Utilising standard samples instead of randomly collected food waste in composting: Implementation strategy and feasibility evaluation.

Randomly collected food waste results in inaccurate experimental data with poor reproducibility for composting. This study investigated standard food waste samples as replacements for randomly collected food waste. A response surface methodology was utilised to analyse data from a 28-day compost process optimisation experiment using collected food waste, and the optimal combination of composting parameters was derived. Experiments using different standard food waste samples (high oil and salt, high oil and sugar, balanced diet, and vegetarian) were conducted for 28 days under optimal conditions. The ranking of differences between the standard samples and collected food waste was vegetarian > balanced diet > high oil and sugar > high oil and salt. Statistical analysis indicated t-tests for increased oil and salt samples and collected food waste were not significant, and Cohen's d effect values were minimal. High oil and salt samples can be used as replacements for collected food waste in composting experiments.

Personalized smart voice-based electronic prescription for remote at-home feedback management in cardiovascular disease rehabilitation: a multi-center randomized controlled trial.

Objective: To investigate the quality and efficacy of remote at-home rehabilitation for patients with cardiovascular disease (CVD) using personalized smart voice-based electronic prescription, and further explore the standardized health management mode of remote family cardiac rehabilitation. Trial design: A multicenter, randomized (1:1), non-blind, parallel controlled study. Methods: A total of 171 patients with CVD who were admitted to 18 medical institutions in China from April 2021 to October 2022 were randomly divided into a treatment group (86 cases) and a control group (85 cases) in a non-blinded experiment, based on the sequence of enrollment. The control group received routine at-home rehabilitation training, and the treatment group received remote feedback-based at-home cardiac rehabilitation management based on routine at-home rehabilitation training. The primary outcome was the difference in VO2peak (mL/min/kg) after 12 weeks. A linear mixed model was developed with follow-up as the dependent variable. Age and baseline data were utilized as covariates, whereas hospital and patient characteristics were adjusted as random-effect variables. As the linear mixed model can accommodate missing data under the assumption of random missing data, there was no substitute missing value for quantitative data. Results: A total of 171 participants, with 86 in the experimental group and 85 in the control group, were included in the main analysis. The analysis, which used linear mixing model, revealed significant differences in cardiopulmonary function indexes (VO2/kg peak, VO2peak, AT, METs, and maximum resistance) at different follow-up time (0, 4, and 12 weeks) in the experimental group (p < 0.05). In the control group, there was no significant difference in cardiopulmonary values at different follow-up time (0, 4, and 12 weeks; p > 0.05). VO2/kg peak (LS mean 1.49, 95%CI 0.09-2.89, p = 0.037) and other indicators of cardiopulmonary function (p < 0.05) were significantly different between the experimental group and the control group at week 12. The results were comparable in the complete case analysis. Conclusion: The remote home cardiac rehabilitation management mode using personalized smart voice-based electronic prescription provides several benefits to patients, including improvements in muscle strength, endurance, cardiopulmonary function, and aerobic metabolism. It also helps reduce risk factors for cardiovascular disease and enhances patients' self-management abilities and treatment compliance.Clinical trial registration: http://www.chictr.org.cn, identifier ChiCTR2100044063.

Prediction of cooling effect of constant temperature community bin based on BP neural network.

In order to explore the influence of outdoor microclimate on the cooling effect of constant temperature community bin, the temperature prediction model was predicted. The temperature and microclimate data sets of the community bin were collected in summer from May 2021 to September 2021. The climatic characteristics included cloudy and sunny conditions, and the environmental factors included outdoor temperature, air speed, air relative humidity, and solar radiation intensity. Stepwise regression method was used to test the significance of environmental factors, and the corresponding regression equation was obtained. BP neural network was used to establish temperature prediction models under cloudy and sunny conditions, respectively. The results showed that the coefficient of determination (R2) of the two models was above 0.8, and the environmental factors with significant influence were screened out. The root mean square error (RMSE) between the training value and the actual value established by BP neural network was 0.83 °C, and the determination coefficient (R2) was 0.968. Under sunny conditions, the root mean square error (RMSE) of predicted value and measured value was 0.65 °C, and the determination coefficient (R2) was 0.982. According to the analysis of the sample data, it showed that the BP neural network was more accurate than stepwise regression, and could be used to predict the temperature of community bin, which provided model basis for the practical application of intelligent temperature control community bin in summer.

Design and parameter optimization of community bins based on evaporative cooling.

Aiming at the challenge of bad odors emanating from rotting perishable kitchen waste in summer within the garbage collection chain, the fan-pad system, which is widely used in agricultural facility systems, was applied to the design of community bins. In this regard, a community bin based on a fan-pad operating mechanism was developed. Computational fluid dynamics (CFD) was then used to numerically analyze the cooling effect of the community bin. Under conditions comprising of an outdoor temperature of 35 °C, an installation height of the wet curtain of the cooling system h1, an installation height of the fan h2, and varying distance d between the trash can and the wet curtain, and the average temperature T of 16 temperature measurement points was analyzed. Design-Expert software was used to design the Box-Behnken Design (BBD) experiment, and regression analysis was carried out. Under the optimized parameter combination, the average temperature T of the temperature measurement point was 24.82 °C by simulation. Through field test verification, it was established that the maximum relative error between the temperature of each measuring point and the simulation result was 1.54%, and the average temperature T fluctuated within the range of 0.5 °C of the simulation value.Implications Statement: By creatively integrating the agricultural apparatus with our daily community bin, our research presents great interdisciplinary originality and potential in wide application. Meanwhile, our research also gives a new solution to saving the energy wasted by community dust room based on air conditioner cooling. We hold the believe that our research can arrest great attention of scholars, managers, and people interested in sanitation apparatus. Additionally, our research also provides more theoretical and technical support for the design and application of sanitation collecting apparatus.

Sinomenine prevents the development of cardiomyopathy in diabetic rats by inhibiting inflammatory responses and blocking activation of NF-κB.

Diabetic cardiomyopathy is a severe complication of diabetes mellitus (DM). The goal of current work was to study the effects of sinomenine on streptozotocin-induced cardiomyopathy in rats. DM in rats was induced by intraperitoneal injection of streptozotocin. Cardiac function was evaluated by measuring left ventricle end-diastolic diameter, left ventricle end-systolic diameter and ejection fraction. Cardiac inflammation was evaluated by the degree of infiltration of T lymphocytes and the levels of pro-inflammatory cytokines. Sinomenine attenuated diabetic symptoms without affecting plasma glucose. Cardiac dysfunction in the sinomenine-treated diabetic rats was significantly improved, as reflected by decreased levels of left ventricle end-diastolic diameter, left ventricle end systolic diameter and an increased level of ejection fraction. Sinomenine observably reduced cardiomyocyte hypertrophy in DM rats. Moreover, sinomenine reduced infiltration of CD3+ and CD68+ positive cells and decreased the levels of tumor necrosis factor-α, interlukin-1 and interlukin-6. Finally, sinomenine-treated rats showed a reduced expression of NF-κB and an increased expression of IκB in the myocardium compared with the myocardium of untreated diabetic rats. Our results indicate sinomenine significantly improves cardiac function in diabetic rats, which may be attributed to the deactivation of NF-κB and the blockade of inflammatory cytokine-mediated immune reactions.