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Abstract Background In response to environmental degradation and the associated health challenges, the Chinese government has implemented a comprehensive array of environmental protection measures. Given the health enhancement objective of environmental protection measures and the considerable costs involved in the implementation process, evaluating whether environmental regulation is beneficial to reducing the health costs of the population is of great significance for enhancing environmental governance efficiency and social welfare. The data from the Chinese Family Panel Survey (CFPS) is applied to examine the effect of environmental regulation on the reduction of residents’ health costs from a microscopic perspective. Results The results indicate that for a 1% increase in total investment in environmental governance, residents’ health costs will decrease by 0.189%. The examination of the causal pathway suggests that implementing environmental regulation can diminish residents’ health costs through improving air quality and residents’ health status. Concurrently, there exist significant heterogeneities in the role of environmental regulation in reducing residents’ health costs. The effect of environmental regulation is more pronounced for the young, males, and individuals with better self-perceived health. Furthermore, the outcome of environmental regulation exhibits greater efficacy in urban areas compared to rural areas. Lastly, market-incentive environmental regulation in reducing health costs is more effective than command-controlled regulation. Conclusions Enhancing the intensity of environmental regulation contributes to decreasing residents’ health costs. The findings can provide policy reference for implementing environmental governance and achieving tangible enhancements in individuals' life quality.

Jimsar shale oil in China has undergone a rapid decline in formation energy and has a low recovery rate, with poor reservoir permeability. CO2 injection has become the main method for improving oil recovery. Pre-fracturing with CO2 energy storage in Jimsar shale oil has been performed, yielding a noticeable increase in oil recovery. However, the CO2 injection mechanism still requires a deeper understanding. Focusing on Jimsar shale oil in China, this paper studies the effect of CO2 on crude oil viscosity reduction, miscible phase testing, and the law of imbibition displacement. The results show that CO2 has a significant viscosity reduction effect on Jimsar shale oil, with a minimum miscible pressure between CO2 and Jimsar shale oil of 25.51 MPa, which can allow for miscibility under formation conditions. A rise in pressure increased the displacement capacity of supercritical CO2, as well as the displacement volume of crude oil. However, the rate of increase gradually declined. This research provides a theoretical basis for CO2 injection fracturing in Jimsar shale oil, which is helpful for improving the development effects of Jimsar shale oil.

The spread of visceral leishmaniasis (VL), a serious global zoonotic parasitic disease, is mostly under control; however, several cases have been reported in recent decades in Xinjiang, China. This study aimed to analyze the epidemiological status and spatiotemporal clustering characteristics of VL in Xinjiang, China, between 2004 and 2021 to provide a basis for the development and implementation of surveillance and response measures. Data on VL incidence during 2004–2021 were collected from the National Diseases Reporting Information System of China. Global spatial autocorrelation analysis, identification of local indicators of spatial association, and spatial–temporal clustering analysis were conducted to identify the distribution and high-risk areas. A total of 2034 VL cases were reported, with a mean annual incidence of 0.50 per 100,000. There was a general decreasing trend in the incidence of VL during our study period. The majority of the cases were reported from October to February of the following year, and fewer cases were reported from April to July. Spatial autocorrelation analysis revealed that the incidence of VL was spatially clustered within a few counties. Significant differences were observed during the study period (Moran’s I = 0.74, Z = 4.900, p < 0.05). The male-to-female ratio was 1.37:1, and most patients were in the age group 0–3 years. Cases were primarily distributed in seven regions and two autonomous prefectures, and Kashgar reported the highest number of cases (1688, 82.98%). Spatial analysis revealed that the aggregation of VL was predominantly observed in southwest Xinjiang. This was in alignment with the high-risk areas identified by spatiotemporal clustering analysis. The H-H clustering region was primarily observed in Gashi, Atushi, Shufu, Injisha, Kashgar, Yepuhu, and Bachu. These findings indicate that integrated control measures must be taken in different endemic areas to strengthen the VL control program in Xinjiang, China.

Our prophase studies have manifested that the sweet triterpenoid glycoside from the leaves of Cyclocarya paliurus (CPST) effectively improved the disorders of glucolipid metabolism in vitro and in patients. The current purpose was to further detect its mechanisms involved. The results demonstrated that CPST could ameliorate high-fat diet (HFD)-induced insulin resistance (IR), which was linked to reducing HFD-induced mice's body weight, serum glucose (GLUO), triglyceride (TG), total cholesterol (T-CHO) and low-density lipoprotein cholesterol (LDL-C), lowering the area under the oral glucose tolerance curve and insulin tolerance, elevating the percentage of brown adipose, high-density lipoprotein cholesterol (HDL-C), reducing fat droplets of adipocytes in interscapular brown adipose tissue (iBAT) and cross-sectional area of adipocytes. Further studies manifested that CPST obviously downregulated TLR4, MyD88, NLRP3, ASC, caspase-1, cleased-caspase-1, IL-18, IL-1β, TXNIP, and GSDMD protein expressions and p-NF-кB/NF-кB ratio in iBAT. These aforementioned findings demonstrated that CPST ameliorated HFD induced IR by regulating TLR4/NF-κB/NLRP3 signaling pathway, which in turn enhancing insulin sensitivity and glucose metabolism.

ZnO-CeO2 hollow nanospheres have been successfully synthesized via the hard templating method, in which CeO2 is used as the support skeleton to avoid ZnO agglomeration. The synthesized ZnO-CeO2 hollow nanospheres possess a large electrochemically active area and high electron transfer owing to the high specific surface area and synergistic effect of ZnO and CeO2. Due to the above advantages, the resulting ZnO-CeO2 hollow spheres display high sensitivities of 1122.86 μA mM−1 cm−2 and 908.53 μA mM−1 cm−2 under a neutral environment for the selective detection of dopamine and uric acid. The constructed electrochemical sensor shows excellent selectivity, stability and recovery for the selective analysis of dopamine and uric acid in actual samples. This study provides a valuable strategy for the synthesis of ZnO-CeO2 hollow nanospheres via the hard templating method as electrocatalysts for the selective detection of dopamine and uric acid.

Ultrasonically-induced nanoemulsions have been widely investigated for the development of functional food, cosmetics, and pharmaceuticals due to ideal droplet sizes (DS), low polydispersity index (PDI), and superior physical stability. However, a series of frequently-used ultrasonic set-ups mainly suffered from a low ultrasonic energy efficiency caused by the large acoustic impedance and energy consumption, subordinately confronted with a low throughput, complicated fabrication with complex structure and weak ultrasonic cavitation. Herein, we employed a typical ultrasonic microreactor (USMR) that ensured the high-efficient energy input and generated intense cavitation behavior for efficient breakage of droplets and continuous production of unified oil-in-water (O/W) nanoemulsions in a single cycle and without any pre-emulsification treatment. The emulsification was optimized by tuning the formula indexes, technological parameters, and numerical analysis using Response Surface Methodology (RSM), followed by a comparison with the emulsification by a traditional ultrasonic probe. The USMR exhibited superior emulsification efficiency and easy scale-up with remarkable uniformity by series mode. In addition, concurrent and uniform nanoemulsions with high throughput could also be achieved by a larger USMR with high ultrasonic power. Based on RSM analysis, uniform DS and PDI of 96.4 nm and 0.195 were observed under the optimal conditions, respectively, well consistent with the predicted values. Impressively, the optimal nanoemulsions have a uniform spherical morphology and exhibited superior stability, which held well in 45 days at 4℃ and 25℃. The results in the present work may provide a typical paradigm for the preparation of functional nanomaterials based on the novel and efficient emulsification tools.

BackgroundFrontal lobe epilepsy (FLE) is the second most common type of focal epilepsy, however, imaging studies of FLE have been far less than Temporal lobe epilepsy (TLE) and the structural findings were not consistent in previous literature.ObjectInvestigate the changes in cortical thickness in patients with FLE and the alteration of the structural covariance networks (SCNs) of cortical thickness with graph-theory.MethodThirty patients with FLE (18 males/12 females; 28.33 ± 11.81 years) and 27 demographically matched controls (15 males/12 females; 29.22 ± 9.73 years) were included in this study with high-resolution structural brain MRI scans. The cortical thickness was calculated, and structural covariance network (SCN) of cortical thickness were reconstructed using 68 × 68 matrix and analyzed with graph-theory approach.ResultCortical thickness was not significantly different between two groups, but path length and node betweenness were significantly increased in patients with FLE, and the regional network alterations were significantly changed in right precentral gyrus and right temporal pole (FDR corrected, p

ObjectivesThis study explores the factors influencing the construction duration of public health emergency medical facilities and the ways in which they can be enhanced.MethodsCombining 30 relevant emergency medical facility construction cases in different cities in China from 2020 to 2021, seven condition variables and an outcome variable were selected, and necessary and sufficient condition analyses of duration influence factors were conducted using the fsQCA method.ResultsThe consistency of seven condition variables was

Hybrid pairing of the corresponding silkworm species is a pivotal link in sericulture, ensuring egg quality and directly influencing silk quantity and quality. Considering the potential of image recognition and the impact of varying pupal postures, this study used machine learning and deep learning for global modeling to identify pupae species and sex separately or simultaneously. The performance of traditional feature-based approaches, deep learning feature-based approaches, and their fusion approaches were compared. First, 3600 images of the back, abdomen, and side postures of 5 species of male and female pupae were captured. Next, six traditional descriptors, including the histogram of oriented gradients (HOG), and six deep learning descriptors, including ConvNeXt-S, were utilized to extract significant species and sex features. Finally, classification models were constructed using the multilayer perceptron (MLP), support vector machine, and random forest. The results indicate that the {HOG + ConvNeXt-S + MLP} model excelled, achieving 99.09% accuracy for separate species and sex recognition and 98.40% for simultaneous recognition, with precision–recall and receiver operating characteristic curves ranging from 0.984 to 1.0 and 0.996 to 1.0, respectively. In conclusion, it can capture subtle distinctions between pupal species and sexes and shows promise for extensive application in sericulture.

Target pests of genetically engineered crops producing both defensive allelochemicals and Bacillus thuringiensis (Bt) toxins often sequentially or simultaneously uptake allelochemicals, Bt toxins, and/or insecticides. How the three types of toxins interact to kill pests remains underexplored. Here we investigated the interactions of Bt toxin Vip3A, plant allelochemical flavone, and insecticide emamectin benzoate in Spodoptera frugiperda. Simultaneous administration of flavone LC25 + Vip3A LC25, emamectin benzoate LC25 + Vip3A LC25, and flavone LC15 + emamectin benzoate LC15 + Vip3A LC15 but not flavone LC25 + emamectin LC25 yielded a mortality significantly higher than their expected additive mortality (EAM). One-day pre-exposure to one toxin at LC5 followed by six-day exposure to the same toxin at LC5 plus another toxin at LC50 showed that the mortality of flavone LC5 + Vip3A LC50, emamectin benzoate LC5 + Vip3A LC50, and Vip3A LC5 + emamectin benzoate LC50 were significantly higher than their EAM, while that of flavone LC5 + emamectin benzoate LC50 was significantly lower than their EAM. No significant difference existed among the mortalities of Vip3A LC5 + flavone LC50, emamectin benzoate LC5 + flavone LC50, and their EAMs. The results suggest that the interactions of the three toxins are largely synergistic (inductive) or additive, depending on their combinations and doses.

Although diatom records from lake sediments have been used for quantitative paleoclimatic reconstruction, their validity and sensitivity have rarely been tested rigorously. At Yunlong Lake, an alpine lake in Southwest China, we studied the seasonal succession of diatom assemblages to produce a mean surface water temperature (MSWT) transfer function. In addition, based on the spatial distribution of surface diatom assemblages with water depth, we produced a diatom-water depth (WD) transfer function. Combined with the analysis of diatom assemblages in a sediment core (YL2013-A), changes in surface water temperature and water level over the last ∼100 years were quantitatively reconstructed using the diatom-based transfer functions. Comparison with records of regional meteorology and reservoir water capacity revealed that the diatom-based lake water level reconstruction is a sensitive indicator of short-term fluctuations in precipitation, and it also reflects a long-term stepwise rise in water level caused by the impounding and large-scale extension of the reservoir. In addition, the diatom-inferred MSWT is consistent with the changes in air temperature prior to large-scale human disturbance of the site. However, after the extension of the reservoir, although the regional air temperature continued to increase, the water temperature decreased substantially. This suggests that the large increase in lake water volume in the short term led to a decrease in the average water temperature, which in turn led to the occurrence of a diatom bloom in the cold season. The results demonstrate that diatom transfer functions based on modern observations of the same lake has a high environmental sensitivity and can be used for the quantitative reconstruction of regional climate change. Overall, our findings provide a foundation for the use of lake diatom records for quantitative paleoclimatic reconstruction on various timescales.

The carbon emissions trading market and direct power purchases by large consumers are two promising directions of power system development. To trace the carbon emission flow in the power grid, the theory of carbon emission flow is improved by allocating power loss to the load side. Based on the improved carbon emission flow theory, an optimal dispatch model is proposed to optimize the cost of both large consumers and the power grid, which will benefit from the carbon emissions trading market. Moreover, to better simulate reality, the direct purchase of power by large consumers is also considered in this paper. The OPF (optimal power flow) method is applied to solve the problem. To evaluate our proposed optimal dispatch strategy, an IEEE 30-bus system is used to test the performance. The effects of the price of carbon emissions and the price of electricity from normal generators and low-carbon generators with regards to the optimal dispatch are analyzed. The simulation results indicate that the proposed strategy can significantly reduce both the operation cost of the power grid and the power utilization cost of large consumers.

Seeking a strategy for triggering the cryptic natural product biosynthesis to yield novel compounds in the plant-associated fungus Xylaria sp., the effect of culture conditions on metabolite production was investigated. A shift in the production of five known cytochalasin-type analogues 1–5 to six new α-pyrone derivatives, xylapyrones A–F (compounds 6–11), from a solid to a liquid medium was observed. These compounds were identified by analysis of 1D and 2D NMR and HRMS data. Compounds 1–3 showed moderate cytotoxicity against HepG2 and Caski cancer cell lines with IC50 values ranging from 25 to 63 μM and compounds 4–11 were found to be inactive, with IC50 values >100 μM.

In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G) technique, electric vehicles (EVs) can act as mobile energy storage units, which could be a solution for load frequency control (LFC) in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC) theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG) are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances.

Background: Multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) hinder the progress of TB control. Objective: To track the trend of drug-resistant tuberculosis (DR-TB) prevalence in Zhejiang Province from 1999 to 2013, and identify risk factors of resistance to second-line drugs among MDR-TB patients. Design: Four DR-TB surveys had been done in Zhejiang Province in 1999, 2004, 2008 and 2013 through questionnaires, in which demographic and epidemiological items were included. After questionnaires, drug susceptibility testing (DST) targeted at four first-line drugs was done for all TB patients and DST targeted at six second-line drugs (only in 2008 and 2013) for MDR-TB patients. The drug resistance trend over time was analyzed using the Cochran–Armitage test. The factors associated with resistance to second-line drugs among MDR-TB patients were examined by a multivariate logistic regression model. Results: Of 936 patients enrolled, 27 (3.21%) and 20 (21.28%) MDR-TB cases were registered as new and previously treated cases, respectively. MDR-TB showed a decreasing trend (Z = −3.31, p

The smart grid is arguably one of the most complex cyber-physical systems (CPS). Complex security challenges have been revealed in both the physical and the cyber parts of the smart grid, and an integrative analysis on the cyber-physical (CP) security is emerging. This paper provides a comprehensive and systematic review of the critical attack threats and defence strategies in the smart grid. We start this survey with an overview of the smart grid security from the CP perspective, and then focuses on prominent CP attack schemes with significant impact on the smart grid operation and corresponding defense solutions. With an in-depth review of the attacks and defences, we then discuss the opportunities and challenges along the smart grid CP security. We hope this paper raises awareness of the CP attack threats and defence strategies in complex CPS-based infrastructures such as the smart grid and inspires research effort toward the development of secure and resilient CP infrastructures.

Nowadays, low frequency oscillation has become a major problem threatening the security of large-scale interconnected power systems. According to generation mechanism, active power oscillation of electric power systems can be classified into two categories: free oscillation and forced oscillation. The former results from poor or negative damping ratio of power system and external periodic disturbance may lead to the latter. Thus control strategies to suppress the oscillations are totally different. Distinction from each other of those two different kinds of power oscillations becomes a precondition for suppressing the oscillations with proper measures. This paper proposes a practical approach for power oscillation classification by identifying real-time power oscillation curves. Hilbert transform is employed to obtain envelope curves of the power oscillation curves. Twenty sampling points of the envelope curve are selected as the feature matrices to train and test the supporting vector machine (SVM). The tests on the 16-machine 68-bus benchmark power system and a real power system in China indicate that the proposed oscillation classification method is of high precision.

This paper proposed a fault-tolerant approach based on information fusion (IF) to automatically locate the transient voltage disturbance source (TVDS) in smart distribution grids. We first defined three credibility factors that will influence the reliability of the direction-judgments at each power quality monitor (PQM). Then we proposed two rules of influence and a verification factor for the distributed generation (DG) integration. Based on the two sets of direction-judgment criteria, a novel decision-making method with fault tolerance based on the IF theory is proposed for automatic location of the TVDS. Three critical schemes, including credibility fusion, conflict weakening, and correction for DG integration, have been integrated in the proposed fusion method, followed by a reliability evaluation of the location results. The proposed approach was validated on the IEEE 13-node test feeder, and the TVDS location results demonstrated the effectiveness and fault tolerance of the IF based approach.