogen responses. SAG21 upregulation by ethylene was abolished in the erf1 mutant, while wound-induced SAG21 expression was abolished in anac71 mutants, indicating SAG21 expression can be regulated by several distinct transcription factors depending on the stress condition.
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.