deepAFT: A nonlinear accelerated failure time model with artificial neural network.

The Cox regression model or accelerated failure time regression models are often used for describing the relationship between survival outcomes and potential explanatory variables. These models assume the studied covariates are connected to the survival time or its distribution or their transformations through a function of a linear regression form. In this article, we propose nonparametric, nonlinear algorithms (deepAFT methods) based on deep artificial neural networks to model survival outcome data in the broad distribution family of accelerated failure time models. The proposed methods predict survival outcomes directly and tackle the problem of censoring via an imputation algorithm as well as re-weighting and transformation techniques based on the inverse probabilities of censoring. Through extensive simulation studies, we confirm that the proposed deepAFT methods achieve accurate predictions. They outperform the existing regression models in prediction accuracy, while being flexible and robust in modeling covariate effects of various nonlinear forms. Their prediction performance is comparable to other established deep learning methods such as deepSurv and random survival forest methods. Even though the direct output is the expected survival time, the proposed AFT methods also provide predictions for distributional functions such as the cumulative hazard and survival functions without additional learning efforts. For situations where the popular Cox regression model may not be appropriate, the deepAFT methods provide useful and effective alternatives, as shown in simulations, and demonstrated in applications to a lymphoma clinical trial study.

Associations of meteorological factors and dynamics of scrub typhus incidence in South Korea: A nationwide time-series study.

Scrub typhus, also known as Tsutsugamushi disease, is a climate-sensitive vector-borne disease that poses a growing public health threat. However, studies on the association between scrub typhus epidemics and meteorological factors in South Korea need to be complemented. Therefore, we aimed to analyze the association among ambient temperature, precipitation, and the incidence of scrub typhus in South Korea. First, we obtained data on the weekly number of scrub typhus cases and concurrent meteorological variables at the city-county level (Si-Gun) in South Korea between 2001 and 2019. Subsequently, a two-stage meta-regression analysis was conducted. In the first stage, we conducted time-series regression analyses using a distributed lag nonlinear model (DLNM) to investigate the association between temperature, precipitation, and scrub typhus incidence at each location. In the second stage, we employed a multivariate meta-regression model to combine the association estimates from all municipalities, considering regional indicators, such as mite species distribution, Normalized Difference Vegetation Index (NDVI), and urban-rural classification. Weekly mean temperature and weekly total precipitation exhibited a reversed U-shaped nonlinear association with the incidence of scrub typhus. The overall cumulative association with scrub typhus incidence peaked at 18.7 C° (with RRs of 9.73, 95% CI: 5.54-17.10) of ambient temperature (reference 9.7 C°) and 162.0 mm (with RRs of 1.87, 95% CI: 1.02-3.83) of precipitation (reference 2.8 mm), respectively. These findings suggest that meteorological factors contribute to scrub typhus epidemics by interacting with vectors, reservoir hosts, and human behaviors. This information serves as a reference for future public health policies and epidemiological research aimed at controlling scrub typhus infections.

Short-term exposure to extreme temperature and outpatient visits for respiratory diseases among children in the northern city of China: a time-series study.

BACKGROUND: Although studies have indicated that extreme temperature is strongly associated with respiratory diseases, there is a dearth of studies focused on children, especially in China. We aimed to explore the association between extreme temperature and children's outpatient visits for respiratory diseases and seasonal modification effects in Harbin, China. METHODS: A distributed lag nonlinear model (DLNM) was used to explore the effect of extreme temperature on daily outpatient visits for respiratory diseases among children, as well as lag effects and seasonal modification effects. RESULTS: Extremely low temperatures were defined as the 1st percentile and 2.5th percentile of temperature. Extremely high temperatures were defined as the 97.5th percentile and 99th percentile of temperature. At extremely high temperatures, both 26 °C (97.5th) and 27 °C (99th) showed adverse effects at lag 0-6 days, with relative risks (RRs) of 1.34 [95% confidence interval (CI): 1.21-1.48] and 1.38 (95% CI: 1.24-1.53), respectively. However, at extremely low temperatures, both - 26 °C (1st) and - 23 °C (2.5th) showed protective effects on children's outpatient visits for respiratory diseases at lag 0-10 days, with RRs of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.95), respectively. We also found seasonal modification effects, with the association being stronger in the warm season than in the cold season at extremely high temperatures. CONCLUSIONS: Our study indicated that extremely hot temperatures increase the risk of children's outpatient visits for respiratory diseases. Efforts to reduce the exposure of children to extremely high temperatures could potentially alleviate the burden of pediatric respiratory diseases, especially during the warm season.

The impact of apparent temperature on the emergency visits for traumatic fractures in Hangzhou, China.

BACKGROUND: Traumatic fractures occur frequently worldwide. However, research remains limited on the association between short-term exposure to temperature and traumatic fractures. This study aims to explore the impact of apparent temperature (AT) on emergency visits (EVs) due to traumatic fractures. METHODS: Based on EVs data for traumatic fractures and the contemporary meteorological data, a generalized Poisson regression model along with a distributed lag nonlinear model (DLNM) were undertaken to determine the impact of AT on traumatic fracture EVs. Subgroup analysis by gender and age and sensitivity analysis were also performed. RESULTS: A total of 25,094 EVs for traumatic fractures were included in the study. We observed a wide "J"-shaped relationship between AT and risk of traumatic fractures, with AT above 9.5 °C positively associated with EVs due to traumatic fractures. The heat effects became significant at cumulative lag 0-11 days, and the relative risk (RR) for moderate heat (95th percentile, 35.7 °C) and extreme heat (99.5th percentile, 38.8 °C) effect was 1.311 (95% CI: 1.132-1.518) and 1.418 (95% CI: 1.191-1.688) at cumulative lag 0-14 days, respectively. The cold effects were consistently non-significant on single or cumulative lag days across 0-14 days. The heat effects were higher among male and those aged 18-65 years old. The sensitivity analysis results remained robust. CONCLUSION: Higher AT is associated with cumulative and delayed higher traumatic fracture EVs. The male and those aged 18-65 years are more susceptible to higher AT.

Exploring the effects and interactions of meteorological factors on the incidence of scrub typhus in Ganzhou City, 2008-2021.

BACKGROUND: Scrub typhus poses a substantial risk to human life and wellbeing as it is transmitted by vectors. Although the correlation between climate and vector-borne diseases has been investigated, the impact of climate on scrub typhus remains inadequately comprehended. The objective of this study is to investigate the influence of meteorological conditions on the occurrence of scrub typhus in Ganzhou City, Jiangxi Province.  METHODS: From January 1, 2008 to December 31, 2021, we gathered weekly records of scrub typhus prevalence alongside meteorological data in Ganzhou city. In order to investigate the correlation between meteorological factors and scrub typhus incidence, we utilized distributional lag nonlinear models and generalized additive models for our analysis. RESULTS: Between 2008 and 2021, a total of 5942 cases of scrub typhus were recorded in Ganzhou City. The number of females affected exceeded that of males, with a male-to-female ratio of 1:1.86. Based on the median values of these meteorological factors, the highest relative risk for scrub typhus occurrence was observed when the weekly average temperature reached 26 °C, the weekly average relative humidity was 75%, the weekly average sunshine duration lasted for 2 h, and the weekly mean wind speed measured 2 m/s. The respective relative risks for these factors were calculated as 3.816 (95% CI: 1.395-10.438), 1.107 (95% CI: 1.008-1.217), 2.063 (95% CI: 1.022-4.165), and 1.284 (95% CI: 1.01-1.632). Interaction analyses showed that the risk of scrub typhus infection in Ganzhou city escalates with higher weekly average temperature and sunshine duration. CONCLUSION: The findings of our investigation provide evidence of a correlation between environmental factors and the occurrence of scrub typhus. As a suggestion, utilizing environmental factors as early indicators could be recommended for initiating control measures and response strategies.

Emergency room visits (ERVs) among occupational groups associated with ambient conditions in Taiwan.

OBJECTIVE: This population-based study explored emergency room visits (ERVs) from all-causes, circulatory and respiratory diseases among different occupational groups in Taiwan associated with ambient average temperature. METHOD: Daily area-age-sex specific ERVs records were obtained from the Taiwan's Ministry of Health and Welfare from 2009 to 2018. Distributed lag-nonlinear model (DLNM) was used to estimate the exposure-response relationships between daily average temperature and ERVs for all-causes, circulatory and respiratory diseases by occupational groups. Random-effects meta-analysis was used to pool the overall cumulative relative risk (RR) and 95% confidence interval (CI). RESULTS: The exposure-response curves showed ERVs of all-cause and respiratory diseases increased with rising temperature across all occupational groups. These effects were consistently stronger among younger (20-64 years old) and outdoor workers. In contrast, ERVs risk from circulatory diseases increased significantly during cold snaps, with a substantially higher risk for female workers. Interestingly, female workers, regardless of indoor or outdoor work, consistently showed a higher risk of respiratory ERVs during hot weather compared to males. Younger workers (20-64 years old) exhibited a higher risk of ERVs, likely due to job profiles with greater exposure to extreme temperatures. Notably, the highest risk of all-causes ERVs was observed in outdoor male laborers (union members), followed by farmers and private employees, with the lowest risk among indoor workers. Conversely, female indoor workers and female farmers faced the highest risk of respiratory ERVs. Again, female farmers with consistent outdoor exposure had the highest risk of circulatory ERVs during cold conditions. CONCLUSION: Our findings highlighted the complexity of temperature-related health risks associated with different occupational contexts. The population-level insights into vulnerable occupational groups could provide valuable comprehension for policymakers and healthcare practitioners.

Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China.

Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1-2.5, and coarse particles (PM2.5-10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015-2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 µg/m3 for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10. An inter-quartile range increase for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3-51.9%), 53.7% (22.4-93.1%), 32.6% (15.0-53.0%), 35.1% (17.7-55.0%) and 25.9% (13.0-40.3%) in MD-related deaths at lag 0-3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75-84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.

Effects of ambient temperature and humidity on COPD mortality in Ganzhou city, China.

This study used the time series data of Ganzhou city to explore the individual and interaction effects of temperature and humidity on COPD death, and identify vulnerable subgroups of the population. We collected daily COPD mortality and meteorological data in Ganzhou from 2016 to 2019. The nonlinear distribution lag model was used to examine the associations and interaction between daily mean temperature and humidity and COPD mortality. For the total population, male and 65 years old or above, the relative risk (RR) for COPD mortality could be significant at extremely low temperature (3.3 ℃), reaching 1.799 (95% confidence interval [CI]: 1.216, 2.662), 1.894 (95% CI: 1.164, 3.084) and 1.779 (95% CI:1.185, 2.670). Also, at extremely low humidity (47.8%), the risk reached 1.888 (95% CI: 1.217, 2.930), 1.837 (95% CI: 1.066, 3.165) and 2.166 (95% CI: 1.375, 3.414). The cumulative COPD death risk for females was 3.524 (95% CI: 1.340, 9.267) at high temperature (30.7 ℃), 1.953(95% CI: 1.036, 3.683) at low humidity (47.8%) and 1.726 (95% CI: 1.048, 2.845) at high humidity (96.7%). For the total COPD deaths and subgroups, the interaction effects between daily temperature and humidity were not significant (p > 0.05). Both extremely low temperature and low humidity increased the risk of COPD death in Ganzhou city, especially for males and people over 65 years old. Females were more sensitive to extremely high temperature and humidity. Patients with COPD should pay attention to self-protection under extreme temperature and humidity weather conditions.

Association of ambient temperature with intentional self-harm and suicide death in Seoul: a case-crossover design with a distributed lag nonlinear model.

Previous epidemiological studies have reported a short-term association between ambient temperature and suicide risk. To gain a clearer understanding of this association, it is essential to differentiate the risk factors for intentional self-harm (ISH) from those specifically associated with suicide deaths. Therefore, this study aims to examine whether the association between daily temperature and ISH or suicide deaths differs by age and sex. Between 2014 and 2019, cases of emergency room visits related to ISH and suicide deaths in Seoul were identified. A time-stratified case-crossover design was used to adjust for temporal trends and seasonal variation. A distributed lag nonlinear model was used to analyze the nonlinear and time-delayed effect of ambient temperature on ISH and suicide deaths. Positive associations were observed between temperature and both ISH and suicide deaths. For ISH, the relative risk (RR) was high at 1.17 (95% confidence interval (CI): 1.03, 1.34) for a temperature of 25.7 °C compared with 14.8 °C. The RR for suicide death was higher than those for ISH, at 1.43 (95% CI: 1.03, 2.00) for a temperature of 33.7 °C. These associations varied by age and sex, with males and females aged 35-64 years showing increased susceptibility to suicide deaths. This study provides detailed evidence that unusually high temperatures, both anomalous and out of season, may trigger suicidal behaviors, including both ISH and suicide deaths.

A Quantity-Dependent Nonlinear Model of Sodium Cromoglycate Suppression on Beta-Conglycinin Transport.

Understanding the transport mechanism is crucial for developing inhibitors that block allergen absorption and transport and prevent allergic reactions. However, the process of how beta-conglycinin, the primary allergen in soybeans, crosses the intestinal mucosal barrier remains unclear. The present study indicated that the transport of beta-conglycinin hydrolysates by IPEC-J2 monolayers occurred in a time- and quantity-dependent manner. The beta-conglycinin hydrolysates were absorbed into the cytoplasm of IPEC-J2 monolayers, while none were detected in the intercellular spaces. Furthermore, inhibitors such as methyl-beta-cyclodextrin (MßCD) and chlorpromazine (CPZ) significantly suppressed the absorption and transport of beta-conglycinin hydrolysates. Of particular interest, sodium cromoglycate (SCG) exhibited a quantity-dependent nonlinear suppression model on the absorption and transport of beta-conglycinin hydrolysates. In conclusion, beta-conglycinin crossed the IPEC-J2 monolayers through a transcellular pathway, involving both clathrin-mediated and caveolae-dependent endocytosis mechanisms. SCG suppressed the absorption and transport of beta-conglycinin hydrolysates by the IPEC-J2 monolayers by a quantity-dependent nonlinear model via clathrin-mediated and caveolae-dependent endocytosis. These findings provide promising targets for both the prevention and treatment of soybean allergies.

Association between ambient temperature and hospitalizations for urolithiasis in four counties of Ganzhou, China.

We collected meteorological and urolithiasis-related hospitalization data from four counties in Ganzhou City for 2018-2019 and used the DLNM method to assess the lagged and cumulative effects of temperature on urolithiasis hospitalizations and obtain the total effect after meta-combination. Based on the nonlinear association between temperature and urolithiasis hospitalizations, the relative risk of overall high temperature (30℃) was 2.10 (95% CI: 1.07-4.10). No statistically significant difference (p = 0.07) was observed between males (RR = 2.04, 95% CI: 1.42-2.94) and females (RR = 1.45, 95% CI: 1.09-1.92) for the heat effect, which was higher in the ≥ 60 years age group (RR = 3.18, 95% CI: 1.76-5.76) than in the < 60 years age group (p = 0.007). High temperatures increased the risk of hospitalization for urolithiasis in Ganzhou, China, and the risk was greatest for individuals aged 60 and above, with similar risks observed across counties and genders.

Scaling features in high-concentrations PM2.5 evolution: the Ignored factor affecting scarlet fever incidence.

As an acute respiratory disease, scarlet fever has great harm to public health. Some evidence indicates that the time distribution pattern of heavy PM2.5 pollution occurrence may have an impact on health risks. This study aims to reveal the relation between scaling features in high-concentrations PM2.5 (HC-PM2.5) evolution and scarlet fever incidence (SFI). Based on the data of Hong Kong from 2012 to 2019, fractal box-counting dimension (D) is introduced to capture the scaling features of HC-PM2.5. It has been found that index D can quantify the time distribution of HC-PM2.5, and lower D values indicate more cluster distribution of HC-PM2.5. Moreover, scale-invariance in HC-PM2.5 at different time scales has been discovered, which indicates that HC-PM2.5 occurrence is not random but follows a typical power-law distribution. Next, the exposure-response relationship between SFI and scale-invariance in HC-PM2.5 is explored by Distributed lag non-linear model, in conjunction with meteorological factors. It has been discovered that scale-invariance in HC-PM2.5 has a nonlinear effect on SFI. Low and moderate D values of HC-PM2.5 are identified as risk factors for SFI at small time-scale. Moreover, relative risk shows a decreasing trend with the increase of exposure time. These results suggest that exposure to short-term clustered HC-PM2.5 makes individual more prone to SFI than exposure to long-term uniform HC-PM2.5. This means that individuals in slightly-polluted regions may face a greater risk of SFI, once the PM2.5 concentration keeps rising. In the future, it is expected that the relative risk of scarlet fever for a specific region can be estimated based on the quantitative analysis of scaling features in high-concentrations PM2.5 evolution.

[Effect of Diurnal Temperature Range on the Number of Residents Hospitalized Due to Stroke in Lanzhou].

Objective To analyze the relationship between diurnal temperature range (DTR) and the hospitalization of stroke in Lanzhou,so as to provide a scientific basis for probing into the mechanism of temperature changes in inducing stroke and formulating comprehensive prevention and control measures for stroke by relevant departments.Methods The information of the patients hospitalized due to stroke in Lanzhou during January 2014 to December 2019 and the air pollutants (PM10,SO2,and NO2) and meteorological data in the same period were collected for statistical analysis.Spearman rank correlation analysis was performed to analyze the correlations between air pollutants and meteorological factors.The distributed lag nonlinear model was adopted to fit the relationship between DTR and the number of stroke inpatients,and three-dimensional diagrams and the correlation diagrams of DTR against stroke risk were established.The stratified analysis was performed according to gender and age (< 65 years and ≥65 years).Results From 2014 to 2019,a total of 92 812 stroke patients were hospitalized in Lanzhou,with a male-to-female ratio of 1.35:1.There was a nonlinear relationship between DTR and the number of stroke inpatients in Lanzhou,which presented a lag effect.The low DTR at 4.5 ℃ had the largest RR value of 1.25 (95%CI=1.16-1.35) for stroke inpatients at a cumulative lag of 18 d.The effect of high DTR (18.5 ℃) on the hospitalization of stroke patients peaked at a cumulative lag of 21 d,with an RR value of 1.09 (95%CI=1.01-1.18).The stratified analysis results suggested that low levels of DTR had greater effects on the hospitalization of male stroke patients and stroke patients <65 years.Conclusions Short-term exposure to different levels of DTR had an impact on the number of stroke inpatients,and low levels of DTR had a slightly greater impact on stroke inpatients than high levels of DTR.Importance should be attached to the protection of males and people aged <65 years at low levels of DTR.

Time Dependence Between Tobacco Consumption and Lung Cancer Mortality in Spain.

OBJECTIVES: Lung cancer is the leading cause of cancer death and the second most common cancer in both sexes worldwide, with tobacco being its main risk factor. The aim of this study is to establish the temporal relationship between smoking prevalence and lung cancer mortality in Spain. METHODS: To model the time dependence between smoking prevalence and lung cancer mortality, a distributed lag non-linear model was applied adjusting for sex, age, year of mortality and population at risk. Smoking prevalence data from 1991-2020 were used. Considering a maximum lag of 25 years, mortality data from 2016-2020 were included. The effect of prevalence on mortality for each lag is presented in terms of relative risk (RR). To identify the lag at which smoking prevalence has the greatest effect on mortality, the RR of the different lags were compared. RESULTS: The optimal lag observed between smoking prevalence and lung cancer mortality in Spain was 15 years. The maximum RR was 2.9 (95%CI: 2.0-4.3) for a prevalence of 71% and a 15-year lag. The RR was 1.8 for a prevalence of 33%, an approximate median value between 1991-2020, and a 15-year lag. CONCLUSIONS: In Spain, lung cancer mortality is affected by smoking prevalence 15 years prior. Knowing the evolution of the smoking prevalence series in a country and establishing a lag time is essential to predict how lung cancer incidence and mortality will evolve.

Deep learning based model predictive controller on a magnetic levitation ball system.

The magnetic levitation (maglev) ball system is a prototypical Single-Input-Single-Output (SISO) system, characterized by its pronounced nonlinearity, rapid response, and open-loop instability. It serves as the basis for many industrial devices. For describing the dynamics of the maglev ball system precisely in the pseudo linear model, the long short-term memory (LSTM) based auto-regressive model with exogenous input variables (LSTM-ARX) is proposed. Firstly, the LSTM network is modified by incorporating the auto-regressive structure with respect to sequence input, allowing it to deduce a locally linearized model without the need for Taylor expansion. Then, the LSTM-ARX model is transformed into a linear parameter varying (LPV) state space model, and upon this foundation, a model predictive controller (MPC) is proposed. Specifically, when deducing the MPC, the deep learning-based model is linearized by fixing its state input at the current state, so that the nonlinear, non-convex optimization problem can be converted to a finite-horizon quadratic programming problem, thereby deriving the explicit form of MPC. To further enhance the efficiency of the controller in real-time control tasks, a predictive functional controller (PFC) is proposed. It employs multiple nonlinear functions to fit the control sequence, thereby reducing the number of decision variables of the on-line optimization problem in MPC. The proposed controller was successfully applied to the real-time control of the maglev ball system. Simulation and real-time control experiments have validated the improvement in transient performance and efficiency of the LSTM-ARX model-based PFC (LSTM-ARX-PFC).

Time series analysis of the interaction between ambient temperature and air pollution on hospitalizations for AECOPD in Ganzhou, China.

This study aimed to investigate the univariate and bivariate effects of ambient temperature and air pollutants on 57,251 inpatients with AECOPD (Acute Exacerbation of Chronic Obstructive Pulmonary Disease) in Ganzhou from January 1, 2016, to December 31, 2019. We categorized the daily mean temperature and air pollutant variables based on the exposure-response curve of the Distributed Lag Non-Linear Model. Poisson regression model was used for interaction and stratification analysis. The Relative Excess Risk due to Interaction (RERI) with 95% confidence intervals (95% CI) between daily mean temperature (Tmean) and air pollutants including NO2, PM2.5, and PM10 were - 0.428 (95% CI - 0.637, - 0.218), -- 0.227 (95% CI - 0.293, - 0.161), and - 0.119 (95% CI - 0.159, - 0.079). Further stratification analysis showed the relative risk (RR) (95% CI) of high NO2 (> 33 µg/m3) at low Tmean (≤ 28 °C) was 1.119 (95% CI 1.096, 1.142). Low temperatures with high PM10 in men and high PM2.5 in women were associated with a higher risk of AECOPD hospitalization. The results indicate a higher risk of hospitalization for AECOPD when there is with high concentrations of air pollution at low temperatures.

Meteorological parameters and hospital-acquired falls-A multicenter retrospective study based on 10 years of adverse events reporting system data.

Objective and rationale: Hospital-acquired falls are common and serious adverse events in medical institutions, with high incidence and injury rates. Studying the occurrence patterns of hospital-acquired falls is important for preventing falls in hospitalized patients. However, the effect of meteorological factors on hospital-acquired falls has not been elucidated. Therefore, this study explored the impact of meteorological parameters on hospital-acquired falls in Chongqing, China, and provided new ideas for the clinical prevention of falls in patients. Methods: Correlation analysis and distributed lag nonlinear models were employed to analyze the relationship between 3890 cases of hospital-acquired falls and meteorological data in 13 hospitals in 11 districts and counties in Chongqing from January 2013 to April 2023. Results: The number of hospital-acquired falls demonstrated a nonlinear correlation with the daily average relative humidity and negatively correlated with sunshine duration; however, temperature, air pressure, and wind speed were not correlated. Compared to the reference humidity (87 %), the immediate effects of daily average relative humidity (65-68 % and 90-97 %) increased the risk of hospital-acquired falls on the same day (relative risk [RR]:1.027-1.243). When the daily average relative humidity was 95-97 %, lags of 0-1 d and 8-12 d had greater effects on falls (RR:1.073-1.243). The daily average relative humidities of 62-74 % and 91-97 % were statistically significant at cumulative relative risk (CRR)of 4, 7, 10, and 14 d with a cumulative lag (CRR: 1.111-4.277). On sex and age stratification, the lag and cumulative effects of relative humidity more significantly impacted falls in women and patients aged ≥65 years. Conclusion: Daily average relative humidity had a nonlinear correlation and lag effect on hospital-acquired falls; therefore, medical institutions should pay attention to the effect of relative humidity on hospital-acquired falls in patients, especially old and female patients.

Investigating the impact of air pollution and temperature changes on emergency admissions (cardiovascular + respiratory) disease in the city of Bojnord, northeastern Iran.

Cardiovascular (CVD) + Respiratory diseases are recognized as the main cause of death worldwide. Fluctuations in temperature and air pollution have been reported as one of the most important causes of cardiovascular & respiratory diseases. Therefore, in the current study, we assessed the relationship between ambient air temperature and pollution on the number of total emergency hospital admission due to cardiovascular and respiratory conditions in the City of Bojnord, northeastern Iran. The meteorological data, including daily temperature, relative humidity and concentrations of five air pollutants CO, NO2, NOX SO2, and PM10 were obtained from online electronic sensors at the Bojnurd meteorological station from 21th March 2018 to 20th March 2020. Statistical analysis, penalized distributed lag non-linear method was applied using R Software. Also, sensitivity analysis test was calculated by using appropriate application. The results of the study revealed that the effect of higher and lower temperatures was observed immediately from the first day and the second week, respectively. Also result showed with increase and decrease temperature, significantly increased the risk of hospitalization by 36% (RR, 1.36; 95% CI (1), 0.95 to 1.95) and 17% (RR, 1.17; 95% CI (1), 0.88 to 1.55) until the lag 25th day, respectively. Based on the results, increasing temperature significantly increased the hospitalization rate of cardiopulmonary patients, but the effect of cold was not significant on the population as well as age and gender subgroups. Study have also proved that there is no significance correlation between air pollutant and Cardiovascular & respiratory diseases.

Indirect Measurement of Variables in a Heterogeneous Reaction for Biodiesel Production.

This research focuses on the development of a state observer for performing indirect measurements of the main variables involved in the soybean oil transesterification reaction with a guishe biochar-based heterogeneous catalyst; the studied reaction takes place in a batch reactor. The mathematical model required for the observer design includes the triglycerides' conversion rate, and the reaction temperature. Since these variables are represented by nonlinear differential equations, the model is linearized around an operation point; after that, the pole placement and linear quadratic regulator (LQR) methods are considered for calculating the observer gain vector L(x). Then, the estimation of the conversion rate and the reaction temperature provided by the observer are used to indirectly measure other variables such as esters, alcohol, and byproducts. The observer performance is evaluated with three error indexes considering initial condition variations up to 30%. With both methods, a fast convergence (less than 3 h in the worst case) of the observer is remarked.

Association between ambient temperature and mammalian-related injuries in Guangzhou, China, 2014-2019.

BACKGROUND: Meteorological factors are associated with various health outcomes. However, it remains uncertain whether ambient temperature affects animal aggressive behaviors and causes mammalian-related injuries (MRI) in humans. The study aimed to examine the effect of daily mean temperature on MRI in Guangzhou, China. METHODS: Individual cases of MRI were obtained from Guangzhou Injury Surveillance System during 2014-2019. A combination of a distributed lag nonlinear model and conditional quasi-Poisson regression, implemented within a time-stratified case-crossover design, was employed to evaluate the association between temperature and MRI. Subgroup analyses were conducted by sex, age group, education level, and types of mammals. RESULT: This study included 24,206 MRI cases among which 89.7 % were caused by cats or dogs. We observed a nonlinear relationship between daily mean temperature and MRI. The impact of high temperatures was most pronounced on the current day and remained statistically significant on the next day. Compared with the reference temperature with a minimum risk of injuries (9.3 °C, approximately 2nd percentile of temperature), 75th percentile of temperature (27.4 °C) exerted the greatest relative risk (RR) of injuries (RR = 1.45, 95 % CI: 1.25-1.68) over lag 0-1 days. In subgroup analyses, the effects of high temperatures among males and females were similar. Individuals aged 15-34 years and 35-59 years were more susceptible to MRI at high temperatures compared to other age groups. The risk of injuries caused by cats or dogs consistently increased with high temperatures. We did not find significant impacts of low temperatures. CONCLUSION: Short-term heat exposure plays an important role in the occurrence of MRI. The findings highlight the importance of enhancing public awareness regarding the high temperature-associated hazards posed by mammals. There is a need for enhanced regulations and measures on the management for cats and dogs to mitigate the harm caused in hot seasons.