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Physical inactivity and sedentary behavior (SB) have attracted growing attention globally since they relate to noninfectious chronic diseases (NCDs) and could further result in the loss of life. This systematic literature review aimed to identify existing evidence on the efficacy of mobile health (mHealth) technology in inducing physical activity and reducing sedentary behavior for physically inactive people. Studies were included if they used a smartphone app in an intervention to improve physical activity and/or sedentary behavior for physically inactive individuals. Interventions could be stand-alone interventions or multi-component interventions, including an app as one of several intervention components. A total of nine studies were included, and all were randomized controlled trials. Two studies involved interventions delivered solely via a mobile application (stand-alone intervention) and seven studies involved interventions that used apps and other intervention strategies (multi-component intervention). Methodological quality was assessed, and the overall quality of the studies was ensured. The pooled data favored intervention in improving physical activity and reducing sedentary behavior. This review provided evidence that mobile health intervention improved physical activity and reduced sedentary behavior among inactive individuals. More beneficial effects can be guaranteed when interventions include multiple components. Further studies that maintain the effectiveness of such interventions are required to maximize user engagement and intervention efficacy.

The Mediator complex plays a key role in gene transcription. In particular, the interaction of the Mediator complex with nuclear receptors, the known transcription factors, regulates multiple nuclear receptor-mediated gene transcription pathways and associated cellular functions. Dysregulation of the interaction of the Mediator complex with nuclear receptors results in many pathological processes, such as cancer, metabolic and neuronal diseases. Thus, understanding of the mechanism by which the Mediator complex regulates the nuclear receptor-mediated transcriptional activity and biological function is crucial for therapy of both the Mediator complex- and nuclear receptor-associated diseases. In this review article, we attempt to summarize current research progress in the interaction of the Mediator complex with nuclear receptors and the associated nuclear receptor transcriptional signaling pathways, explore the clinical potential of the Mediator complex as a therapeutic target, and provide new perspectives for the treatment of diseases associated with the Mediator complex and nuclear receptors.

Background Exercise habits significantly influence the mental health of university students. However, previous research has often neglected the endogeneity issues in this context, leading to biased estimates and limiting the ability to establish a clear causal relationship. This study aimed to address endogeneity issues and investigate the causal effect of exercise habits on the mental health of university students. Methods This cross-sectional study was conducted involving 1,120 university students from China. Data on demographic characteristics, exercise habits, and mental health were collected using both online and offline questionnaires. To evaluate the mental health benefits of exercise habits, we employed both the instrumental variable (IV) approach and ordinary least squares (OLS) regression. Results The OLS estimates revealed a positive association between exercise habits and positive affect (β = 0.179, p  < .001), life satisfaction (β = 0.134, p  < .001), and self-actualization (β = 0.086, p  < .001) among university students. The IV analysis indicated that exercise habits positively influenced positive affect (β = 0.263, p  < .001), life satisfaction (β = 0.151, p  = .006 < .01), and self-actualization (β = 0.102, p  = .013 < .05). A comparison of the estimation results suggests that the OLS approach underestimates the mental health benefits of exercise habits. Conclusions This study provides preliminary causal evidence that exercise habits contribute to the promotion of mental health in university students. These findings offer valuable insights into potential preventive strategies for addressing mental health issues in this population through exercise interventions.

Macropinocytosis is a non-selective, clathrin-independent endocytic process that facilitates bulk internalization of extracellular fluid and its dissolved components (including proteins, lipids, and nucleotides) through plasma membrane remodeling and the subsequent formation of macropinosomes. This evolutionarily conserved cellular process plays important roles in nutrient supply, immune response, and metabolism. Particularly, cancer cells exploit activated macropinocytosis to obtain nutrients for supporting proliferation and survival under nutritional stress. Thus, macropinocytosis emerges as an important target for cancer therapy. Furthermore, as activated macropinocytosis constitutively uptakes extracellular fluids into cancer cells, it has been utilized for delivering anti-tumor drugs in cancer therapy. In this review, we systematically addressed progress in cancer therapeutic strategies in both targeting macropinocytosis and utilizing macropinocytosis as an anti-cancer drug delivering tool, including therapeutic applications with macropinocytosis inhibitors; metabolic modulators; methuosis (the macropinocytosis-associated cell death) inducers; and macropinocytosis-mediated anti-cancer drug delivery strategies such as nanoparticles, viral vectors, extracellular vesicles, and targeted conjugates. We conclude that developing targeted macropinocytosis anti-cancer drugs and exploring macropinocytosis-dependent anti-cancer drug delivery systems open new avenues for cancer therapy.

The feedback spring rod of the armature assembly was eliminated in the double-redundancy electro-hydraulic servo valve (DREHSV), which employed a redundant design in contrast to the typical double-nozzle flapper electro-hydraulic servo valve (DNFEHSV). The pilot stage was mainly composed of four torque motors, and the double-system spool was adopted in the power stage. Consequently, the difficulty of spool displacement control was increased. By artificially changing the structural parameters of the simulation model in accordance with the theoretical analysis through AMESim, this paper aimed to study the dynamics and static characteristics of the DREHSV. The advantage of redundant design was further demonstrated by disconnecting working coils and setting the different worn parts of the spool. On the test bench, the necessary experiments were performed. Through simulation, it was discovered that when the clogged degree of the nozzle is increased, the zero bias value increases, the pressure and flow gain remain unchanged, and the internal leakage decreases. The pressure gain changes very little, the flow gain close to the zero position grows, the zero leakage increases significantly, and the pilot stage leakage changes very little as a result of the wear of the spool throttling edge. The basic consistency between the simulation curves and the experimental findings serve to validate the accuracy of the AMESim model. The findings can serve as a theoretical guide for the design, debugging, and maintenance of the DREHSV. The simulation model is also capable of producing a large amount of sample data for DREHSV fault diagnosis using a neural network.

China has witnessed massive economic development in the past few decades and one of the consequences of increased urbanization has been the reduction of physical activity in the adult population. In light of this trend, the researcher has conducted this study with the aim of examining how the low physical activity levels lead to exercise procrastination in the longer run by looking at data collected from Chinese adults that have at least a year or so experience of athletics of any type. The variables that were studied for this purpose in this research include the low level of physical activity as the independent variable, exercise procrastination as dependent and three mediating variable i.e. Low level of perceived self-efficacy in the athletes, perceived task difficulty in the athletes and negative affectivity in the athletes. The researcher conducted an in-depth literature review that led to the formation of 4 hypotheses for direct and indirect relationships. The researcher used positivism to conduct this quantitative research. The nature of research is exploratory with the random sampling technique used to conduct the survey. . Moreover, data is collected through an online questionnaire. The collected data was used to test the hypotheses through statistical and analytical procedures using SPSS. Various tests were applied including descriptive tests, KMO tests, CFA and SEM. The results of SEM showed that the direct impact of low physical activity was insignificant on exercise procrastination. As for the indirect effects, the mediation of negative affect and low self-efficacy were significant while that of perceived task difficulty was insignificant. In addition, the researcher has presented the limitations as well as the future directions that can be adopted in future researches.

PurposeAs a highly knowledge-intensive activity, digitalization is changing the construction industry landscape and is encouraging construction firms to explore the transformation. This study establishes a new theoretical model aimed at examining the impact of three types of intellectual capital (IC) on digitalization through the lens of knowledge-based view and explores how IC and digitalization influence sustainability performance from the triple bottom line principles.Design/methodology/approachA questionnaire survey was conducted to collect data from Chinese construction firms using convenience sampling. A total of 181 valid responses were obtained. Then, a partial least squares structural equation modelling (PLS-SEM) technique was executed through Smart PLS 3.0 software. The measurement model was assessed to ensure reliability and validity, and the structural model was analysed to test the proposed hypotheses.FindingsThe empirical results confirm the positive impact of IC on digitalization and digitalization on sustainability performance. Moreover, digitalization plays a significant mediating role in the relationship between IC and sustainability performance.Originality/valueThe results provide empirical evidence supporting the different roles of IC and digitalization in improving sustainability. The findings contribute to enhancing the understanding of digitalization practices from the perspective of IC and provide theoretical and managerial implications for sustainability issues in the context of the construction industry.

Background and objectives Antibody-negative autoimmune encephalitis (AE) is a form of encephalitis characterized by the absence of detectable autoimmune antibodies, despite immunological evidence. However, data on management of patients with antibody-negative AE in the intensive care unit (ICU) are limited. This study aimed to explore the characteristics and subtypes of antibody-negative AE, assess the effects of immunotherapy, and identify factors independently associated with poor functional outcomes in patients requiring intensive care. Methods This retrospective, single-center study analyzed consecutive adult patients diagnosed with antibody-negative AE and admitted to the ICU of a large tertiary hospital between 2019 and 2023. Multivariate regression analysis was used to identify factors linked to poor functional outcomes six months after ICU admission, as defined by a modified Rankin Scale score of 3–6. Generalized linear mixed models were applied to evaluate the effect of immunotherapy on longitudinal changes in the Clinical Assessment Scale in Autoimmune Encephalitis and modified Rankin Scale scores. Results Of the 1220 patients with severe encephalitis admitted to the ICU, 107 were diagnosed with antibody-negative AE and included in the analysis. Six months after ICU admission, 67 patients (62.6%) had poor functional outcomes, including 28 deaths (26.2%). Factors independently associated with poor outcomes were high-dose corticosteroid therapy (odds ratio [OR] 8.734, 95% confidence interval [CI] 2.483–30.717), older age at onset (OR 1.063, 95% CI 1.028–1.099), acute respiratory failure at ICU admission (OR 10.931, 95% CI 2.062–57.751), and dyskinesia/dystonia (OR 14.109, 95% CI 1.336–148.957). The generalized linear mixed model also indicated that high-dose corticosteroid therapy was associated with poorer longitudinal outcomes. Conclusions While high-dose corticosteroids are frequently used to treat AE, their risks may outweigh their benefits in severe antibody-negative AE cases. Older patients and those with dyskinesia/dystonia or respiratory failure, may require more careful monitoring and timely intervention for improved outcomes. However, prospective validation of these findings is necessary to confirm their applicability and guide future treatment strategies.

The quality and productivity of die castings are directly influenced by the injection system performance of the die-casting machine, making advanced performance monitoring of paramount importance. However, with the present technology, it is impossible to discriminate between the hydraulic components that influence the operation of a pressured injection system due to their sheer number and complexity. On the other hand, it is challenging to pinpoint the pressured injection system while it is in the poor performance stage due to the complexity and variety of the working conditions in actual production as well as the lack of data. In this paper, the hydraulic principle of the pressure injection system is examined, and a simulation model of the pressure injection system is built by adjusting the values of various components and running simulation experiments to produce a sample set. The sample set is fed into an intelligent evaluation approach that combines BP neural networks, convolutional neural networks (CNN), and long short-term memory networks (LSTM). The above intelligent algorithm is used to obtain both the performance index of the pressurized injection system and the components that lead to the low-performance index. The Dempster-Shafer (DS) theory is used to perform information fusion on the component classification results, and a new neural network is designed to perform information fusion on the performance metric evaluation results. The combined results are the final classification and regression results. Later, simulation tests are used to compare and validate the method. The findings demonstrate that the proposed intelligent algorithm outperforms previous algorithms in terms of accuracy and stability. In terms of component classification, the average accuracy for BP-LSTM is 87.83%, CNN-LSTM is 90.63%, after stacking it is 93.31%, and the proposed method is 95.67%. For performance evaluation, the average R2 of BP-LSTM is 0.88 and the average MAE is 3.09; the average R2 of CNN-LSTM is 0.908 and the average MAE is 2.64; and the average R2 of the proposed method is 0.947 and the average MAE is 1.86.

Natural fibers exhibit noticeable variations in their cross-sections, and measurements assuming a circular cross-section can lead to errors in the values of their properties. Providing more accurate geometric information of fiber cross-sections is a key challenge. Based on microscopic images of natural fiber structures, this paper proposes a natural fiber microstructure detection method based on the CA-DeepLabv3+ network model. The study investigates a natural fiber microstructure image segmentation algorithm that uses MobileNetV2 as the feature extraction backbone network, optimizes the Atrous Spatial Pyramid Pooling (ASPP) module through cascading, and embeds an Efficient Multi-scale Attention (EMA) mechanism. The results show that the algorithm proposed in this paper can accurately segment the microstructures of multiple types of natural fibers, achieving an average pixel accuracy (mPA) of 95.2% and a mean Intersection over Union (mIoU) of 90.7%.