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Deep learning framework for hourly air pollutants forecasting using encoding cyclical features across multiple monitoring sites in Beijing
Abstract Environmental managers and citizens alike are concerned with air quality. Early warning systems for air pollution are essential to prevent health issues and implement effective prevention strategies. This paper proposes a comprehensive, reliable system with air quality prediction and assessment modules for China’s air pollution. In this study, six air pollutants were observed, including Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Ozone (O3), Sulphur Dioxide (SO2), Fine particulate matter (PM2.5), and Coarse particulate matter (PM10). The current dataset includes hourly air pollutants data from 10 national air-quality monitoring sites, such as Aotizhongxin, Changping, Dongsi, Guanyuan, Huairou, Nongzhanguan, Shunyi, Tiantan, Wanliu, and Wanshouxigong. The dataset was recorded hourly from 01/03/2013 to 28/02/2017. Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) were developed with both unencoded and encoded features to address the forecasting challenge of multivariate time series, specifically in predicting air pollution concentrations. The results showed that, the top accuracy was as follows: 93.8% at the Wanshouxigong station using CNN-Encoded, 91.9% at the Nongzhanguan station using (DNN-Encoded and CNN-Encoded), 93.4% at Aotizhongxin station using DNN-Encoded, 96.2% at Nongzhanguan station using DNN-Encoded, 94% at Dongsi station using CNN-Unencoded, and 92.4% at Aotizhongxin station using (CNN-Unencoded and DNN-Encoded) in forecasting CO, NO2, O3, PM2.5, PM10 and SO2 pollutants, respectively. The findings indicated that the suggested approaches are efficient and dependable for environmental supervisors in the monitoring and management of air pollution.
A large cross-sectional study on the prevalence and predictors of donor and donation images in patients after heart transplantation
Abstract Recovery and clinical outcomes following organ transplantation may be negatively influenced by psychological distress. Limited reports from recipients indicate that thoughts and feelings related to the donor/transplanted organ – referred to as donor and donation images (DDI) – may be a source of such distress. The term DDI encompasses all thoughts and emotions that organ recipients associate with the donor or the donated organ. However, empirical knowledge of DDI remains limited. This quantitative survey involving 407 participants represents the first and largest study to quantitatively examine DDI in patients after heart transplantation (HTX). The results revealed a very high prevalence of DDI (91%), with occurrences reported intermittently and often clustered around the time of transplantation, both before and after HTX. Psychological distress predicted the occurrence of DDI before and after HTX and almost all emotions experienced and reported pre-HTX were associated with higher odds of pre-HTX DDI, suggesting it may be a concurrent phenomenon of overall emotional activation. Due to the involvement of emotions associated with uncertainty and low personal control, along with high situational control, DDI may be a part of coping. Some reported avoiding DDI suggesting that, sometimes, they might also represent a stressor. Future studies should further investigate the effects of DDI, including its impact on transplant outcome.
Nonlinear electronic oscillators as time sensors for high-precision positioning applications
Evaluation of the potential for diagnosis of fungal keratitis using a Fusarium-specific antibody
An integrated widely targeted metabolomics and network pharmacology study of Persicaria runcinata var. Sinensis against arthritis
Cyclodextrin attenuates atherosclerosis by diminishing gasdermin D (GSDMD)-mediated pyroptosis
Temporally consistent Koopman autoencoders for forecasting dynamical systems
Exposure of cells to near-infrared irradiation relaxes chromatin compaction and facilitates recognition of cyclo-butane pyrimidine dimers
Abstract Ultraviolet A and B (UVA 320–400 nm and UVB 280–320 nm) induced cyclobutane-pyrimidine dimers (CPDs) are the most critical lesions caused by environmental sun exposure. Here we show that CPD removal is accelerated when, in addition to UV, cells are simultaneously exposed to water-filtered near-infrared (nIR, 750–1600 nm). The described effect is dose-dependent on the nIR-dose and is found in skin keratinocytes and fibroblasts. Accelerated removal of CPDs, which coincides with chromatin relaxation and faster CPD recognition, occurs after nIR exposure. While nIR alone does not affect cellular survival, co-exposure to UVB leads to reduced cellular survival and an increased number of mutations. Increasing single strand break levels (SSB) occur transiently after nIR exposure and independent of reactive oxygen species (ROS) formation. These data suggest that the rate-limiting step in the NER repair process – damage recognition – is facilitated by nIR-induced chromatin relaxation, causing the accumulation of unnatural high levels of SSBs and single stranded DNA, unfavourable for the cell fate resulting in reduced survival and increased mutation rates. Since nIR modulates the UV-dependent damage response, risk estimation of solar radiation-induced DNA damage should not only consider the UV components but also include the nIR fraction of the solar spectrum.
Socioeconomic disparities in heat vulnerability among adults in Finland
Nomogram for the prediction of the prognosis of patients with triple-negative invasive ductal carcinoma of breast after neoadjuvant chemotherapy
The prognostic significance of the NMD core factor UPF1 in low-grade glioma
Relationship between free fatty acids and diabetic retinopathy in male patients with type 2 diabetes
Abstract This study aims to evaluate the association between fasting serum free fatty acids (FFAs) and diabetic retinopathy (DR) in a population of Chinese men with type 2 diabetes mellitus (T2DM). A total of 781 eligible subjects participated in this cross-sectional study. We collected clinical data and information about the patient’s examination and laboratory tests. The Shapiro–Wilk test was employed to assess the normality of continuous variables. For continuous variables with non-normal distributions, the Mann–Whitney U test and the Kruskal-Wallis test was utilized for comparisons. Categorical variable comparisons were performed using the chi-square test. Logistic regression analyses and restricted cubic spline (RCS) curves were conducted to examine the association between FFAs levels and DR. FFAs levels were slightly lower in the DR group compared to the NDR group (0.35 vs. 0.41 mmol/L, p < 0.05). The logistic regression model did not identify a statistically significant linear relationship between FFAs levels and DR incidence (OR = 0.776, 95% CI: 0.308–1.955, p = 0.591). After adjusting for various confounding factors, RCS curves revealed a U-shaped relationship between FFAs and DR. This relationship was validated in subgroup analyses stratified by age, diabetes duration, BMI, and alcohol consumption status. The U-shaped curve was evident in most subgroups, indicating that both low and high levels of FFAs are associated with an increased risk of DR. IIn this study, we found a U-shaped relationship between FFAs and DR in Chinese men with T2DM. Both low and high levels of FFAs were associated with an increased risk of DR.
Unveiling Calotropis procera’s promising wound healing secrets by QSAR, molecular docking, DFT and ADMET profiling
Accuracy of labeled THC potency across flower and concentrate cannabis products
Comparison of visual functions among early and late onset myopia
Abstract Early-onset myopia (EOM) progresses more rapidly and sets a higher risk of developing high myopia, whereas late-onset myopia (LOM) is typically associated with lower refractive error. However, differences in visual function between these groups remain underexplored. This cross-sectional study compared high-contrast visual acuity, low-contrast visual acuity, contrast sensitivity function (CSF), blur perception, and depth of focus in individuals with EOM and LOM. Twenty participants (10 EOM, 10 LOM) aged 18–35 years with myopia ranging from − 0.50 to − 6.00 D were included. Visual function assessments were conducted using MATLAB and PsychoPy software, with all measurements taken under full-distance spectacle correction. While high-contrast and low-contrast visual acuity showed no significant differences, CSF parameters showed significant differences. The area under the curve, peak spatial frequency, and cutoff spatial frequency were significantly lower in EOM than in LOM (p = 0.019, 0.032, and 0.005, respectively). Blur perception thresholds also varied, though statistical significance was not reached. These findings suggest that individuals with EOM may show compromised contrast sensitivity, possibly affecting their overall visual quality. Understanding these functional differences can help in developing targeted interventions for myopia management, ensuring personalized approaches to optimize visual performance across different onset groups.
Construction and validation of the prosocial adolescent risk-taking questionnaire (PAR-Q)
Integrating multi-omic data to identify key genes and pathways involved in rice bacterial leaf streak disease
Cross-language dissemination of Chinese classical literature using multimodal deep learning and artificial intelligence
Introducing electric spring in the voltage frequency regulation of a multi area multi source integrated power system network
Abstract The present work demonstrates the application of an electric spring in a multi-source interconnected power system in which coordinated control of frequency and voltage loop is investigated. A two-area power system is considered with non–linearity for the thermal power system, such as generation rate constraint and governor dead band, so that the developed model is realistic. A novel cascade controller, namely a two–degree–of–freedom proportional–integral–derivative controller cascaded with a proportional–integral–derivative controller (2DOFPID–PID), is utilized for the first time for reducing the area control error to zero in both the control areas. A powerful algorithm known as the Golden Jackal Algorithm (GJA) is considered for tuning the controller parameters and achieving the minimum performance index. System dynamic responses are observed for the coordinated automatic load frequency control and automatic voltage regulator during step load perturbations and random load perturbations. Selection of the best performance index (PI) among integral of squared error (ISE), integral of time multiplied by absolute error (ITAE), integral of time multiplied by squared error (ITSE), and Integral of absolute error (IAE) proves that ITAE serves the best among others. To model an AC/DC bus, system responses are also investigated with a parallel AC/DC link that depicts satisfactory results in terms of overshoot, undershoot, and settling time. Modelling of the electric spring in the proposed system is integrated to check the terminal voltage deviation and frequency deviation, and mitigate them. Results show reduced generator terminal deviation in both the control areas. Comparison of different powerful algorithms with the proposed one infers the superiority of the proposed golden jackal algorithm with reference to the performance index vs. number of iterations.