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The return of crop residues to cultivated fields has numerous agronomic and soil quality benefits and, therefore, the areal extent of crop residue cover (CRC) could provide a rapid measure of the sustainability of agricultural production systems in a region. Recognizing the limitations of traditional CRC methods, a new method is proposed for estimating the spatial and temporal distribution of maize residue cover (MRC) in the Jilin Province, NE China. The method used random forest (RF) algorithms, 13 tillage indices and 9 textural feature indicators derived from Sentinel-2 data. The tillage indices with the best predictive performance were STI and NDTI (R2 of 0.85 and 0.84, respectively). Among the texture features, the best-fitting was Band8AMean-5∗5 (R2 of 0.56 and 0.54 for the line-transect and photographic methods, respectively). Based on MSE and InNodePurity, the optimal combination of RF algorithm for the line-transect method was STI, NDTI, NDI7, NDRI5, SRNDI, NDRI6, NDRI7 and Band3Mean-3∗3. Likewise, the optimal combination of RF algorithm for the photographic method was STI, NDTI, NDI7, SRNDI, NDRI6, NDRI5, NDRI9 and Band3Mean-3∗3. Regional distribution of MRC in the Jilin Province, estimated using the RF prediction model, was higher in the central and southeast sections than in the northwest. That distribution was in line with the spatial heterogeneity of maize yield in the region. These findings showed that the RF algorithm can be used to map regional MRC and, therefore, represents a useful tool for monitoring regional-scale adoption of conservation agricultural practices.

Conservation tillage is an important conservation measure for arable land in modern agricultural production, which plays an essential role in protecting black soil and improving the quality of arable land. The estimation of maize residue cover (MRC) can be used to obtain the spatial distribution characteristics of conservation tillage, which is essential for government departments to promote conservation tillage technology and understand the implementation of it. In this paper the southern part of the Songnen Plain was used as the study area, and Sentinel-2 MSI images and Sentinel-1 SAR images were used as data sources to correlate the spectral indices and radar backscatter coefficients with the field sampling data in the study area. The MRC estimation model of the study area was constructed using the Random Forest (RF) model, the Multiple Linear Stepwise Regression (MLSR) model, and Back Propagation Neural Network (BPNN) model, respectively. The results of the study showed that the correlation coefficients of normalized difference tillage index (NDTI), simple tillage index (STI), normalized difference index (NDI5), NDI7, shortwave infrared normalized difference residue index (SINDRI), normalized difference senescent vegetation index (NDSVI), normalized difference residue index 2 (NDRI2), NDRI3, NDRI4, NDRI5, NDRI6, NDRI7, NDRI8, NDRI9, and MRC in the study area were greater than 0.4, and the correlation coefficients were higher for NDTI and STI, which reached 0.861 and 0.860, respectively. The correlation coefficient between VV and MRC was 0.56 and between VH and MRC was 0.594. We used MLSR, RF, and BPNN methods in combination with Sentinel-2 MSI images and Sentinel-1 SAR images for MRC estimation. The synergistic use of Sentinel-2 MSI images and Sentinel-1 SAR images helped to improve the accuracy of the MRC estimation models and the correlation coefficient R2 of all three models to greater than 0.8. Based on the statistical analysis of remote sensing estimation results, we found that the average value of the MRC of the maize growing areas in Changchun, Siping, and eastern Songyuan in November 2020 was 66%, and 2% of farmland in the study area had a MRC of less than 30%.

Abstract The homeostasis of the gut microbiota is a crucial factor in regulating peripheral and central blood pressure. Formulating a food-derived mixture of antioxidants, anti-inflammatory compounds and prebiotics to maintain the homeostasis of the gut microbiota will be essential for preventing and alleviating hypertension. Although bioactive peptides and plant extracts have been demonstrated not only to be excellent antioxidants and anti-inflammatory agents but also to promote the homeostasis of the microbiota, few studies have investigated the influence of multiple peptides mixed with plant extracts on the gut microbiota of hypertensive rats. This is the first study to characterize the fecal microbiome of spontaneously hypertensive rats supplemented with a mixture of multiple peptides and plant extracts by integrating 16 S rRNA gene sequencing. During the six-week experiment, the animals were healthy and without mortality. The results revealed that oral supplementation with the formulation reduced both systolic and diastolic blood pressure, improved the gut microbiota by increasing the ratio of Bacteroidetes to Firmicutes, and increased the relative abundance of specific genera, such as Lactobacillus. This study suggested that a synergistic formulation of multiple peptides mixed with plant extracts could be a novel strategy for preventing and alleviating hypertensive diseases. Graphical Abstract

Abstract Background The neural cells in the brains of patients with Parkinson’s disease (PWP) display aberrant synchronized oscillatory activity within the beta frequency range. Additionally, enhanced gamma oscillations may serve as a compensatory mechanism for motor inhibition mediated by beta activity and also reinstate plasticity in the primary motor cortex affected by Parkinson’s disease. Transcranial alternating current stimulation (tACS) can synchronize endogenous oscillations with exogenous rhythms, thereby modulating cortical activity. The objective of this study is to investigate whether the addition of tACS to multidisciplinary intensive rehabilitation treatment (MIRT) can improve symptoms of PWP so as to enhance the quality of life in individuals with Parkinson’s disease based on the central-peripheral-central theory. Methods The present study was a randomized, double-blind trial that enrolled 60 individuals with Parkinson’s disease aged between 45 and 70 years, who had Hoehn-Yahr scale scores ranging from 1 to 3. Participants were randomly assigned in a 1:1 ratio to either the tACS + MIRT group or the sham-tACS + MIRT group. The trial consisted of a two-week double-blind treatment period followed by a 24-week follow-up period, resulting in a total duration of twenty-six weeks. The primary outcome measured the change in PDQ-39 scores from baseline (T0) to 4 weeks (T2), 12 weeks (T3), and 24 weeks (T4) after completion of the intervention. The secondary outcome assessed changes in MDS-UPDRS III scores at T0, the end of intervention (T1), T2, T3, and T4. Additional clinical assessments and mechanistic studies were conducted as tertiary outcomes. Discussion The objective of this study is to demonstrate that tACS can enhance overall functionality and improve quality of life in PWP, based on the framework of MIRT. Additionally, it seeks to establish a potential correlation between these therapeutic effects and neuroplasticity alterations in relevant brain regions. The efficacy of tACS will be assessed during the follow-up period in order to optimize neuroplasticity and enhance its potential impact on rehabilitation efficiency for PWP. Trial registration Chinese Clinical Trial Registry ChiCTR2300071969. Registered on 30 May 2023.

Remote sensing estimation of maize residue cover (MRC) can rapidly acquire large-scale data on MRC, crucial for monitoring and promoting conservation tillage. Herein, seven tillage indices derived from Sentinel-2 satellite imagery were analyzed alongside measured MRC data to assess their correlation with MRC. MRC estimation models were built using six machine learning algorithms, including back propagation neural network (BPNN), random forest (RF), support vector regression (SVR), extreme gradient boosting (XGBoost), Stacking1, and Stacking2. Model performance was compared using the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The potential for conservation tillage was explored. The results showed that the R2 values of the seven tillage indices in the study area exceeded 0.5, with particularly high correlations for NDTI and STI, with R2 values of 0.755 and 0.751, respectively. When using machine learning algorithms to construct models, the Stacking2 model exhibited the highest estimation accuracy, with an R2 of 0.923, RMSE of 3.32%, and MAE of 0.025, while Stacking1 also demonstrated robust performance, with an R2 of 0.910, RMSE of 3.45%, and MAE of 0.029. Among the base models, XGBoost achieved the highest estimation performance and the lowest error, with R2, RMSE, and MAE values of 0.884, 4.77%, and 0.031, respectively. The R2 values of RF, SVR, and BPNN were 0.865, 0.859, and 0.842, respectively, with RMSE values of 4.06%, 4.76%, and 5.91%, and MAE values of 0.039, 0.047, and 0.059, respectively. These results indicate that the Stacking2 model demonstrates a significant advantage in prediction accuracy. Geostatistical analysis of the inversion results of the Stacking2 model revealed that the proportions of farmland with MRC values exceeding 30% in Changchun, Songyuan, and Siping were 81.90%, 77.96%, and 83.58%, respectively. This indicates that Changchun and Siping have greater potential for implementing conservation tillage. This study demonstrates that the stacking ensemble learning model significantly improves the predictive performance by leveraging the strengths of multiple base models and accurately monitoring the spatial distribution of MRC.

The management of crop residues in farmland is crucial for increasing soil organic matter and reducing soil erosion. Identifying the regional extent of crop residue cover (CRC) is vital for implementing conservation tillage and formulating agricultural subsidy policies. The Google Earth Engine (GEE) and remote sensing images from 2019 to 2023 were used to obtain spectral characteristics before the maize seedling stage in Northeast China, followed by constructing the CRC estimation models using machine learning algorithms. To avoid the impact of multicollinearity among data, three machine learning algorithms—ridge regression (RR), partial least squares regression (PLSR), and least absolute shrinkage and selection operator (LASSO)—were employed. By comparing the accuracy of these methods, the most accurate model was determined and applied to subsequent CRC estimation. Based on the estimated CRC and Conservation Technology Information Center definitions of tillage practices, the conservation tillage mapping was completed, and the spatiotemporal distribution characteristics were thoroughly analyzed. The following findings were demonstrated: (1) the PLSR-based model outperformed RR (Pearson’s correlation coefficient (r) = 0.8875, R2 = 0.7877, RMSE = 6.99%) and LASSO (r = 0.8903, R2 = 0.7926, RMSE = 6.88%) with higher accuracy (r = 0.9264, R2 = 0.8582, RMSE = 4.93%). (2) Over the five years, the average no-tillage (NT) proportion in the study area was 15.9%, reduced tillage (RT) was 17.8%, and conventional tillage (CT) was 66.3%. In 2020 and 2022, NT rates were significantly higher at 27.5% and 15.5%, while RT were 15.7% and 30.0%, respectively. (3) Compared to the Sanjiang and Liaohe Plains (RT = 1907 km2 and 1336 km2, and NT = 559 km2 and 585 km2, respectively), the Songnen Plain exhibited higher conservation tillage rates (where RT was 3791 km2 and NT was 1265 km2). This provides crucial scientific evidence for the management and planning of conservation tillage, thereby optimizing farmland production planning, enhancing production efficiency, and promoting the development of sustainable agricultural production systems.

The southern catfish (Silurus meridionalis) is an economically important carnivorous freshwater fish in China. In this study, we compared the properties of skin collagen from southern catfish fed with raw food (RF) and cooked food (CF). The skin collagen yield in the RF group (8.66 ± 0.11%) was significantly higher than that of the CF group (8.00 ± 0.27%). SDS-PAGE, circular dichroism spectroscopy, and FTIR analyses revealed that the collagen extracted from southern catfish skin in both groups was type I collagen, with a unique triple helix structure and high purity. The thermal denaturation temperature of collagen in the RF group (35.20 ± 0.11 °C) was significantly higher than that of the CF group (34.51 ± 0.25 °C). The DPPH free radical scavenging rates were 68.30 ± 2.41% in the RF collagen and 61.78 ± 3.91% in the CF collagen, which was higher than that found in most fish collagen. Both the RF and CF groups had high ability to form fibrils in vitro. Under the same conditions, the CF group exhibited faster fibril formation and a thicker fibril diameter (p < 0.05). In addition, the RF group exhibited significantly higher expression of col1a1 compared to the CF group. These results indicated that feeding southern catfish raw food contributed to collagen production, and the collagen from these fish may have potential in biomaterial applications.

Supercapacitors (SCs) are widely recognized as competitive power sources for energy storage. The hierarchical structure of nickel vanadium sulfide nanoparticles encapsulated on graphene nanosheets (NVS/G) was fabricated using a cost-effective and scalable solvothermal process. The reaction contents of the composites were explored and optimized. TEM images displayed the nickel vanadium sulfide nanoparticles (NVS NPs) with 20–30 nm average size anchored to graphene nanosheets. The interconnection of graphene nanosheets encapsulating NVS nanoparticles effectively reduces the ion diffusion path between the electrode and electrolyte, thereby enhancing electrochemical performance. The NVS/G composite demonstrated improved electrochemical performance, achieving a maximum of 1437 F g−1 specific capacitance at 1 A g−1, remarkable rate capability retaining of 1050 F g−1 at 20 A g−1, and exceptional cycle stability with 91.2% capacitance retention following 10,000 cycles. The NVS/G composite was employed as a cathode, and reduced graphene oxide (rGO) was used as an anode material to assemble a device. Importantly, asymmetric SCs using NVS/G//rGO achieved 74.7 W h kg−1 energy density at 0.8 kW kg−1 power density, along with outstanding stability with 88.2% capacitance retention following 10,000 cycles. These superior properties of the NVS/G electrode highlight its significant potential in energy storage applications.

Abstract. Background:. Screening using low-dose computed tomography (LDCT) is a more effective approach and has the potential to detect lung cancer more accurately. We aimed to conduct a meta-analysis to estimate the accuracy of population-based screening studies primarily assessing baseline LDCT screening for lung cancer. Methods:. MEDLINE, Excerpta Medica Database, and Web of Science were searched for articles published up to April 10, 2022. According to the inclusion and exclusion criteria, the data of true positives, false-positives, false negatives, and true negatives in the screening test were extracted. Quality Assessment of Diagnostic Accuracy Studies-2 was used to evaluate the quality of the literature. A bivariate random effects model was used to estimate pooled sensitivity and specificity. The area under the curve (AUC) was calculated by using hierarchical summary receiver-operating characteristics analysis. Heterogeneity between studies was measured using the Higgins I2 statistic, and publication bias was evaluated using a Deeks’ funnel plot and linear regression test. Results:. A total of 49 studies with 157,762 individuals were identified for the final qualitative synthesis; most of them were from Europe and America (38 studies), ten were from Asia, and one was from Oceania. The recruitment period was 1992 to 2018, and most of the subjects were 40 to 75 years old. The analysis showed that the AUC of lung cancer screening by LDCT was 0.98 (95% CI: 0.96–0.99), and the overall sensitivity and specificity were 0.97 (95% CI: 0.94–0.98) and 0.87 (95% CI: 0.82–0.91), respectively. The funnel plot and test results showed that there was no significant publication bias among the included studies. Conclusions:. Baseline LDCT has high sensitivity and specificity as a screening technique for lung cancer. However, long-term follow-up of the whole study population (including those with a negative baseline screening result) should be performed to enhance the accuracy of LDCT screening.

With the deepening exploratory development, geological targets are gradually shifting from conventional reservoirs to unconventional ones. The sandstone reservoirs in the northeast margin of the Ordos Basin are stacked vertically and change quickly horizontally with thin thicknesses. Therefore, traditional inversion technology cannot satisfy the requirements of precise prediction of thin reservoirs. To solve this problem, this paper integrated geological, seismic and logging data based on the GR curve. A wave form simulation of the MG block in the eastern margin of Ordos Basin was conducted, and the distribution of sandstone reservoirs in the target bed was depicted. The results showed that the waveform indication simulation profiles had a high resolution both horizontally and vertically. They were also in line with the drilling well and strongly correlated with the seismic waveform, which could reflect the spatial variation in the reservoir and accord with the law of geological deposition in the study area. Therefore, as a more efficient inversion method, waveform indication simulation provided a strong support for the refined study of thin inter-bedded reservoirs and helped to maximize the development and utilization of gas resources.

Reconfigurable and tunable terahertz electronic devices are promising for various technological applications, for which metamaterials are receiving interest. Here, a graphene/gold bilayer metasurface enables the creation of a frequency-selective absorber with electrical tuning in the 0.1–1 THz range.

Recently, coordination polymers (CPs) have been frequently reported in the field of energy storage as electrode materials for lithium-ion batteries (LIBs) due to their highly adjustable architectures, which have a variety of active sites and obviously defined lithium transport routes. A well-designed redox-active organic linker with potential active sites for storing lithium ions, pyrazine-2,3-dicarboxylate (H2PDA), was applied for generating CPs by a simple hydrothermal method. When employed as anode materials in LIBs, those two one-dimensional (1D) CPs with an isomorphic composition, [M(PDA)(H2O)2]n (M = Co for Co-PDA and Ni for Ni-PDA), produced outstanding reversible capacities and stable cycling performance. The Co-PDA displays a substantial reversible capacity of 936 mAh g−1 at 200 mA g−1 after 200 cycles, as well as an excellent cycling life at high currents. According to the ex situ characterizations, the high reversible specific capacity of the post-cycled electrodes was found to be a result of both the transition metal ions and the organic ligands, and Co-PDA and Ni-PDA electrode materials show reversible insertion/extraction processes that are accompanied by crystallization to an amorphous state.

China’s rapid urbanization has greatly boosted the quality of life of its traditionally impoverished regions. Research into the spatial distribution characteristics, evolution and spatial correlation of the quality of life in impoverished regions can help illuminate the experience of successful development and construct a knowledge base for authorities to devise development strategies. This study focuses its attention on the historically impoverished districts and counties (which are designated as parallel administrative units in China) of Guizhou Province in southwestern China. Extensively citing official statistics on districts and counties released by China’s National Bureau of Statistics and local governments, it assesses the quality of life of those places in the 3 years of 2000, 2010, and 2020 from the four dimensions of economy, society, culture, and environment. The aim is to illustrate the distribution characteristics and the evolution of quality of life in Guizhou’s historically impoverished districts and counties. In order to understand the characteristics of spatial clustering as well as the patterns of evolution of the quality of life of Guizhou’s impoverished districts and counties, the study incorporates spatial autocorrelation analysis into a spatio-temporal analysis of local quality of life. It could presumably help enrich the knowledge base that local authorities draw on to formulate development strategies that are scientific and adapted to local conditions. The study found that while the overall quality of life in all the impoverished districts and counties of Guizhou Province has improved, large gaps in quality of life between eastern and western regions of the province persisted. In addition, the driving force behind the evolution in the overall quality of life of those places changed with time, as did the characteristics of the spatial aggregation in quality of life.

High temperature (high-Tc) superconductors (HTS) have found many applications in the last two decades. To microwave researchers and engineers, the ultra-low surface resistance of the thin-film HTS materials at microwave and millimeter frequencies and the highly non-linear Josephson junctions are of particular interest. The former can be exploited in the design and fabrication of passive microwave components and circuits with superior performance, and the latter can be exploited to create many novel active HTS devices. This paper provides an overview of the state-of-art development of HTS devices and circuits for microwave and mm-wave communication front-end receiver systems. The paper is particularly focused on the latest advancement of HTS Josephson junction based active devices, monolithic microwave integrated circuits (MMIC), and whole receiver systems integrated with cryocoolers.

Lake water surface albedo (LWSA) is a critical parameter for describing energy flux balance at the air–water interface. It is used to measure the capacity of lake water surface reflectance in the shortwave radiation band, which controls the energy partitioning between atmosphere and lake. LWSA and its driving factors, including solar radiation angle, water quality and meteorology, in lakes of Northeast China was analyzed in this research. Solar altitude angle emerged as the most important controlling factor of LWSA. The results showed a strong reduction in LWSA values with increase in solar altitude angle. The study also documented a strong effect of suspended matter on the radiative properties of lakes surface, leading to increased LWSA with increased in suspended matter concentration, especially at high solar altitude angles (R2: 0.76). While no significant association (R2: 0.11) was found between LWSA and chlorophyll-a concentration, LWSA was positively correlated with wind speed (R2 of 0.62 and 0.50 at high and low solar altitude angles, respectively), likely a consequence of wind-driven sediment resuspension in lake waters. Although chromophoric dissolved organic matter (CDOM) and organic particulate matter can affect energy partitioning and spectral distribution of incident solar radiation in lake waters, there was insufficient evidence of measurable effects on LWSA. Variations in LWSA recorded in this study were primarily dependent on similar solar altitude angles and backscattering properties of inorganic particulate matter suspended in the water column. Higher surface albedo was found in the turbid lakes.

Abstract Gas diffusion electrode (GDE) setups have been recently introduced as a new experimental approach to test the performance of fuel cell catalysts under high mass transport conditions, while maintaining the simplicity of rotating disk electrode (RDE) setups. In contrast to experimental RDE protocols, for investigations using GDE setups only few systematic studies have been performed. In literature, different GDE arrangements were demonstrated, for example, with and without an incorporated proton exchange membrane. Herein, we chose a membrane‐GDE approach for a comparative RDE–GDE study, where we investigate several commercial standard Pt/C fuel cell catalysts with respect to the oxygen reduction reaction (ORR). Our results demonstrate both the challenges and the strengths of the new fuel cell catalyst testing platform. We highlight the analysis and the optimization of catalyst film parameters. That is, instead of focusing on the intrinsic catalyst ORR activities that are typically derived in RDE investigations, we focus on parameters, such as the catalyst ink recipe, which can be optimized for an individual catalyst in a much simpler manner as compared to the elaborative membrane electrode assembly (MEA) testing. In particular, it is demonstrated that ∼50% improvement in ORR performance can be reached for a particular Pt/C catalyst by changing the Nafion content in the catalyst layer. The study therefore stresses the feasibility of the GDE approach used as an intermediate “testing step” between RDE and MEA tests when developing new fuel cell catalysts.

Modification of the divergent wind components and domain of interests can result in obvious changes in the kinetic energy (KE) budget of typhoons and other synoptic systems. Before analyzing the effects of divergent winds on the KE budget of Typhoon Rumbia (2018) during its entire life cycle, especially in its extratropical transition (ET) process, a hybrid integral method to partition the horizontal wind fields in a limited domain with high accuracy is adopted, in comparison with the commonly used iterative method under two sets of domains, that is, the typhoon following domain and the outermost domain that covers the entire typhoon track. The relative importance of the divergent and non-divergent winds in the KE budget is investigated in the three stages of the ET process, namely, the pre-development, re-intensification, and dissipation stages. It is found that the divergent winds computed by the iterative method with a lower accuracy result in sizable errors in spatiotemporal variations of the KE of the typhoon during its ET process, which thus leads to obvious forecasting errors.

American shad (Alosa sapidissima), introduced from the United States, has become one of the most expensive farmed fish in the aquatic product market of China. The shad reveals significant sexual dimorphism in growth and behaviors. For the study, five male-specific tags were identified in two-generation breeding populations of Alosa sapidissima and were verified by PCR amplification. Averages of 10,245,091 and 8,685,704 raw and enzyme reads were obtained by high-throughput sequencing of the 2b-RAD library, respectively. 301,022 unique tags were obtained from the sequences of twenty samples with sequencing depths of 0 to 500. Finally, 274,324 special tags and 29,327 SNPs were selected with a sequencing depth of 3 to 500. Eleven preliminary screening male-specific tags and three male heterogametic SNP loci were isolated. After verification by PCR amplification, five male-specific sequences of 27 bp located on chromosome 3 were screened out. Chromosome 3 could be assumed to be the sex chromosome of Alosa sapidissima. Sex-specific markers will provide invaluable and systematic animal germplasm resources to allow for the precise identification of neo-males for the all-female breeding of Alosa sapidissima in commercial aquaculture.

To screen for common target genes in intracranial aneurysms (IA) and type 2 diabetes mellitus (T2DM), construct a common transcriptional regulatory network to predict clusters of candidate genes involved in the pathogenesis of T2DM and IA, and identify the common neurovascular markers and pathways in T2DM causing IA. Microarray datasets (GSE55650, GSE25462, GSE26969, GSE75436, and GSE13353) from the GEO database were analyzed in this research. Screening of the IA and the T2DM datasets yielded a total of 126 DEGs, among which 78 were upregulated and 138 were downregulated. Functional enrichment analysis revealed that these DEGs were enriched for a total of 68 GO pathways, including extracellular matrix composition, coagulation regulation, hemostasis regulation, and collagen fiber composition pathways. We also constructed transcriptional regulatory networks, and identified key transcription factors involved in both the conditions. Univariate logistic regression analysis showed that ARNTL2 and STAT1 were significantly associated with the development of T2DM and IA, acting as the common neurovascular markers for both the diseases. In cellular experiments, hyperglycemic microenvironments exhibited upregulated STAT1 expression. STAT1 may be involved in the pathogenesis of IA in T2DM patients. Being the common neurovascular markers, STAT1 may acts as novel therapeutic targets for the treatment of IA and T2DM.

Individual surveillance methods help identify subtle health risks that may be overlooked in room surveillance. This study aims to investigate campus environmental health issues by tracking university students’ daily exposure processes in their living environment. A field survey was conducted among 58 students at a university in northern China. They were equipped with a “companion data collection device” to record exposure experiences and activity pathways related to light, heat, and air environments. A questionnaire was also administered. Morning exposure to adequate light (Circadian Stimulus ≥ 0.3) increased alertness, but only 57% of undergraduates met this standard, and 67% of those waking up after 8 AM experienced this. People with different preferences chose diverse dining spots, and those favoring “roasted,” “stir-fried,” and “deep-fried” foods encountered higher PM2.5 pollution concentrations during meals. During periods of central heating, there is a trade-off between ventilation and heating efficiency. “Slightly open window” for bedroom ventilation at night resulted in a slight temperature decrease of about 1.2 °C but effectively controlled the increase in CO2 concentrations (about 180 ppm). Companion-type data collection shifts focus from buildings to individuals, providing the means and basis for identifying potential health risks in daily campus life.

Crop residue burning produces a lot of polluting gases and fine particles, endangering human health, damaging soil structure, and causing fire accidents. In addition to the impact of residue burning on the local environment, pollutants can spread with the wind to more distant areas and impact their air quality. Nevertheless, a comparative analysis of the impact of two common residue burning parameters, the number of residue fire points, and residue burned area on urban air quality indicators has not been reported. In this study, the correlation between these two different residue burning parameters on air quality in Daqing City (Western Heilongjiang Province, China) was investigated comparatively using the Visible Infrared Imaging Radiometer Suite (VIIRS) fire point product, the Moderate-resolution Imaging Spectroradiometer (MODIS) burned area product, and buffer zone analysis. The association between MODIS burned area products and air quality index (AQI) was found to be around 0.8. Meanwhile, it was found that the correlation between the number of residue fire points extracted from the VIIRS active fire products and air quality was above 0.6, again with a maximum of 0.75 at a buffer radius of 50 km. Within other levels of buffer zones, the correlation between residue burned area and AQI was consistently higher than that between residue fire points and AQI. By comparing the correlation between VIIRS fire points, MODIS burned area, and the concentration of each AQI pollutant, it can be found that the correlation between the concentration of each AQI pollutant and the residue burned area was higher than that and the fire points number. MODIS burned area monitoring, on the other hand, detects changes in the time series of images taken by satellite at two transit moments to obtain a new burned area and cumulative burned area during this period, allowing the monitoring of fire traces caused by fire points at non-transit moments. From analyzing the correlation between residue fire points, residue burned area, and the concentration of each pollutant (PM2.5, PM10, CO, NO2, SO2, and O3), we found significant correlations between residue burning and PM2.5, PM10, CO, and NO2 concentrations, with the highest correlation (R2) of 0.81 for PM2.5. Moreover, the correlation between residue burned area and PM2.5, PM10, CO, and NO2 concentrations was significantly higher than that between the number of residue fire points and their concentrations.

Fluoroquinolone antibiotics are widely used in human and veterinary medicine and are ubiquitous in the environment worldwide. This paper recapitulates the occurrence, fate, and ecotoxicity of fluoroquinolone antibiotics in various environmental media. The toxicity effect is reviewed based on in vitro and in vivo experiments referring to many organisms, such as microorganisms, cells, higher plants, and land and aquatic animals. Furthermore, a comparison of the various toxicology mechanisms of fluoroquinolone antibiotic residues on environmental organisms is made. This study identifies gaps in the investigation of the toxic effects of fluoroquinolone antibiotics and mixtures of multiple fluoroquinolone antibiotics on target and nontarget organisms. The study of the process of natural transformation toward drug-resistant bacteria is also recognized as a knowledge gap. This review also details the combined toxicity effect of fluoroquinolone antibiotics and other chemicals on organisms and the adsorption capacity in various environmental matrices, and the scarcity of data on the ecological toxicology evaluation system of fluoroquinolone antibiotics is identified. The present study entails a critical review of the literature providing guidelines for the government to control the discharge of pollutants into the environment and formulate policy coordination. Future study work should focus on developing a standardized research methodology for fluoroquinolone antibiotics to guide enterprises in the design and production of drugs with high environmental biocompatibility.

BackgroundExpanding the druggable novel anaplastic lymphoma kinase (ALK) fusions list is crucial to the precise treatment of patients with cancer with positive ALK fusions. The intergenic-ALK fusions accounted for a substantial proportion of ALK fusions. However, they were typically considered of limited clinical significance due to the obscure functional partners. In this case report, a patient carrying intergenic-ALK fusion presents an excellent outcome after taking the new second-generation tyrosine kinase inhibitor (TKI) candidate, WX-0593.Case PresentationA 47-year-old Chinese female patient diagnosed with IVB lung adenocarcinoma was admitted to the hospital with large dimension lesions in the left lobe of the lung. After 1 week of first line chemotherapy, no response was found. A novel ALK rearrangement generated by a fusion of the intergenic region between SLC8A1 and PKDCC to the intron 19 of ALK was presented after next-generation sequencing and was further confirmed by Sanger’s sequencing. High expression of ALK was revealed by immunohistochemistry. The patient was directed to engage in phase III clinical trial (NCT04632758) and received an orally active second-generation ALK inhibitor WX-0593. Over the course of 17 months, the partial response was obtained without significant side effects.ConclusionIn summary, a patient with non–small cell lung cancer harboring a novel intergenic-ALK fusion, whose intergenic breakpoint was located between SLC8A1 and PKDCC, benefited from a potent ALK TKI candidate WX-0593. This finding extended the scope of targetable ALK fusions. More importantly, it highlighted the advantages of next-generation sequencing in identifying rare but functional ALK fusions, which eventually benefit patients.

An exponential function model was developed based on the red band from Landsat and in situ data. The model performed well, the calibration determination coefficient (R2) was 0.82 and validation metrics root-mean-square error, mean absolute percent error, and bias was 8.23 mg/L, 30% and −2.35 mg/L, respectively. Then, the time series of total suspended matter (TSM) concentrations for the lakes across Inner Mongolia were presented using the Landsat data from 1984–2019. The results showed that the number of the lakes with TSM decrease was slightly more than that with TSM increase (57% versus 43%). A total of 70.72% of those lakes had a changing rate less than 1 mg/L/yr in TSM, while the other 29.28% had a changing rate more than 1 mg/L/yr. In some lakes (24.2%), the coefficient of variation was greater than 102% indicating significant spatial variation. The TSM less than 20 mg/L mainly appeared in the reservoirs. Based on different environmental backgrounds, this study showed comprehensive estimates (increasing and decreasing regions) of TSM concentrations. Finally, the relative roles of several factors to the TSM changes were quantified and examined at different scales. The responses of TSM changes to NDVI representing vegetation coverage indicated that vegetation played an important role for most lakes. Whilst wind speed and precipitation significantly affected a few lakes. For most lakes, the TSM were affected by multiple factors, where a single factor could not be highlighted. Nevertheless, a comprehensive analysis of the factors surrounding a lake remains relevant for determining the possible trend (better or worse) of its TSM variation.

Monitoring water quality of inland lakes and reservoirs is a great concern for the public and government in China. Water turbidity is a reliable and direct indicator that can reflect the water quality. Remote sensing has become an efficient technology for monitoring large-scale water turbidity. This study aims to search an optimal regression model to accurately predict water turbidity using remote sensing data. To achieve this goal, 187 water samples were collected from field campaigns across Northeast China, in 2018, of which the samples were gathered within ±6 days of Sentinel-2 overpasses. The spectral reflectance data was used as independent variables for modeling. The simple regression, partial least squares regression, support vector regression, extreme learning machine, back-propagation neural network, classification and regression tree, gradient boosting decision tree (GBDT), random forest (RF), and K-nearest neighbor were used to compare. From model validation, we identified GBDT as the best regression model (R2 = 0.88, RMSE = 9.90 NTU, MAE = 6.71 NTU). We applied GBDT to retrieve the water turbidity and obtained a satisfactory result. Feature selection technique from tree-based ensemble method was also tested. We selected B2, B3, B4, and B5 as the important variables because of their high ability to explain the variation of turbidity. These results demonstrated the significance of using a promising method to retrieve water turbidity using Sentinel-2 imagery at the regional scale. It is beneficial to monitor the spatial-temporal distribution of water turbidity; support water quality management and inland water environment protection.

Because of global warming, the water cycle has intensified and precipitation has changed, with monsoons evolving to become more complex, particularly in monsoon fringe areas. Therefore, it is important to use stable isotopes to trace moisture sources in monsoon fringe areas, such as semiarid areas. In this study, in situ measurements of water vapor isotopes were obtained in the monsoon fringe areas of Lanzhou (36.1° N, 103.7° E), between May and November 2019 with the aim of analyzing the stable isotope composition and atmospheric water vapor variation to improve our understanding of moisture transport. The following results were obtained: stable isotopic variation of atmospheric water vapor shows an alternation between west and southwest moisture with wind directions and sources of water vapor, with δ18O and δ2H varying from high to low. In the Lanzhou valley, water vapor isotopes show a distinct daily cycle of δ17O, δ18O, and δ2H and are consistent with temperature changes. Water vapor isotopes, particularly d-excess, are correlated with temperature and absolute humidity. With regard to the local atmospheric water vapor line (LAVL), we show that the slope and intercept of the LAVL are affected by sub-cloud secondary evaporation and topography.

The burning of straw is a very destructive process that threatens people’s livelihoods and property and causes irreparable environmental damage. It is therefore essential to detect and control the burning of straw. In this study, we analyzed Sentinel-2 data to select the best separation bands based on the response characteristics of clouds, smoke, water bodies, and background (vegetation and bare soil) to the different bands. The selected bands were added to the red, green, and blue bands (RGB) as training sample data. The band that featured the highest detection accuracy, RGB_Band6, was finally selected, having an accuracy of 82.90%. The existing object detection model cannot directly handle multi-band images. This study modified the input layer structure based on the YOLOv5s model to build an object detection network suitable for multi-band remote sensing images. The Squeeze-and-Excitation (SE) network attention mechanism was introduced based on the YOLOv5s model so that the delicate features of smoke were enhanced, and the Convolution + Batch normalization + Leaky ReLU (CBL) module was replaced with the Convolution + Batch normalization + Mish (CBM) module. The accuracy of the model was improved to 75.63%, which was 1.81% better than before. We also discussed the effect of spatial resolution on model detection and where accuracies of 84.18%, 73.13%, and 45.05% for images of 60-, 20-, and 10-m resolution, respectively, were realized. The experimental results demonstrated that the accuracy of the model only sometimes improved with increasing spatial resolution. This study provides a technical reference for the monitoring of straw burning, which is vital for both the control of straw burning and ways to improve ambient air quality.

As the population grows, the development of conservation tillage offers a means of promoting the sustainability of agricultural engineering. Remote sensing images with high spatial and temporal resolutions enable the accurate monitoring of conservation tillage on a broad spatial scale, further promoting conservation tillage research. This paper describes using streamlined time series Sentinel-2 images based on the Google Earth Engine (GEE) cloud platform for mapping maize tillage practices in the Songnen Plain region of Northeast China. Based on the correlation with the normalized difference tillage index (NDTI) and maize residue coverage (MRC) data, the optimal time series and streamlining functions in the GEE cloud platform are determined. Estimates of MRC and the mapping of tillage practices in the Songnen Plain for 2019–2022 are then determined using GEE and a previous model. Geostatistical analysis using ArcGIS is applied to analyze the spatial and temporal distribution characteristics of MRC and conservation tillage over the Songnen Plain. The results show that time series images from 20–30 May achieve an r value of 0.902 and an R2 value of 0.8136 when using the median streamlining function. The mean MRC for the study area in 2022 is 2.3%, and an overall upward trend in conservation tillage is observed (from 0.08% in 2019 to 0.25% in 2022). Our analysis shows that MRC monitoring and conservation tillage mapping can be performed over a broad spatial scale using remote sensing technology based on the GEE cloud platform. Spatial and temporal information on farm practices provides a theoretical basis for agricultural development planning efforts, which can promote sustainable agricultural development.

In the remote sensing monitoring of conservation tillage, the acquisition of remote sensing data with high spatial and temporal resolution is critical. The current optical remote sensing images cannot realize both temporal and spatial resolution, especially under cloud and rain interference. Thus, this study employs the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) to obtain the normalized difference tillage index (NDTI) with both temporal and spatial resolution estimated by Sentinel−2 and MODIS using the Index−then−Blend (IB) and Blend−then−Index (BI) fusion schemes. After comparison, the IB scheme was better than the BI scheme in predicting results and prediction efficiency. The NDTI predicted by ESTARFM and Sentinel−2 on June 12, 2020 was compared. A coefficient of determination R2 of 0.73 and RMSE of 0.000117 was obtained, indicating a high prediction accuracy, which meets the prediction requirements. Based on the predicted ESTARFM NDTI of the study area on May 17, 2021, the maize residue cover (MRC) of the study area was estimated using the previously constructed MRC unary linear regression model. The MRC of the sampling points of the remote sensing images was estimated by verifying the predicted ESTARFM NDTI with the MRC of the sampling points taken in the field extracted by the maximum likelihood classifier, which has a coefficient of determination R2 of 0.78 and RMSE of 0.00676, signifying better prediction results. The proposed method provides considerable data sources for the remote sensing monitoring studies of conservation tillage.

Surface-engineered coatings have been increasingly applied to functionalize fabrics due to the ease of deposition of the coatings and their effectiveness in endowing the fabric with abundant properties. Among the surface modification methods, layer-by-layer (LbL) self-assembly has emerged as an important approach for creating multifunctional surfaces on fabrics. In this review, bibliometric analysis with the visualization analysis of LbL self-assembly coatings on fabrics was performed on publications extracted from the Web of Science (WOS) from 2005 to 2021 based on the CiteSpace software. The analysis results showed that research on LbL self-assembly coatings on fabrics has attracted much attention, and this technique has plentiful and flexible applications. Moreover, research on the LbL self-assembly method in the field of functionalization of fabrics has been summarized, which include flame retardant fabric, antibacterial fabric, ultraviolet resistant fabric, hydrophobic fabric and electromagnetic shielding fabric. It was found that the functionalization of the fabric has been changing from singularity to diversification. Based on the review, several future research directions can be proposed. The weatherability, comfort, cost and environmental friendliness should be considered when the multifunctional coatings are designed.

This paper presents a 245 GHz wireless communications system with a data rate of 30 Giga bits per second (Gbps) at a 1.2 m distance, which proves the potential for future high-speed communications beyond 5G technology. The system consists of low-complexity and real-time base-band modules to provide the high-speed wideband signal processing capability. Multi-channel base-band signals are combined and converted to 15.65 ± 6.25 GHz wideband intermediate frequency (IF) signals. A novel 245 GHz waveguide bandpass filter (BPF) with low loss and high selectivity is designed and applied to a terahertz (THz) front-end for image rejection and noise suppression. Configuration of the base-band, IF, and THz front-end modules is also given in detail. The 245 GHz wireless communication link is demonstrated over a distance of 1.2 m.

Polycyclic aromatic hydrocarbons (PAHs) are one of the important environmental pollutants that are mainly originated from industrial activities, vehicle emissions, biomass combustion, etc. Nowadays, the surrounding environment of the abandoned industrial area may still have potential health effects on the population, but current researches have paid less attention to this issue. Therefore, we report a comparative investigation focusing on the concentration, distribution, source identification, and risk assessment of PAHs in soils from surrounding areas of an abandoned industrial district and an ecological village in Zhejiang Province, China. Our findings are as follows: the levels of ∑16PAHs ranged from 150.2 to 83096 ng·g−1 with an average concentration of 7680.4 ng·g−1 in industrial area, whereas 49.4 to 778.2 ng·g−1 with an average concentration of 213.5 ng·g−1 in rural area. Although high molecular weight PAHs were both dominant contaminants in study areas, the composition profiles of 16 priority PAHs in soils from the two sampling sites had large differences. Source identification analysis verified that fossil fuel burning and vehicle emissions were the main sources of PAHs in industrial area, while the primary sources were biomass burning and vehicle emission in rural area. The incremental lifetime cancer risk results demonstrated that dermal contact was the most influential factor for all groups, and adults might face higher potential health risk than children in both industrial and rural areas. Moreover, the overall ecological risk of soil PAH pollution was low in rural area, but some individual samples were still high in the abandoned industrial area. Our research is of great significance for the management of the surrounding environment of abandoned industrial areas.

Controlling straw burning is important for ensuring the ambient air quality and for sustainable agriculture. Detecting burning straw is vital for managing and controlling straw burning. Existing methods for detecting straw combustion mainly look for combustion products, especially smoke. In this study, the improved You Only Look Once version 5 (YOLOv5s) algorithm was used to detect smoke in Sentinel-2 images captured by remote sensing. Although the original YOLOv5s model had a faster detection speed, its detection accuracy was poor. Thus, a convolutional block attention module was added to the original model. In addition, in order to speed up the convergence of the model, this study replaced the leaky Rectified Linear Unit (leaky ReLU) activation function with the Mish activation function. The accuracy of the improved model was approximately 4% higher for the same detection speed. The improved YOLOv5s had a higher detection accuracy and speed compared to common target detection algorithms, such as RetinaNet, mask Region-Based Convolutional Neural Network (R-CNN), Single-Shot Multibox Detector (SSD), and faster R-CNN. The improved YOLOv5s analyzed an image in 2 ms. In addition, mAP50 exceeded 94%, demonstrating that with this study’s improved method, smoke can be quickly and accurately identified. This work may serve as a reference for improving smoke detection, and for the effective management and control of straw burning.

The start of the growing season (SOS) is a vital ecological indicator for climate change and the terrestrial ecosystem. Previous studies have reported that the SOS over the Northern Hemisphere (NH) has experienced remarkable changes in the past few decades. However, because of the different spatial and temporal coverages of existing SOS studies, a coherent and robust account for SOS changes in the NH has been lacking. Using satellite-retrieved vegetation-phenology datasets, ground observations, and several auxiliary datasets, this study evaluated the performance of the latest MODIS vegetation-dynamics dataset (MCD12Q2-C6) and explored the distribution and attribution of the SOS to climate change over the NH for the period 2001–2018. The validation results using the Chinese Ecosystem Research Network (CERN) and Lilac-leafing observations (Lilac) displayed that the MCD12Q2-C6 has a good performance in SOS monitoring over the NH mid-latitudes. Meanwhile, evidence from MCD12Q2-C6 pointed out that the SOS was advanced by 2.08 days on average over the NH during 2001–2018, especially for Europe, China, and Alaska, United States. In addition, detailed-sensitivity analysis showed that the increased surface air temperature (Ts) (−1.21 ± 0.34 days °C−1) and reduced snow-cover fraction (Sc) (0.62 ± 0.29 days%−1) were the key driving factors of the observed SOS changes over the NH during 2001–2018. Compared with Ts and Sc, the role of total precipitation (Pt) was minor in dominating the spring vegetation-phenology changes at the same period. The findings of this study contribute to our understanding of the responses of SOS to the competing changes of Ts, Pt, and Sc over the NH.

Research on tight gas reservoirs in the eastern margin of the Ordos Basin, China, has recently become a hot spot. This paper mainly studies the reservoir characteristics of tight sandstone in the north-central area close to the provenance in eastern Linxing. Cast thin section, scanning electron microscopy, high-pressure mercury injection, and X-ray diffraction (XRD) were applied to discriminate the tight sandstone reservoir differences between the Permian Taiyuan and Shanxi formations in the study area. The results show that the deltaic tight sandstones in the Shanxi Formation are dominated by lithic quartz sandstone and lithic sandstone with an average porosity of 2.3% and permeability of 0.083 mD. The epicontinental tight sandstones in the Taiyuan Formation are mainly lithic sandstone and lithic quartz sandstone, with average porosities and permeabilities of 6.9% and 0.12 mD, respectively. The pore type is dominated by secondary dissolution pores, containing a small number of primary pores, and fractures are not developed. The capillary pressure curves of the Taiyuan Formation sandstone are mainly of low displacement pressure, high mercury saturation, and mercury withdrawal efficiency, while the Shanxi Formation sandstone is mainly of high displacement pressure, low mercury saturation, and withdrawal efficiency. The diagenetic evolution of sandstone in the Shanxi Formation is in meso-diagenesis stage A, and the Taiyuan Formation has entered meso-diagenesis stage B. The siliceous cement in the Taiyuan Formation sandstone enhanced the sandstone resistance to compaction and retained some residual intergranular pores. The pore types in the Shanxi Formation sandstone are all secondary pores, while secondary pores in the Taiyuan Formation sandstone account for approximately 90%. The results can be beneficial for tight gas production in the study area and similar basins.

Laser pulses can be utilized to induce intermediate states of phase change materials between amorphous and crystalline phases, making phase change materials attractive and applicable for multi-level storage applications. In this paper, intermediate states of Ge2Sb2Te5 thin films induced via employing a nanosecond multi-pulse laser with different energy and pulse duration were performed by Raman spectroscopy, reflection measurement and thermal simulations. Upon laser-crystallized Ge2Sb2Te5 films, optical functions change drastically, leading to distinguishable reflectivity contrasts of intermediate states between amorphous and crystalline phases due to different crystallinity. The changes in optical intensity for laser-crystallized Ge2Sb2Te5 are also accompanied by micro-structure evolution, since high-energy and longer pulses result in higher-level intermediate states (corresponding to high reflection intensity) and largely contribute to the formation of stronger Raman peaks. By employing thermal analysis, we further demonstrated that the variations of both laser fluence and pulse duration play decisive roles in the degree of crystallinity of Ge2Sb2Te5 films. Laser fluence is mainly responsible for the variations in crystallization temperature, while the varying pulse duration has a great impact on the crystallization time. The present study offers a deeper understanding of the crystallization characteristic of phase change material Ge2Sb2Te5.

Background/Purpose: Only limited information is available about the detailed characteristics of qnrD, a plasmid-mediated quinolone resistance (PMQR) gene. This study aimed to understand the distribution of qnrD and the characterization of qnrD-carrying plasmids in Proteeae. Methods: The distribution of qnrD genes was investigated by polymerase chain reaction (PCR) amplification in 203 consecutive nonduplicate clinical isolates of Proteeae collected from inpatients at the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. The minimum inhibitory concentrations (MICs) of antibiotics were measured by agar dilution method and other PMQR determinants were also determined by PCR. qnrD was positioned via Southern hybridization and the transferability of qnrD-carrying plasmids was achieved by conjugation experiment. The genetic environment of qnrD was investigated by sequencing, and chromosomal polymorphism for qnrD-positive strains was analyzed by pulsed-field gel electrophoresis (PFGE). Results: Forty strains carried qnrD, showing decreased fluoroquinolone susceptibility or low-level fluoroquinolone resistance. qnrD was encoded on the plasmid of about 2.7 kb or 5.2 kb in length, which cannot be transferred by liquid conjugation or filter mating, but can be successfully transferred by transduction. The transformants showed 62.5–300-fold increases in the MICs of quinolones compared with the recipient. The plasmids carrying qnrD showed a high similarity with that of Providencia spp. and Proteus vulgaris. PFGE analysis demonstrated that these isolates were divergent and not clone related. Conclusion: qnrD could have originated from Proteeae or presented in these bacteria as a reservoir; furthermore, qnrD could be transferred and spread within the same or across different bacterial species if the plasmids acquired mobile elements under antimicrobial selective pressures.

The combination of mode division multiplexing (MDM) based on orbital angular momentum (OAM) modes with wavelength division multiplexing (WDM) has attracted considerable attention due to its ability to increase optical transmission capacity. However, the switching of the multi-wavelength and multi-order OAM mode in an all-fiber structure has always been a challenge. As a solution, a thermally tunable dual-core photonic crystal fiber (DC-PCF) is proposed to achieve multi-order and multi-wavelength switching of the OAM mode. The results show that the OAM mode with topological charge m = ±1 can be excited with the linear polarization fundamental mode (LPFM) and circular polarization fundamental mode (CPFM). In addition, the device can effectively excite a high-purity ±1st order OAM mode with wavelengths ranging from 1520 to 1575 nm by thermal tuning. The purity of the mode is in excess of 99%, and the energy conversion efficiency (ECE) is above 95%. The proposed design is expected to be applied in all-fiber communication systems combined with MDM and WDM.

Korean pine is a gymnosperm, and gymnosperms have relatively large genome sequences and lack a model organism reference genome. Understanding the important gene expression in the tissue growth process of needles (T1), stems (T2), female flowers (T3) and cones (T4) of the Korean pine is necessary to develop and compound the enzyme genes related to secondary metabolite synthesis. Simple sequence repeat (SSR) markers were explored based on the expressed sequence tag (EST). High-throughput sequencing technology was used to compare and analyse transcriptomes of four different tissue parts of the Korean pine, yielding many differentially expressed unigene sequences. Fluorescently labelled SSR primers were designed to analyse the polymorphism level of 60 open-pollinated families from the Heilongjiang province of China. The research showed that (1) 21.3 GB of data was obtained from the transcriptome sequencing, and 41,476 candidate unigenes were identified based on sequence annotation using various databases. Clusters from orthologous groups and gene ontology function classification tools were used to divide the annotated transcript sequences into 56 functional categories. (2) Cones had the highest number of expressed genes during puberty, with rich expression as they were being formed. (3) By pathway enrichment analysis, 16 key enzyme genes related to fatty acid synthesis in other homologous species were obtained. (4) Ten novel polymorphic fluorescence labelling were used to identify 60 open-pollinated families with a medium polymorphism level. The research showed that high-throughput sequencing technology could analyse the transcriptome expression level between different organisms, and SSR markers were successfully developed.

Objectives: Perfluorooctane sulfonate (PFOS) and zinc oxide nanoparticles (ZnO-NPs) are frequently detected in the environment but few studies have assessed the joint toxicity of them. Oxidative stress and apoptosis to zebrafish (Danio rerio) embryos induced by the PFOS and ZnO-NPs were investigated in this study. Material and Methods: The embryos were exposed to the PFOS (0, 0.4, 0.8 and 1.6 mg/l), ZnO-NPs (12.5, 25, 50 mg/l) and PFOS plus ZnO-NPs (0.4+12.5, 0.8+25 and 1.6+50 mg/l) mixture solutions until 96 h post-fertilization. Activities of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (Gpx) and malondialdehyde (MDA) content were measured in zebrafish embryos after exposure lasting for 96 h. At the same time, the genes expression related to reactive oxygen species (ROS) generation, oxidative damage and apoptosis were also measured. Results: A significant induction of the ROS accompanied by the increase in the activity of the Gpx and MDA contents were found in co-treatment groups. Furthermore, several apoptosis pathway related genes such as Bax, p53, caspase-3 and caspase-9 were significantly up-regulated in the PFOS plus ZnO-NPs exposure groups, while anti-apoptotic gene Bcl-2 was significantly down-regulated in the PFOS plus ZnO-NPs exposure groups. In addition, some oxidative stress-related genes such as Cat, GSH peroxidase 1 (Gpx1a) and superoxide dismutase 1 (Sod1) were also significantly down-regulated after the PFOS plus ZnO-NPs co-treatments. Conclusions: The results demonstrated that the PFOS plus ZnO-NPs co-exposure could cause more serious oxidative stress and apoptosis than the PFOS and ZnO-NPs exposure alone at the exposure concentrations above. The synergistic effects of the PFOS and ZnO-NPs may be the important mechanisms of their toxicity to zebrafish embryos. Int J Occup Med Environ Health 2017;30(2):213–229

Background: Studies on the association between spicy food intake and cancer risk have reported inconsistent results. We quantitatively assessed this association by conducting a meta-analysis based on evidence from case–control studies. Methods: PubMed, EMBASE, and the Cochrane Library were searched for eligible publications. Combined odds ratios (OR s) with their 95% confidence interval (CI) were calculated using a random- or fixed-effects model. The methodological quality of the included articles was assessed using the Newcastle–Ottawa scale (NOS). All data were analyzed using STATA 11.0 software (version 11.0; StataCorp., College Station, TX, USA). Subgroup analyses were also performed with stratification by region, sex, number of cases, cancer subtype, source of the control group, and NOS score. Results: A total 39 studies from 28 articles fulfilled the inclusion criteria for the meta-analysis (7884 patients with cancer and 10,142 controls). Comparison of the highest versus lowest exposure category in each study revealed a significant OR of 1.76 (95% CI = 1.35–2.29) in spite of significant heterogeneity (P < 0.001). In the subgroup analyses, this positive correlation was still found for gastric cancer, different regions, different numbers of cases, different sources of the control group, and high-quality articles (NOS score of ≥ 7). However, no statistically significant association was observed for women, esophageal cancer, gallbladder cancer, or low-quality articles (NOS score of

Coal burning is a main concern for a range of atmospheric pollutants, including the environmentally sensitive element chromium (Cr). Cr migrates to the environment through stack emissions and can leach out from solid coal-burning byproducts, thereby causing adverse effects on the ecosystem. In this study, atmospheric emissions of Cr from six coal-fired power plants (CFPPs), as well as the distribution of Cr inside these CFPPs in Guizhou Province, Southwest China, were investigated. Among the six CFPPs, one was a circulating fluidized bed boiler and the others were pulverized coal boilers. The results showed that Cr in the feed fuel of these CFPPs ranged from 39.5 to 101.5 mg·kg−1 (average: 68.0 ± 24.8 mg·kg−1) and was approximately four times higher than the national and global average. Cr in the feed fuel correlated significantly with the ash yield, demonstrating that Cr in coal is closely associated with ash-forming minerals. After the coal combustion and the treatment by different air pollution control devices, most Cr (>92%) in the installation was retained in the captured fly ash and bottom ash, with less as gypsum (0.69–7.94%); eventually, only 0.01–0.03% of Cr was emitted into the atmosphere with a concentration of 1.4–2.2 μg·Nm−3. The atmospheric emission factors of Cr for these utility boilers were as low as 14.86 ± 3.62 mg Cr·t−1 coal, 7.72 ± 2.53 μg Cr (kW·h)−1, and 0.70 ± 0.19 g Cr·TJ−1, respectively. About 981 kg·y−1 of Cr was discharged into the atmosphere from Guizhuo’s CFPPs in 2017, much lower than previous reported values. Most of the Cr in the CFPPs ended up in solid combustion products, identifying the need for the careful disposal of high-Cr-containing ashes (up to 500 mg·kg−1) to prevent possible mobilization into the environment.

In order to realize intelligent and autonomous navigation, a bio-inspired method of autonomous positioning using spatial association based on place cells firing is proposed. First, a vision sensor is used to get the landmarks in the environment and the distances between the agent and the different landmarks so as to construct an internal map of place cells. Then, we build a relationship between the distances and the activities of place cells using a radial basis function neural network, and further achieve the memory and association of spatial locations by comparing the activities of all place cells. Finally, we also provide a detailed analysis on the feasibility of this method for autonomous positioning and how the involved parameters in the model have an influence on the performance of positioning. The result of simulation shows that the method presented is effective and feasible for autonomous positioning.

Nanopores are extremely developed and randomly distributed in shale gas reservoirs. Due to the rarefied conditions in shale strata, multiple gas transport mechanisms coexist and need further understanding. The commonly used slip models are mostly based on Maxwell slip boundary condition, which assumes elastic collisions between gas molecules and solid surfaces. However, gas molecules do not rebound from solid surfaces elastically, but rather are adsorbed on them and then re-emitted after some time lag. A Langmuir slip permeability model was established by introducing Langmuir slip BC. Knudsen diffusion of bulk phase gas and surface diffusion of adsorbed gas were also coupled into our nanopore transport model. Considering the effects of real gas, stress dependence, thermodynamic phase changes due to pore confinement, surface roughness, gas molecular volume, and pore enlargement due to gas desorption during depressurization, a unified gas transport model in organic shale nanopores was established, which was then upscaled by coupling effective porosity and tortuosity to describe practical SGR properties. The bulk phase transport model, single capillary model, and upscaled porous media model were validated by data from experimental data, lattice Boltzmann method or model comparisons. Based on the new gas transport model, the equivalent permeability of different flow mechanisms as well as the flux proportion of each mechanism to total flow rate was investigated in different pore radius and pressure conditions. The study in this paper revealed special gas transport characteristics in shale nonopores and provided a robust foundation for accurate simulation of shale gas production.

Light availability in lakes or reservoirs is affected by optically active components (OACs) in the water. Light plays a key role in the distribution of phytoplankton and hydrophytes, thus, is a good indicator of the trophic state of an aquatic system. Diffuse attenuation of photosynthetic active radiation (PAR) (Kd(PAR)) is commonly used to quantitatively assess the light availability. The PAR and the concentration of OACs were measured at 206 sites, which covered 26 lakes and reservoirs in Northeast China. The spatial distribution of Kd(PAR) was depicted and its association with the OACs was assessed by grey incidences(GIs) and linear regression analysis. Kd(PAR) varied from 0.45 to 15.04 m−1. This investigation revealed that reservoirs in the east part of Northeast China were clear with small Kd(PAR) values, while lakes located in plain areas, where the source of total suspended matter (TSM) varied, displayed high Kd(PAR) values. The GIs and linear regression analysis indicated that the TSM was the dominant factor in determining Kd(PAR) values and best correlated with Kd(PAR) (R2 = 0.906, RMSE = 0.709). Most importantly, we have demonstrated that the TSM concentration is a reliable measurement for the estimation of the Kd(PAR) as 74% of the data produced a relative error (RE) of less than 0.4 in a leave-one-out cross validation (LOO-CV) analysis. Spatial transferability assessment of the model also revealed that TSM performed well as a determining factor of the Kd(PAR) for the majority of the lakes. However, a few exceptions were identified where the optically regulating dominant factors were chlorophyll-a (Chl-a) and/or the chromophroic dissolved organic matter (CDOM). These extreme cases represent lakes with exceptionally clear waters.

Satellite remote sensing provides a powerful tool for assessing lake water surface temperature (LWST) variations, particularly for large water bodies that reside in remote areas. In this study, the MODIS land surface temperature (LST) product level 3 (MOD11A2) was used to investigate the spatiotemporal variation of LWST for 56 large lakes across the Tibetan Plateau and examine the factors affecting the LWST variations during 2000–2015. The results show that the annual cycles of LWST across the Tibetan Plateau ranged from −19.5 °C in early February to 25.1 °C in late July. Obvious diurnal temperature differences (DTDs) were observed for various lakes, ranging from 1.3 to 8.9 °C in summer, and large and deep lakes show less DTDs variations. Overall, a LWST trend cannot be detected for the 56 lakes in the plateau over the past 15 years. However, 38 (68%) lakes show a temperature decrease trend with a mean rate of −0.06 °C/year, and 18 (32%) lakes show a warming rate of (0.04 °C/year) based on daytime MODIS measurements. With respect to nighttime measurements, 27 (48%) lakes demonstrate a temperature increase with a mean rate of 0.051 °C/year, and 29 (52%) lakes exhibit a temperature decrease trend with a mean rate of −0.062 °C/year. The rate of LWST change was statistically significant for 19 (21) lakes, including three (eight) warming and 17 (13) cooling lakes for daytime (nighttime) measurements, respectively. This investigation indicates that lake depth and area (volume), attitude, geographical location and water supply sources affect the spatiotemporal variations of LWST across the Tibetan Plateau.

A practical compact solid-state terahertz imaging system is presented. Various beam guiding architectures were explored and hardware performance assessed to improve its compactness, robustness, multi-functionality and simplicity of operation. The system performance in terms of image resolution, signal-to-noise ratio, the electronic signal modulation versus optical chopper, is evaluated and discussed. The system can be conveniently switched between transmission and reflection mode according to the application. A range of imaging application scenarios was explored and images of high visual quality were obtained in both transmission and reflection mode.