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Abstract The frontier molecular orbitals of organic semiconductor materials play a crucial role in the performance of photoelectric devices, including organic photovoltaics (OPVs), organic light-emitting diodes (OLEDs), and organic photodetectors (OPDs). In this work, a model for predicting frontier molecular orbital of organic materials, including HOMO and LUMO levels, is established with the extreme gradient boosting algorithm and Klekota-Roth fingerprints. The correlation coefficients of HOMO or LUMO energy levels in the testing set are 0.75 and 0.84 in the transfer model from 11,626 DFT data in Harvard Energy database to 1198 experimental data in literature. The difference between the ML predicted value and the experimental value is smaller than the difference between ML prediction and DFT calculation, always less than 10%. Moreover, based on correlation and SHAP interpretability analysis, 13 key structural fragments influencing energy levels are selected to further verify the effective regulation of the frontier molecular orbital by the key structural fragments in practical applications. Considering the completely opposite regulatory functions of key structural fragments on HOMO and LUMO energy levels, four new Y6 derivatives, Y-PCP, Y-P6F, Y-PCF, and Y-P4FC, are designed to flexibly modify the HOMO and LUMO energy levels. The prediction trends of ML align closely with the computational trends from DFT. It is worth noting that the accuracy of LUMO energy level prediction by the prediction model makes up for the instability of DFT calculation on LUMO energy level. This work offers a cost-effective method to accelerate the acquisition of electronic properties of organic materials.

To clarify the thermal runaway characteristics of lithium-ion battery pack, this study has established a thermal runaway experimental platform based on actual power battery pack. A 4 in series and 4 in parallel battery pack was assembled using 86 Ah lithium iron phosphate batteries, and the experiment of thermal runaway induced by overcharging and unilateral preheating was carried out. The behavior and characteristics including the temperature change characteristics of each cell, the heat generated and transfer paths during thermal runaway propagation, the voltage changes of each serial module and the total voltage, flame evolution behavior, gas generation characteristics, debris, and mass loss were investigated. The research results show that module 1 was the first to experience thermal runaway due to preheating. The redistributed current caused the batteries in the remaining modules to rapidly generate heat. Subsequently, the heat transfer from module 1 triggered thermal runaway in modules 2, 3, and 4 in sequence. The entire flame combustion process lasted for 38 min, with the maximum temperature reaching 937.1 °C, resulting in thermal runaway in all batteries. The sequence of thermal runaway has been clarified, with the flame generated by the ignition of the battery casing, connecting tabs, and combustible gases emitted from the batteries serving as the primary paths for heat transfer and thermal radiation. The experimental results provide valuable insights into the thermal engineering issues of large-scale lithium-ion battery pack.

Abstract Background Postoperative pneumonia (POP) is the most prevalent of all nosocomial infections in patients who underwent cardiac surgery. The aim of this study was to identify independent risk factors for pneumonia after cardiac surgery, from which we constructed a nomogram for prediction. Methods The clinical data of patients admitted to the Department of Cardiothoracic Surgery of Nanjing Drum Tower Hospital from October 2020 to September 2021 who underwent cardiac surgery were retrospectively analyzed, and the patients were divided into two groups according to whether they had POP: POP group (n=105) and non-POP group (n=1083). Preoperative, intraoperative, and postoperative indicators were collected and analyzed. Logistic regression was used to identify independent risk factors for POP in patients who underwent cardiac surgery. We constructed a nomogram based on these independent risk factors. Model discrimination was assessed via area under the receiver operating characteristic curve (AUC), and calibration was assessed via calibration plot. Results A total of 105 events occurred in the 1188 cases. Age (>55 years) (OR: 1.83, P=0.0225), preoperative malnutrition (OR: 3.71, P 135 min (OR: 2.80, P 20 hours (OR: 3.11, P

Abstract Background Postoperative hyper-inflammation is a frequent event in patients with acute Stanford type A aortic dissection (ATAAD) after surgical repair. This study's objective was to determine which inflammatory biomarkers could be used to make a better formula for identifying postoperative hyper-inflammation, and which risk factors were associated with hyper-inflammation. Methods A total of 405 patients were enrolled in this study from October 1, 2020 to April 1, 2023. Of these patients, 124 exhibited poor outcomes. In order to investigate the optimal cut-off values for poor outcomes, logistic and receiver operating characteristic analyses were performed on the following parameters on the first postoperative day: procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6), and systemic immune-inflammation index (SII). These cut-off points were used to separate the patients into hyper-inflammatory (n = 52) and control (n = 353) groups. Finally, the logistic were used to find the risk factors of hyper-inflammatory. Results PCT, CRP, IL-6, and SII were independent risk factors of poor outcomes in the multivariate logistic model. Cut-off points of these biomarkers were 2.18 ng/ml, 49.76 mg/L, 301.88 pg/ml, 2509.96 × 109/L respectively. These points were used to define postoperative hyper-inflammation (OR 2.97, 95% CI 1.35–6.53, P 180 min, and deep hypothermia circulatory arrest (DHCA) > 40 min were the independent risk factors for hyper-inflammation. Conclusions PCT > 2.18, CRP > 49.76, IL-6 > 301.88, and SII 180 min and DHCA > 40 min were separate risk factors for postoperative hyper-inflammation.

Owing to the volatility and intermittency of renewable energy generation units in microgrids, effective energy scheduling methods are essential for efficient renewable energy utilization and stable microgrid operation. In recent years, microgrid energy optimization scheduling based on deep reinforcement learning (DRL) has made significant progress. With the development of the microgrid, the drawbacks of the traditional DRL agent, such as long training time and poor convergence effect, are gradually revealed. This paper proposes a generative adversarial imitation learning method with Wasserstein distance for optimal energy scheduling in the microgrid. This method combines a proximal policy optimization algorithm to optimize energy scheduling and reduce microgrid operating costs. First, the agent adaptively learns the action exploration process by imitating expert trajectories. Second, based on the generative adversarial theory, a discriminator network is added, and the Wasserstein distance is introduced into the discriminator network to distinguish between the generative and expert strategies. This feedback assists in updating the neural network parameters. Finally, the effectiveness of the proposed method is verified through an arithmetic example analysis.

The preparation parameters of PM6:Y6 non-fullerene organic solar cells (OSCs) have significant influence on the power conversion efficiency (PCE). Herein, machine learning (ML) models are applied for analyzing the quantitative effects of the PCE on PM6:Y6 non-fullerene OSCs from the perspective of fabrication parameters. Random Forest (RF) model has the best evaluation performance and is considered as the best model among the six different algorithms. The Pearson correlation coefficient, coefficient of determination, root mean square error, mean absolute error, and mean absolute percentage error of the test set in the RF model are 0.836, 0.668, 0.695, 0.538, and 0.035, respectively. In addition, the most important preparation parameters for PCE are the effective area of OSCs, type of solvent and solvent additives, spin-coating speed, total concentration, annealing temperature, annealing time from SHAP analysis. The optimized PCE can be obtained in PM6:Y6 non-fullerene OSCs when the effective area is between 4 and 6 mm2, the spin-coating speed is 3000 rpm, and the total concentration is 18 mg ml−1, respectively. The contour map further reflects that the optimal annealing temperature are 80 or 105 °C, and the corresponding annealing time are 5 or 9 min, respectively. Based on the above preparation conditions, we verified through the experimental design that the optimal PCE is 16.91%, and the relative error with the ML prediction is only 1.24%. Our research provides low time and cost guidance on preparation parameter matching for the development of high-performance the PM6:Y6 non-fullerene OSCs.

Summary: The abnormal reproduction of algae in water worldwide is prominent in the context of human interference and global climate change. This study first thoroughly analyzed the effects of physical factors, such as light, temperature, hydrodynamics, and operational strategies, on algal growth and their mechanisms. Physical control techniques are safe and have great potential for preventing abnormal algal blooms in the absence of chemical reagents. The focus was on the principles and possible engineering applications of physical shading, ultrasound, micro-current, and ultraviolet (UV) technologies, in controlling abnormal algal reproduction. Physical shading can inhibit or weaken photosynthesis in algae, thereby inhibiting their growth. Ultrasound mainly affects the physiological and biochemical activities of cells by destroying the cell walls, air cells, and active enzymes. Micro-currents destroy the algal cell structure through direct and indirect oxidation, leading to algal cell death. UV irradiation can damage DNA, causing organisms to be unable to reproduce or algal cells to die directly. This article comprehensively summarizes and analyzes the advantages of physical prevention and control technologies for the abnormal reproduction of algae, providing a scientific basis for future research. In the future, attempts will be made toward appropriately and comprehensively utilizing various physical technologies to control algal blooms. The establishment of an intelligent, comprehensive physical prevention and control system to achieve environmentally friendly, economical, and effective physical prevention and control of algae, such as the South-to-North Water Diversion Project in China, is of great importance for specific waters.

Forest fires constitute a widespread and impactful natural disaster, annually ravaging millions of hectares of forests and posing a severe threat to human life and property. Accurate quantitative prediction of forest fire spread is essential for devising swift risk management strategies and implementing effective firefighting approaches. In response to this imperative, this study introduces a Forest Fire Spread Behavior Prediction (FFSBP) model, encompassing two integral components: the Forest Fire Spread Process Prediction (FFSPP) model and the Forest Fire Spread Results Prediction (FFSRP) model. The FFSPP model involves the prediction of the direction and speed of forest fire spread, achieved through a fusion of the Cellular Automata model and the Wang Zhengfei model. On the other hand, the FFSRP model focuses on forecasting the extent of the burned area, leveraging machine learning methods. To validate the efficacy of the proposed models, a real case study is undertaken using the “3.29 Forest Fire” incident in China. The FFSPP model is validated against this case, while the FFSRP model is assessed using a real fire dataset obtained from Montesinho National Forest Park in Portugal. Results from the validation process reveal that during the natural development period of the “3.29 Forest Fire,” the FFSPP model predicts a burned area of 286.81 hm2, with an associated relative error of 28.94%. This relative error is notably smaller than those observed in the Farsite and Prometheus fire behavior simulation models. Additionally, the FFSRP model demonstrates commendable predictive performance, particularly in the context of small and medium-sized fire scenarios. These findings underscore the potential of the FFSBP model as a valuable tool in enhancing forest fire prediction accuracy and facilitating more robust risk mitigation and firefighting strategies.

Accurate wind speed prediction is extremely critical to the stable operation of power systems. To enhance the prediction accuracy, we propose a new approach that integrates bidirectional long short-term memory (BiLSTM) with fully adaptive noise ensemble empirical modal decomposition (CEEMDAN), the RIME optimization algorithm (RIME), and a multi-head self-attention mechanism (MHSA). First, the historical data of wind farms are decomposed via CEEMDAN to extract the change patterns and features on different time scales, and different subsequences are obtained. Then, the parameters of the BiLSTM model are optimized using the frost ice optimization algorithm, and each subsequence is input into the neural network model containing the MHSA for prediction. Finally, the predicted values of each component are weighted and reconstructed to obtain the predicted values of wind speed time series. According to the experimental results, the method can predict the short-term wind speeds of wind farms more accurately. We verified the effectiveness of the method by comparing it with different models.

Catalyzed by Rh2(esp)2 (10 mol%) and (±)-BINAP (20 mol%) in DCE at 80 °C, the cascade assembly between diazobarbiturates and alkylidene pyrazolones proceeded readily and produced spiro-furopyrimidines in 38–96% chemical yields. The chemical structure of the prepared spirofuro-pyrimidines was firmly confirmed by X-ray diffraction analysis.

Cladophora is commonly found in marine and freshwater around the globe and provides productivity for littoral zone microorganisms and invertebrates. The eutrophication of the water body has led to the abnormal proliferation of Cladophora in some water, often in river coast channel outbreaks. Even under the nutritional deficiency systems, such as the central trunk canal of the South-to-North Water Diversion in China, Cladophora’s blooms affect water quality and seriously jeopardize human health. Thus, the structural characteristics of Cladophora cells and spores, the factors affecting the growth of Cladophora cells, and the mechanisms of damage and destruction of Cladophora cells and spores were investigated. Cladophora cells are cylindrical with very thick cell walls. The inner layer of the spore wall is a thin membrane which contains the nucleus of the spore. The growth and spreading of Cladophora cells are affected by various environmental factors such as light, temperature, water depth, water level, nutrient salts, pH, etc. Some physical treatment measures, such as ultrasounds, would destroy the cell walls and membranes of Cladophora by its high-intensity mechanical action. Chemicals and aquatic plant measures can destroy Cladophora cells’ photosynthesis system, antioxidant enzyme systems, proteins, and ultrastructure. Based on the mechanisms for these cell damage and destruction, a combination of measures that are likely to inhibit the growth of Cladophora cells effectively was suggested. Furthermore, the damaged cells of Cladophora could provide some environmental benefits. Aggregated results could provide a scientific basis for further research on the control of blooms of Cladophora or the reuse of Cladophora cells as a natural resource.

Abstract Background Myocardial injury-related cardiogenic shock (MICS) is significantly associated with poor outcomes in patients after cardiac surgery. Herein, we aimed to investigate the risk factor for postoperative MICS. Methods We performed a case-control study on 792 patients undergoing cardiac surgery from 2016 to 2019, including 172 patients with postoperative MICS and 620 age- and sex-matched controls. MICS was defined as composite criteria: a cardiac index of 5 mmol/L at the end of the surgery, a vasoactive-inotropic score of > 40 at the end of the surgery, and a cardiac troponin T (cTnT) level of > 0.8 µg/L on postoperative day 1 (POD1) with an increase of > 10% on POD 2. Results A total of 4671 patients who underwent cardiac surgery in our hospital between 2016 and 2019 were included; of these, 172 (3.68%) had MICS and the remaining 4499 did not. For investigating the risk factors, we selected 620 age- and sex-matched controls. In the univariate analysis, MICS was significantly associated with death (P 2 h (OR: 3.16, 95% CI: 1.94–5.15, P

In recent years, the outbreak of infectious diseases has highlighted the need for improved planning of hospital buildings. Traditional planning for infectious disease hospitals only considers the impact of wind and pollutant diffusion, without analysing pollutant diffusion under different thermal conditions. To reveal the distribution of pollutants in infectious disease hospitals under different thermal conditions, this study conducted wind tunnel tests and numerical analyses of pollutant diffusion in the environment surrounding an infectious disease hospital in Changsha, China. The results show that the pollutant concentration mainly depends on the local wind speed. In the range of Rb = −1.25 to 1.25, the concentration of pollutants was mainly affected by the disturbance of the flow field in areas with rough surfaces, where the effect of the thermal stability of the atmosphere on pollutant diffusion was relatively small. However, in relatively flat regions, the thermal stability of the atmosphere played a significant role in pollutant diffusion around the buildings.

The characterization of dissolved organic matter (DOM) is important for better understanding of the migration and transformation mechanisms of DOM in water bodies and its interaction with other contaminants. In this work, fluorescence characteristics and molecular compositions of the DOM samples collected from the mainstream, tributary, and sewage outfall of the Inner Mongolia section of the Yellow River (IMYR) were determined by using fluorescence spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). In addition, concentrations of potentially toxic elements (PTEs) in the relevant surface water and their potential relationships with DOM were investigated. The results showed that the abundance of tyrosine-like components increased significantly in downstream waters impacted by outfall effluents and was negatively correlated with the humification index (HIX). Compared to the mainstream, outfall and tributaries have a high number of molecular formulas and a higher proportion of CHOS molecular formulas. In particular, the O5S class has a relative intensity of 41.6% and the O5-7S class has more than 70%. Thirty-eight PTEs were measured in the surface water samples, and 12 found above their detective levels at all sampling sites. Protein-like components are positively correlated with Cu, which is likely indicating the source of Cu in the aquatic environment of the IMYR. Our results demonstrated that urban wastewater discharges significantly alter characteristics and compositions of DOM in the mainstream of IMYR with strongly anthropogenic features. These results and conclusions are important for understanding the role and sources of DOM in the Yellow River aquatic environment.

Abstract Background Recent high-quality trials have shown that the anti-inflammatory effects of colchicine reduce the risk of cardiovascular events in patients suffering post-myocardial infarction and chronic coronary disease. The effect of colchicine in patients undergoing non-coronary artery bypass grafting (non-CABG) with cardiopulmonary bypass remains unclear. We aim to evaluate the effect of colchicine on myocardial protection in patients who underwent non-CABG cardiac surgery. Method Patients were randomly assigned to colchicine or placebo groups starting 72 h before scheduled cardiac surgery and for 5 days thereafter (0.5 mg daily).The primary outcome was the level of cardiac troponin T (cTnT) at postoperative 48 h. The secondary outcomes included troponin I (cTnI) and creatine kinase-MB (CK-MB), inflammatory biomarkers (procalcitonin and interleukin-6, etc.), and adverse events (30-day mortality, stroke, ECMO and IABP use, etc.). Results A total of 132 patients underwent non-CAGB cardiac surgery, 11were excluded because of diarrhea (n = 6) and long aortic cross-clamp time > 2 h (n = 5), 59 were assigned to the colchicine group and 62 to the placebo group. Compared with the placebo group, cTnT (median: 0.3 μg/L, IQR 0.2–0.4 μg/L vs. median: 0.4 μg/L, IQR 0.3–0.6 μg/L, P

In the field of reliability engineering, covariate information shared among product units within a specific group (e.g., a manufacturing batch, an operating region), such as operating conditions and design settings, exerts substantial influence on product lifetime prediction. The covariates shared within each group may be missing due to sensing limitations and data privacy issues. The missing covariates shared within the same group commonly encompass a variety of attribute types, such as discrete types, continuous types, or mixed types. Existing studies have mainly considered single-type missing covariates at the individual level, and they have failed to thoroughly investigate the influence of multi-type group-shared missing covariates. Ignoring the multi-type group-shared missing covariates may result in biased estimates and inaccurate predictions of product lifetime, subsequently leading to suboptimal maintenance decisions with increased costs. To account for the influence of the group-shared missing covariates with different structures, a new flexible lifetime model with multi-type group-shared latent heterogeneity is proposed. We further develop a Bayesian estimation algorithm with data augmentation that jointly quantifies the influence of both observed and multi-type group-shared missing covariates on lifetime prediction. A tripartite method is then developed to examine the existence, identify the correct type, and quantify the influence of group-shared missing covariates. To demonstrate the effectiveness of the proposed approach, a comprehensive simulation study is carried out. A real case study involving tensile testing of molding material units is conducted to validate the proposed approach and demonstrate its practical applicability.

The precipitation characteristics in Hangzhou of Zhejiang Province, China under the background of global climate change are analyzed using the meteorological observation data obtained from the Hangzhou base station in this study. We investigate the climate characteristics of precipitation in Hangzhou from several aspects, such as centennial trend, seasonal change, periodicity and the variation of extreme precipitation. Our results show a linear decreasing trend and obvious interdecadal characteristics in the precipitation of Hangzhou on a centennial timescale. Significantly increased amplitude of precipitation fluctuation was observed since the beginning of the 21st century. For the interdecadal variation of seasonal precipitation on a centennial timescale, precipitation in autumn showed a decreasing trend of 8.1 mm/10a, whereas the trends for the other three seasons were statistically insignificant. The precipitation in Hangzhou showed a decreasing trend in spring and an increasing trend in winter over the past 30 years. Our analyses reveal distinct precipitation cycles, including a quasi-30-year cycle since the 1960s and a quasi-10-year cycle since the 1980s. However, the periodicity has weakened in the past 10 years. In addition, the occurrence of torrential rain has increased rapidly in the past 10 years. Furthermore, influenced by global climate change and regional processes, the variation of extreme precipitation in Hangzhou has changed, which shows strong correlations with the overall trend of annual precipitation. The annual maximum daily precipitation in Hangzhou was mainly in the range of 0–40 mm from 1951 to 1980 and in the range of 40–80 mm from 1981 to 2010 with the maximum daily precipitation occurrence rate of 4.7 times/10a and 6.3 times/10a, respectively. This study emphasizes the risk of urban waterlogging caused by short-term heavy rainfall and provides useful reference to the assessment of extreme meteorological and hydrological disaster risk in Hangzhou.

Dissolved organic matter (DOM) plays a major role in ecological systems, affecting the fate and transportation of iron (Fe) and phosphorus (P). To better understand the geochemical cycling of these components, soil and sediment samples were collected around a reservoir downstream of a typical temperate forest in Northeast China. The DOM fractions from these soils, river, and reservoir sediments were extracted and then characterized by spectroscopic techniques. Comparative characterization data showed that the DOM pool of the Xishan Reservoir was partly autochthonous and derived from runoff and deposition of material in terrestrial ecosystems upstream. The upper reaches of the reservoir had significantly lower total Fe (TFe) content in the DOM extracts than those found in the reservoir (p

Abstract Study objective The purpose of the present study was to evaluate the efficacy of levosimendan in patients with acute myocardial infarction related ventricular septal rupture (AMI-VSR) underwent cardiac surgery. Design Prospective observational cohort study with propensity score analysis. Patients There were 261 patients with AMI-VSR in our study. After 1:1 propensity matching, 106 patients (53 levosimendan and 53 control) were selected in the matched cohort. Interventions None. Measurements Patients who received levosimendan were assigned to the levosimendan group (n = 164). The patients who were not received were levosimendan assigned to the control group (n = 97). The levosimendan was initiated immediately after cardiopulmonary bypass. Then, it has been maintained during the postoperative 3 days. The poor outcomes were identified as follows: death and postoperative complications (postoperative stroke, low cardiac output syndromeneeded mechanical circulatory support after surgery, acute kidney injury (≥ stage III), postoperative infection or septic shock, new developed atrial fibrillation or ventricular arrhythmias). Main results Before matching, the control group had more length of ICU stay (6.69 ± 3.90 d vs. 5.20 ± 2.24 d, p

Under the catalysis of Rh2(OAc)4 (10 mol%) and binapbisphosphine ligand (±)-L3 (20 mol%) in DCE at 80 °C, the cascade cyclization of diazoimides with alkylidenepyrazolones underwent stereoselectively (dr > 20:1), affording pyrazole-fused oxa-bridged oxazocines in reasonable chemical yields. The chemical structure and relative configuration of title products were firmly identified by X-ray diffraction analysis.

Reservoirs have an important impact on riverine material migration and transformation. Taking a drinking water reservoir located in the cold-temperature forest in the Xiaoxing’an mountains as an example, we comprehensively analyzed the fractions and interrelationships of phosphorus (P) and iron (Fe) from soils to riverine and reservoir sediments and discussed the coordinated migration and transformation process of regional P and Fe and the effects of dam interception. The results showed that iron-bound P (Fe-P) and aluminum-bound P (Al-P) were significantly correlated with adsorbed Fe(II), carbonate-bound Fe (Fecarb), low-activity silicate-bound Fe (Feprs), and total contents of Fe (TFe), which indicated that the geochemical cycling of these P fractions and Fe fractions is likely closely related and active in the soils and sediments. Calcium-bound P (Ca-P) was significantly correlated with magnate (Femag) and Feprs, which may be due to the correlation between their background values in this area. The contents of active P including loosely sorbed P (L-P), Al-P, and Fe-P in the reservoir’s sediments were significantly higher than those in the upstream soils and sediments (p < 0.05). However, Ca-P and residual P (Res-P) in soil and sediment samples showed no significant difference between the reservoir and its upstream (p = 0.309 > 0.05 and p = 0.748 > 0.05, respectively). Construction of reservoirs has played a certain role in intercepting P, especially bioavailable P, transferred from upstream soils and riverine sediments. The contents of highly active Fe fractions including easily reducible (amorphous) Fe oxide (Feox1), reducible (crystalline) Fe oxide (Feox2) and Fecarb (p < 0.01), and other Fe fractions (p < 0.05) in the sediments of the reservoir were significantly higher than those in the soil or sediment samples from upstream. This indicated that all Fe fractions migrated in the river were affected by the dam interception. The effects of dam interception would affect the bioavailability of P and Fe and enhance the cycling of nutrients in the region. Finally, this also effects the bioavailability and cycling of P and Fe in the downstream rivers and even the oceans.

The power conversion efficiency (PCE) of ternary polymer solar cells (PSCs) with non-fullerene has a phenomenal increase in recent years. However, improving the open circuit voltage (Voc) of ternary PSCs with non-fullerene still remains a challenge. Therefore, in this work, machine learning (ML) algorithms are employed, including eXtreme gradient boosting, K-nearest neighbor and random forest, to quantitatively analyze the impact mechanism of Voc in ternary PSCs with the double acceptors from the two aspects of photovoltaic materials. In one aspect of photovoltaic materials, the doping concentration has the greatest impact on Voc in ternary PSCs. Furthermore, the addition of the third component affects the energy offset between the donor and acceptor for increasing Voc in ternary PSCs. More importantly, to obtain the maximum Voc in ternary PSCs with the double acceptors, the HOMO and LUMO energy levels of the third component should be around (−5.7 ± 0.1) eV and (−3.6 ± 0.1) eV, respectively. In the other aspect of molecular descriptors and molecular fingerprints in the third component of ternary PSCs with the double acceptors, the hydrogen bond strength and aromatic ring structure of the third component have high impact on the Voc of ternary PSCs. In partial dependence plot, it is clear that when the number of methyl groups is four and the number of carbonyl groups is two in the third component of acceptor, the Voc of ternary PSCs with the double acceptors can be maximized. All of these findings provide valuable insights into the development of materials with high Voc in ternary PSCs for saving time and cost.

Lithium-ion batteries (LIBs) are widely used in electrochemical energy storage and in other fields. However, LIBs are prone to thermal runaway (TR) under abusive conditions, which may lead to fires and even explosion accidents. Given the severity of TR hazards for LIBs, early warning and fire extinguishing technologies for battery TR are comprehensively reviewed in this paper. First, the TR reaction mechanism and hazards of LIBs are discussed. Second, the TR early warning and monitoring methods of LIBs are summarized in five aspects consisting of acoustic, heat, force, electricity, and gas. In addition, to reduce the fire and explosion hazards caused by the TR of LIBs, the highly efficient extinguishing agents for LIBs are summarized. Finally, the early warning technology and fire extinguishing agent are proposed, which provides a reference for the hazard prevention and control of energy storage systems.

Enrichment of nutrients is believed to lead to coastal hypoxia which have become a seasonal phenomenon over large river estuarine areas such as the Mississippi River-Northern Gulf of Mexico and Changjiang-East China Sea. A similar nutrient enrichment process exists in the Pearl River. However, hypoxia occurs only as episodic events over a relatively small area. We hypothesize that frequent wind events play the interruptive mechanism in preventing the seasonal formation of bottom hypoxia. We used 29 years’ time series data of dissolved oxygen (DO) and winds in the Hong Kong coastal waters to test the hypothesis. Our results show that bottom DO at 3 stations in southern waters of Hong Kong occasionally drops below the hypoxic level (2 mg/L), lasting only for less than one month in summer. Episodic hypoxia events appear to occur more frequently in recent years, but bottom DO does not show a significantly decreasing trend. The wind speed of 6 m/s appears to be a threshold, above which a wind event could destroy water column stratification and interrupt the formation of low-oxygen (DO

Falls have caught great harm to the elderly living alone at home. This paper presents a novel visual-based fall detection approach by Dual-Channel Feature Integration. The proposed approach divides the fall event into two parts: falling-state and fallen-state, which describes the fall events from dynamic and static perspectives. Firstly, the object detection model (Yolo) and the human posture detection model (OpenPose) are used for preprocessing to obtain key points and the position information of a human body. Then, a dual-channel sliding window model is designed to extract the dynamic features of the human body (centroid speed, upper limb velocity) and static features (human external ellipse). After that, MLP (Multilayer Perceptron) and Random Forest are applied to classify the dynamic and static feature data separately. Finally, the classification results are combined for fall detection. Experimental results show that the proposed approach achieves an accuracy of 97.33% and 96.91% when tested with UR Fall Detection Dataset and Le2i Fall Detection Dataset.

How to improve the subseasonal forecast skills of dynamic models has always been an important issue in atmospheric science and service. This study proposes a new dynamical-statistical forecast method and a stable components dynamic statistical forecast (STsDSF) for subseasonal outgoing long-wave radiation (OLR) over the tropical Pacific region in January-February from 2004 to 2008. Compared with 11 advanced multi-model ensemble (MME) daily forecasts, the STsDSF model was able to capture the change characteristics of OLR better when the lead time was beyond 30 days in 2005 and 2006. The average pattern correlation coefficients (PCC) of STsDSF are 0.24 and 0.16 in 2005 and 2006, while MME is 0.10 and 0.05, respectively. In addition, the average value of PCC of the STsDSF model in five years is higher than MME in 7–11 pentads. Although both the STsDSF model and MME show a similar temporal correlation coefficient (TCC) pattern over the tropical Pacific region, the STsDSF model error grows more slowly than the MME error during 8–12 pentads in January 2005. This phenomenon demonstrates that STsDSF can reduce dynamical model error in some situations. According to the comparison of subseasonal forecasts between STsDSF and MME in five years, STsDSF model skill depends strictly on the predictability of the dynamical model. The STsDSF model shows some advantages when the dynamical model could not forecast well above a certain level. In this study, the STsDSF model can be used as an effective reference for subseasonal forecast and could feasibly be used in real-time forecast business in the future.

The oceanic absorption of atmospheric CO _2 acidifies seawater, which accelerates CaCO _3 dissolution of calcifying organisms, a process termed dissolution effect. Promoted CaCO _3 dissolution increases seawater ALK (alkalinity), enhancing ocean carbon sink and mitigating ocean acidification. We incorporate different parameterizations of the link between CaCO _3 dissolution and ocean acidification into an Earth System Model, to quantify the feedback of the dissolution effect on the global carbon cycle. Under SRES A2 CO _2 emission scenario and its extension with emissions of 5,000 PgC in ∼400 years, in the absence of the dissolution effect, accumulated ocean CO _2 uptake between year 1800 and 3500 is 2,041 PgC. The consideration of the dissolution effect increases ocean carbon sink by 195–858 PgC (10%–42%), and mitigates the decrease in surface pH by 0.04–0.17 (a decrease of 10%–48% in [H ^+ ] (hydrogen ion concentration)), depending on the prescribed parameterization scheme. In the epipelagic zone, relative to the Arc-Atlantic Ocean, the Pacific-Indian Ocean experiences greater acidification, leading to greater dissolution effects and the resultant stronger feedbacks on ocean carbon sink and acidification in the Pacific-Indian Ocean. Noteworthy, the feedback of dissolution effect on ocean carbon sink can be comparable with or stronger than the feedback from CO _2 -induced radiative warming. Our study highlights the potentially critical role played by CaCO _3 dissolution effect in the ocean carbon sink, global carbon cycle and climate system.

The reanalysis of sea surface wind speed is compared with the measured wind speed of five offshore wind towers in Zhejiang, China. The applicability of reanalysis data in the Zhejiang coastal sea surface and the climatic characteristics of sea surface wind power density is analyzed. Results show that the reanalysis of wind field data at the height of 10 m can well capture the wind field characteristics of the actual sea surface wind field. The sea surface wind power density effective hours increases from west to east and north to south. Then Empirical orthogonal function (EOF) is used to analyze the sea surface wind power density anomaly field, and the first mode is a consistent pattern, the second mode is a North-South dipole pattern, the third mode is an East-West dipole pattern respectively. The stability of wind energy resources grows more stable with increasing distance from the coast, and the northern sea area which is far away from the coastal sea is more stable than that of the southern sea area. The yearly linear trend of sea surface wind power density is in an East-West dipole pattern respectively. The wind energy resources are more stable farther from the coast, and the wind energy resources in the northern sea are more stable than that of the southern sea. The yearly linear trend of sea surface wind power density is the East-West dipole type, the seasonal linear trend is a significant downward trend from West to East in spring, and on the contrary in summer, a non-significant trend in autumn and winter. The monthly change index shows that the linear trend near the entrance of Hangzhou Bay in Northern Zhejiang is of weak increase or decrease, which is good for wind energy development. When the wind power density is between 0 and 150 W·m−2, its frequency mainly shows the distribution trend of high in the West and low in the East, but the wind power density is between 150 and 600 W·m−2, its distribution is the opposite.

Since preindustrial times, atmospheric CO2 content increased continuously, leading to global warming through the greenhouse effect. Oceanic carbon sequestration mitigates global warming; on the other hand, oceanic CO2 uptake would reduce seawater pH, which is termed ocean acidification. We perform Earth system model simulations to assess oceanic CO2 uptake, surface temperature, and acidification for Zhejiang offshore, one of the most vulnerable areas to marine disasters. In the last 40 years, atmospheric CO2 concentration increased by 71 ppm, and sea surface temperature (SST) in Zhejiang offshore increased at a rate of 0.16°C/10a. Cumulative oceanic CO2 uptake in Zhejiang offshore is 0.3 Pg C, resulting in an increase of 20% in sea surface hydrogen ion concentration, and the acidification rate becomes faster in the last decade. During 2020–2040, under four RCP scenarios, SST in Zhejiang offshore increases by 0.3–0.5°C, whereas cumulative ocean carbon sequestration is 0.150–0.165 Pg C. Relative to RCP2.6, the decrease of surface pH in Zhejiang offshore is doubled under RCP8.5. Furthermore, simulated results show that the relationship between CO2 scenario and oceanic carbon cycle is nonlinear, which hints that deeper reduction of anthropogenic CO2 emission may be needed if we aim to mitigate ocean acidification in Zhejiang offshore under a higher CO2 concentration scenario. Our study quantifies the variation characteristics of oceanic climate and carbon cycle fields in Zhejiang offshore, and provides new insight into the responses of oceanic carbon cycle and the climate system to oceanic carbon sequestration.

In the context of global warming, how to measure summer climate suitability at a local scale is important for meteorological services. Considering meteorological and ecological conditions, body comfort, and the atmospheric environment, an assessment method for summer climate suitability for Zhejiang Province is proposed. In this paper, a summer suitable index (SSI) for Zhejiang is calculated, including four secondary indices: a summer cool index (SCI), a comfort days index (CDI), a good air days index (GADI) and a vegetation cover index (VCI). Using a local evaluation criterion, summer climate suitable areas are distinguished objectively according to the SSI. The results show that especially suitable regions account for 4.97% of Zhejiang Province, very suitable regions account for 22.2%, suitable regions account for 39.58%, and general regions account for 33.25%. The summer climate suitable areas are located mainly in high mountains and hills and coastal island areas while plain areas cannot be considered a suitable destination for summer tourism. By comparison and discussion, the SSI is demonstrated to capture summer climate suitability well. In contrast to a fixed evaluation index, benchmark values obtained for the SSI depend on the local climate and the index is straightforward to apply.

Abstract Background Our aim is to study the existence of the TLR9/TGF-β1/PDGF-B pathway in healthy humans and patients with systemic lupus erythematosus (SLE), and to explore its possible involvement in the pathogenesis of lupus nephritis (LN). Methods Protein levels of the cytokines were detected by ELISA. mRNA levels of the cytokines were analyzed by real-time PCR. MTT assay was used to test the proliferation of mesangial cells under different treatments. Results Compared to healthy controls (N Control = 56), levels of Toll-like receptor (TLR)9, transforming growth factor (TGF)-β1, and platelet-derived growth factor B (PDGF-B) were increased significantly in the peripheral blood of SLE patients (N SLE = 112). Significant correlations between the levels of TLR9, TGF-β1, and PDGF-B were observed in both healthy controls and SLE patients. The levels of TGF-β1 and PDGF-B were greatly enhanced by TLR9 activation in primary cell cultures. The proliferation of mesangial cells induced by the plasma of SLE patients was significantly higher than that induced by healthy controls; PDGF-B was involved in this process. The protein levels of PDGF-B homodimer correlated with the levels of urine protein in SLE patients with LN (N LN =38). Conclusions The TLR9/TGF-β1/PDGF-B pathway exists in humans and can be excessively activated in SLE patients. High levels of PDGF-B may result in overproliferation of mesangial cells in the kidney that are involved in the development of glomerulonephritis and LN. Further studies are necessary to identify TLR9, TGF-β1, and PDGF-B as new therapeutic targets to prevent the development of glomerulonephritis and LN.

BackgroundMycoplasma pneumoniae pneumonia (MPP) is one of the most common community-acquired pneumonia; this study is to explore the immune-pathogenesis of children MPP.MethodsNext-generation transcriptome sequencing was performed on the bronchoalveolar lavage fluid cells from six children with MPP and three children with foreign body aspiration as control. Some of the results had been validated by quantitative real-time PCR in an expanded group of children.ResultsResults revealed 810 differentially expressed genes in MPP group comparing to control group, of which 412 genes including RLTPR, CARD11 and RASAL3 were upregulated. These upregulated genes were mainly enriched in mononuclear cell proliferation and signaling biological processes. Kyoto encyclopedia of genes and genomes pathway analysis revealed that hematopoietic cell linage pathway, natural killer cell-mediated cytotoxicity pathway, and T cell receptor signaling pathway were significantly upregulated in MPP children. In addition, significant alternative splicing events were found in GNLY and SLC11A1 genes, which may cause the differential expressions of these genes.ConclusionOur results suggest that NK and CD8+ T cells are over activated and proliferated in MPP children; the upregulated IFNγ, PRF1, GZMB, FASL, and GNLY may play important roles in the pathogenesis of children MPP.

The risk of drought in the Yangtze River Delta Region (YRDR) was assessed using the method of natural disaster risk assessment. Based on the index of disaster risk, the assessment results of risk elements such as drought hazard and vulnerability were calculated in the YRDR. The division of relative drought risk levels in the YRDR was produced at the scale of county (city, district) and township. The results indicated that the areas of highest hazard of drought are located in the northern area of the YRDR. Areas with the greatest vulnerability of drought included Shanghai, Jiaxing, Wuxi, and Hangzhou. The highest risks of drought were mainly distributed in the north of the YRDR; the proportion of slightly high and extremely high risk areas in Shanghai, Nantong, Zhenjiang, Yangzhou, and Taizhou (Jiangsu province) is over 95%. The lowest-risk areas included the southeast coastal area of the YRDR, especially in Hangzhou, and Taizhou (Zhejiang province), where the proportion of slightly high and extremely high risk areas is below 5%. Based on this drought risk assessment, it is critical to establish a drought assessment system including both guarding against and addressing drought.

Particulate organic carbon (POC) plays an important role in the global carbon cycle. The POC in the Changjiang Estuary and adjacent coastal region of the East China Sea (ECS) is dominated by riverine input and marine production and is significantly influenced by the three gorges project (TGP). A coupled physical-biogeochemical model was used to evaluate TGP’s impact on POC. The results demonstrate that TGP regulates the area influenced by diluted water and POC through direct river and sediment discharge and affects the ecosystem. From the early to later TGP construction periods, the surface region with high-POC concentration (>40 μmol L−1) decreases by 20.5% in area and 11.5% in concentration. Meanwhile, POC in the whole water column decreases from 19.5 to 17.8 μmol L−1. By contrast, the concentrations of chlorophyll-a (Chl-a) and related nutrients increase. A three end-member mixing model based on quasi-conservative temperature and salinity is used to quantify relative contributions of different water sources to POC in our research area. We also estimate the biological POC production by the difference between the physical-biogeochemical model predicted POC and three end-member model mixing POC. The result demonstrate that under the regulation of TGP in the later period, the decrease of sediment load increases water transparency, which favors photosynthesis and oceanic biological produced POC. In addition, over 70% of the areas have C/Chl-a > 200 and high C/N ratios, which are circumstantial evidences that organic detritus and terrestrial input sources still dominate in the Changjiang Estuary and adjacent coastal ECS but are influenced by TGP’s regulation.

Based on the analysis of the feature of Asian continent becoming cold in the early 21st century winter under the background of global warming, the Asian Warming Hole (AWH) index is proposed in this paper to measure the intensity during the cold events process. Result shows that the Asian continent is indeed experiencing a cold stage in the early 21st century winter, but it is just in a cold phase and will become warmer in the future. In recent years the activity of the winter cold events has an obvious quasi-four-year cycle, which can be reflected by atmospheric circulation, and AO (Arctic Oscillation) may play a very important role. It is credible that Asian surface temperature will be higher in the coming 3-4 years compared with 2011 winter, signifying that the precipitation may increase correspondingly.

Distinguishing the predictable 10–30-day stable components (STs) in the actual atmosphere has been important in atmospheric science research. In this study, a new method for extracting 10–30-day STs was developed with the use of historical observations. We extracted and analyzed 10–30-day STs via statistical extrapolation tests. The results show that the STs are maintained uniformly at the intraseasonal time scale; the overall trends in the atmospheric motion are revealed. Comparisons between pentad-by-pentad changes in the explained variances of the 10–30-day STs under ENSO phases show that the explained variance transmission attenuation trends for El Niño and La Niña years are weaker and more continuous than those of neutral years. Data for 10–30-day STs can remain continuous and stable from one month to the next. The proposed method and results present a new means of extracting predictable STs from the atmosphere using historical data.