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Despite substantial evidence suggesting that hydrogen gas (H2) can enhance osmotic tolerance in plants, the conventional supply method of hydrogen-rich water (HRW) poses challenges for large-scale agricultural applications. Recently, magnesium hydride (MgH2), a hydrogen storage material in industry, has been reported to yield beneficial effects in plants. This study aimed to investigate the effects and underlying mechanisms of MgH2 in plants under osmotic stress. Mung bean seedlings were cultured under control conditions or with 20% polyethylene glycol (PEG)-6000, with or without MgH2 addition (0.01 g L−1). Under our experimental conditions, the MgH2 solution maintained a higher H2 content and longer retention time than HRW. Importantly, PEG-stimulated endogenous H2 production was further triggered by MgH2 application. Further results revealed that MgH2 significantly alleviated the inhibition of seedling growth and reduced oxidative damage induced by osmotic stress. Pharmacological evidence suggests the MgH2-reestablished redox homeostasis was associated with activated antioxidant systems, particularly the ascorbate–glutathione cycle. The above observations were further supported by the enhanced activities and gene transcriptional levels of ascorbate peroxidase, monodehydroascorbate reductase, dehydroascorbate reductase, and glutathione reductase. Overall, this study demonstrates the importance of MgH2 in mitigating osmotic stress in mung bean seedlings, providing novel insights into the potential agricultural applications of hydrogen storage materials.

Fungal diseases not only reduce the yield of edible mushrooms but also pose potential threats to the preservation and quality of harvested mushrooms. Cobweb disease, caused primarily by fungal pathogens from the Hypocreaceae family, is one of the most significant diseases affecting edible mushrooms. Deciphering the genomes of these pathogens will help unravel the molecular basis of their evolution and identify genes responsible for pathogenicity. Here, we present high-quality genome sequences of three cobweb disease fungi: Hypomyces aurantius Cb-Fv, Cladobotryum mycophilum CB-Ab, and Cladobotryum protrusum CB-Mi, isolated from Flammulina velutipes, Agaricus bisporus, and Morchella importuna, respectively. The assembled genomes of H. aurantius, C. mycophilum, and C. protrusum are 33.19 Mb, 39.83 Mb, and 38.10 Mb, respectively. This is the first report of the genome of H. aurantius. Phylogenetic analysis revealed that cobweb disease pathogens are closely related and diverged approximately 17.51 million years ago. CAZymes (mainly chitinases, glucan endo-1,3-beta-glucosidases, and secondary metabolite synthases), proteases, KP3 killer proteins, lipases, and hydrophobins were found to be conserved and strongly associated with pathogenicity, virulence, and adaptation in the three cobweb pathogens. This study provides insights into the genome structure, genome organization, and pathogenicity of these three cobweb disease fungi, which will be a valuable resource for comparative genomics studies of cobweb pathogens and will help control this disease, thereby enhancing mushroom quality.

Deoxynivalenol (DON), 3-acetyldeoxynivalenol (3-ADON) and 15-acetyldeoxynivalenol (15-ADON) belong to type B trichothecenes that are widely detected in agricultural products as one of the most common classes of mycotoxins. In the present study, we aimed to characterize the alteration of lipid metabolism in normal human hepatocytes by poisoning with DON and its acetylated derivatives. After verifying the hepatotoxicity of the three toxins, DON, 15-ADON, and 3-ADON, the mRNA expression was determined by transcriptomics, and the results showed that DON and 15-ADON had a significant regulatory effect on the transcriptome, in which glycerophospholipid metabolism pathway and phospholipase D signaling pathways have not been reported in studies of DON and its acetylated derivatives. For further validation, we explored lipid metabolism in depth and found that PC (15:0/16:0), PC (16:1/18:3), PC (18:1/22:6), PC (16:0/16:0), PC (16:0/16:1), PC (16:1/18:1), PC (14:0/18:2), PE (14:0/16:0) and PE (18:1/18:3) were downregulated for all nine lipids. Combined with the transcriptome results, we found that hepatic steatosis induced by the three toxins, DON, 15-ADON and 3-ADON, was associated with altered expression of genes related to lipid oxidation, lipogenesis and lipolysis, and their effects on lipid metabolism in L-02 cells were mainly realized through the PC-PE cycle.

This research explores the architecture and efficacy of GaN/AlxGa1−xN-based heterojunction phototransistors (HPTs) engineered with both a compositionally graded and a doping-graded base. Employing theoretical analysis along with empirical fabrication techniques, HPTs configured with an aluminum compositionally graded base were observed to exhibit a substantial enhancement in current gain. Specifically, theoretical models predicted a 12-fold increase, while experimental evaluations revealed an even more pronounced improvement of approximately 27.9 times compared to conventional GaN base structures. Similarly, HPTs incorporating a doping-graded base demonstrated significant gains, with theoretical predictions indicating a doubling of current gain and experimental assessments showing a 6.1-fold increase. The doping-graded base implements a strategic modulation of hole concentration, ranging from 3.8 × 1016 cm−3 at the base–emitter interface to 3.8 × 1017 cm−3 at the base–collector junction. This controlled gradation markedly contributes to the observed enhancements in current gain. The principal mechanism driving these improvements is identified as the increased electron drift within the base, propelled by the intrinsic electric field inherent to both the compositionally and doping-graded structures. These results highlight the potential of such graded base designs in enhancing the performance of GaN/AlxGa1−xN HPTs and provide crucial insights for the advancement of future phototransistor technologies.

Inland aquaculture ponds, as an important land use type, have brought great economic benefits to local people but at the same time have caused many environmental problems threatening regional ecology security. Therefore, understanding the spatiotemporal pattern of aquaculture ponds and its potential influence on water quality is vital for the sustainable development of inland lakes. In this study, based on Landsat5/8 images, three types of land features, namely spectral features, index features, and texture features, and five machine learning algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), artificial neural network (ANN), k-nearest neighbor (KNN), and Gaussian naive Bayes (GNB), were combined to identify aquaculture ponds and some other primary land use types around a typical inland lake of China. The results demonstrated that the XGBoost algorithm that integrated the three features performed the best among all groups of the five machine learning algorithms and the three features, with an overall accuracy of up to 96.15%. In particular, the texture features provided additional useful information besides the spectral features to allow more accurately separation of aquaculture ponds from other land use types and thus improve the land use mapping ability in complex inland lakes. Next, this study examined the tendency of aquaculture ponds and found a segmented increase mode, namely sharp increase during 1984–2003 and then slow elevation since 2003. Further positive correlation detected between the area of aquaculture ponds and the phytoplankton population dynamics suggest a likely influence of aquaculture activity on the lake water quality. This study provides an important scientific basis for the sustainable management and ecological protection of inland lakes.

In this paper, the characteristics of absolute value memristors are verified through the circuit implementation and construction of a chaotic system with a conditional symmetric fractional-order memristor. The dynamic behavior of fractional-order memristor systems is explored using fractional-order calculus theory and the Adomian Decomposition Method (ADM). Concurrently, the investigation probes into the existence of coexisting symmetric attractors, multiple coexisting bifurcation diagrams, and Lyapunov exponent spectra (LEs) utilizing system parameters as variables. Additionally, the system demonstrates an intriguing phenomenon known as offset boosting, where the embedding of an offset can adjust the position and size of the system’s attractors. To ensure the practical applicability of these findings, a fractional-order sliding mode synchronization control scheme, inspired by integer-order sliding mode theory, is designed. The rationality and feasibility of this scheme are validated through a theoretical analysis and numerical simulation.

The dispersal strategies of a species can affect its invasion success. Investigations into the dispersal strategies of invasive species in relation to different factors help improve our understanding of invasion mechanisms and provide knowledge for population management and invasion evaluation. Tetranychus ludeni Zacher (Acari: Tetranychidae) is an invasive species which is native to Europe but is now cosmopolitan. Here, we examined the effects of age and density on dispersal in mated females. Our results show that older females that are capable of producing more eggs within 24 h were more likely to disperse and moved longer distances than younger ones with fewer eggs. Older females spread most of their eggs out of their natal habitats and over longer distances, which reduced competition and increased offspring fitness. Females exhibited significantly increased dispersal probability and distances with an increase in population density to avoid crowding. The synchronization of dispersal and reproduction, along with the positive density-dependent dispersal strategy, may facilitate the habitat colonization and invasion speed of T. ludeni.

Net Primary Productivity (NPP) is a critical metric for assessing terrestrial carbon sequestration and ecosystem health. While advancements in NPP modeling have enabled estimation at various scales, hidden anomalies within NPP time series necessitate further investigation to understand the driving forces. This study focuses on Shandong Province, China, generating a high-resolution (250 m) monthly NPP product for 2000–2019 using the Carnegie–Ames–Stanford Approach (CASA) model, integrated with satellite remote sensing and ground observations. We employed the Seasonal Mann–Kendall (SMK) Test and the Breaks For Additive Season and Trend (BFAST) algorithm to differentiate between gradual declines and abrupt losses, respectively. Beyond analyzing land use and land cover (LULC) transitions, we utilized Random Forest models to elucidate the influence of environmental factors on NPP changes. The findings revealed a significant overall increase in annual NPP across the study area, with a moderate average of 503.45 gC/(m2·a) during 2000–2019. Although 69.67% of the total area displayed a substantial monotonic increase, 3.89% of the area experienced abrupt NPP losses, and 8.43% exhibited gradual declines. Our analysis identified LULC transitions, primarily driven by urban expansion, as being responsible for 55% of the abrupt loss areas and 33% of the gradual decline areas. Random Forest models effectively explained the remaining areas, revealing that the magnitude of abrupt losses and the intensity of gradual declines were driven by a complex interplay of factors. These factors varied across vegetation types and change types, with explanatory variables related to vegetation status and climatic factors—particularly precipitation—having the most prominent influence on NPP changes. The study suggests that intensified land use and extreme climatic events have led to NPP diminishment in Shandong Province. Nevertheless, the prominent positive vegetation growth trends observed in some areas highlight the potential for NPP enhancement and carbon sequestration through targeted management strategies.

The utilization of radiative transfer models for interpreting remotely sensed data to evaluate forest disturbances is a cost-effective approach. However, the current radiative transfer modeling approaches are either too abstract (e.g., 1D models) or too complex (detailed 3D models). This study introduces a novel multilayer heterogeneous 3D radiative transfer framework with medium complexity, termed MART3D, for characterizing forest disturbances. MART3D generates 3D canopy structures accounting for the within-crown clumping by clustering leaves, which is modeled as a turbid medium, around branches, applicable for forests of medium complexity, such as temperate forests. It then automatically generates a multilayer forest with grass, shrub and several layers of trees using statistical parameters, such as the leaf area index and fraction of canopy cover. By employing the ray-tracing module within the well-established LargE-Scale remote sensing data and image Simulation model (LESS) as the computation backend, MART3D achieves a high accuracy (RMSE = 0.0022 and 0.018 for red and Near-Infrared bands) in terms of the bidirectional reflectance factor (BRF) over two RAMI forest scenes, even though the individual structures of MART3D are generated solely from statistical parameters. Furthermore, we demonstrated the versatility and user-friendliness of MART3D by evaluating the band selection strategy for computing the normalized burn ratio (NBR) to assess the composite burn index over a forest fire scene. The proposed MART3D is a flexible and easy-to-use tool for studying the remote sensing response under varying vegetation conditions.

Lateral flow immunoassay (LFIA) is extensively utilized for point-of-care testing due to its ease of operation, cost-effectiveness, and swift results. This study investigates the flow dynamics and reaction mechanisms in LFIA by developing a three-dimensional model using the Richards equation and porous media transport, and employing numerical simulations through the finite element method. The study delves into the transport and diffusion behaviors of each reaction component in both sandwich LFIA and competitive LFIA under non-uniform flow conditions. Additionally, the impact of various parameters (such as reporter particle concentration, initial capture probe concentrations for the T-line and C-line, and reaction rate constants) on LFIA performance is analyzed. The findings reveal that, in sandwich LFIA, optimizing parameters like increasing reporter particle concentration and initial capture probe concentration for the T-line, as well as adjusting reaction rate constants, can effectively enhance detection sensitivity and broaden the working range. Conversely, in competitive LFIA, the effects are inverse. This model offers valuable insights for the design and enhancement of LFIA assays.

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Through detailed drill-core description, petrography, cathodoluminescence imaging, and geochemistry analysis, sedimentary deposits with a high content of volcanogenic components (27.6%) were discovered in the Shanxi Formation of the Daniudi Gas Field, Ordos Basin. The volcanogenic components include volcanogenic quartz, lava fragments (dominated by rhyolite fragments), tuff fragments, and tuffaceous matrix. In addition, at least two volcanic ash layers were discovered. Although the metamorphic rocks of the Precambrian succession in the ancient land of Yin Mountain are usually considered the primary source of the Shanxi formation, it is most likely that the volcanogenic components were derived from intermediate-acid volcanic materials that accumulated in the Daqingshan area during the Late Carboniferous to Early Permian. Those volcanogenic components are mainly transported by flowing water rather than by air from origin to basin. In addition, the accumulation of volcanic materials in the Daqingshan area was controlled by volcanic eruptions occurring solely in this area, rather than by the Inner Mongolia Orogenic Belt. Those volcanic eruptions were related to the southward subduction of the Paleo-Asian Ocean Plate beneath the northern margin of the North China Plate in the Late Carboniferous to Early Permian. The active continental margin related to the subduction of the Paleo-Asian Ocean Plate lasted at least until the Early Permian, and the closure of the Paleo-Asian Ocean must have occurred later than the Early Permian.

From August to October 2018, a series of strong earthquake (EQ) events occurred in southeast Asia and northern Oceania (22°S to 0°N, 115°E to 170°E) within 50 days. In this paper, we analyze the features of ionospheric plasma perturbations, recorded by the Plasma Analyzer Package (PAP) and Langmuir probe (LAP) onboard the China Seismo-Electromagnetic Satellite (CSES-01), before four EQs with magnitudes of Ms 6.9 to Ms 7.4. The ion parameters such as the oxygen ion density (No+), the ion drift velocity in the vertical direction (Vz) under the conditions of geomagnetic storms, and strong EQs are compared. The results show that within 1 to 15 days before the strong EQs, the No+ and the electron density (Ne) increased while the electron temperature (Te) decreased synchronously. Meanwhile, the Vz significantly increased along the ground-to-space direction. The relative variation of No+ and Vz before the strong EQs is more prominent, and the Vz is not easily influenced by the geomagnetic storm but is susceptible to the seismic activities. Our results suggest that the anomaly of ionospheric plasma perturbations occurring in this area is possibly related to the pre-EQ signatures.

Integrated access and backhaul (IAB) networks offer transformative benefits, primarily their deployment flexibility in locations where fixed backhaul faces logistical or financial challenges. This flexibility is further enhanced by IAB’s inherent ability for adaptive network expansion. However, existing IAB network planning models, which are grounded in the facility location problem and are predominantly addressed through linear programming, tend to neglect crucial geographical constraints. These constraints arise from the specific deployment constraints related to the positioning of IAB donors to the core network, and the geographic specificity required for IAB-node placements. These aspects expose an evident research void. To bridge this, our research introduces a geographically aware optimization methodology tailored for IAB deployments. In this paper, we detail strategies for both single-hop and multi-hop situations, concentrating on IAB donors distribution and geographical constraints. Uniquely in this study, we employ the inherent data rate limitations of network nodes to determine the maximum feasible hops, differing from traditional fixed maximum hop count methods. We devise two optimization schemes for single-hop and multi-hop settings and introduce a greedy algorithm to effectively address the non-convex multi-hop challenge. Extensive simulations across various conditions (such as diverse donor numbers and node separations) were undertaken, with the outcomes assessed against the benchmark of the single-hop scenario’s optimal solution. Our findings reveal that the introduced algorithm delivers efficient performance for geographically constrained network planning.

Natural products are a main source of new chemical entities for use in drug and pesticide discovery. In order to discover lead compounds with high herbicidal activity, a series of new pyrido[2,3-d] pyrimidine derivatives were designed and synthesized using 2-chloronicotinic acid as the starting material. Their structures were characterized with 1H NMR, 13C NMR and HRMS, and the herbicidal activities against dicotyledonous lettuce (Lactuca sativa), field mustard (Brassica campestris), monocotyledonous bentgrass (Agrostis stolonifera) and wheat (Triticum aestivum) were determined. The results indicated that most of the pyrido[2,3-d] pyrimidine derivatives had no marked inhibitory effect on lettuce at 1 mM. However, most of the pyrido[2,3-d] pyrimidine derivatives possessed good activity against bentgrass at 1 mM. Among them, the most active compound, 3-methyl-1-(2,3,4-trifluorophenyl)pyrido[2,3-d]pyrimidine-2,4(1H,3H)-dione (2o), was as active as the positive controls, the commercial herbicides clomazone and flumioxazin. Molecular simulation was performed with molecular docking and DFT calculations. The docking studies provided strong evidence that 2o acts as an herbicide by inhibition of protoporphyrinogen oxidase. However, the physiological results indicate that it does not act on this target in vivo, implying that it could be metabolically converted to a compound with a different molecular target.

Background: Dermatofibroma has various pathological classifications, some of which pose a risk of recurrence and metastasis. Distinguishing these high-risk dermatofibromas based on appearance alone can be challenging. Therefore, high-frequency ultrasound may provide additional internal information on these lesions, helping to identify high-risk and low-risk dermatofibroma early. Methods: In this retrospective study, 50 lesions were analyzed to explore the correlation between clinical and high-frequency ultrasound features and dermatofibroma risk level. Based on their pathological features, the lesions were divided into high-risk (n = 17) and low-risk (n = 33) groups. Subsequently, an identification model based on significant high-frequency ultrasound features was developed. Results: Significant differences were observed in the thickness, shape, internal echogenicity, stratum basal, and Doppler vascular patterns between the high-risk and low-risk groups. The median lesion thickness for the high-risk dermatofibroma group was 4.1 mm (IQR: 3.2–6.1 mm), while it was 3.1 mm (IQR: 1.3–4.2 mm) for the low-risk dermatofibroma group. In the high-risk dermatofibroma group, irregular morphology was predominant (70.6%, 12/17), the most common being dermis-to-subcutaneous soft tissue penetration (64.7%, 11/17), and heterogenous internal echogenicity was observed in the majority of cases (76.5%, 13/17). On the other hand, regular morphology was more prevalent in the low-risk dermatofibroma group (78.8%, 26/33), primarily limited to the dermis layer (78.8%, 26/33), with homogeneous internal echogenicity also being prevalent in the majority of cases (81.8%, 27/33). Regarding the Doppler vascularity pattern, 69.7% (23/33) of low-risk dermatofibromas had no blood flow, while 64.7% (11/17) of high-risk dermatofibromas had blood flow. Conclusion: High-frequency ultrasound is crucial in distinguishing high-risk and low-risk dermatofibromas, making it invaluable for clinical management.

The electric field detector of the CSES satellite has captured a vast number of lightning whistler events. To recognize them effectively from the massive amount of electric field detector data, a recognition algorithm based on speech technology has attracted attention. However, this approach has failed to recognize the lightning whistler events which are contaminated by other low-frequency electromagnetic disturbances. To overcome this limitation, we apply the single-channel blind source separation method and audio recognition approach to develop a novel model, which consists of two stages. (1) The training stage: Firstly, we preprocess the electric field detector wave data into the audio fragment. Then, for each audio fragment, mel-frequency cepstral coefficients are extracted and input into the long short-term memory network for training the novel lightning whistler recognition model. (2) The inference stage: Firstly, we process each audio fragment with the single-channel blind source to generate two different sub-signals. Then, for each sub-signal, the mel-frequency cepstral coefficient features are extracted and input into the lightning whistler recognition model to recognize the lightning whistler. Finally, the two results above are processed by decision fusion to obtain the final recognition result. Experimental results based on the electric field detector data of the CSES satellite demonstrate the effectiveness of the algorithm. Compared with classical methods, the accuracy, recall, and F1-score of this algorithm can be increased by 17%, 62.2%, and 50%, respectively. However, the time cost only increases by 0.41 s.

Ionospheric disturbances are mainly caused by solar and Earth surface activity. The electromagnetic data collected by the CSES (China Seismo-Electromagnetic Satellite, popularly known as the Zhangheng-1 satellite) can capture many space disturbances. Different spatial disturbances can exhibit distinctive shapes on spectrograms. Constant-frequency electromagnetic disturbances (CFEDs) such as artificially transmitted VLF radio waves, power line harmonics, and satellite platform disturbances can appear as horizontal lines on spectrograms. Therefore, we used computer vision and machine learning techniques to extract the frequency of global CFEDs and analyze their strong spatial signal characteristics. First, we obtained time-frequency spectrograms from CSES VLF electric-field waveform data using Fourier transform. Next, we employed an unsupervised clustering algorithm to automatically recognize CFED horizontal lines on spectrograms, merging horizontal lines from different spectrograms, to obtain the CFED horizontal-line frequency range. In the third stage, we verified the presence of CFEDs in power spectrograms, thus extracting their true frequency values. Finally, for strong CFED signals, we generated eight revisited periods, resulting in 10,230 power spectrograms for analyzing each CFED’s spatial characteristics using a combined periodic sequence and spatial region that included frequency offsets, frequency fluctuations, and signal non-observation areas. These findings contribute to enhancing the quality of CSES observational data and provides a theoretical basis for constructing global CFED spatial background fields and earthquake monitoring and early prediction systems.

The theoretical development of Schumann Resonances has spanned more than a century as a form of global natural electromagnetic resonances. In recent years, with the development of electromagnetic detection technology and the improvement in digital processing capabilities, the connection between Schumann Resonances and natural phenomena, such as lightning, earthquakes, and Earth’s climate, has been experimentally and theoretically demonstrated. This article is a review of the relevant literature on Schumann Resonance observation experiments, theoretical research over the years, and a prospect based on space-based observations. We start with the theoretical background and the main content on Schumann Resonances. Then, observations and the identification of Schumann Resonance signals based on ground and satellite data are introduced. The research and related applications of Schumann Resonances signals are summarized in terms of lightning, earthquakes, and atmosphere. Finally, the paper presents a brief study of Schumann Resonances based on the China Seismo-Electromagnetic Satellite (CSES) and preliminary ideas about how to improve the identification and application of space-based Schumann Resonances signals.

Parkinson’s disease (PD) is the second most common neurodegenerative disease; it mainly occurs in the elderly population. Cuproptosis is a newly discovered form of regulated cell death involved in the progression of various diseases. Combining multiple GEO datasets, we analyzed the expression profile and immunity of cuproptosis-related genes (CRGs) in PD. Dysregulated CRGs and differential immune responses were identified between PD and non-PD substantia nigra. Two CRG clusters were defined in PD. Immune analysis suggested that CRG cluster 1 was characterized by a high immune response. The enrichment analysis showed that CRG cluster 1 was significantly enriched in immune activation pathways, such as the Notch pathway and the JAK-STAT pathway. KIAA0319, AGTR1, and SLC18A2 were selected as core genes based on the LASSO analysis. We built a nomogram that can predict the occurrence of PD based on the core genes. Further analysis found that the core genes were significantly correlated with tyrosine hydroxylase activity. This study systematically evaluated the relationship between cuproptosis and PD and established a predictive model for assessing the risk of cuproptosis subtypes and the outcome of PD patients. This study provides a new understanding of PD-related molecular mechanisms and provides new insights into the treatment of PD.

The timely and accurate mapping of crops over large areas is essential for alleviating food crises and formulating agricultural policies. However, most existing classical crop mapping methods usually require the whole-year historical time-series data that cannot respond quickly to the current planting information, let alone for future prediction. To address this issue, we propose a novel spatial–temporal feature and deep integration strategy for crop growth pattern prediction and early mapping (STPM). Specifically, the STPM first learns crop spatial–temporal evolving patterns from historical data to generate future remote sensing images based on the current observations. Then, a robust crop type recognition model is applied by combining the current early data with the predicted images for early crop mapping. Compared to existing spatial–temporal prediction models, our proposed model integrates local, global, and temporal multi-modal features comprehensively. Not only does it achieve the capability to predict longer sequence lengths (exceeding 100 days), but it also demonstrates a significant improvement in prediction accuracy for each time step. In addition, this paper analyses the impact of feature dimensionality and initial data length on prediction and early crop mapping accuracy, demonstrating the necessity of multi-modal feature fusion for spatial–temporal prediction of high-resolution remote sensing data and the benefits of longer initial time-series (i.e., longer crop planting time) for crop identification. In general, our method has the potential to carry out early crop mapping on a large scale and provide information to formulate changes in agricultural conditions promptly.

The apple leaf-curling midge, Dasineura mali Kieffer (Diptera: Cecidomyiidae), is an invasive pest of apple, and can contaminate fresh fruit for export, causing biosecurity problems. To provide crucial information for its pest risk analysis, forecast, and management, we investigated the effects of temperatures (5, 10, 15, 20 and 25 °C) and daylengths (10, 11, 12, 13, 14 and 15 h) on its development and survival. The midge eggs failed to hatch at 5 °C and larvae could not complete development at 10 °C. Pupation and emergence rates were significantly higher at 20 °C than at 15 °C and 25 °C. Daylength had no effect on these parameters. The low temperature threshold and thermal requirement to complete development from eggs to adults were 3.7 °C and 627 degree-days, respectively. The midge had a significantly lower thermal requirement for the completion of its lifecycle at 20 °C (614.5 degree-days) than at 15 °C (650.1 degree-days) and 25 °C (634.8 degree-days). The thermal model developed in this study provided accurate predictions of the number of D. mali generations and adult emergence time in each generation in different regions of New Zealand. We suggest that the model could be used to predict population dynamics of this pest in other parts of the world.

The bridge-type bridge crane is a common lifting equipment used in modern factories and workshops. During the crane’s operation, the positioning of the trolley and the swing of the load can significantly impact the bridge crane’s safety and reliability. In this paper, we propose a variable universe fuzzy multi-parameter self-tuning PID (VUFMS-PID) control strategy for controlling the trolley’s movement. Our control strategy uses scaling factor variation to dynamically adjust the number of fuzzy control rules based on the system error and error rate of change. This approach improves control accuracy and enhances the crane’s stability and safety. Simulation results demonstrate that our proposed control strategy outperforms both the fuzzy PID and traditional PID control strategies. Specifically, it reduces the crane trolley’s positioning time and the maximum swing angle of the load. Our control strategy exhibits good adaptive ability and robustness, which further improves the stability and safety of the bridge-type bridge crane operation.

Dilated cardiomyopathy (DCM) is characterized by left ventricular or biventricular enlargement with systolic dysfunction. To date, the underlying molecular mechanisms of dilated cardiomyopathy pathogenesis have not been fully elucidated, although some insights have been presented. In this study, we combined public database resources and a doxorubicin-induced DCM mouse model to explore the significant genes of DCM in full depth. We first retrieved six DCM-related microarray datasets from the GEO database using several keywords. Then we used the “LIMMA” (linear model for microarray data) R package to filter each microarray for differentially expressed genes (DEGs). Robust rank aggregation (RRA), an extremely robust rank aggregation method based on sequential statistics, was then used to integrate the results of the six microarray datasets to filter out the reliable differential genes. To further improve the reliability of our results, we established a doxorubicin-induced DCM model in C57BL/6N mice, using the “DESeq2” software package to identify DEGs in the sequencing data. We cross-validated the results of RRA analysis with those of animal experiments by taking intersections and identified three key differential genes (including BEX1, RGCC and VSIG4) associated with DCM as well as many important biological processes (extracellular matrix organisation, extracellular structural organisation, sulphur compound binding, and extracellular matrix structural components) and a signalling pathway (HIF-1 signalling pathway). In addition, we confirmed the significant effect of these three genes in DCM using binary logistic regression analysis. These findings will help us to better understand the pathogenesis of DCM and may be key targets for future clinical management.

With the wide application of electric vehicles and the development of battery technology, pure electric construction machinery (PECM) has received more and more attention due to its high efficiency and no pollution. The working conditions of construction machinery are complex and accompanied by periodical working conditions and heavy load. For electric construction machinery, a heavy load represents an energy supply with a large current. To adapt to the working conditions of PECM, this paper proposes a robust controller to regulate the current of the hybrid energy system (HES) which include the battery and supercapacitor. The V-type operating conditions of a 5-ton pure electric loader are the research focus to analyze the working principles of the HES. The topology and energy flow patterns of the HES are proposed and analyzed. The model of the battery, supercapacitor, and DC/DC converter are depicted, and the robust control method is designed. An electric loader experiment platform is created to verify the effectiveness of the robust control method. Compared with the proportional integral control effect, the experiment results show that the proposed control method had good control performance and could better regulate the current. It can be used as a reference value for other dual energy source PECM.

The electromagnetic data observed with the CSES (China Seismo-Electromagnetic Satellite, also known as Zhangheng-1 satellite) contain numerous spatial disturbances. These disturbances exhibit various shapes on the spectrogram, and constant frequency electromagnetic disturbances (CFEDs), such as artificially transmitted very-low-frequency (VLF) radio waves, power line harmonics, and interference from the satellite platform itself, appear as horizontal lines. To exploit this feature, we proposed an algorithm based on computer vision technology that automatically recognizes these lines on the spectrogram and extracts the frequencies from the CFEDs. First, the VLF waveform data collected with the CSES electric field detector (EFD) are converted into a time–frequency spectrogram using short-time Fourier Transform (STFT). Next, the CFED automatic recognition algorithm is used to identify horizontal lines on the spectrogram. The third step is to determine the line frequency range based on the proportional relationship between the frequency domain of the satellite’s VLF and the height of the time–frequency spectrogram. Finally, we used the CSES power spectrogram to confirm the presence of CFEDs in the line frequency range and extract their true frequencies. We statistically analyzed 1034 orbit time–frequency spectrograms and power spectrograms from 8 periods (5 days per period) and identified approximately 200 CFEDs. Among them, two CFEDs with strong signals persisted throughout an entire orbit. This study establishes a foundation for detecting anomalies due to artificial sources, particularly in the study of short-term strong earthquake prediction. Additionally, it contributes to research on other aspects of spatial electromagnetic interference and the suppression and cleaning of electromagnetic waves.

Salmonella negatively impacts the poultry industry and threatens animals’ and humans’ health. The gastrointestinal microbiota and its metabolites can modulate the host’s physiology and immune system. Recent research demonstrated the role of commensal bacteria and short-chain fatty acids (SCFAs) in developing resistance to Salmonella infection and colonization. However, the complex interactions among chicken, Salmonella, host–microbiome, and microbial metabolites remain unelucidated. Therefore, this study aimed to explore these complex interactions by identifying the driver and hub genes highly correlated with factors that confer resistance to Salmonella. Differential gene expression (DEGs) and dynamic developmental genes (DDGs) analyses and weighted gene co-expression network analysis (WGCNA) were performed using transcriptome data from the cecum of Salmonella Enteritidis-infected chicken at 7 and 21 days after infection. Furthermore, we identified the driver and hub genes associated with important traits such as the heterophil/lymphocyte (H/L) ratio, body weight post-infection, bacterial load, propionate and valerate cecal contents, and Firmicutes, Bacteroidetes, and Proteobacteria cecal relative abundance. Among the multiple genes detected in this study, EXFABP, S100A9/12, CEMIP, FKBP5, MAVS, FAM168B, HESX1, EMC6, and others were found as potential candidate gene and transcript (co-) factors for resistance to Salmonella infection. In addition, we found that the PPAR and oxidative phosphorylation (OXPHOS) metabolic pathways were also involved in the host’s immune response/defense against Salmonella colonization at the earlier and later stage post-infection, respectively. This study provides a valuable resource of transcriptome profiles from chicken cecum at the earlier and later stage post-infection and mechanistic understanding of the complex interactions among chicken, Salmonella, host–microbiome, and associated metabolites.

Criegee intermediates (CIs) are important in the sink of many atmospheric substances, including alcohols, organic acids, amines, etc. In this work, the density functional theory (DFT) method was used to calculate the energy barriers for the reactions of CH3CHOO with 2-methyl glyceric acid (MGA) and to evaluate the interaction of the three functional groups of MGA. The results show that the reactions involving the COOH group of MGA are negligibly affected, and that hydrogen bonding can affect the reactions involving α-OH and β-OH groups. The water molecule has a negative effect on the reactions of the COOH group. It decreases the energy barriers of reactions involving the α-OH and β-OH groups as a catalyst. The Born-Oppenheimer molecular dynamic (BOMD) was applied to simulate the reactions of CH3CHOO with MGA at the gas-liquid interface. Water molecule plays the role of proton transfer in the reaction. Gas-phase calculations and gas-liquid interface simulations demonstrate that the reaction of CH3CHOO with the COOH group is the main pathway in the atmosphere. The molecular dynamic (MD) simulations suggest that the reaction products can form clusters in the atmosphere to participate in the formation of particles.

Criegee intermediates (CIs) are important zwitterionic oxidants in the atmosphere, which affect the budget of OH radicals, amines, alcohols, organic/inorganic acids, etc. In this study, quantum chemical calculation and Born–Oppenheimer molecular dynamic (BOMD) simulation were performed to show the reaction mechanisms of C2 CIs with glycolic acid sulfate (GAS) at the gas-phase and gas–liquid interface, respectively. The results indicate that CIs can react with COOH and OSO3H groups of GAS and generate hydroperoxide products. Intramolecular proton transfer reactions occurred in the simulations. Moreover, GAS acts as a proton donor and participates in the hydration of CIs, during which the intramolecular proton transfer also occurs. As GAS widely exists in atmospheric particulate matter, the reaction with GAS is one of the sink pathways of CIs in areas polluted by particulate matter.

Brimonidine tartrate (BRT) is a highly selective α2 adrenergic receptor agonist as treatment for patients with open angle glaucoma and high intraocular pressure. The objective of this study was to formulate an ophthalmic ion-sensitive in situ gel (ISG) of BRT to increase the retention time of the drug and its bioavailability. The optimum formulation of 2 mg/mL BRT-ISG was obtained with 0.45% gellan gum as the gel matrix. In vitro release results showed that the water-soluble drug bromonidine tartrate in ocular in situ gels exhibited a high burst effect and fast release in solution. The results of dialysis membrane permeation showed that there was a significant difference between the commercially available and BRT-ISG groups after 45 min. The results of the pre-corneal retention study indicated that gellan gum can effectively prolong ocular surface retention. Preliminary stability results showed that it should be stored in a cool and dark place, and the formulation under long-term preservation can be basically stable. The pharmacokinetic study of the BRT-ISG in the anterior chamber of the rabbit eye was studied by microdialysis technique, and microdialysis samples were analyzed by LC-MS/MS. The pharmacokinetic study showed that the BRT-ISG reached Cmax (8.16 mg/L) at 93 min after administration, which was 2.7 times that of the BRT eye drops, and the AUC(0-t) (1397.08 mg·min/L) was 3.4 times that of the BRT eye drops. The optimal prescription can prolong the retention time of BRT in front of the cornea and significantly improve the bioavailability of BRT in the eye. Combined with the results of in vitro release, permeation and pre-corneal retention studies, the improvement of BRT-ISG bioavailability in rabbit eyes was found to be mainly due to the retention effect after the mixture of ISG and tears.

Salmonella enterica serovar Typhimurium (ST) is a food-borne pathogen that can infect animals and humans. It is currently the most common bacterial pathogen that negatively affects the poultry industry. Although different chicken breeds have been observed to exhibit diverse resistance to ST infection, the underlying genetic mechanisms remain unclear and the genes involved in this differential disease resistance need to be identified. To overcome this knowledge gap, we used a liver transcriptome analysis to screen differentially expressed genes (DEGs) in two different chicken breeds (local Beijing You (BY) and commercial Guang Ming No. 2 broiler line B (GM)) before and after ST infection. We also performed weighted gene co-expression network analysis (WGCNA) to detect hub genes, and employed selection signal analysis of candidate genes. Three promising genes (EGR1, JUN and FOS) were eventually identified, and were significantly and differentially expressed in the same breed under different conditions, and in the two breeds after ST infection. Hub genes, such as PPFIA4 and ZNF395, were identified using WGCNA, and were associated with the ratio of heterophils to lymphocytes (H/L), an indicator of disease resistance. the present study identified several genes and pathways associated with resistance to ST infection, and found that BY had greater resistance to ST infection than GM. The results obtained provide valuable resources for investigating the mechanisms of resistance to ST infection in different chicken breeds.

Methomyl is one of the most important carbamates that has caused potential hazardous effects on both human beings and the environment. Here, we systematically investigated the hydrolysis mechanism of methomyl catalyzed by esterase PestE using molecular dynamics simulations (MD) and quantum mechanics/molecular mechanics (QM/MM) calculations. The hydrolysis mechanism involves two elementary steps: (Ⅰ) serine-initiated nucleophilic attack and (Ⅱ) C-O bond cleavage. Our work elicits the atomic level details of the hydrolysis mechanism and free energy profiles along the reaction pathway. The Boltzmann-weighted average potential barriers are 19.1 kcal/mol and 7.5 kcal/mol for steps Ⅰ and Ⅱ, respectively. We identified serine-initiated nucleophilic attack as the rate determining-step. The deep learning-based kcat prediction model indicated that the barrier of the rate-determining step is 15.4 kcal/mol, which is in good agreement with the calculated results using Boltzmann-weighted average method. We have elucidated the importance of the protein–substrate interactions and the roles of the key active site residues during the hydrolysis process through noncovalent interactions analysis and electrostatic potential (ESP) analysis. The results provide practical value for achieving efficient degradation of carbamates by hydrolases.

Natural products are a source for pesticide or drug discovery. In order to discover lead compounds with high fungicidal or herbicidal activity, new niacinamide derivatives derived from the natural product niacinamide, containing chiral flexible chains, were designed and synthesized. Their structures were confirmed by 1H NMR, 13C NMR and HRMS analysis. The fungicidal and herbicidal activities of these compounds were tested. The fungicidal activity results demonstrated that the compound (S)-2-(2-chloronicotinamido)propyl-2-methylbenzoate (3i) exhibited good fungicidal activity (92.3% inhibition) against the plant pathogen Botryosphaeria berengriana at 50 μg/mL and with an EC50 of 6.68 ± 0.72 μg/mL, which is the same as the positive control (fluxapyroxad). Compound 3i was not phytotoxic and could therefore be used as a fungicide on crops. Structure-activity relationships (SAR) were studied by molecular docking simulations with the succinate dehydrogenase of the fungal mitochondrial respiratory chain.

CCCH zinc finger proteins contain one to six tandem CCCH motifs composed of three cysteine and one histidine residues and have been widely found in eukaryotes. Plant CCCH proteins control a wide range of developmental and adaptive processes through DNA–protein, RNA–protein and/or protein–protein interactions. The complex networks underlying these processes regulated by plant CCCH proteins are often involved in phytohormones as signal molecules. In this review, we described the evolution of CCCH proteins from green algae to vascular plants and summarized the functions of plant CCCH proteins that are influenced by six major hormones, including abscisic acid, gibberellic acid, brassinosteroid, jasmonate, ethylene and auxin. We further compared the regulatory mechanisms of plant and animal CCCH proteins via hormone signaling. Among them, Arabidopsis AtC3H14, 15 and human hTTP, three typical CCCH proteins, are able to integrate multiple hormones to participate in various biological processes.

The recognition algorithm of the lightning whistler wave, based on intelligent speech, is the key technology to break the bottleneck of massive data and study the temporal and spatial variation rules of the lightning whistler wave. However, its recognition effect depends on the hyperparameters determined by manual experiments repeatedly, which takes a great deal of time and cannot guarantee the best recognition effect of the model. Therefore, we proposed the lightning whistler wave recognition algorithm based on grey wolf optimization (GWO). In this paper, the GWO algorithm is used to automatically find the best value of hyperparameters of Long Short-Term Memory (LSTM) in their limited searching space. Here we consider the number of hidden units (hu) and learning rate (lr) as the hyperparameters to be optimized, and the spatial coordinate (hu, lr) as the grey wolf position. By the end of the GWO process, we obtain the position of the wolf king α with the optimal hu and lr searched by the GWO algorithm. Then we use the optimal hu and lr to configure LSTM and perform supervised learning on the train set to obtain the final lightning whistler wave speech recognition model. Through experimental verification, the recognition model based on the GWO not only overcomes the uncertainty of the traditional model relying on manual finetuning of parameters and realizes the mechanism of automatic search and acquisition of hyperparameters, but also its recognition effect improves by about 2% in accuracy, F1score, and other metrics compared with the model trained by manually setting hyperparameters.

The malignancy with the greatest global mortality rate is lung cancer. Lung adenocarcinoma (LUAD) is the most common subtype. The evidence demonstrated that voltage-gated potassium channel subunit beta-2 (KCNAB2) significantly participated in the initiation of colorectal cancer and its progression. However, the biological function of KCNAB2 in LUAD and its effect on the tumor immune microenvironment are still unknown. In this study, we found that the expression of KCNAB2 in tissues of patients with LUAD was markedly downregulated, and its downregulation was linked to accelerated cancer growth and poor clinical outcomes. In addition, low KCNAB2 expression was correlated with a deficiency in immune infiltration. The mechanism behind this issue might be that KCNAB2 influenced the immunological process such that the directed migration of immune cells was affected. Furthermore, overexpression of KCNAB2 in cell lines promoted the expression of CCL2, CCL3, CCL4, CCL18, CXCL9, CXCL10, and CXCL12, which are necessary for the recruitment of immune cells. In conclusion, KCNAB2 may play a key function in immune infiltration and can be exploited as a predictive biomarker for evaluating prognosis and a possible immunotherapeutic target.

Synthetic cannabinoids, a class of psychoactive compounds, are controlled as new psychoactive substances (NPSs) identified by the early warning system (EWS) of the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). At present, several new synthetic cannabinoids have appeared in the illegal drug market, including 4-methylnaphthalen-1-yl-(1-pentylindol-3-yl) methanone (JWH-122), methyl (1-(5-fluoropentyl)-1H-indazole-3-carbonyl)-L-valinate (5F-AMB), and methyl 2-(1-(4-fluorobenzyl)-1Hindazole-3-carboxamido)-3-methylbutanoate (AMB-FUBINACA). A convenient, rapid, and highly sensitive analytical method was developed to determine three synthetic cannabinoids in rat plasma and urine. The liquid chromatography tandem mass spectrometry (LC-MS/MS) method was optimized and validated to analyze the three synthetic cannabinoids in rat plasma and urine. The method identified intra-assay precision (1.3–9.0% and 2.8–6.7%), inter-assay precision (3.0–8.6% and 3.9–8.8%), limits of detection (0.003–0.004 ng/mL and 0.00125–0.002 ng/mL) and quantification (0.012–0.016 ng/mL and 0.003–0.005 ng/mL), recovery (95.4–106.8% and 92.0–106.8%) for rat plasma and urine, and the matrix effect (93.4–118.0%) for rat urine, and the correlation coefficients were above 0.99 in the linear range. The established LC-MS/MS method was successfully used to simultaneously detect the JWH-122 and 5F-AMB in rat plasma and JWH-122, 5F-AMB, and AMB-FUBINACA in rat urine. The present study provides methodological support for internal exposure assessment of three synthetic cannabinoids and promotes the quantitative analysis and technical supervision of synthetic cannabinoids.

Levodopa-induced dyskinesia (LID) is a common complication of chronic dopamine replacement therapy in the treatment of Parkinson’s disease (PD), and a noble cause of disability in advanced PD patients. Circular RNA (circRNA) is a novel type of non-coding RNA with a covalently closed-loop structure, which can regulate gene expression and participate in many biological processes. However, the biological roles of circRNAs in LID are not completely known. In the present study, we established typical LID rat models by unilateral lesions of the medial forebrain bundle and repeated levodopa therapy. High-throughput next-generation sequencing was used to screen circRNAs differentially expressed in the brain of LID and non-LID (NLID) rats, and key circRNAs were selected according to bioinformatics analyses. Regarding fold change ≥2 and p < 0.05 as the cutoff value, there were a total of 99 differential circRNAs, including 39 up-regulated and 60 down-regulated circRNAs between the NLID and LID groups. The expression of rno-Rsf1_0012 was significantly increased in the striatum of LID rats and competitively bound rno-mir-298-5p. The high expression of target genes PCP and TBP in LID rats also supports the conclusion that rno-Rsf1_0012 may be related to the occurrence of LID.

The dynamic equation of a mass point in the circular restricted three-body problem is governed by Coriolis and centrifugal force, in addition to a co-rotating potential relative to the frame. In this paper, we provide an explicit, symmetric integrator for this problem. Such an integrator is more efficient than the symplectic Euler method and the Gauss Runge–Kutta method as regards this problem. In addition, we proved the integrator is symplectic by the discrete Hamilton’s principle. Several groups of numerical experiments demonstrated the precision and high efficiency of the integrator in the examples of the quadratic potential and the bounded orbits in the circular restricted three-body problem.

Perchlorate is a well-known thyroid-disrupting chemical as well as an extremely stable inorganic pollutant widely distributed in the environment. Therefore, perchlorate posts potential risks to the environment as well as human health. Crayfish is a dominant aquatic food with increasing consumption levels in recent years. It is crucial to evaluate the accumulation of perchlorate with well-water-soluble properties in crayfish and to assess its health risks. In our present study, we obtained crayfish samples from cultivated ponds and markets based on the regions of the Middle and Lower Reaches of the Yangtze River. The perchlorate concentration was measured in all 206 samples using ultra-high performance liquid chromatography coupled with mass spectrometry (UPLC–MS). Monte Carlo simulation was used to perform health risk assessments. The results indicated that perchlorate levels ranged from 7.74–43.71 μg/kg for cultivated crayfish and 4.90–16.73 μg/kg for crayfish sold in markets. The perchlorate accumulation mainly occurred in exoskeleton parts. All the HQ values were remarkable, at less than one—indicating that perchlorate exposure through the ingestion of crayfish does not pose an appreciable risk to human health.

In this paper, hydrophobic luminescent CdSe quantum dots are successfully dispersed in a mixture of styrene and methyl methacrylate through the oleic to methacrylic acid ligand exchange. Further in situ solution polymerization of the quantum dots in a mixture of styrene and methyl methacrylate followed by electrospinning allowed us to prepare luminescence hybrid styrene-co-methyl methacrylate fibers embedded with quantum dots. CdSe@P(S+MMA) hybrid fibers with 27% quantum yield showed excellent moisture, heat and salt resistance with a photoluminescence output below 120 °C. When dry heated, the hybrid fibers of the fluorescence signals decreased with temperature to 79%, 40%, 28%, 20% and 13% at 120 °C, 140 °C, 160 °C, 180 °C and 200 °C, respectively, due the to the chemical degradation of CdSe QDs. Such hybrid fibers show the potential to manufacture wearable moisture- and heat-sensing protective clothing in a 120–200 °C range due to the thermal-induced quenching of quantum dot photoluminescence.

Collecting sweat and monitoring its rate is important for determining body condition and further sweat analyses, as this provides vital information about physiologic status and fitness level and could become an alternative to invasive blood tests in the future. Presented here is a one-dollar, disposable, paper-based microfluidic chip for real-time monitoring of sweat rate. The chip, pasted on any part of the skin surface, consists of a skin adhesive layer, sweat-proof layer, sweat-sensing layer, and scale layer with a disk-shape from bottom to top. The sweat-sensing layer has an impressed wax micro-channel containing pre-added chromogenic agent to show displacement by sweat, and the sweat volume can be read directly by scale lines without any electronic elements. The diameter and thickness of the complete chip are 25 mm and 0.3 mm, respectively, permitting good flexibility and compactness with the skin surface. Tests of sweat flow rate monitoring on the left forearm, forehead, and nape of the neck of volunteers doing running exercise were conducted. Average sweat rate on left forearm (1156 g·m−2·h−1) was much lower than that on the forehead (1710 g·m−2·h−1) and greater than that on the nape of the neck (998 g·m−2·h−1), in good agreement with rates measured using existing common commercial sweat collectors. The chip, as a very low-cost and convenient wearable device, has wide application prospects in real-time monitoring of sweat loss by body builders, athletes, firefighters, etc., or for further sweat analyses.

Driven by the objective of earthquake disaster prevention and mitigation, China launched the Zhangheng mission to build a stereoscopic earthquake monitoring system from the lithosphere to space. This report briefly presents the possible seismic ionospheric disturbances recorded by the first probe of the Zhangheng mission, which is known as the China-Seismo-Electromagnetic Satellite (CSES). The routine data preprocessing and seismo-ionospheric information analysis methods are briefly introduced. The possible seismo-ionospheric disturbances that appeared during the strong shallow earthquakes (with a magnitude over 7 and a depth shallower than 30 km) are analyzed by using CSES and other multi-source data. Investigating seismo-ionospheric mechanisms requires multidisciplinary knowledge involving geophysics, atmosphere/ionosphere physics, geochemistry/atmospheric chemistry, etc. We state that the results from the CSES scientific application center are preliminary, calling for international scientists to contribute to the seismo-ionospheric perturbation phenomena, which is one of the most challenging scientific problems.

Temperature is the primary factor affecting the law of coal gas desorption. When the core method is used to measure the coal seam gas content (CSGS), the temperature of the coal core sample (CCS) will increase. The heat generated by the core bit cutting and rubbing the coal during coring is transferred to the CCS through the core tube, resulting in the temperature rising of the CCS. Because the CCS entering the core tube during coring is a dynamic process, the temperature of CCS is difficult to measure. To solve this problem, the temperatures of the core tube wall during coring in the Jiulishan coal mine (JLS), Guhanshan coal mine (GHS) and Zhaogu coal mine (ZG) at the core depth of 20 m were measured by the self-designed temperature measuring device. The thermodynamic models of the core bit and the core tube during coring were established. The reliability of the model was verified by comparing the numerical simulation results with the field measurement results. The verified model was used to predict the temperature changes of the core tube wall during coring in different strength coal seams and different core depths. The results show that the temperature change of the core tube wall was divided into a slowly temperature rising stage Ⅰ, a fast temperature rising stage Ⅱ and a slowly temperature rising and slowly temperature falling stage Ⅲ, which correspond to the process of pushing the core tube, drilling the CCS and early stage and later stage of withdrawing the core tube, respectively. The maximum temperature of the core tube wall appears in the first 3 min of withdrawing the core tube, and increases with the core depth increasing. The temperature of the measuring point at the end of drilling the CCS and the maximum temperature during coring linearly increase with the core depth. The temperature heating rate of the core tube is negatively linear, with the coal seam strength during pushing the core tube wall process. However, the temperature heating rate of the core tube wall is positively linear with the coal seam strength during drilling the CCS process. This study can provide a basis for further research on the dynamic distribution characteristics of temperature in the CCS during coring, which is of profound significance to calculate the gas loss amount and CSGC.

Salmonella causes significant economic loss to the poultry industry and represents a real threat to human health. The region of difference 21 (ROD21) pathogenicity island removal is a genetic mechanism by which Salmonellaenteritidis (SE) invades the intestinal epithelium and induces systemic infection in mice. The heterophil/lymphocyte (H/L) ratio reflects the chicken’s robustness and immune system status. The H/L ratio is considered a disease resistance trait, and it could be used as a marker for selecting Salmonella resistance in live chickens. However, the association of the H/L ratio with Salmonella resistance and the inflammatory response remains to be elucidated. Moreover, the kinetics of ROD21 excision in the intestine and immune organs of chickens is unknown. Therefore, this study aimed to investigate the bacterial load, the ROD21 excision, the IL-1β, IL-8, and INF-γ blood serum concentration kinetics, and the association with the H/L ratio in chicken at 1, 3, 7, and 21 days post-SE infection. The results showed a significant correlation between the H/L ratio and the bacterial load in the ileum and caecum at 7 dpi. The ROD21 pathogenicity island absolute and relative excision in the caecum were positively correlated at 1 dpi but negatively correlated at 7 dpi with the H/L ratio. However, in the liver, we found the opposite tendency. The association of the H/L ratio with IL-1β, IL-8, and INF-γ blood serum concentrations showed that a low H/L ratio is correlated with increased IL-1β and INF-γ at 21 dpi. This study confirmed that the H/L ratio is associated with robustness and Salmonella-resistance in chicken. The methodology used in this study can separate individuals into susceptible and resistant and can help in the selection and breeding of Salmonella-resistant chickens.

The heterophil/lymphocyte (H/L) ratio has been extensively studied to select poultry that are resistant to environmental stressors. Chickens with a low H/L ratio are superior to the chickens with a high H/L ratio in survival, immune response, and resistance to Salmonella infection. However, this disease resistance ability is likely to be associated with enhanced intestinal immunity. Therefore, to expand our understanding of these underlying resistance mechanisms, it is crucial to investigate the correlation between the H/L ratio as a blood immune indicator in live chickens and the intestinal barrier function and immunity. Jinxing yellow chickens H/L line one-day-old were divided into non-infected (NI) and Salmonella enteritidis infected (SI) at 7-days old. After dividing the birds into NI and SI, blood samples were taken for H/L ratios determination, and subsequently, birds from the SI group were infected with Salmonella enteritidis (SE). We assessed the effects of SE infection on the (i) goblet cells number from the ileum and caecum gut-segments, (ii) ileal mucosa morphology, and (iii) immune gene mRNA expressions from the ileum and caecum of NI and SI chickens at 7 and 21 days-post-infection (dpi). We found that the H/L ratio was negatively correlated with most intestinal immune indices, particularly with the goblet cells number and with IL-1β, IL-8, and IFN-γ ileal expressions. In conclusion, these results suggest that the H/L ratio is associated with the intestinal barrier and immune response for SE clearance and that the chickens with a low H/L ratio displayed enhanced intestinal immunity. This study expands the current knowledge that is related to using the H/L ratio to select and breed resistant broiler chickens.

Ultrawide bandgap (UWBG) semiconductor materials, with bandgaps far wider than the 3.4 eV of GaN, have attracted great attention recently. As a typical representative, wurtzite aluminum nitride (AlN) material has many advantages including high electron mobility, high breakdown voltage, high piezoelectric coefficient, high thermal conductivity, high hardness, high corrosion resistance, high chemical and thermal stability, high bulk acoustic wave velocity, prominent second-order optical nonlinearity, as well as excellent UV transparency. Therefore, it has wide application prospects in next-generation power electronic devices, energy-harvesting devices, acoustic devices, optical frequency comb, light-emitting diodes, photodetectors, and laser diodes. Due to the lack of low-cost, large-size, and high-ultraviolet-transparency native AlN substrate, however, heteroepitaxial AlN film grown on sapphire substrate is usually adopted to fabricate various devices. To realize high-performance AlN-based devices, we must first know how to obtain high-crystalline-quality and controllable AlN/sapphire templates. This review systematically summarizes the recent advances in fabricating wurtzite AlN film on (0001)-plane sapphire substrate. First, we discuss the control principles of AlN polarity, which greatly affects the surface morphology and crystalline quality of AlN, as well as the electronic and optoelectronic properties of AlN-based devices. Then, we introduce how to control threading dislocations and strain. The physical thoughts of some inspirational growth techniques are discussed in detail, and the threading dislocation density (TDD) values of AlN/sapphire grown by various growth techniques are compiled. We also introduce how to achieve high thermal conductivities in AlN films, which are comparable with those in bulk AlN. Finally, we summarize the future challenge of AlN films acting as templates and semiconductors. Due to the fast development of growth techniques and equipment, as well as the superior material properties, AlN will have wider industrial applications in the future.

An effective Hamiltonian finite element method is presented in this paper to investigate the three-dimensional dynamic responses of a towed cable-payload system with large deformation. The dynamics of a flexible towed system moving in a medium is a classical and complex rigid-flexible-liquid coupling problem. The dynamic governing equation is derived from the Hamiltonian system and built-in canonical form. A Symplectic algorithm is built to analyze the canonical equations numerically. Logarithmic strain is applied to estimate the large deformation effect and the system stiffness matrix will be updated for each calculation time step. A direct integral solution of the medium drag effect is derived in which the traditional coordinate transformation is avoided. A conical pendulum system and a 180° U-turn towed cable system are conducted and the results are compared with those retraced from the existing Hamiltonian method based on small deformation theory and the dynamic software of Livermore software technology corp. (LS-DYNA). Furthermore, a circularly towed system is analyzed and compared with experimental data. The comparisons show that the presented method is more accurate than the existing Hamiltonian method when large deformation occurred in the towed cable due to the application of logarithmic strain. Furthermore, it is more effective than LS-DYNA to treat the rigid-flexible-liquid coupling problems in the costs of CPU time.

Due to the addition of the drag reducer in refined oil pipelines for increasing the pipeline throughput as well as reducing energy consumption, the classical method based on the Darcy-Weisbach Formula for precise pressure loss calculation presents a large error. Additionally, the way to accurately calculate the pressure loss of the refined oil pipeline with the drag reducer is in urgent need. The accurate pressure loss value can be used as the input parameter of pump scheduling or batch scheduling models of refined oil pipelines, which can ensure the safe operation of the pipeline system, achieving the goal of energy-saving and cost reduction. This paper proposes the data-driven modeling of pressure loss for multi-batch refined oil pipelines with the drag reducer in high accuracy. The multi-batch sequential transportation process and the differences in the physical properties between different kinds of refined oil in the pipelines are taken into account. By analyzing the changes of the drag reduction rate over time and the autocorrelation of the pressure loss sequence data, the sequential time effect of the drag reducer on calculating pressure loss is considered and therefore, the long short-term memory (LSTM) network is utilized. The neural network structure with two LSTM layers is designed. Moreover, the input features of the proposed model are naturally inherited from the Darcy-Weisbach Formula and on adaptation to the multi-batch sequential transportation process in refined oil pipelines, using the particle swarm optimization (PSO) algorithm for network hyperparameter tuning. Case studies show that the proposed data-driven model based on the LSTM network is valid and capable of considering the multi-batch sequential transportation process. Furthermore, the proposed model outperforms the models based on the Darcy-Weisbach Formula and multilayer perceptron (MLP) from previous studies in accuracy. The MAPEs of the proposed model of pipelines with the drag reducer are all less than 4.7% and the best performance on the testing data is 1.3627%, which can provide the calculation results of pressure loss in high accuracy. The results also indicate that the model’s capturing sequential effect of the drag reducer from the input data set contributed to improving the calculation accuracy and generalization ability.

A polypropylene (PP) film is usually used as a dielectric material in capacitors as well as cables. However, PP films may degrade because of the combined effect of temperature and electric field. In an earlier study, plain PP films and PP films loaded with nano-metric natural clay were studied under sinusoidal (AC) electric fields at power frequency and temperatures above the ambient. To better understand the electrical characteristics of PP film under various conditions, the objective of this study is to determine the time-to-breakdown of the plain PP and PP filled with 2% (wt) natural nano-clay when subjected to time-invariant (DC) electric fields at elevated temperatures. In order to achieve this objective, the effects of uniform as well as non-uniform electric fields were compared at the same temperature for the PP film. In this study, experimental results indicated that the time-to-breakdown of all PP films, plain or filled with nano-clay, decreases with the increase in electric field intensity, non-uniformity of the electric field, and temperature. It was also found that the time-to-breakdown of PP film filled with 2% (wt) natural nano-clay under DC electric field is longer and less sensitive to temperature. Furthermore, when compared with the results under the uniform electric field, PP film filled with 2% (wt) nano-metric natural clay indicates shorter time-to-failure under non-uniform DC electric fields. Finally, the morphology of the samples was observed by digital camera, optical micrography, and SEM, to better understand the mechanism of the breakdown.