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Estimating and monitoring chlorophyll content is a critical step in crop spectral image analysis. The quick, non-destructive assessment of chlorophyll content in rice leaves can optimize nitrogen fertilization, benefit the environment and economy, and improve rice production management and quality. In this research, spectral analysis of rice leaves is performed using hyperspectral and fluorescence spectroscopy for the detection of chlorophyll content in rice leaves. This study generated ninety experimental spectral datasets by collecting rice leaf samples from a farm in Sichuan Province, China. By implementing a feature extraction algorithm, this study compresses redundant spectral bands and subsequently constructs machine learning models to reveal latent correlations among the extracted features. The prediction capabilities of six feature extraction methods and four machine learning algorithms in two types of spectral data are examined, and an accurate method of predicting chlorophyll concentration in rice leaves was devised. The IVSO-IVISSA (Iteratively Variable Subset Optimization–Interval Variable Iterative Space Shrinkage Approach) quadratic feature combination approach, based on fluorescence spectrum data, has the best prediction performance among the CNN+LSTM (Convolutional Neural Network Long Short-Term Memory) algorithms, with corresponding RMSE-Train (Root Mean Squared Error), RMSE-Test, and RPD (Ratio of standard deviation of the validation set to standard error of prediction) indexes of 0.26, 0.29, and 2.64, respectively. We demonstrated in this study that hyperspectral and fluorescence spectroscopy, when analyzed with feature extraction and machine learning methods, provide a new avenue for rapid and non-destructive crop health monitoring, which is critical to the advancement of smart and precision agriculture.

Abstract Background The purpose of this study is to assess the level of knowledge, attitudes, and willingness to organ donation among the general public in China. Methods The study population consisted of 4274 participants from Eastern, Central and Western China. The participants’ knowledge, attitudes and willingness to organ donation were collected by a self-designed questionnaire consisting of 30 items. Knowledge is measured by 10 items and presented as a 10 point score, attitudes is measured by 20 items using a 5-step Likert scale and total score ranged between 0 and 80; while the willingness to donate is assessed as binary variable (0 = No; 1 = Yes). A logistic regression model was used to assess the association of knowledge and attitudes with willingness to organ donation, controlling for demographic and socioeconomic confounders. Results The questionnaire response rate was 94.98%. The mean score (± SD) of the general public’s knowledge to organ donation was 6.84 ± 1.76, and the mean score (± SD) of attitudes to organ donation was 47.01 ± 9.07. The general public’s knowledge and attitudes were the highest in Eastern China, followed by West and Central China. The logistic regression model indicated a positive association between knowledge and the willingness to organ donation (OR = 1.12, 95%CI: 1.08, 1.17; P

Abstract Background Previous studies have suggested that maternal stress could increase the risk of some adverse pregnancy outcomes, but evidence on congenital heart disease (CHD) is limited. We aimed to explore the association between maternal exposure to life events during pregnancy and CHD in offspring. Methods The data was based on an unmatched case-control study about CHD conducted in Shaanxi province of China from 2014 to 2016. We included 2280 subjects, 699 in the case group and 1581 in the control group. The cases were infants or fetuses diagnosed with CHD, and the controls were infants without any birth defects. The life events were assessed by the Life Events Scale for Pregnant Women, and were divided into positive and negative events for synchronous analysis. A directed acyclic graph was drawn to screen the confounders. Logistic regression was employed to estimate the odds ratio and 95% confidence interval for the effects of life events on CHD. Results After controlling for the potential confounders, the pregnant women experiencing the positive events during pregnancy had lower risk of CHD in offspring than those without positive events (OR = 0.38, 95%CI: 0.30 ~ 0.48). The risk of CHD in offspring could increase by 62% among the pregnant women experiencing the negative events compared to those without (OR = 1.62, 95%CI: 1.29 ~ 2.03). Both effects showed a certain dose-response association. Besides, the positive events could weaken the risk impact of negative events on CHD. Conclusion It may suggest that maternal exposure to negative life events could increase the risk of CHD in offspring, while experiencing positive events could play a potential protective role.

Introduction To investigate the relationship between long-term change trajectory in body mass index (BMI) and the hazard of type 2 diabetes among Chinese adults.Research design and methods Data were obtained from the China Health and Nutrition Survey (CHNS). Type 2 diabetes was reported by participants themselves in each survey wave. The duration of follow-up was defined as the period from the first visit to the first time self-reported type 2 diabetes, death, or other loss to follow-up from CHNS. The patterns of change trajectories in BMI were derived by latent class trajectory analysis method. The Fine and Gray regression model was used to estimate HRs with corresponding 95% CIs for type 2 diabetes.Results Four patterns of the trajectories of change in BMI were identified among Chinese adults, 42.7% of participants had stable BMI change, 40.8% for moderate BMI gain, 8.9% for substantial BMI gain and 7.7% for weight loss. During the follow-up with mean 11.2 years (158 637 person-years contributed by 14 185 participants), 498 people with type 2 diabetes (3.7%) occurred. Risk of type 2 diabetes was increased by 47% among people who gained BMI more substantially and rapidly (HR: 1.47, 95% CI 1.08 to 2.02, p=0.016) and increased by 20% among those in people with the moderate BMI gain (HR: 1.20, 95% CI 0.98 to 1.48, p=0.078), compared with those with stable BMI change.Conclusions Long-term substantial gain of BMI was significantly associated with an increased risk of type 2 diabetes in the Chinese adults.

Bisphenol A (BPA) is suspected to be associated with several chronic metabolic diseases. The aim of the present study was to review previous epidemiological studies that examined the relationship between BPA exposure and the risk of obesity. PubMed, Web of Science, and Embase databases were systematically searched by 2 independent investigators for articles published from the start of database coverage until January 1, 2020. Subsequently, the reference list of each relevant article was scanned for any other potentially eligible publications. We included observational studies published in English that measured urinary BPA. Odds ratios with corresponding 95% confidence intervals for the highest versus lowest level of BPA were calculated. Ten studies with a sample size from 888 to 4793 participants met our inclusion criteria. We found a positive correlation between the level of BPA and obesity risk. A dose–response analysis revealed that 1-ng/mL increase in BPA increased the risk of obesity by 11%. The similar results were for different type of obesity, gender, and age.

Background Birth weight is closely related to infant survival and future health, growth and development. In developing countries, the incidence of low birth weight is twice as high as in developed countries. Due to the low economic and medical level in northwest China, the problem of low birth weight needs to be solved urgently. Methods We developed the predictive model based on data sets from a cross-sectional study conducted in northwest China, and data were collected from August 2013 to November 2013. A total of 27,233 patients were included in the study. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select the optimal predictive characteristics among risk factors. The selected characteristics in the LASSO regression were used in multivariate logistic regression to build the prediction model. C-index and calibration plot were used to evaluate the degree of discrimination and calibration of the model. The decision curve is used to evaluate the net benefit rate of the application of the predictive tool. Bootstrapping validation was used for internal validation. Results Nomogram included gestational age, the sex of the attendance, the mother's education level, antenatal care, the mother's occupation, pregnancy-induced hypertension, family income, exposure to pesticides and nutritional supplements. The C-index of the predicted nomogram was 0.698(95% confidence interval: 0.671–0.725), C-index of internal verification was 0.694, indicating that the model had a good identification ability. Calibration plot showed that the model had good calibration. Decision curve indicated that patients with a threshold probability of low birth weight between 1% and 71% would benefit more from using the prediction tool. Conclusion The use of this predictive model will contribute to clinicians and pregnant women to make personalized predictions easily and quickly so that early lifestyle detection and medical intervention can be undertaken by physicians and patients. [ABSTRACT FROM AUTHOR]

To evaluate the effects of filter-feeding fishes on water quality and bacterial community in the rice–crayfish coculture system, four different stocking densities of bighead carp (0, 500, 1000, 1500 ind./200 m2) were set up in rice–crayfish coculture systems. Water samples in the systems were collected biweekly to detect dissolved oxygen (DO), temperature (T), potential of Hydrogen (pH), ammonia nitrogen (NH4+-N), nitrite nitrogen (NO2−-N), nitrate nitrogen (NO3−-N), total nitrogen (TN), total phosphorus (TP), and Chlorophyll-a (Chl-a); the bacterial community in the water was analyzed simultaneously, then the correlation between water quality and microorganisms were studied. The results showed that concentrations of TN, TP, NO2−-N, and NH4+-N decreased while DO and NO3−-N increased along with the breeding process. NO2−-N, NO3−-N, TN, and NH4+-N were important environmental factors affecting the bacterial community structure in water (p < 0.05). Bighead carp stocking had an impact on the diversity, richness, and evenness of the bacterial communities in the systems. The dominant bacteria in the four different carp density groups were Proteobacteria, Actinomycetes, Bacteroidetes, and Cyanobacteria. Bighead carp increased the abundance of Bacteroidea but reduced that of Actinomycetes, Cyanobacteria, and Proteobacteria. The introduction of bighead carp promoted the conversion of nitrogen and phosphorus, reducing the risk of cyanobacterial blooms. Group 1000 ind./200 m2 exhibited the best effect on the removal of nitrogen and phosphorus from the water body.

The Danjiangkou Reservoir is the water source of the middle route of China’s South-to-North Water Diversion Project, encompassing the Dan Reservoir and Han Reservoir. However, little is known about the ecological functions of this important ecosystem. Based on a survey conducted in 2023 in the Dan Reservoir, a mass balance model was constructed using Ecopath with Ecosim 6.6 software to characterize its food web structure and ecosystem properties. The model consisted of 18 functional groups, including producers, consumers, and detritus, covering the entire process of energy flow in the ecosystem. The outputs indicated that the fractional trophic level of functional groups in the Dan Reservoir ecosystem ranged from 1.00 to 3.50. The ecotrophic efficiencies of the main economic fish species were all less than 0.9, and the ecotrophic efficiencies of phytoplankton and detritus were less than 0.5. There were two main food chains: the detritus food chain (39%) and the grazing food chain (61%). The total energy transfer efficiency between trophic levels was only 6.02%, and there was a significant phenomenon of energy transfer blockage between trophic levels II and V. Analysis of the overall characteristics of the ecosystem revealed that the total primary production to total biomass (67.96619), connectance index (0.274), and Finn’s cycling index (2.856) of the Dan Reservoir ecosystem all indicate that the ecosystem is immature, with low nutrient recycling efficiency and poor resistance to external disturbances. This may be related to the low proportion of silver carp and bighead carp in the reservoir and the unreasonable structure of the fish community. Our results suggest that it is necessary to scientifically adjust the structure of the fish community, enhance the proportion of filter-feeding and omnivorous fish to improve the energy flow efficiency, and promote the maturity and stability of the Dan Reservoir.

Ludwigite ore is a typical low-grade boron ore accounting for 58.5% boron resource of China, which is mainly composed of magnetite, lizardite and szaibelyite. During soda-ash roasting of ludwigite ore, the presence of lizardite hinders the selective activation of boron. In this work, lizardite and szaibelyite were prepared and their soda-ash roasting behaviors were investigated using thermogravimetric-differential scanning calorimetry (TG-DSC), X-ray diffraction (XRD), and scanning electron microscope and energy dispersive spectrometer (SEM-EDS) analyses, in order to shed light on the soda-ash activation of boron within ludwigite ore. Thermodynamics of Na2CO3-MgSiO3-Mg2SiO4-Mg2B2O5 via FactSage show that the formation of Na2MgSiO4 was preferential for the reaction between Na2CO3 and MgSiO3/Mg2SiO4. While, regarding the reaction between Na2CO3 and Mg2B2O5, the formation of NaBO2 was foremost. Raising temperature was beneficial for the soda-ash roasting of lizardite and szaibelyite. At a temperature lower than the melting of sodium carbonate (851 °C), the soda-ash roasting of szaibelyite was faster than that of lizardite. Moreover, the melting of sodium carbonate accelerated the reaction between lizardite with sodium carbonate.