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Background With the gradual deepening of the comprehensive reform of community health services, the prevention and control of single diseases for the entire population in the community is also constantly being optimized, However, there is still a lack of appropriate evaluation methods in the community to reflect its prevention and control effectiveness evaluation. Objective By analyzing and exploring the cost effect of the existing whole-population prevention and control measures of osteoporosis in Fenglin community, from 2016 to 2022, this paper answers the initial results and possible problems of the whole-population prevention and control of single disease in the community. Methods This study conducted a cost-effectiveness analysis on 4 293 community residents who received osteoporosis prevention and treatment in Fenglin community from 2016 to 2022. Divide the research object into three states based on bone density values: healthy, low bone mass, and osteoporosis, and construct a Markov model to analyze the influencing factors of different state transitions. And based on the predicted values of the Markov model combined with quality adjusted life years (QALY) , the increment of quality adjusted life years (QALY) is calculated. All costs invested in prevention and control work from 2016 to 2022 are counted, and the effectiveness of prevention and control is evaluated by the cost/quality adjusted life year increment ratio. Quality adjusted life years (QALY) are obtained by calculating the health utility value and expected life determined through literature search. Results The total cost of osteoporosis prevention and treatment in Fenglin community was 33 814 102.15 yuan. The total quality-adjusted life years of 4 293 community osteoporosis prevention and treatment population were 77 098.288 9 at the first diagnosis, the average per capita was 17.959, and the standard deviation was 9.34. At the second diagnosis, the total quality-adjusted life years were 79 616.936 1, the mean per capita was 18.546, the standard deviation was 9.342, and the difference between the two diagnoses was 2 518.647 2. The incremental cost-effectiveness ratio (ICER) is 2 132.907 0 yuan /QALY, and the incremental cost-effectiveness ratio (ICER) is less than 1 times (66 965.10 yuan) per capita GDP, indicating that the intervention scheme is fully cost-effective. Conclusion This study combined Markov model and quality-adjusted life years (QALY) to make a preliminary evaluation of the prevention and treatment effect of osteoporosis in Fenglin community. The results showed that the intervention program of osteoporosis prevention and treatment in Fenglin community was worth investing, and provided a certain basis for the accurate prevention and treatment decision of osteoporosis in the future.

Due to the severity of resource consumption and uncertainty in orders, new challenges have arisen for production scheduling in enterprises. This paper studies the scheduling problem of minimising the total weighted tardiness for jobs with fuzzy processing times and due dates on identical parallel machines with resource constraint. To address this research problem, we first propose methods to calculate the upper bound of resource consumption and the maximum number of machines that can be used, effectively reducing the search space and improving the algorithm's efficiency. Secondly, a local search algorithm based on job swapping is proposed to enhance the algorithm's performance. Then, repair algorithms based on job removal and job swapping are designed to repair infeasible solutions. Finally, we propose a fuzzy genetic algorithm (FGALS) to solve the problem based on the above elements. Through extensive simulation experiments, the effectiveness and efficiency of the FGALS algorithm are verified by comparing it with commercial solver Gurobi and several meta-heuristic algorithms. [ABSTRACT FROM AUTHOR]

In order to study the optimization strategy of chemical instrumentation analysis methods, it can make the chemical instrumentation analysis methods more optimized. This paper proposes an improved sparrow search algorithm MSSA based on the ADDIE model, and a decision tree analysis method under random forest is introduced to assist chemical instrumentation analysis. The optimal prediction value of the algorithm is judged analytically, and adaptive operations change the size of the neighbourhood space to obtain the optimal strategy of the algorithm by a merit-seeking mechanism. The decision tree and evaluation indicators are then constructed with the decision tree under a random forest algorithm, and the indicators are used to select the optimisation path. From the experiments, it can be seen that the improved sparrow search algorithm MSSA strategy based on the ADDIE model can improve the optimisation ability of the algorithm. Furthermore, the MSSA algorithm also shows excellent performance in the experiments and obtains the best coverage effect. The coverage rate of the optimised chemical instrumentation analysis method reached 94.55%, which was 9.87%, 4.15%, 6.68%, 3.22% and 7.28% higher than other types of algorithms, respectively. It illustrates that the improved MSSA algorithm under the ADDIE model can also obtain better optimisation capability for practical chemical instrumental analysis method optimisation problems. The evaluation index complements this under the decision tree, which shows that the model is more conducive to the analytical capability of chemical instruments. It also provides a direction for solving the problem of choosing the optimal analytical method in chemical instrumentation analysis.

In order to explore the applicability of random forest algorithm in the detection of alcoholic foreign matter and to improve the identification of alcoholic products. In this paper, based on the random forest algorithm, the feature values of random forest are fuzzified using the fuzzy comprehensive evaluation method, and the application model of alcohol foreign body detection anomaly based on random forest fuzzy tree nodes is established. And the reliability of the random forest algorithm is verified by the quantitative analysis of the three test indexes (i.e., recall, precision, and accuracy) and the anomaly proportion coefficient of the test data set by the algorithm in this paper. The results show that the recall, precision, and accuracy of the random forest-based anomaly detection for alcoholic beverage foreign objects are 99.65%, 95.49%, and 97.19%, respectively, and the average value of the three eigenvalues of this paper’s algorithm is 97.44%, which is 59.89%, 43.98%, and 1.92% higher than the other three algorithms, respectively. In terms of the anomaly proportion coefficient, the stability of the algorithm in this paper is the best when the coefficient takes values between [0.2, 0.6]. It can be shown that the algorithm based on random forest can be applied to the foreign matter detection of wine, and through the detection of anomalies, the quality of the wine currently undergoing detection can be clearly and explicitly analyzed, which also provides a new direction for the application of the random forest algorithm.

Background: The impact of and countermeasures for Ureaplasma spp. in neonates remain controversial. The aim of this study was to evaluate the associated perinatal factors that can predict the likelihood of respiratory tract Ureaplasma spp. colonization and analyze the subsequent clinical course of affected infants, thereby providing the rationale for their diagnosis, treatment, and future study. Methods: This was a retrospective observational study of infants born at a gestational age (GA) of less than 32 weeks. Results: The prevalence of respiratory tract Ureaplasma spp. colonization was 25.8% (75/291), and it increased with a decrease in GA and birth weight (BW). Maternal vaginal Ureaplasma spp. colonization increased the risk of neonatal Ureaplasma spp. colonization, with an OR of 7.8 (95% CI: 3.1, 20.0). Infants with Ureaplasma spp. colonization had a higher white blood cell (WBC) count, normal C-reactive protein (CRP) level, and higher failure rate of weaning from mechanical ventilation (30.7% vs. 17.1%, p = 0.014); they also suffered more from interstitial pneumonia (20.0% vs. 5.6%, p < 0.001) and bronchopulmonary dysplasia (36.0% vs. 13.4%, p < 0.001). Infants receiving anti-Ureaplasma spp. treatment had a lower GA, lower BW, and more severe respiratory syndromes. However, the difference in respiratory manifestation became insignificant after adjusting for GA. Conclusions: GA and maternal vaginal Ureaplasma spp. colonization could be used to predict neonatal respiratory tract Ureaplasma spp. colonization. An elevated WBC count combined with normal CRP is a good marker of Ureaplasma spp. colonization/infection. It is conventional practice to start anti-Ureaplasma spp. treatment when infants present with a deteriorated respiratory condition. This practice warrants further investigation considering GA as a predominant intermediate variable. [ABSTRACT FROM AUTHOR]

Objectives: Network pharmacology is essential for understanding the multi-target and multi-pathway therapeutic mechanisms of traditional Chinese medicine. This study aims to evaluate the influence of database quality on target identification and to explore the therapeutic potential of rhynchophylline (Rhy) in treating overactive bladder (OAB). Methods: An OAB dataset was constructed through extensive literature screening. Using this dataset, we applied network pharmacology to predict potential targets for Rhy, which is known for its therapeutic effects but lacks a well-defined target profile. Predicted targets were validated through in vitro experiments, including DARTS and CETSA. Results: Our analysis identified Rhy as a potential modulator of the M3 receptor and TRPM8 channel in the treatment of OAB. Validation experiments confirmed the interaction between Rhy and these targets. Additionally, the GeneCards database predicted other targets that are not directly linked to OAB, corroborated by the literature. Conclusions: We established a more accurate and comprehensive dataset of OAB targets, enhancing the reliability of target identification for drug treatments. This study underscores the importance of database quality in network pharmacology and contributes to the potential therapeutic strategies for OAB. [ABSTRACT FROM AUTHOR]

As a departure from previous research that takes social ventures as a distinct organizational type, this study investigates the relationship between the pro‐market institutions in a country and the degree of hybridity in social ventures, focusing on the dimension of organizational goals. Additionally, it examines the contingent effects of organizational activities, such as the novelty of market offering and the implementation of social performance measurement. Combining Global Entrepreneurship Monitor data in 2009 and 2015 with other cross‐national databases, we test our theoretical predictions using 3648 startup social ventures across 42 countries. We find that pro‐market institutions have an inverted U‐shaped effect on the degree of hybridity in social ventures. Furthermore, the novelty of market offering and social performance measurement attenuate the impact of pro‐market institutions on organizational hybridity by shifting the inverted U‐shape to relatively negative and linear. Through this cross‐level empirical exploration, we develop a richer explanation of organizational hybridity and contribute to the growing literature on social ventures and hybrid organizations. [ABSTRACT FROM AUTHOR]

PM2.5 pollution poses an important threat to the atmospheric environment and human health. To precisely forecast PM2.5 concentration, this study presents an innovative combined model: EMD-SE-GWO-VMD-ZCR-CNN-LSTM. First, empirical mode decomposition (EMD) is used to decompose PM2.5, and sample entropy (SE) is used to assess the subsequence complexity. Secondly, the hyperparameters of variational mode decomposition (VMD) are optimized by Gray Wolf Optimization (GWO) algorithm, and the complex subsequences are decomposed twice. Next, the sequences are divided into high-frequency and low-frequency parts by using the zero crossing rate (ZCR); the high-frequency sequences are predicted by a convolutional neural network (CNN), and the low-frequency sequences are predicted by a long short-term memory network (LSTM). Finally, the predicted values of the high-frequency and low-frequency sequences are reconstructed to obtain the final results. The experiment was conducted based on the data of 1009A, 1010A, and 1011A from three air quality monitoring stations in the Beijing area. The results indicate that the R2 value of the designed model increased by 2.63%, 0.59%, and 1.88% on average in the three air quality monitoring stations, respectively, compared with the other single model and the mixed model, which verified the significant advantages of the proposed model. [ABSTRACT FROM AUTHOR]

Background: N1-Methyladenosine (m1A) is an abundant modification of transcripts regulating mRNA structure and translation efficiency. However, the characteristics and biological functions of mRNA m1A modification in adult hippocampal neurogenesis remain enigmatic. Results: We found that m1A demethylase Alkbh3 was dramatically enriched in neurons and neuronal genesis. Functionally, depletion of Alkbh3 in neural stem cells (NSCs) significantly decreased m1A modification, neuronal differentiation and proliferation coupling with increasing gliogenesis, whereas overexpressing Alkbh3 facilitated neuronal differentiation and proliferation. Mechanistically, the m1A demethylation of Mmp15 mRNA by Alkbh3 improved its RNA stability and translational efficacy, which promoted neurogenesis. Therapeutically, the silencing of Alkbh3 reduced hippocampal neurogenesis and impaired spatial memory in the adult mice. Conclusions: We reveal a novel function of m1A demethylation on Mmp15 mRNA in Alkbh3-mediated neurogenesis, which shed light on advancing Alkbh3 regulation of neurogenesis as a novel neurotherapeutic strategy. [ABSTRACT FROM AUTHOR]

Rural tourism is a new driving force for achieving rural revitalization and development, promoting rural economic prosperity, and serving as a new industrial approach to achieving the transformation and upgrading of farmers' livelihoods. This paper focuses on Manas County as the research subject and employs farmer questionnaire interviews and participatory rural appraisal methods to categorize villages into four types: "scenic area-dependent" villages, "industry-dependent" villages, "folklore-dependent" villages, and "suburban-dependent" villages. Based on the sustainable livelihood analysis framework proposed by the Department for International Development, we developed a sustainable livelihood framework for farm households in Manas County and analyzed the effects of rural tourism on farm households' livelihood capital and livelihood strategies as the watershed of the rural tourism takes shape, taking livelihood capital and livelihood strategies as the entry point. The factors influencing the livelihood capital and livelihood options of farm households in the context of rural tourism are analyzed. The results show that: (1) The overall livelihood capital of farmers engaging in rural tourism is significantly greater than that of farmers not participating in rural tourism. Additionally, variations exist in the livelihood capital of different types of rural tourism within villages. (2) Participation in rural tourism significantly influences farmers' choices of livelihood strategies. Compared with individuals who do not engage in rural tourism, those involved in rural tourism are more likely to opt for self-management livelihood strategies. The proportion of self-managed farmers in villages based around scenic areas is the highest. (3) The effect of rural tourism on farm households in Manas County is generally positive, and various types of villages yield different impact effects. (4) Participation in rural tourism significantly increases the possibility of farmers choosing self-management livelihood strategies, while it reduces the possibility of farmers choosing agriculture-oriented livelihood strategies. In all villages, except those dependent on industry, the decision to engage in rural tourism significantly impacts farmers' selection of self-management livelihood strategies. [ABSTRACT FROM AUTHOR]