The Eastern Himalayan Syntaxis (EHS), featured by an exceptionally intense compression orogeny and an extremely rapid surface erosion rate, stands out as a prime area for investigating surface processes and landscape evolution. Understanding the formation of the EHS holds significant importance in advancing our comprehension of the evolutionary dynamics within the Tibetan Plateau and the complex interplay between endogenic and exogenic geological processes. Currently, two models, namely the tectonic aneurysm and the syntaxis expansion model, have been proposed to explain the formation and evolution of this syntaxis. In this study, we employ a multi-disciplinary approach, integrating geomorphic indices such as slope, relief, Hypsometric Integral (HI), Normalized Channel Steepness (Ksn), River Slope-Basin Area Integration (χ), combined with erosion rates on long-medium-short term timescales obtained from thermochronology, cosmogenic nuclides 10Be and landslide disaster probability data. Our findings suggest a relatively high tectonic activity in the confluence of the Yigong and Parlung Rivers in the northern end of the syntaxis. Moreover, our data reveals that spatial variability of tectonic activity is the primary driver of regional geomorphologic features and the spatial-temporal characteristics of erosion observed in the EHS, with lithology and climatic precipitation playing a lesser role. Furthermore, the northwards migration of the EHS appears to elucidate the shift of tectonic activity and rapid erosion from the core of the syntaxis near the Namche Barwa towards the confluence of the Yigong and Parlung Rivers. This northwards migration of the EHS underscores the need for increased attention to the high geological hazard risk in the northern part of the EHS.

Rapid analysis and characterization of compounds by mass spectrometry may overlook trace compounds, although targeted analysis methods can significantly improve detection sensitivity, it is difficult to discover novel scaffold compounds. This study developed a strategy for discovering trace compounds in the aging process of traditional Chinese medicine based on MS fragmentation and known metabolic pathway. Specifically, we found that the characteristic component of C. reticulata 'Chachi', methyl N-methylanthranilate (MMA), fragmented in ESI-CID to produce rearrangement ion 3-hydroxyindole, which has been proven to exist in trace amounts in C. reticulata 'Chachi' comparing with the reference substance by LC-MS/MS. By combining the known metabolic pathways of 3-hydroxyindole and the possible methylation reactions that may occur during aging, 10 possible indole derivatives were untargeted predicted. These compounds were confirmed to originate from MMA by purchasing or synthesizing reference substances and all of them were detected in C. reticulata 'Chachi' through LC-MS/MS analysis, achieving trace compound analysis from untargeted to targeted. It may contribute to explain the aging mechanism of C. reticulata 'Chachi' and the strategy of CID-induced special rearrangement ion binding metabolic pathway has potential application value in discovering trace compounds.

This study uses a recently developed theory and technique to examine post-acquisition evidence as to the motives for mergers and acquisitions(M&As), and decomposed the M/B ratio into three components: firm-specific error, time-series sector error, and long-run value-to-book. We make a multidimensional grouping according to the frequency of M&As , payment method, proportion of shares acquired, M/B ratio before the merger and total assets of the acquirers before the merge. The results confirm that M&As involve multiple motives, such as market timing, industry and economic shocks, agency and hubris. Using a sample of 2,035 M&As in China, we find that 59% are related to market timing, 68% are related to agency and hubris, 21% are related to industry and economic shocks, 51% are related to multiple motives. Our empirical research finds that the main motives for M&As of listed companies in China are value-decreasing, which have negative impact on the acquirers‘ sustainable development.

Gastroesophageal (GE) junction adenocarcinoma is an aggressive malignancy of growing incidence and is associated with public health issues such as obesity and GERD. Management has evolved over the last 2 decades to incorporate a multidisciplinary approach including endoscopic intervention, and neoadjuvant chemotherapy/ chemoradiation and minimally invasive or more limited surgical approaches. Surgical approaches include esophagectomy, total gastrectomy, and more recently proximal gastrectomy. This review analyzes the evidence for and applicability of these varied approaches in management as well areas of continued controversy and investigation.

Pulmonary sarcoidosis is a multisystem granulomatous interstitial lung disease (ILD) with a variable presentation and prognosis. Early accurate detection of pulmonary sarcoidosis may prevent progression to pulmonary fibrosis, a serious and potentially life-threatening form of the disease. However, the lack of a gold-standard diagnostic test and specific radiographic findings pose challenges in diagnosing pulmonary sarcoidosis. Chest computed tomography (CT) imaging is commonly used but requires expert, chest-trained radiologists to differentiate pulmonary sarcoidosis from lung malignancies, infections, and other ILDs. In this work, we developed a multichannel, CT and radiomics-guided ensemble network (RadCT-CNNViT) with visual explainability for pulmonary sarcoidosis vs. lung cancer (LCa) classification using chest CT images. We leverage CT and hand-crafted radiomics features as input channels, and a 3D convolutional neural network (CNN) and vision transformer (ViT) ensemble network for feature extraction and fusion before a classification head. The 3D CNN sub-network captures localized spatial information of lesions, while the ViT sub-network captures long-range, global dependencies between features. Through multichannel input and feature fusion, our model achieved the highest performance with accuracy, sensitivity, specificity, and combined AUC of 0.93±0.04, 0.94±0.04, 0.93±0.08 and 0.97 respectively in a 5-fold cross-validation study with pulmonary sarcoidosis (n=126) and LCa (n=93) cases. The model offers promising potential for improving the diagnosis of pulmonary sarcoidosis. A detailed ablation study showing the impact of CNN+ViT compared to CNN or ViT alone, and CT+radiomics input, compared to CT or radiomics alone, is also presented in this work.

We have investigated the interfacial dislocations in InxGa1–xN/GaN (0 ≤ x ≤ 0.20) heterostructures using diffraction contrast analysis in a transmission electron microscopy. The analysis indicate that the structural properties of the interface dislocations depend on the indium composition. For lower indium composition up to x = 0.09, we observed that the screw-type dislocations and dislocation half loops occurred at the interface even though the former do not contributes toward elastic relaxation of the misfit strain in the InGaN layer. With the increase of indium composition (0.13 ≤ x ≤ 0.17), in addition to the network of screw-type dislocations, edge-type misfit dislocations were found generated with their density gradually increasing. For higher indium composition (0.18 ≤ x ≤ 0.20), all the interfacial dislocations are transformed into a network of straight misfit dislocations along the <10-10> directions leading to partially relaxation of the InGaN epilayer. The presence of dislocation half loops may be explained by slip on the basal plane, the formation of misfit dislocations are attributed to punch-out mechanism.

This study investigated the capability of vocal-identity-cloning Artificial Intelligence (AI) to encode human-specific confident, doubtful, and neutral-intending emotive states. Linear mixed-effects models and machine learning classification with eXtreme Gradient Boosting were employed to examine the underlying acoustic signatures from 2,700 audio clips, comprising of sentences spoken by human speakers and two sets of equivalences (AI-Geography/AI-Trivia, based on the trained text) generated by voice-cloning models designed to clone human speakers’ identities. Compared with neutral-intending voice, human speakers lengthened their vocal tract, raised the fundamental frequency, and increased Chroma constant-Q transform when they intended to be confident; An opposite pattern was shown when they intended to be doubtful. The two sets of AI sounds displayed a similar pattern to human speech, suggesting a shared mechanism for encoding vocal expression across sources. The 1,000 times training-testing classification models reported an in-group advantage for AI sources. The algorithms, trained on AI-Geography/AI-Trivia, resulted in higher accuracies when tested within these AI sources than when tested on human audio. All between-source classifications reported above-chance-level (1/3) accuracies. These findings highlighted that voice-cloning AI, the widely used conversational agent, can learn and generate human-specific vocally-expressed confidence.

Sentinel-1 (S1) extra-wide (EW) swath data in cross-polarization (horizontal-vertical, HV or vertical-horizontal, VH) are strongly affected by the scalloping effect and thermal noise, particularly over areas with weak backscattered signals, such as sea surfaces. Although noise vectors in both the azimuth and range directions are provided in the standard S1 EW data for subtraction, the residual thermal noise still significantly affects sea ice detection by the EW data. In this paper, we improve the denoising method developed in previous studies to remove the additive noise for the S1 EW data in cross-polarization. Furthermore, we propose a new method for eliminating the residual noise (i.e. multiplicative noise) at the sub-swath boundaries of the EW data, which cannot be well processed by simply subtracting the reconstructed 2-D noise field. The proposed method of removing both the additive and multiplicative noise was applied to EW HV-polarized images processed using different Instrument Processing Facility (IPF) versions. The results suggest that the proposed algorithm significantly improves the quality of EW HV-polarized images under various sea ice conditions and sea states in marginal ice zone (MIZ) of the Arctic. This is of great support for the utilization of cross-polarization SAR images in wide swaths for intensive sea ice monitoring in polar regions.

An 8-months old male American Staffordshire terrier was referred for a no weightbearing lameness of the right pelvic limb, hyperthermia, lethargy and inappetence caused by hematogenous osteomyelitis. Orthopedic, radiographic and tomographic examinations revealed a bone sequestrum of 4 x 1.4 cm and active periosteal reaction of the caudo-lateral cortical in the metaphysis and the distal third of the right femoral diaphysis, medullary osteolysis and interruption of the cranio-medial cortical profile, with involvement of the femoral trochlea leading to a secondary medial patella luxation. Once skeletally mature, after 4 months from surgical debridement and aggressive antibiotic therapy against Klebsiella oxytoca revealed by bacteriological exam, the patient underwent prosthetic surgery for the application of a custom-made patellar groove replacement (PGR) to fill the bone defect and restore the femoral trochlea surface. Despite the serious injury that afflicted the right pelvic limb, the surgery had satisfactory outcomes until the last 18-months postoperative follow up.

Gastric outlet obstruction (GOO) poses a common and challenging clinical scenario, characterized by mechanical blockage in the pylorus, distal stomach, or duodenum, resulting in symptoms such as nausea, vomiting, abdominal pain, and early satiety. Its diverse etiology encompasses both benign and malignant disorders. The spectrum of current treatment modalities extends from conservative approaches to more invasive interventions, incorporating procedures like surgical gastroenterostomy (SGE), self-expandable metallic stents (SEMS) placement, and the advanced technique of endoscopic ultrasound-guided gastroenterostomy (EUS-GE). While surgery is favored for longer life expectancy, stents are preferred in malignant gastric outlet stenosis. The novel EUS-GE technique, employing a lumen-apposing self-expandable metal stent (LAMS), combines the immediate efficacy of stents with the enduring benefits of gastroenterostomy. Despite its promising outcomes, EUS-GE is a technically demanding procedure requiring specialized expertise and facilities.

Cold atmospheric plasma (CAP) has emerged as a promising therapeutic technology, distinguished by its safety, efficiency, and minimal side effects. With increasing applications in dermatology, CAP demonstrates antimicrobial efficacy against bacteria, viruses, and fungi, supports tissue proliferation and wound healing, and hinders the growth and migration of tumor cells. This review encompasses the concept, physical characteristics, and current research applications of CAP in dermatology. CAP, a gas cloud produced by ionizing gases, operates at room temperature, ensuring safety and efficacy in dermatological use. Its effects are mediated through active components like reactive oxygen and nitrogen species (RONS) and ultraviolet radiation. The extensive research covered in this paper explores CAP's applications in skin infections, immune-related diseases, and tumor diseases. As a biologically suitable technology, cold atmospheric pressure plasma finds widespread use in medicine, including medical device sterilization, dentistry, oncology, and dermatology. The direct and indirect forms of CAP applications, including plasma-activated liquids, complement each other. CAP holds promise as a dermatological treatment technique, but further exploration and research are needed. This article briefly explores CAP's diverse applications and potential utility within dermatology. The objective is to enhance the progress of plasma medicine by furnishing a concise overview of the applications of this groundbreaking technology in dermatological contexts.

Orogenic antimony-gold deposits contribute significantly to the global antimony resource base. China's orogenic antimony-gold deposits are primarily in southern Tibet. Investigations indicate that antimony combines and migrates with sulfur hydroxides in ore-forming fluids. Previous research on fluid inclusions in orogenic antimony-gold ores with sedimentary rock accommodation revealed the presence of organic inclusions, including liquid hydrocarbons, alongside common components such as CO2, H2O, CH4, and NaCl. However, the impact of liquid hydrocarbons on antimony migration and mineralization is still de-batable. To investigate the transportability of antimony by liquid hydrocarbons in orogenic antimony ores, we selected n-dodecanethiol and n-dodecane as the subjects. We measured the solubility and occurrence form of antimony in these compounds at various temperatures and durations. The results indicate that after 5 and 10 days of reaction at 100 °C, the antimony concentrations in the n-dodecanethiol and n-dodecane groups were 67.44±7.62 ppm, 75.15±16.74 ppm, 1.40±1.02 ppm, and 3.02±3.09 ppm, respectively. At 150 °C for 5 and 10 days, the respective concentrations were 50.58±5.39 ppm, 77.26±45.20 ppm, 2.66±3.08 ppm, and 2.41±2.03 ppm. At 200 °C for 5 and 10 days, the corresponding concentrations were 339.76±71.94 ppm, 218.97±25.03 ppm and 6.53±7.17 ppm, 2.27±0.82 ppm (n=3). The measured solubility of antimony in the n-dodecanethiol group increased gradually with rising temperature. The solubility of antimony in the n-dodecane group was low and notably inferior to that observed in the n-dodecanethiol group. X-ray photoelectron spectroscopy (XPS) analysis demonstrated a distinct thiol (R-SH) peak at 163.31 eV and compound peaks of antimony reacting with thiols at 162.06 and 160.87 eV. This suggests that antimony predominantly forms complexes with thiols for migration. Our findings suggest that specific liquid hy-drocarbon components, predominantly thiols, can interact with antimony at metallogenic temperatures and persist in ore-forming fluids, facilitating migration and mineral enrichment. Earlier experimental studies on gold and crude oil have indicated that liquid hydrocarbons also play an essential role in the transportation and enrichment of gold during the formation of gold deposits, thus indicating that liquid hydrocarbons possess the considerable potential to act as an ore-forming fluid during orogenic antimony-gold deposit formation in southern Tibet.

Based on the Expected Utility Theory and Regret Theory, the Extended Regret Theory (ERT) is proposed in this paper to study the optimal pricing strategy of retailers in e-commerce environment. Taking the diversity of sales channels and the uncertainty of consumers in e-commerce environment into consideration, author of the paper designs an extended regret utility function which comprehensively considers both pessimistic and optimistic attitudes of decision makers in retailing industry to describe their regret-avoidance behavior. According to the sensitivity analysis, it is found that the optimal retail price decreases as the consumer price sensitivity coefficient increases, yet does not show variation with changes of the consumers pessimism degree. Moreover, the optimal retail price(s) obtained under EUT, ERT and combination of EUT and ERT represent the same.

In this perspective article, we ponder topographical enhancements of artificial neural networks. In our recent paper in JMLR, we proved a quasi-equivalence between the network width and depth and also discussed the power of intra-links, which can be viewed as network height. In 1982, Hopfield published a network to model human associative memory, which contains many loops for dynamic evolution toward fixed points. Based on noising-denoising loops, diffusion models are recently developed to enable Bayesian modeling and inference with big data. Furthermore, we envision development of multi-AI-agent systems through “netware” engineering as a quantum leap of software engineering for emergent behaviors and autonomous AI at individual and population levels. We believe that the novel use of links and loops in space and time via multi-scale coupling would catalyze the next-generation neural networks.

The representation of aerosols in climate-chemistry models is important for air quality and climate change research, but it can require significant computational resources. To overcome this, simpler modules such as modal aerosol modules with three lognormal modes (MAM3) can be used. In this study, the coupling of the Carbon Bond Mechanism, version Z (CBMZ), and MAM3 chemistry modules in WRF-CAM5 was improved by adding biomass-burning emissions to both gas- and particle-phase chemistry and incorporating a conversion mechanism between volatile organic compounds (VOCs) and secondary organic carbons (SOCs). The study conducted six simulations over the western U.S. and northeastern Pacific region and compared the model’s performance with observational benchmarks such as reanalysis, ground-based, and satellite data. The results showed that the model with enhanced chemistry capabilities had a 31% and 58% reduction in root-mean-square errors (RMSE) for black carbon (BC) and organic carbon (OC) surface concentrations, respectively. The earlier release of the WRF-CAM5 version had two deficiencies that were addressed in this study. This research highlights the importance of accurate aerosol representation in climate-chemistry models for improving accuracy and reducing errors in simulations.

The North China Plain is among the regions most afflicted by ground fissure disasters in China. Recent urbanization has accelerated ground fissure activity in the three counties of the northern North China Plain, posing significant threats to both the natural environment and socioeconomic sustainability. Despite the increased attention, a lack of comprehensive understanding persists due to delayed recognition and limited research. This study conducted field visits and geological surveys across 43 villages and 80 sites to elucidate the spatial distribution patterns of ground fissures in the aforementioned counties. By integrating these findings with regional geological data, we formulated a causative model to explain ground fissure formation. Our analysis reveals a concentration of ground fissures near the Niuxi and Rongxi faults, with the former exhibiting the most extensive distribution. The primary manifestations of ground fissures include linear cracks and patch-shaped collapse pits, predominantly oriented in east-west and north-south directions, indicating tensile failure with minimal vertical displacement. Various factors contribute to ground fissure development, including fault activity, ancient river channel distribution, bedrock undulations, rainfall, and ground settlement. Fault activity establishes a concealed fracture system in shallow geotechnical layers, laying the groundwork for ground fissure formation. Additionally, the distribution of ancient river channels and bedrock undulations modifies regional stress fields, further facilitating ground fissure emergence. Rainfall and differential ground settlement serve as triggering mechanisms, exposing ground fissures at the surface. This research offers novel insights into the causative mechanisms of ground fissures in the northern North China Plain, providing valuable scientific evidence for mitigating ground fissure disasters during the urbanization process in the region.

Based on the teaching material of "Robotics" course, this paper studied the automatic knowledge graph construction, including knowledge points extraction and knowledge point relation extraction. We proposed a new method of extracting the first-level, second-level, and third-level knowledge points as well as their prerequisite relations of knowledge points in the textbook. For the problem of insufficient knowledge of the pre-trained language model in the specific field, methods such as incremental pre-training and optimization of cost functions are employed to integrate subject knowledge into the pre-trained language model, thus improving its effectiveness. To overcome the problem that the traditional method of relationship extraction can not be applied directly to the extraction of teaching materials, a new scheme for knowledge point relationship extraction based on keyword relationship is proposed. The experimental data from textbooks shows that the F1 score of knowledge point extraction reaches 93%, considerably improved compared to the traditional model. Consequently, the knowledge point entity extraction and relationship extraction methods based on the pre-trained model can effectively extract structured information and facilitate the automatic construction of knowledge graphs.

Aim: To analysis the relationship between healthy adults right ventricular diameter (RVD) and geographical factors. Location: China’s 22 provinces, municipalities and autonomous regions. Methods: Using correlation analysis the relationship between RVD and nine geographic factors, build predictive models by factor analysis. Results: There is significant correlation between RVD and geographical factors, and the annual average temperature is most relevant geographical factors, a predictive model was built by factor analysis: Ŷ = 19.46 + 0.0007072X1 + 0.001034X2 -0.05412X3 -0.001405X4 -0.0006351X5 + 0.02903X6 + 0.01243X7 -0.01033X8 + 0.03816X9 ± 0.63. Then using Kriging interpolation interpolate the geographical distribution of Chinese healthy adult right ventricular diameter reference value in ArcGIS software. Main Conclusion: If geographic factors can be derived in anywhere of China, RVD can be calculated by the model, you can also get RVD from geographical distribution.

This paper investigates the leader–follower formation tracking control of underactuated surface vessels (USVs) with input saturation. Each vessel is subject to the uncertainties induced by model uncertainties and environmental disturbances. At first, an event-trigged extended state observer (ETESO) is used to recover the velocity, yaw rate and the uncertainties. Then, an estimator is used to estimate velocity of the leader. An event-trigged controller (ETC) is constructed based on the estimator, the observer and extra variables. Specifically, extra variables are used to solve the underactuated problem and input saturation. Stability analysis of control system is given to prove all signals are bounded. Simulations demonstrate that the ETESO can estimate accurately the uncertainties, the velocity and yaw rate; the ETC can largely reduce the action times of actuator.

In this paper, we focus on developing a novel method to extract sea ice cover (i.e., discrimination/classification of sea ice and open water) using Sentinel-1 (S1) cross-polarization (vertical-horizontal, VH or horizontal-vertical, HV) data in extra wide (EW) swath mode based on the machine learning algorithm support vector machine (SVM). The classification basis includes the S1 radar backscatter coefficients and texture features that are calculated from S1 data using the gray level co-occurrence matrix (GLCM). Different from previous methods where appropriate samples are manually selected to train the SVM to classify sea ice and open water, we proposed a method of unsupervised generation of the training samples based on two GLCM texture features, i.e. entropy and homogeneity, that have contrasting characteristics on sea ice and open water. We eliminate the most uncertainty of selecting training samples in machine learning and achieve automatic classification of sea ice and open water by using S1 EW data. The comparison shows good agreement between the SAR-derived sea ice cover using the proposed method and a visual inspection, of which the accuracy reaches approximately 90% - 95% based on a few cases. Besides this, compared with the analyzed sea ice cover data Ice Mapping System (IMS) based on 728 S1 EW images, the accuracy of extracted sea ice cover by using S1 data is more than 80%.

Amorphous germanium films on non-refractory glass substrates were annealed by ultrashort near-infrared (1030 nm, 1.4 ps) and mid-infrared (1500 nm, 70 fs) laser pulses. Crystallization of germanium irradiated at a laser energy density (fluence) range from 25 to 400 mJ/cm2 under single-shot and multi-shot conditions was investigated using Raman spectroscopy. The dependence of the fraction of the crystalline phase on the fluence was obtained for picosecond and femtosecond laser annealings. The regimes of almost complete crystallization of germanium films over the entire thickness are obtained (from the analysis of Raman spectra with excitation of 785 nm laser). The possibility of scanning laser processing is shown, which can be used to create films of micro and nanocrystalline germanium on flexible substrates.

Viruses are silent enemies that intrude and take control of the plant cell's machinery for their own multiplication. Infection by viruses and the resulting damage is still a major challenge in the agriculture sector. Plants have the ability to fight back, but the ability of viruses to counteract and mutate at a fast rate helps them to hide from the host response. Therefore, classical approaches for introgressing resistance genes by breeding have obtained limited success in counteracting the virus menace. Genetic modification (GM) based strategies have been successful in engineering artificial resistance in plants. Several different approaches based on pathogen derived resistance, antisense constructs, hairpin RNA, double stranded RNA etc. have been used to enhance plant resistance to the virus. Recently, genome editing (GE) strategies mainly involving the CRISPR/Cas mediated modifications are being used for virus control. In this review, we discuss the developments and advancements in the GM and GE based methods in tackling virus infection in plants.

Cancer develops from abnormal cell growth in the body, causing significant mortalities every year. To date, potent therapeutic approaches have been developed to eradicate tumor cells, but intolerable toxicity and drug resistance can occur in treated patients, limiting the efficiency of existing treatment strategies. Therefore, searching for novel genes critical for cancer progression and therapeutic response is urgently needed for successful cancer therapy. Recent advances in bioinformatic and proteomic techniques have allowed the identification of a novel category of peptides encoded by non-canonical open reading frames (ncORFs) from historically non-coding genomic regions. Surprisingly, many of the ncORFs express functional microproteins that play a vital role in human cancers. In this review, we provide a comprehensive description of different ncORF types with coding capacity and technological methods in discovering ncORFs among human genomes. We also summarize the diagnostic and prognostic value of these ncORF as well as their carcinogenic role in cancer progression and underestimated potential as therapeutic targets.

Natural gas hydrate, also known as combustible ice and mainly composed of methane, it is identified as the potential clean energy in the 21th century. Due to its large reserves, gas hydrate can ease problems caused by energy resource shortage and has gained attention around the world. In this paper, we focus on the exploration and development of gas hydrate as well as discussing its status and future development trend in China and abroad, then we analyze its opportunities and challenges in China from four aspects: resource, technology, economy and police with five forces model and PEST method. The results show, China has abundance gas hydrate resource; however the backward technologies and inadequate investment has seriously hindered the future development of gas hydrate, so China should establish relevant cooperation framework and intuitional arrangement to attract more investment as well as breaking through technical difficulties to make gas hydrate commercialization as soon as possible.

Photocatalytic degradation plays a crucial role in wastewater treatment, and the key to achieving high efficiency is to develop photocatalytic systems that possess excellent light absorption, carrier separation efficiency, and surface-active sites. Among various photocatalytic systems, S-type heterojunctions have shown remarkable potential for efficient degradation. This work delves into construction of S-type heterojunctions of ternary indium metal sulfide and bismuth ferrite nanofibers with introduction of sulfur vacancy defects and morphology modifications to enhance the photocatalytic degradation performance. Through the impregnation method, BiFeO₃/Zn₂S₄ heterojunction materials were synthesized and optimized30% BiFeO₃/Zn₂S₄ heterojunction exhibited superior photocatalytic performance with higher sulfur vacancy concentration than Zn₂S₄. The in-situ XPS results demonstrate that the electrons between Zn₂S₄ and BFO are transferred via S-Scheme, and after modification, Zn₂S₄ has a more favorable surface morphology for electron transport, and its flower-like structure interacts with the nanofibers of BFO, which has a further enhancement of the reaction efficiency for degrading pollutants. This exceptional material demonstrated a remarkable 99% degradation of Evans blue within 45 min and a significant 68% degradation of ciprofloxacin within 90 min. This work provides a feasible idea for developing photocatalysts to deal with the problem of polluted water resources under practical conditions.

Connected and Autonomous Vehicle (CAV) combines technologies of autonomous vehicle (AV) and connected vehicles (CV) to develop quicker, more reliable and safer traffic. Artificial Intelligence (AI) based CAV solutions play significant roles in sustainable city. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on driver; increased connectivity increases the exposures of vehicles vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles vulnerabilities to negatively impact the performance and operations of CAV. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAV, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAV is elaborated from both viewpoints of intra-vehicle system and inter-vehicle system. We pointed out that securing the perception and operations of CAV would be the top requirement to enable CAV to be applied safely and reliably in practice. Also, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAV.

We investigate numerically the interactions of in-phase Airy beams modulated by a fundamental Gaussian beam and fourth-order diffraction in Kerr nonlinear media. Directly numerical simulations show that normal (anomalous) fourth-order diffractions and in-phase (out-of-phase) Gaussian beam affect the interactions of solitons generated from Airy beams in unique manners. Different from previous results that interactions between in-phase (out-of-phase) conventional beams are always attractive (repulsive), many anomalous interactions of Airy beams are obtained. Stable bound states of breathing Airy soliton pairs can be formed with the help of fourth-order diffraction and fundamental Gaussian beam.

This paper integrates carrier manifolds from control theory and hybrid systems modeling to develop a novel mathematical framework for Artificial General Intelligence (AGI). Carrier manifolds represent the state space of complex AGI systems, while hybrid systems model discrete and continuous dynamics together. The proposed architecture embeds carrier manifold into GPTProX, a hybrid AI solver combining conversational AI, logic programming, and optimization.

The emergence of multi-drug resistant E. coli is an important matter of increasing considerable concern to global public health. The aim of this study was to investigate the incidence, antibiotic resistance pattern, phylogroups and genetic variation of E. coli isolates from raw milk, vegetable salad and ground meat samples. Methods: Culture-based techniques, Kirby-Bauer disk diffusion susceptibility testing, PCR and RAPD assays were used to determine the incidence rate, antimicrobial resistance pattern, phylogenetic groups and genetic diversity of the E. coli isolates. Results: E. coli isolates were highly resistant to amoxicillin (79.16%), trime-thoprim-sulfamethoxazole (70.83%), amoxicillin-clavulanic acid (62.50%), tetracycline (54.16%), chloramphenicol (54.16%), nitrofurantoin (54.16%), ampicillin (45.83%), streptomycin (45.83%), and kanamycin (33.33%); and completely susceptible to norfloxacin and azithromycin. 70.83% of the isolates were multi-drug resistant. Most E. coli isolates (46%) belonged to phylogroup A. RAPD with UBC245 primer categorized the isolates into 11 clusters. A high level of genetic di-versity was found among the isolates; however, 33.3% of the isolates were grouped in a major cluster (R5). Conclusions: Antibiotic resistance patterns are randomly distributed among the ge-netic clusters. Novel, practical, efficient food safety control and surveillance systems of multi-drug resistant foodborne pathogens are required to control the foodborne pathogen contamina-tion.

The way in which a perforated structure is formed has attracted much interest in the porous membrane research community. This novel structure gives materials an excellent antifouling property as well as a low operating pressure and other benefits. Unfortunately, the current membrane fabrication methods usually involve multi-step processes and the use of organic solvents or additives. Our study is the first to offer a way to prepare perforated membrane by using a physical foaming technique with CO₂ as the blowing agent. We selected thermoplastic polyurethane (TPU) as the base material because it is a biocompatible elastomer with excellent tensility, high abrasion resistance, and good elastic resilience. Various processing parameters, which included the saturation pressure, the foaming temperature, and the membrane thickness, were applied to adjust the TPU membrane’s perforated morphology. We proposed a possible formation mechanism of the perforated membrane. The as-prepared TPU membrane had good mechanical properties with a tensile strength of about 5 MPa and an elongation at break above 100%. Such mechanical properties make this novel membrane usable as a self-standing filter device. In addition, its straight-through channel structure can separate particles and meet different separation requirements.

Based on the deployment of global innovation value chain, the article analyzes the existing independent innovation capability of Guangzhou, and analyzes in detail from innovative talents, innovation system, innovation culture and innovation environment. The role of the central city of Guangzhou has led to research on issues such as the common development of cities in Guangdong and the Pearl River Delta. Using the combination of qualitative analysis and quantitative analysis, we can find out the shortcomings of Guangzhou's independent innovation capability, explore the causes of problems, and seek solutions to the main problems.

This study presents an innovative analytical method for the detection and quantification of 14 β-agonists in pork using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method involves the use of a solid phase microextraction (SPME) probe, consisting of a wooden tip coated with polyacrylonitrile (PAN) and molecularly imprinted polymer (MIP). This probe has been integrated into an automated extraction device, designed in our laboratory to extract the target analytes prior to LC-MS/MS analysis. Compared to the traditional solid-phase extraction (SPE) procedure, the proposed approach significantly reduces the costs related to adsorbent ma-terial and solvent consumption, and shortens purification time, thereby reducing both the tech-nical workload and associated expenses. The methodology has been carefully validated in ac-cordance with the National Standard of the People's Republic of China (GB/T 22286-2008), evalu-ating key parameters including the limit of detection (LOD), limit of quantification (LOQ), matrix effects, linearity, and both intra-day and inter-day precision. The average recovery rates for all β-agonists were observed to lie between 71.6% and 82.2%, with relative standard deviations (RSDs) consistently below 15% for both types of precision. The LOD and LOQ values were found to range from 0.09 to 0.39 μg/kg and 0.27 to 0.99 μg/kg, respectively. In terms of accurate detection of positive samples, the developed method demonstrated a closer approximation to the true value of the sample compared to the National Standard method GB/T 31658.22-2022. Overall, the proposed method exhibits substantial promise for the routine assessment of β-agonists in pork and presents a practical alternative for compliance monitoring in regulatory settings.

A transport process was studied from an aqueous solution containing oxalic acid and 100 mg/L Ge using a flat sheet supported liquid membrane (FSSLM) system. Cyanex 923 immobilized in a polytetrafluoroethylene membrane was employed as a carrier. The solution chemistry and related diagrams were applied to study the transport of germanium. The effectual parameters such as oxalic acid, carrier concentration, and strip reagent composition were evaluated in this study. Based on the results, the oxalic acid concentration of 0.075 mol/L and the carrier concentration of 20 %v/v were the condition in which the efficient germanium transport occurred. Among strip reagents, NaOH (0.04-0.1 mol/L) had the best efficiency to transport germanium through the SLM system. Furthermore, the permeation model was obtained to calculate the mass transfer resistances of the membrane (Δ_m) and feed (Δ_f) phases. According to the results, the values of 1 and 1345 s/cm were evaluated for Δ_m and Δ_f, respectively.

The shortwave infrared Ge-Si photodetector will become the core device of the LiDAR optical receiver. In order to meet the urgent demand for photodetectors in the LiDAR field, we have designed and produced a 32×32 pixel Ge-Si photodetector array proposed and developed to meet the performance requirements of the detector array. A dark current detection system for fast scanning and detecting large-scale Ge-Si detector arrays is proposed and developed to achieve rapid detection of dark current in each pixel of the detector. The system was used to validate the main performance indicators of the detector array we designed, achieving rapid discrimination of array performance and rapid localization of damaged pixels. The scanning test results show that the average dark current of the detector array chip we designed is at the nano ampere level, and the proportion of bad points is less than 1%. The consistency of the array chip is high, which can meet the requirements of light detection at the receiving end of the LiDAR. This work laid the foundation for our subsequent development of a LiDAR prototype system.

Predicting the outcome of a future game between two National Basketball Association (NBA) teams poses a challenging problem of interest to statistical scientists as well as the general public. In this article, we formalize the problem of predicting the game results as a classification problem and apply the principle of maximum entropy to construct NBA maximum entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs by the NBAME model. The best NBAME model is able to correctly predict the winning team 74.4 percent of the time as compared to some other machine learning algorithms which is correct 69.3 percent of the time.

Background: New open-source electric-grid planning models have the potential to improve power system planning and bring a wider range of stakeholders into the planning process for next-generation, high-renewable power systems. However, it has not yet been established whether open-source models perform similarly to the more established commercial models for power system analysis. This reduces their credibility and attractiveness to stakeholders, postponing the benefits they could offer. In this paper, we report the first model intercomparison between an open-source power system model and an established commercial production cost model. Results: We compare the open-source Switch 2.0 to GE Energy Consulting’s Multi Area Production Simulation (MAPS) for production-cost modeling, considering hourly operation under 17 scenarios of renewable energy adoption in Hawaii. We find that after configuring Switch with similar inputs to MAPS, the two models agree closely on hourly and annual production from all power sources. Comparing production gave a coefficient of determination of 0.996 across all energy sources and scenarios, indicating that the two models agree on 99.6% of the variation. For individual energy sources, the coefficient of determination was 69–100. Conclusions: Although some disagreement remains between the two models, this work indicates that Switch is a viable choice for renewable integration modeling, at least for the small power systems considered here. Although some disagreement remains between the two models, this work indicates that Switch is a viable choice for renewable integration modeling, at least for the small power systems considered here.

In view of the problem of charging and hydrogen filling facilities construction in the transition from fuel vehicles to electric vehicles and hydrogen fuel cell vehicles, in order to meet the electric energy demand of electric vehicles and hydrogen energy demand of hydrogen fuel cell vehicles at the same time, this paper puts forward a method of siting and capacity determination of electric-hydrogen refueling integrated station (EHRIS) based on Voronoi diagram and particle swarm algorithm based on calculating the demand of charging and filling of hydrogen in vehicles. Firstly, OD pair(Origin-Destination) is used to represent the starting point and end point of the car to portray the travel demand of the car, and on the basis of the traffic network model, the shortest driving path of the new energy car is determined by Dijkstra algorithm, and Monte Carlo simulation is used to get the electric-hydrogen energy demand of the car; secondly, the Voronoi diagram is introduced to classify the service scope of the electric-hydrogen charging station to determine the equipment capacity of the electric-hydrogen charging station, while taking into account the electric-hydrogen charging and refueling capacity. Secondly, a Voronoi diagram is introduced to divide the service scope of the EHRIS, determine the capacity of the equipment in the EHRIS, and consider the distance constraints between the sites of EHRIS, so as to make the division of the site and service scope more reasonable. Finally, a dynamic optimal current model framework for distribution networks based on second-order cone relaxation is established, and each element of the active distribution network is planned, so that the distribution network can operate safely and stably after being connected to the EHRIS. With the objective of minimizing the total social cost of EHRIS and considering the constraints of the charging equipment and hydrogen production and injection equipment of the EHRIS, a siting and capacity model to meet the electric-hydrogen energy demand of electric and hydrogen fuel cell vehicles is developed, and solved by a particle swarm algorithm. Finally, the simulation planning is carried out with Sioux Falls city and IEEE33 network, which ensures the stable operation of the power grid while meeting the energy demand of automobiles, and the results verify the effectiveness and feasibility of the proposed method.

Rapeseed (Brassica napus L.) is one of the most important oil crops in China. Improving oil production of rapeseed is an important way to ensure the safety of edible oil in China. Oil production is an important index to reflect the quality of rapeseed and is determined by oil content and yield. Applying nitrogen is an important way to ensure a high yield. However, increasing nitrogen application would decrease oil content. Thus, it is critical to screen elite germplasm resources with stable or improved oil content under high nitrogen and to investigate the molecular mechanisms of nitrogen regulation of oil accumulation. In this paper, we review the effects of nitrogen levels on rapeseed yields and oil content, aiming to reveal the mechanisms of nitrogen regulation in oil accumulation and thereby provide a theoretical basis for breeding varieties with high oil content.

Flexible and stretchable conductive materials have received significant attention in several applications such as flexible displays and sensors. In this paper, we report a highly dispersed porous Ag nanoflakes with clean surfaces were fabricated through an explosive growth process. The evolution process from silver nanoflakes to nanomeshes occurred by the novel “dissolution–recrystallization” solvothermal process. The as-obtained Ag meshes have the dual nature of nanoflakes and nanoparticles, which could create an intercross and interpenetration conductive network structures between silver and polymer in the printed elastic conductor, therefore, the silver meshes as conductive fillers used in elastic conductor simultaneously exhibit high conductivity and mechanical durability.

This paper proposes a novel single-stage buck-boost three-Level neutral-point-clamped (NPC) inverter with two independent dc sources coupled for the grid-tied photovoltaic (PV) application, which can effectively solve the unbalanced operational conditions generally appeared between two coupled independent PV sources induced by the unequal irradiation and temperature distribution. The proposed control scheme can simultaneously guarantee the maximum power point (MPP) operation of both PV sources and maintain the output waveform quality. Compared to the traditional two-stage PV inverter, the proposed NPC inverter could reduce the PV array voltage requirement and dc-link capacitors’ voltage rating, meanwhile show the advantage in operational efficiency. MATLAB simulations and the captured experimental results are presented to show the performance of the proposed three-level inverter.

Prunus tenella is a rare and precious relict plant in China. It is an important genetic resource for almond improvement and an indispensable material in ecological protection and landscaping. However, the research of molecular breeding and genetic evolution has been severely restricted, due to the lack of genome information. In this investigation, we created a chromosome-level genomic pattern of P. tenella, 231Mb in length with a contig N50 of 18.1 Mb by Hi-C techniques and high-accuracy PacBio HiFi sequencing. The present assembly predicted 32088 protein-coding genes, and an examination of the genome assembly indicated that 94.7% among all assembled transcripts were alignable to the genome assembly; most (97.24%) were functionally annotated. By phylogenomic genome comparison, we found that P. tenella is an ancient group that diverged approximately 13.4 million years ago (Mya) from 13 additional closely related species and about 6.5 Mya from the cultivated almond. Collinearity analysis revealed that P. tenella is highly syntenic and has high sequence conservation with almond and peach. However, this species also exhibit many presence/absence variants. Moreover, a large inversion at the 7,588 kb position of chromosome 5 was observed, which may have a significant association with phenotypic traits. Lastly, population genetic structure analysis in eight different populations indicated a high genetic differentiation among the natural distribution of P. tenella. This high-quality genome assembly provides critical clues and comprehensive information for the systematic evolution, genetic characteristics, and functional gene research of P. tenella. Moreover, it provides a valuable genomic resource for in-depth study in protecting, developing, and utilizing P. tenella germplasm resources.

The origin and significance of the tonalite–trondhjemite–granodiorite (TTG) units and the familiar metabasite xenoliths they host in the Yangtze Craton, China, remain controversial, and resolving these issues is important if we are to understand the evolution of the early Yangtze Craton. We focused on biotite–tremolite schist xenoliths in the Archean TTG units of the Kongling high-grade metamorphic terrane, and U–Pb dating of their zircons yielded ²⁰⁷Pb/²⁰⁶Pb ages of ca. 3.00 Ga, which provides a minimum age for the formation of the pre-metamorphic basic igneous rock. The host TTGs and late intrusive granitic dikes yield three groups of upper intercept ages at 2.87–2.88, 2.91–2.94, and 3.07 Ga, and a concordant age at 2.94 Ga, which suggest that the Yangtze continental nucleus underwent three important metamorphic–magmatic events in the Mesoarchean at ca. 3.00, 2.94, and 2.87 Ga. The biotite–tremolite schists have high ratios of K₂O/Na₂O and high contents of CaO, Cr, and Ni, thus showing the characteristics of high-K calc-alkaline island-arc volcanic rocks (basalt–andesite) that form by the partial melting of subducted oceanic crust. The data also provide further proof that a Mesoarchean metamorphic basement exists in the Yangtze Plate. Derivation of the magmatic protoliths of the biotite–tremolite schist enclaves from an oceanic crust during slab subduction, and the presence of these xenoliths within the TTG suite, indicate the existence of the initiation of plate tectonics during the Mesoarchean (≤2.94 Ga).

In recent decades, as eutrophication in inland and coastal waters (ICWs) has increased due to anthropogenic activities and global warming, so has the need for timely monitoring. Compared with traditional sampling and laboratory analysis methods, satellite remote sensing technology can provide macro-scale, low-cost, and near real-time water quality monitoring services. The Geostationary Ocean Color Imager (GOCI), integrated onboard the Communication Ocean and Meteorological Satellite (COMS) from the Republic of Korea, was the first geostationary ocean color observation satellite and was operational from April 1, 2011 to March 31, 2021. Over ten years, GOCI has observed oceans, coastal waters, and inland waters within its 2,500 km×2,500 km target area centered on the Korean Peninsula. The most attractive feature of GOCI, compared with other commonly used watercolor sensors, was its high temporal resolution (1h, eight times daily from 0 UTC to 7 UTC), providing the opportunity to monitor the quality of ICWs, where optical properties can change rapidly throughout the day. This systematic review aims to comprehensively review GOCI features and applications in ICWs, analyzing progress in atmospheric correction algorithms and water quality monitoring. Analyzing 123 articles from the Web of Science and China National Knowledge Infrastructure (CNKI) through a bibliometric quantitative approach, we examined GOCI’s strength and performance with different processing methods. These articles reveal that GOCI played an essential role in monitoring the ecological health of ICWs in its observation area in East Asia. GOCI has led the way to a new era of geostationary ocean satellites, providing new technical means for monitoring water quality in oceans, coastal zones, and inland lakes. We also discuss the challenges encountered by geostationary satellites in monitoring water quality and provide suggestions for improvements.

In numerical simulations, achieving high accuracy without significantly increasing computational costs is often challenging. To address this, this paper presents an improved finite volume weighted essentially non-oscillatory (WENO) scheme tailored for applicability in computational fluid dynamics (CFD) and implemented in the flow solver NUAA-Turbo for simulating turbomachinery flows using both RANS and RANS/LES coupling. Firstly, the new WENO scheme is validated against classic numerical test cases to assess its stability and reliability in handling discontinuities, the Double problem, and Raleigh-Taylor (RT) instability issues. Compared to the original format, this enhanced finite volume WENO scheme demonstrates superior stability near discontinuities and resolves flow features with the same grid resolution more effectively. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, computations are performed using RANS, and the results obtained using WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupled simulations of turbine wakes and film cooling. The results show that the enhanced finite volume WENO scheme offers improved stability and accuracy in engineering applications, allowing for high-precision calculations with fewer grid points to capture more detailed flow physics, thereby reducing computational costs in aerodynamic applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

This article investigates the potential for carbon reduction in urban parks in Shangqiu City using high-resolution remote sensing imagery. The aim is to guide modern urban carbon neutrality strategies. The carbon reduction potential is estimated based on the mitigation of the urban heat island effect by park greenery, which reduces energy consumption. The parks are regarded as cool island centers, and 100 cooling gradients are gradually formed outward until the temperature reaches that of impermeable urban surfaces. The energy saved by the parks in mitigating the heat island effect is statistically calculated as the carbon reduction potential of urban park greenery. Additionally, this article classifies the sample parks into different categories and selects 26 landscape metrics to analyze their relationship with carbon-saving potential and driving factors.

Water pollution is the main cause of global ecological degradation and seriously affects people's water supply. In order to respond to the water environmental protection policy and provide management departments with a basis for refining water quality, this paper used the environmental Gini coefficient (EGC) method based on four indicators such as water environmental capacity, population, land area, and gross domestic production (GDP) to represent social factors, economic factors, and environmental factors, respectively. After the optimization, for COD, the EGC based on the land area was 0.30, EGC based on population was 0.21, EGC based on environment capacity was 0.02, and the EGC based on GDP was 0.45, and the sum of EGC was 0.962. From this result, we observed that the change in the Gini coefficient of each indicator was not very big. Hence, the most significant change in the Gini coefficient was that of GDP, with a higher rate than other criteria. Then, the COD, AND, and TP discharge allocation model was constructed to obtain the total allocated discharge permit in Lushui Basin. The results found that the total discharge permit allocation of COD, AN, and TP to the Lushui basin were 51483.304 tons/year, 843.119 tons/year, and 340.926 tons/year, respectively. Based on the GIS spatial analysis technology, the distribution of unfair factors that cause pollution inequity was investigated. Finally, the reduction measures were proposed to implement environmental supervision and strengthen water environment management strictly.

Runtime verification (RV) is a lightweight approach to detecting temporal errors of system at runtime. It confines the verification on observed trajectory which avoids state explosion problem.To predict the future violation, some work proposed the predictive RV which uses the information from models or static analysis. But for software whose models and codes cannot be obtained, or systems running under uncertain environment, these predictive methods cannot take effect. Meanwhile, RV in general takes multi-valued logic as the specification languages, for example the " true, false and inconclusive" in three-valued semantics. They cannot give accurate quantitative description of correctness when "inconclusive" is encountered. We in this paper present a RV method which learns probabilistic model of system and environment from history traces and then generates probabilistic runtime monitor to quantitatively predict the satisfaction of temporal property at each runtime state. In this approach, Hidden Markov Model (HMM) is firstly learned and then transformed to Discrete Time Markov Chain (DTMC). To construct incremental monitor, the monitored LTL property is translated into Deterministic Rabin Automaton (DRA). The final probabilistic monitor is obtained by generating the product of DTMC and DRA, and computing the probabilities for each state. With such method, one can give early warning once the probability of correctness is lower than pre-defined threshold, and have the chance to do adjustment in advance. The method has been implemented and experimented on real UAS (Unmanned Aerial Vehicle) simulation platform.

In this paper, the quality change of scallop (Patinopecten yessoensis) in the process of anhydrous storage and transportation after cold-acclimation and induced dormancy was studied, and the regulation mechanism of quality degradation in the storage and transportation in the process of gradient chilling stress and drying exposure was further explored. The results show that while being transferred from anhydrous storage and transportation from hydrous storage and transportation, the breathing pattern of scallops were changed from aerobic to anaerobic. Their gill filaments were altered, and the apparent vitality was constantly declining, which was reflected by the edge shrinkage of pallium and the direct proportion between the edge reduction rate and the stimulus response period. After being in the anhydrous state for 4d, the AEC value dropped to 67.59%. At this time, if they were under hydration again, they would resume a nice growth state. By virtue of proteomics, it was revealed from the analysis that cold acclimation and dry exposure mainly led to changes in biological functions and pathways such as mitochondrial inner membrane and ATP hydrolysis activity. In addition, it can be seen from the functional annotation and enrichment analysis of the metabolite KEGG that cold acclimation promoted the purine metabolism of scallops, while dry exposure inhibited the metabolism of saturated fatty acids. Besides, in this study, the infrared sensing mode was used for the first time to record the heart rate changes of the scallops during circulation, which provides feasibility for the nondestructive vitality monitoring of Lamellibranchia.

In this work, we focus on investigating electrothermal flow in a rotating electric field (ROT-ETF), with primary attention paid to the horizontal traveling-wave electrothermal (TWET) vortex induced at the center of the electric field. The frequency-dependent flow profiles in the microdevice are analyzed using different heat transfer models. Accordingly, we address in particular the importance of electrode cooling in ROT-ETF as metal electrodes of high thermal conductivity while substrate material of low heat dissipation capability are employed to develop such microfluidic chips. Under this circumstance, cooling of electrode array due to external natural convection on millimeter-scale electrode pads for external wire connection occurs and makes the internal temperature maxima shift from the electrode plane to a bit of distance right above the cross-shaped interelectrode gaps, giving rise to reversal of flow rotation from a typical repulsion-type to attraction-type induction vortex, which is in good accordance with our experimental observations of co-field TWET streaming at frequencies on the order of reciprocal charge relaxation time of the bulk fluid. These results point out a way to make a correct interpretation of out-of-phase electrothermal streaming behavior, which holds great potential for handing high-conductivity analytes in modern microfluidic systems.

In this present study, 3-pentadecyl-phenol was selected as a modifier to prepare a foamable phenolic resin with excellent performance, which was successfully prepared by in-situ modification. Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (¹H NMR, ¹³C-NMR) were used to test and characterize the molecular structure of the modified resin. The results showed that 3-pentadecyl-phenol successfully modified the molecular structure of phenolic resin with a reduction in resin gel time. The effect of changing the added amount of 3-pentadecyl-phenol on the mechanical properties, microstructure and flame retardancy of the modified foam was investigated. The results showed that when the amount of added 3-pentadecyl-phenol was 15% of the total amount of phenol, this resulted in the best toughness of the modified foam, which could be increased to 300% compared to the bending deflection of the unmodified phenolic foam. The cell structure showed that the modified phenolic foam formed a more regular and dense network structure and the closed cell ratio was high. Furthermore, the compressive strength, bending strength, and limited oxygen index were improved, while the water absorption rate was lowered. However, the foam density could be kept below 40 mg/cm³, which does not affect the load.

Double suction centrifugal pump installed along the Yellow River faces the serious sediment erosion due to the high sediment content which cause the poor operation efficiency of pump unit. The particle motion characteristics and erosion characteristics in the pump under different flow rates and different particle concentrations were numerically simulated based on the particle track model of solid-liquid two-phase flow. The results show that the flow rate has a significant effect on the particle tracks and the erosion caused by the particles in the impeller. The total erosion rate is positively correlated with the flow rate, and increases with the increase of flow rate. The vortex and secondary flow in the impeller have obvious influence on the particle trajectory, which increases the particle concentration at the trailing edge of the pressure surface and intensifies the impact erosion in this area. The particles carried by the vortex intensifies the local erosion. The particle concentration mainly affects the erosion rate, but has little effect on the erosion position. The in-fluence of flow rate on the pump erosion is greater than that of the particle properties. These results provide a reference for optimization of the design of anti-erosion blades of the double-suction pump and regulation-operation of pumping station.

Elevation has been a cornerstone of biodiversity research, and changes in the environmental factors behind it influence biodiversity and community patterns. Exploring the potential reasons behind liverwort community patterns has been a matter of multiplied interest for ecologists. In the present study, we assessed the liverwort plants of the Sygera Mountain from 3100 m to 4500 m decaying wood, tree, soil, and rock using complex field surveys in 2017 and 2019, and investigated the effects of altitude and various climatic factors on the diversity and community composition of the Sygera Mountain. Also, we used including ANOVA, mixed effects modeling, NMDS, ANOSIM, and CCA, which helped to critically assess the liverwort diversity with respect to environmental variables. The results of the study showed a bimodal variation in the richness of liverwort communities with altitude, with peaks occurring at 3500 m and 4100 m. The variation with altitude was significant, with communities at 4100 m and 4300 m being associated with arid environments, and those at 3100 m and 3300 m favoring areas of higher mean annual temperatures and precipitation. Among the climatic factors, the variation in mean diurnal rang, precipitation, and annual temperature was found to be the determinant of liverwort communities. The results suggest that elevation and daily temperature fluctuations play a crucial role in the distribution and community structure formation of mountain liverwort plants. This study deepens our understanding of liverwort ecology and emphasizes the importance of climatic variables in determining plant community composition.

Intramuscular fat content (IFC) and meat color are vital indicators affecting pork quality. A significant positive correlation between IFC and redness meat color (a* value) indicates that these two traits are likely to be regulated by shared molecular pathways. To identify candidate genes, hub genes, and signaling pathways that regulate these two traits, we measured the IFC and a* value in 147 hybrid pigs and selected individuls with extreme phenotypes for transcriptome analysis. The results revealed 485 and 394 overlapping differentially expressed genes (DEGs) using DESeq2, limma, and edgeR packages affecting IFC and a* value, respectively. Weighted gene co-expression network analysis (WGCNA) identified four modules significantly correlated with IFC and a* value. Moreover, we integrated functional enrichment analysis results based on DEGs, GSEA, and WGCNA conditions to identify candidate genes, and identified 47 and 53 candidate genes affecting IFC and a* value, respectively. The protein-protein interaction (PPI) network analysis of candidate genes showed that 6 and 14 hub genes affecting IFC and a* value, respectively. These genes mainly participated in various pathways related to lipid metabolism and redox reactions. Notably, four crucial hub genes (MYC, SOX9, CEBPB, and PPAGRC1A) were shared for these two traits. After functional annotation of these four hub genes, we hypothesized that the SOX9/CEBPB/PPARGC1A axis could co-regulate lipid metabolism and myoglobin redox response. Further research on these hub genes, especially the SOX9/CEBPB/PPARGC1A axis, will help to understand the molecular mechanism of the co-regulation of IFC and a* value, which will provide the theoretical basis for improving pork quality.

Air pollutants such as volatile organic compounds (VOCs), nitrogen oxides (NOx), sulfur dioxide (SO2), as well as water pollutants including heavy metal, are harmful to human and environment. Effective control and reduction of their pollution is therefore an important topic for today’s scientists. Fly ash (FA) is a type of industrial waste that can cause multiple environmental problems if discharged into the air. On the other hand, because of its high porosity, large specific surface area, and other unique characteristics, the FA can also be used as a low-cost and high efficient adsorbent with some simple modifications. This paper reviews the effects of FA on treatment of the above air and water pollution based on our research experience over many years, including to the current status of global FA utilization, physicochemical properties, principle of adsorption, and the application direction of FA in the future. It focuses on the use of nanocomposite technology to fabricate functional FA fibrous membranes to adsorb VOCs from air, and treat heavy metal wastewater. This present review first describes the fabrication technology of FA nanocomposites and their mechanism of adsorption VOCs from air. Utilization of nanofiber technology to fabricate multi-functional FA emerging composite materials to mitigate air and water pollution has great potential in the future, especially use of pollutant material to control other pollutants.

Drug delivery systems consist of cyclodextrins (CyDs) have kept constant attention for good compatibility, negligible toxicity, and improved pharmacokinetics of drugs. The unique hollow structure has endowed a lot of functions, such as inclusion of guest molecules, functional modification of active hydroxyl groups, and noncovalent interactions. Besides, the polyhydroxy structure has further extended the functions of CyDs by inter/intramolecular interactions and chemical modification. Furthermore, the versatile functions of the complex contribute to physicochemical characteristics alteration of the drugs, therapeutic talent, stimulus-responsive switch, self-assemble capability, and fiber formation. This review attempts to list the recent progress of CyDs and discuss their roles in the drug delivery system. Future perspectives of the construction of CyD-based drug delivery systems are also discussed at the end of this review, which may be the possible directions for the construction of more rational and cost-effective delivery vehicles.

Open source software such as OpenDSS has given a lot of help to distribution network researchers and educators. With high penetration of distributed renewable energy resources into distribution network, tradition distribution steady state analysis software such as OpenDSS is faced with difficulty in handling distributed generators. Three-phase distributed generators are often modeled in sequence frame while unbalanced distribution network are usually modeled in phase frame. So a load flow in sequence-phase coupled frame is proposed to handle models described in both frames. Voltage controlled DGs which are difficult to cope with in OpenDSS are handled in proposed program. The steady state analysis platform is programmed with open source Modelica language and the main aim of this paper is to introduce an open source platform for active distribution network steady analysis include load flow and short circuit analysis which can be easily adopted and improved by other educators and researchers.

In this study, alfalfa silage with different packing densities (500 kg/m3, 600 kg/m3 and 700 kg/m3) were set up under outdoor high temperature and indoor normal temperature. The chemical composition, fermentation quality and microbial community of alfalfa silage were analyzed. The results showed that DM and WAC content decreased with the increase of density. When the density is 600kg/m3, CP content reaches the maximum and ADF content is the lowest. Temperature has a certain effect on alfalfa silage. The content of Lactobacillus plantarum fermented at high temperature is lower than that fermented at normal temperature. At the same time, the content of Lactobacillus plantarum decreased with the increase of packing density. However, the content of Lactobacillus plantarum was the lowest when the packing density was 600 kg/m3 at high temperature. In summary, this study explained the effects of different temperature and density on alfalfa fermentation quality and microbial community, and clarified that the density should be reasonably controlled within 600 kg/m3 during alfalfa silage, providing theoretical support for production practice.

Atoms in Molecules (AIM), Natural Bond Orbital (NBO), and normal coordinate analysis have been carried out at the global minimum structures of TH₅⁺ (T = C/Si/Ge). All these analyses lead to a consistent structure for these three protonated TH₄ molecules. The CH₅⁺ has a structure with three short and two long C-H covalent bonds and no H-H bond. Hence, the popular characterization of protonated methane as a weakly bound CH₃⁺ and H₂ is inconsistent with these results. However, SiH₅⁺ and GeH₅⁺ are both indeed a complex formed between TH₃⁺ and H₂ stabilized by a tetrel bond, with the H₂ being the tetrel bond acceptor. The three-center-two-electron bond (3c-2e) in CH₅⁺ has an open structure, which can be characterized as a V-type 3c-2e bond and that found in SiH₅⁺ and GeH₅⁺ is a T-type 3c-2e bond. This difference could be understood based on the typical C-H, Si-H, Ge-H and H-H bond energies. Moreover, this structural difference observed in TH₅⁺ can explain the trend in proton affinity of TH₄. Carbon is selective in forming a ‘tetrel bond’ and when it does, it might be worthwhile to highlight it as a ‘carbon bond’.

TSPO-PET tracers are sensitive to a single-nucleotide-polymorphism (rs6971-SNP) resulting in low (LAB), medium (MAB) and high (HAB) affinity binders, but the clinical relevance for [18F]GE-180 is still unclear. We evaluate the impact of rs6971-SNP on in vivo [18F]GE-180 binding in healthy brain and in pseudo-reference tissue in neurooncological and neurodegenerative diseases. Standardized uptake values (SUV) of [18F]GE-180-PET were assessed using a manually drawn region of interest in the fronto-parietal and cerebellar hemisphere. SUVs were compared between LAB, MAB and HAB in controls, glioma, 4-repeat tauopathies (4RT) and Alzheimer’s disease (AD) subjects. Second, SUVs were compared between patients and controls within their rs6971-subgroup. After exclusion of patients with prior therapy, n=24 LABs (n=7 controls, n=5 glioma, n=6 4RT, n=6 AD) were analysed. Age- and sex-matched MABs (n=38) and HABs (n=50) were selected. LABs had lower fronto-parietal and cerebellar SUVs when compared to MABs and HABs, but no significant difference was observed between MABs and HABs. Within each rs6971 group no SUV difference between patients and controls was detected in the pseudo-reference tissues. The rs6971-SNP affects [18F]GE-180 quantification, revealing lower binding in LABs when compared to MABs/HABs. Fronto-parietal and cerebellar ROIs were successfully validated as pseudo-reference regions.

We reported previously that poly (3-hydroxybutyrate) (PHB) oligomer is an effective antimicrobial agent against gram-positive bacteria, gram-negative bacteria, fungi and multi-drug resistant bacteria. In this work, it was further found that polyethylene glycol (PEG) can promote the antimicrobial effect of PHB oligomer synergistically. Three hypothetic mechanisms were proposed, that is, generation of new antimicrobial components, degradation of PHB macromolecules and dissolution/dispersion of PHB oligomer by PEG. With a series of systematic experiments and characterizations of HPLC-MS, it was deducted that dissolution/dispersion of PHB oligomer dominated the synergistic antimicrobial effect between PHB oligomer and PEG. This work demonstrates a way for promoting antimicrobial effect of PHB oligomer and other antimicrobial agents through improving hydrophilicity.

The Physics-Informed Neural Networks (PINNs) improve the efficiency of data utilization by combining physical principles with neural network algorithms and ensure that the predictions are consistent and stable with the physical laws. PINNs opens up a new approach to address inverse problems in fluid mechanics. Based on the single-relaxation-time lattice Boltzmann method (SRT-LBM) with the Bhatnagar-Gross-Krook (BGK) collision operator, the PINN-SRT-LBM model is proposed in this paper for solving the inverse problem in fluid mechanics. The PINN-SRT-LBM model consists of three components. The first component involves a deep neural network that predicts the equilibrium control equations in different discrete velocity directions within SRT-LBM. The second component employs another deep neural network to predict non-equilibrium control equations, enabling inference of the fluid's non-equilibrium characteristics. The third component, a physics informed function translates the outputs of the first two networks into physical infor-mation. By minimizing the residuals of the physical partial differential equations (PDEs), the physics informed function infers relevant macroscopic quantities of the flow. The model evolves two sub-models applicable to different dimensions, named PINN-SRT-LBM-I and PINN-SRT-LBM-II models according to the construction of the physical informed function. The innovation of this work is the introduction of SRT-LBM and discrete velocity models as physical drivers into the neural network through the interpretation function. Therefore, PINN-SRT-LBM allows the neural network to handle inverse problems of various dimensions and focus on problem-specific solving. Experimental results confirm the accurate prediction of flow infor-mation at different Reynolds numbers within the computational domain. Relying on the PINN-SRT-LBM models, inverse problems in fluid mechanics can be solved efficiently.

Abstract: To describe the feeder topology and information exchange between intelligent electronic devices (IEDs) for Internet of Things (IoT), it is necessary to extend IEC 61850 and add a logical model. The feeder model described in IEC 61970 is then extended in IEC 61850 to serve as a container for the equipment along the distribution line. For the physical connections in the electrical equipment, both terminal and connectivity node logical models are added. Taking logical node XCBR as the example, its attributes for the terminals are added to the electrical equipment. The logical node LCNN is then further added in order to describe the connectivity node. By next adding the logical node LTPN to describe the topological node, and FTPA to describe the results of the topology analysis, we can efficiently describe the topology analysis results. Based on these new logical nodes, the exchange of topology information between intelligent terminals no longer relies on configuration files, but only requires logical nodes. Through the above expansion, the topology description and information exchange of medium and low voltage feeders are realized.

Embryo stage of oxidation of an epi Ge(001)-2×1 by atomic oxygen and molecular O₂ is studied via synchrotron radiation photoemission. The topmost surface buckled with the up- and down-dimer atoms and the first subsurface layer behave distinctly from the bulk by exhibiting surface core-level shifts in the Ge 3d core-level spectrum. The O₂ molecules become dissociated upon reaching the epi Ge(001)-2×1 surface. One of the O atom removes off the up-dimer atom, and the other bonds with the underneath Ge atom in the subsurface layer. Atomic oxygen adsorbed on the epi Ge(001)-2×1 preferentially in between the up-dimer atoms and the underneath subsurface atoms without affecting the down-dimer atoms. The electronic environment of the O-affiliated Ge up-dimer atoms becomes similar to that of the down-dimer atoms. Both exhibit an enrichment in charge, where the subsurface of the Ge layer is maintained in a charge-deficient state. The dipole moment originally generated in the buckled reconstruction no longer exists, thereby resulting in a decrease in the ionization potential. The down-dimer Ge atoms and the back-bonded subsurface atoms remain inert to atomic O and molecular O₂, a possible cause of low reliability in Ge-related metal-oxide-semiconductor (MOS) devices.

The COVID-19 pandemic was associated with increases in some healthcare-associated infections. We investigated the impact of the pandemic on rates and molecular epidemiology of Clostridioides difficile infection (CDI) within one VA Hospital. We anticipated that the potential widespread use of antibiotics for pneumonia during the pandemic might increase CDI rates given that antibiotics are a major risk for CDI. Hospital data on patients with CDI and recurrent CDI (rCDI) were reviewed pre-COVID-19 pandemic (2015 to 2019) and during the pandemic (2020 - 2021). Restriction endonuclease analysis (REA) strain typing was performed on CD isolates recovered from stool samples collected from 10/2019 – 3/2022. CDI case numbers declined 43.2% in 2020 – 2021 compared to the annual mean over the previous 5 years. Stool test positivity rate was also lower during the COVID-19 pandemic (14.3% vs. 17.2%; P = 0.013). Although inpatient volume declined, rates of CDI among inpatients were reduced by 34.2% in 2020 – 2021. Mean monthly cases of rCDI also declined significantly after 2020 [3.38 (95% CI: 2.89 – 3.87) vs. 1.92 (95% CI: 1.27 – 2.56); P = &lt;0.01]. Prior to the pandemic, REA group Y was the most prevalent CD strain among the major REA groups (27.3%). During the first wave of the pandemic from March 8, 2020, through June 30, 2020, there was an increase in the relative incidence of REA group BI (26.7% vs. 9.1%. After adjusting for CDI risk factors, a multivariable logistic regression model revealed that odds of developing an REA group BI CDI increased during the first pandemic wave (OR 6.41, 95% CI: 1.03 – 39.91) compared to the pre-pandemic period. In conclusion, the incidence of CDI and rCDI decreased significantly during the initial waves of the COVID-19 pandemic. In contrast, REA BI (Ribotype 027), a virulent, previously epidemic CD strain and frequently associated with hospital transmission and outbreaks, reappeared as a prevalent strain during the first wave of the pandemic.

Over recent years, the importance of patent literature has become more recognized in the academic setting. In the context of artificial intelligence, deep learning, and data sciences, patents are relevant to not only industry but also academe and other communities. In this article, we focus on deep tomographic imaging and perform a preliminary landscape analysis of the related patent literature. Our search tool is PatSeer . Our patent bibliometric data is summarized in various figures and tables. In particular, we qualitatively analyze key deep tomographic patent literature.

Suboptimal health status (SHS) is a state between health and disease, has several associated factors, although, its underlying mechanism is still unclear. This study aimed to investigate the status of SHS and its associated factors of high school students in three areas of China (Shanxi, Guangzhou, and Tibet). A multidimensional sub-health questionnaire of adolescent (MSQA) is used to evaluate SHS. Among 1461 respondents, females proportion 56.47% was higher than males 43.53% where SHS was higher in Shanxi followed by Tibet and then Guangzhou. The rural area, grade, lack of sleep, home visit in a week, lack of exercise, a heavy burden of study, smoking, drinking, and fewer friends were the risk factors of SHS, while, families living status, seeking help and extroversion were the protective factors. SHS is significantly associated with different influencing factors. For comprehensive prevention and control measures, reduce the risk factors and enhance the protective factors.

Aeromagnetic compensation plays a vital role in geomagnetic navigation and has received considerable attention throughout last few decades. Classical aeromagnetic compensation methods based on the Tolles–Lawson (T-L) model are mainly aimed at permanent, induced, and eddy-current magnetic interferences of aircraft platform, which ignores other stray magnetic field interference on the platform including the interferences caused by on-board electronic (OBE) systems. In order to cooperate with TL model, magnetometers are usually required to be installed on the extension rod outside the cabin, which is widely applied to geophysical magnetic survey. In order to ensure safety and reduce the cost of platform modification in geomagnetic navigation, it’s necessary to place magnetometers inside the cabin. It also further exacerbates the magnetic interferences and improves the difficulty of magnetic compensation. In this paper, a modified aeromagnetic compensation method is proposed, and the in-cabin OBE interferences are respectively modelled to be proportional to the currents and their temporal variations of different electronic devices. To ensure that modified model adapts to strong OBE interference in the cabin, a cut-off frequency determination method based on curvature calculation and a feature selection method based on correlation calculation are proposed. The cut-off frequency determination method helps to select passband filter which suitable for in-cabin OBE interference. The feature selection method can help to effectively select current and voltage inputs for modified model. In addition, principal component analysis (PCA) is adopted to reduce multicollinearity which is intensified by the extension of OBE interferences in coefficient-estimating. Experiments on public dataset are conducted to illustrate the effectiveness of the proposed method, and the best compensation result achieved 1.71nT of root mean square error (RMSE).

Since the advent of the OBORI, it was subjected to numerous studies. However, most previous studies investigated only the potential impact of the OBORI on the Chinese economy and geopolitics. Therefore, its real effect on Chinese international commerce in OBORI countries is not evaluated yet. Accordingly, this study intends to model the OBORI effect on Chinese product brand purchases across country members. The assessment is made on 18362 purchases of the International Online Consumers (IOCs) from a Chinese international online selling platform. The Data was obtained from a programming language and the octopus software. The OBORI policy's effect on Chinese brands' purchases was examined through a Different In Different Model (DIDM). Results show that the impact of OBORI is weak in the real market. However, it could be significant if OBORI includes more developed and economically strong countries. To Chinese brands and policymakers, we show how the inclusion in the OBORI project of developed countries could contribute more to Chinese product brands' purchases. Thus, the study enables decision-makers to understand the current impact of OBORI on the real market and its potential effect if more developed and economically strong countries are included.

The plate fin heat exchanger is the compact heat exchanger applied in many industries because of its high thermal performance. To enhance the heat transfer of plate fin heat exchanger in further, three new kinds of wavy plate fins, namely perforated wavy fin, staggered wavy fin and discontinuous wavy fin are proposed and investigated by CFD simulations. The effects of key design parameters, including that of waviness aspect ratios, perforation diameters, stagger ratios and breaking distance are investigated, respectively, with the Reynolds number changes from 500 to 4500. It is found that due to the swirl flow and efficient mixing of fluid, the perforation, serration and breaking techniques are beneficial for the enhancement of heat transfer compared to the traditional wavy fin. At the same time, serration is beneficial to reduce the friction factor, and the breaking technique can reduce heat transfer area as well as enhance heat transfer performance. Through the performance evaluation criteria, the staggered wavy fin has an advantage over the small waviness aspect ratio compared to the perforated wavy fin. The maximum performance evaluation criteria (PEC), as high as 1.24, can be obtained for the perforated wavy fin at the largest waviness aspect ratio.

Increasing green total factor productivity is the key to achieving green development in agriculture. This study measured the green total factor productivity of Jiangxi’s agriculture, and its regional and temporal evolution characteristics were examined. The fixed-effects model was then used to investigate the model’s fundamental components empirically. The study’s findings reveal the following: During the period under review, technical change was the primary element driving the rise in the green total factor productivity of agriculture. A rising “U”-shaped trend with notable regional variances characterizes the spatial and temporal evolution. The primary factors that affect changes in green total factor productivity in agriculture include the ease of transportation, the per capita disposable income of rural residents, the level of agricultural mechanization, the degree of urbanization, the level of financial support for agriculture, and the percentage of workers in secondary industries. As a result, it is suggested that, in order to substantially increase agricultural green total factor productivity, agricultural green technological support should be strengthened, more fully developed, and promoted in a multi-pronged approach.

Introduction. Until now, the impact of learning variables on consumers' choices concerning Chinese product brands in the international online shopping framework remains unknown. Accordingly, this study aims to examine the effect of those learning variables on global consumers' choices of Chinese product brands. Method. A total of 44,704 transactions related to the buying process have been collected from a programming language and the Octopus Software within a Chinese International Online Shopping platform. Analysis. The 44,704 transactions have been analyzed through a Decision Tree. Results. The study points out that the number of e-retailers' subscribers reinforces the international consumers' trust online. At the same time, the pricing levels and quantity of product availability are used by global online consumers to assess the originality of Chinese product brands. Conclusions. First, this study extends the existing literature on consumer learning by going beyond the learning variables considered. Second, the study boosts consumer learning literature by elucidating the most significant learning variables guiding international online consumers' choices and purchases. The application of the results will enable brands and e-retailers to understand (1) the stages of the international online consumers' choice; (2) the buying strategies of global consumers.

Until now, the literature on Chinese International Online Shopping (CIOS) (B2C export from China) mainly concentrated on the potential income that it constitutes for Chinese international trade. However, regarding International Online Consumers' (IOCs) purchase behaviors, research does not provide insight into the impact of Countries' Level of Economic Development (CLED) on the IOCs' preferences and choices about Chinese brands. Based on 9971 purchases about Chinese mobile phone brands, countries' macroeconomic data, and a multinomial logistics model (MLM), we examined IOCs' preferences and choices about Chinese brands. The result shows that the CLED influences IOCs' preferences and choices. Consequently, accounting of CLED in consumers’ preferences and choices introduces a new dimension in understanding IOCs' behaviors and attitudes towards Chinese mobile phone brands. This work contributes to Chinese brands' globalization research from the perspective of CLED. Such a model can be used to guide e-retailers and brand managers.

This paper studied the combined influences of the hot streak and swirl on the cooling performances of the NASA C3X guide vane coated with or without TBCs. The results show that: (1) Even under uniform velocity inlet conditions, the hot streak core can be stretched as it impinges the leading edge which causes higher heat load on the suction side of the forward portion. (2) The swirl significantly affects circumferential and radial migration of the hot streak core in the NGV passage. On the passage inlet plane, positive swirl leads to a hotter tip region on the suction side. In comparison, negative swirl leads to a hotter hub region on the pressure side. (3) Under the influence of swirl, migration of coolant improve the coverage of film cooling close to the midspan, while in the regions close to the hub and tip end-wall, the overall cooling performance decrease simultaneously. (4) In the regions with enough internal cooling, the cooling effectiveness increment is always larger than that in other regions. Besides, the overall cooling effectiveness increment decreases on the region covered by film cooling for the coated vane, especially in the region with negative local heat flux.

Fully mechanized mining face production involves complex geological conditions; mining pressure; gas, water, fire and other mining environments. The working face needs a shearer, hydraulic support, a scraper conveyor and other equipment for coordination. The deep integration of intelligent technology with factors such as "humans, machines, the environment, and management" in the workplace is the core content of intelligent coal mines. This paper puts forward an advanced framework for coal mining robot technology systems, including single robots, robotized equipment, robot clusters and unmanned systems. The framework clarifies the common key technologies of coal mining robot research and development and cross-integration with new technologies such as 5G, the industrial internet, big data, artificial intelligence, and digital twins to improve the autonomous and intelligent application of coal mining robots. By establishing a scientific and complete standard system for coal mining robots, we aim to achieve customized research and development and standardized production of various types of robots. A specific analysis was conducted on the research progress of common key technologies such as explosion-proof design, mechanical system innovation, power drive, intelligent sensing, positioning and navigation, and underground communication of coal mining robots. The current research and application status of various types of coal mining robots in China are summarized. A new direction for future coal mine robot research and development is proposed. Moreover, robotic mining systems should be promoted to enhance the overall intelligence level and mining efficiency of mining equipment. To develop human‒machine environment-integrated robots to improve the autonomy and collaboration level of coal mining robots. The digital twinning of the entire mine robot system should be accelerated, the normalized operation level of coal mine robots should be improved, research on coal mining robots, support robots, and transportation robots should be carried out, intelligence should be achieved in fully mechanized mining faces, and equipment support for fewer and unmanned fully mechanized mining faces should be provided. The practical process of implementing coal mining robotization has been summarized, and the technical and engineering feasibility of the coal mining machine population has been verified.

To address the limitations of the current anodes of Li+-ion batteries (LIBs), a Ge/GeO2/Carbon (Ge@GeO2-C) composite was designed by introducing a high-energy ball-milling process for advanced LIBs. Ge@GeO2-C is prepared and characterized by XPS, XRD, SEM, and TEM, which facilitate synthesis and provide controllability with respect to milling time. Interestingly, as the ball-milling time increased, the proportion of metallic Ge increased during the carbon thermal reduction reaction. The electrochemical characteristics of Ge@GeO2-C are assessed using differential capacity analysis (dQ/dV) and galvanostatic charge-discharge techniques to confirm its viability as an anode material in LIBs. The results demonstrated decent initial and secondary capacities of approximately 1800 mAh g-1 (for the first cycle) and 838 mAh g-1 (for the second cycle) at a rate of C/60 by the reaction between Ge and the Li-Ge complex. Furthermore, postmortem characterization was performed to gain an understanding of the material, suggesting future prospects for advanced LIBs.

We investigated the magnetic properties of antiferromagnetic (AFM) topological insulator MnBi$_2$Te$_4$ with partial substitution of Mn atoms by non-magnetic elements (A$_x^{IV}$ = Ge, Pb, Sn). Samples with various element concentrations (10-80%) were studied using SQUID magnetometry. The results demonstrate that, for all substitutes the type of magnetic ordering remains AFM, while the Nèel temperature (T$_N$) and spin-flop transition field (H$_{SF}$) decrease with increasing A$_x^{IV}$ = Ge, Pb, Sn concentration. The rate of decrease varies among the elements, being highest for Pb, followed by Sn and Ge. This behavior is attributed to combined effects of magnetic dilution and lattice parameter increase on magnetic properties, most prominent in (Mn$_{1−x}$Pb$_x$)Bi$_2$Te$_4$. Besides this, the linear approximation of experimental data of T$_N$ and H$_{SF}$ suggests higher magnetic parameters for pure MnBi$_2$Te$_4$ than observed experimentally, indicating the possibility of their non-monotonic variation at low concentrations and the potential for enhancing magnetic properties through doping MnBi$_2$Te$_4$ with small amounts of nonmagnetic impurities. Notably, the (Mn$_{1−x}$Pb$_x$)Bi$_2$Te$_4$ sample with 10% Pb substitution indeed exhibits increased magnetic parameters, which is also validated by local analyses using ARPES. Our findings shed light on tailoring the magnetic behavior of MnBi$_2$Te$_4$-based materials, offering insights for potential applications in device technologies.

The soft robot has many degrees of freedom, strong environmental adaptability and good human-computer interaction ability. As the end-effector of the soft robot, the soft gripper can grasp objects of different shapes without destructivity. Based on the theoretical analysis of the soft robot, the kinematics model of the flexible gripper and the theoretical model of the bending deformation of the air cavity were established. Accordingly, the relationship between the bending angle of the soft gripper and the air pressure was determined. Through the application of finite element software, the bending degree of pneumatic network multi-cavity soft gripper was simulated by finite element software, and the influence of structural parameters of soft actuator on bending deformation was determined. In addition, with the 3D technology conducting the printing of soft gripper fixtures and molds, the injection molding the actuator and the human-computer interaction interface controlling the movement of the gripper, the adaptability of the soft gripper in grasping object was verified. The result shows that the software gripper possesses good flexibility and can better grasp objects of different shapes.

Purpose: School-age children with autism spectrum conditions (ASC) often experience difficulties in speech-in-noise (SiN) perception, leading to increased listening effort that impacts their well-being and academic performance. This study aimed to investigate the SiN processing challenges faced by Mandarin-speaking children with ASC and its impact on their listening effort. Methods: Participants completed sentence recognition tests in both quiet and noisy conditions, with a steady-state noise masker presented at 0 dB signal-to-noise ratio in the noisy condition. We compared recognition accuracy and task-evoked pupil responses from 23 Mandarin-speaking children with ASC to 19 age-matched neurotypical (NT) counterparts to gauge their behavioral performance and listening effort during these auditory tasks. Results: The ASC group demonstrated notably decreased accuracy in noise compared to their NT peers, suggesting poorer SiN perception. Pupillometric data further revealed significantly larger peak dilations in the ASC group than in the NT group under comparable conditions. Importantly, the ASC group's peak dilation in quiet mirrored the NT group's in noise. However, the ASC group exhibited shorter peak latencies and reduced mean dilations than the NT group in similar conditions. Such patterns indicate the ASC group might initially experience a heightened cognitive load but utilize fewer cognitive resources as the task continued, indicating an atypical allocation of cognitive resources and a potential tendency towards relatively superficial and automated auditory processing. Conclusion: Our findings highlight the unique SiN processing challenges children with ASC face, underscoring the importance of a nuanced, individual-centric approach for interventions and support.

The rapid advancements in gene therapy have opened up new possibilities for the treatment of genetic disorders, including Duchenne muscular dystrophy, Thalassemia, cystic fibrosis, Hemophilia, and Familial hypercholesterolemia. The utilization of the clustered regularly interspaced short palindromic repeats (CRISPR) - CRISPR-associated protein (Cas) system has revolutionized the field of gene therapy by enabling precise targeting of genes. In recent years, CRISPR/Cas9 has demonstrated remarkable efficacy in treating cancer and genetic diseases. However, the susceptibility of nucleic acid drugs to degradation by nucleic acid endonucleases, necessitates the development of functional vectors capable of protecting the nucleic acids from enzymatic degradation, while ensuring safety and effectiveness. This review aims to explore the biomedical potential of non-viral vector-explore CRISPR/Cas9 systems for the treatment of genetic diseases. Furthermore, it provides a comprehensive overview of recent research advances in viral and non-viral vector-based gene therapy for genetic disorders, including insights from preclinical and clinical studies. Additionally, the review analyzes the current limitations of these delivery systems and proposes avenues for the development of novel nano-delivery platforms.

Sympatric distribution and temporal overlap of cryptic zooplankton species pose a challenge to the framework of the niche differentiation theory and the mechanisms allowing competitor coexistence. We applied the methods of phylogenetic analysis, DNA taxonomy and statistical analysis to study the temporal distribution patterns of cryptic B. calyciflorus species, an excellent model, in three lakes, and to explore the putative mechanisms for their seasonal succession and temporal overlap. The results showed that in the warm-temperate Lake Yunlong, B. fernandoi and B. calyciflorus s.s. underwent a seasonal succession, which was largely attributed to their differential adaptation to water temperature. In the subtropical Lake Jinghu, B. fernandoi, B. calyciflorus s.s. and B. dorcas exhibited both seasonal succession and temporal overlap. Seasonal successions were largely attributed to their differential adaptation to temperature, and temporal overlap resulted from their differential responses to algal food concentration. In the tropical Lake Jinniu, B. calyciflorus s.s. persisted throughout the year, and overlapped with B. dorcas for 5 months. Temporal overlap resulted from their differential responses to copepod predation. These results indicated that the temporal distribution pattern of cryptic B. calyciforus species and the mechanism allowing competitor coexistence vary with different climate zones.

This paper shares our work in developing and implementing an immersive gamification training platform for students who undergo manufacturing shopfloor training at the School of Engineering, Nanyang Polytechnic, Singapore. In this gamification training platform, we developed a virtual manufacturing shopfloor that is identical to the actual shopfloor located in the school. Students have the freedom to learn the manufacturing shopfloor operations and safety acts through the various game scenarios and training tasks which include workshop safety, CNC machine introduction, CNC machining dynamics, MES, etc. In addition, the assessment feature with immediate feedback were embedded within the gamification platform, which aim to help students to assess their level of understanding and help teachers to monitor the learning progress of their students. To investigate the impact of this gamification training platform on students’ learning outcome and motivation in manufacturing shopfloor technologies and safety acts, a pilot study was conducted in AY2018 semester 2 for a total 134 students from 4 classes of digital & precision engineering diploma. It is found that gamification can be integrated effectively into manufacturing education to motivate students and enhance their learning effectiveness. Based on the collected data from the technical quizzes and satisfactory survey, the results showed that the integration of gamification into the classroom learning not only added a stimulating and captivating game-like layer to the learning experience of the students, but also provided a safe environment for students to learn without fear of making errors. Challenges faced in implementing this gamification training platform will also be discussed in this paper.

Facilitative glucose transporters (GLUT) are transmembrane transporter of proteins involved in glucose transport across the plasma membrane. To date, there is no information about glucose transporter 2 (GLUT2) in blunt snout bream (Megalobram aamblycephala). In this study, GLUT2 were cloned and characterized from blunt snout bream, and its-expression in response to diets with different carbohydrate levels (17.1%; 21.8%; 26.4%; 32.0%; 36.3% and 41.9% of dry matter). In this study, the full-length cDNA of GLUT2 was 2577 bp, including a 5’-untranslated region (UTR) of 73 bp, a 3’-UTR of 992 bp, and an open reading frame of 1512 bp, encoding a polypeptide of 503 amino acids with predicted molecular weight of 55.046 kDa and theoretical isoelectric point of 7.52. GLUT2 has twelve across the membrane area locating at 7-29; 71-93; 106-123; 133-155; 168-190; 195-217; 282-301; 316-338; 345-367; 377-399; 412-434; 438-460 aimo acids respectively. Conservative structure domains located at 12-477 aimo acids belonging to sugar porter family major facilitator superfamily (MFS) transporter. The blunt snout bream GLUT2 showed high identity to their orthologs in other fish species and mammals. Quantitative real-time (qRT)-PCR assays revealed that GLUT2 expression was high in the liver, intestine and kidney; highest in the liver. Compared with the control group (17.1%), high dietary carbohydrate levels (32.0%; 36.3% and 41.9%) resulted in high plasma glucose at 3h after feeding, but high plasma glucose were back to basal at 24h after feeding. Furthermore, high dietary carbohydrate levels significantly improved the glycolysis and inhibitied gluconeogenesis by augmentation of GK and PK expression, inhibition of PEPCK and G6P mRNA levels (P<0.05). However, GLUT2; GK; PK; PEPCK and G6P mRNA levels were back to basal.

With the rapid development of intelligent logistics and network environment, it has become an urgent problem to efficiently and accurately handle and analyse the huge amount of uncertain decision information. Traditional decision making methods often fail to make the best use of complex and incomplete information, especially in the field of cyber defence. To address these problems, this paper introduces a new mathematical tool, discrete multidimensional Z-numbers (MZs), for expressing and dealing with uncertainty and reliability in network defence decisions. In this paper, we first introduce the synthesis method of discrete multidimensional Z-numbers, which allows us to consider the uncertainty and reliability of multi-source information in network defence strategy. Then, the hidden probability of MZs is calculated by using the hidden probability model, and the multidimensional Z+−number is proposed, which improves the expressiveness of the model in dealing with information uncertainty. Based on MZs, we define a variety of utility functions and build a multi-attribute group decision framework for network defence around these functions. The MZs provides a novel perspective for analysing and designing response strategies, especially against highly adaptive and covert attacks. The method in this paper is verified by a case of network security assessment of an intelligent logistics company. The results show that this method can significantly improve the accuracy and efficiency of decision making, demonstrating its unique advantages and wide application potential in network defence. This integrated discrete multidimensional Z-number group decision method is not only suitable for intelligent logistics decision making, but also provides an efficient decision support tool for network defence, which helps to improve the intelligence and adaptability of network security defence.

Marine soft corals are prolific sources of various natural products that have served as a wealthy reservoir of diverse chemical scaffolds for new drug leads. The genus Litophyton contains almost 100 species but only a small part of them had been classified and chemically investigated, which calls for more attentions from the global researchers. In the current work, 109 secondary metabolites have been discussed based on published data from 1975 to July, 2023, covering a period of near five decades. The studied species of the genus Litophyton inhabited various tropical and temperate regions and afforded a variety of biologically active natural products such as terpenes, steroids, alkaloids, and lipids. A wide spectrum of pharmacological effects of these compounds had been evaluated, including cytotoxic, anti-HIV, antibacterial, antifungal, anti-malarial, antifeedant, molluscicidal, PTP1B inhibitory, and insect growth inhibitory activities. This review aims to provide an up-to-date literature survey and comprehensive insight into chemical structures, taxonomical distributions, and biological activities of the reported metabolites from the title genus whenever available.

2-Pyridone ligand-facilitated palladium-catalyzed direct C–H bond functionalization via the transient directing group strategy has become an attractive topic. Here we report a Pd-catalyzed direct β-C(sp3) –H arylation reaction of tertiary aliphatic aldehydes by using an α-amino acid as a transient directing group in combination with a 2-pyridone ligand.

One-step oxidative esterification of 2, 5-furandiformaldehyde (DFF) derived from biomass to prepare Dimethyl Furan-2, 5-dicarboxylate (FDMC) not only simplifies the catalytic process and increases purity of product, but also avoids the polymerization of 5-hydroxymethylfurfural (HMF) at high temperature condition. Gold supported on a series of acidic oxide, alkaline oxide and hydrotalcite were prepared by colloidal deposition to explore the effect of support on the catalytic activities. The Au/Mg3Al-HT catalyst exhibited the best catalytic activity in all catalysts, 97.8% selectivity of FDMC at 99.9% conversion of DFF. And this catalyst is suitable to oxidative esterification of benzaldehyde and furfural as well. X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and CO2 temperature programmed desorption (CO2-TPD) were performed to characterize the catalysts. The results indicated that the medium and strong basic sites in the heterogeneous catalysts benefited for the absorption of intermediate spices, further facilitated the oxidative esterification of aldehyde groups. While, neutral or acidic support tended to aldol condensation reaction. It was worth noting that basicity on the support surface reduce electronic state of the Au nanoparticle (Auδ-), thus enhance the catalytic selectivity of oxidative esterification. This finding demonstrated the support plays crucial role in oxidative esterification.

Pedestrian detection is the core of driver assistance system, which collects the road conditions through the radars or cameras on the vehicle, judges whether there is a pedestrian in front of the vehicle, supports decisions such as raising the alarm, automatically slowing down or emergency stopping to keep pedestrians safe, and improves the security when the vehicle is moving. Suffered from weather, lighting, clothing, large pose variations and occlusion, the current pedestrian detection still has a certain distance from the practical applications. In recent years, deep networks have shown excellent performance for image detection, recognition and classification. Some researchers employed deep network for pedestrian detection and achieve great progress, but deep networks need huge computational resources which make it difficult to put into practical applications. In real scenarios of autonomous vehicle, the computation ability is limited. Thus, the shallow networks such as UDN (Unified Deep Networks) is a better choice since it performs well on consuming less computation resources. Base on UDN, this paper proposes a new deep network model named as two-stream UDN, which augments another branch for solving traditional UDN’s indistinction of the difference between trees / telegraph poles and pedestrians. The new branch accepts the upper third part of the pedestrian image as input, and the partial image has less deformation, stable features and more distinguished characters from other objects. For the proposed two-stream UDN, multi-input features including HOG feature, Sobel feature, color feature and foreground regions extracted by GrabCut segmentation algorithms are fed. Compared with the original input of UDN, the multi-input features are more conducive for pedestrian detection since the fused HOG features and significant objects are more significant for pedestrian detection. Two-stream UDN is trained through two steps: First, the two sub-networks are trained until converge; then we fuse results of the two subnets as the final result and feed it back to the two subnets to fine tune network parameters synchronously. To improve the performance, Softplus is adopted as activation function to obtain faster training speed, and positive samples are mirrored and rotated with small angle to make positive and negative samples more balanced.

Full-scale/model test comparison studies to validate the traditional ABL wind tunnel simulation technique are reviewed. According to the literature review, notable discrepancies between full-scale measurement results and model test results were observed by most performed comparison studies, but the causes of the observed discrepancies were not revealed in a scientific way by those studies. In this regard, a new research scheme for future full-scale/model test comparison studies is proposed in this article, which utilizes the multiple-fan actively controlled wind tunnel simulation technique. With the new research scheme, future full-scale/model test comparison studies are expected to reasonably disclose the main problems with the traditional ABL wind tunnel simulation technique, and the technique can be improved correspondingly.

Food waste is a common issue arising from grinding of food by experimental animals, leading to excessive food scraps falling into cages. In the wild, animals grind food by gnawing vegetation and seeds, potentially damaging the ecological environment. However, limited ecology studies have focused on food grinding behavior since the last century, with even fewer on rodent food grinding, particularly recently. Although food grinding function is partially understood, biological purposes remain under-investigated and driving factors unclear. This review aims to explain potential causes of animal food grinding, identify influencing factors, and discuss contexts and limitations. Specifically, we emphasize recent progress on gut microbiota significance for food grinding. Moreover, we show abnormal food grinding is determined by degree of excess normal behavior, emphasizing food grinding is not meaningless. Findings from this review promote comprehensive research on the myriad factors, multifaceted roles, and intricate evolution underlying food grinding behavior, benefiting laboratory animal husbandry and ecological environment protection, and identifying potential physiological benefits yet undiscovered.

The impact of sex in the development of long-term toxicities affecting the quality of life of cancer survivors has not been investigated experimentally. To address this issue, a series of neurologic and cardiologic endpoints were used to investigate sex-based differences triggered by paclitaxel treatment and radiotherapy exposure. Male and female WT mice were treated with Paclitaxel (150 and 300 mg/kg) administered weekly over 6 weeks or exposed to 19 Gy cardiac irradiation. Cohorts were analyzed for behavioral and neurobiologic endpoints to assess systemic toxicity of paclitaxel or cardiovascular endpoints to assess radiotherapy toxicity. Interestingly, female WT mice exhibited enhanced tolerance compared to male WT mice regardless of the treatment regimen. To provide insight into the possible sex-specific protective mechanisms, rhoB deficient animals and elderly mice (22 months) were used with a focus on the possible contribution of sex hormones including estrogen. RhoB deficiency and advanced age had no impact on neurocognitive impairment induced by Paclitaxel but reversed the cardioprotection was observed in females after radiotherapy. Conversely, rhoB deficiency protected males from radiation toxicity. In sum, rhoB was identified as a molecular determinant driving estrogen dependent cardioprotection in female mice, whereas neuroprotection was not sex-hormone dependent. To our knowledge, this study revealed for the first time sex- and organ-specific responses to paclitaxel and radiotherapy.

To accurately predict the matching relationships between the various components and the engine performance in the whole aero-engine environment, this study introduces a two-dimensional throughflow simulation method for the whole aero-engine. This method is based on individual throughflow solvers for the turbo-machinery and the combustor. It establishes a throughflow simulation model for the whole engine by integrating with the compressor-turbine co-operating equations and boundary conditions. The turbo-machinery throughflow solver employs a circumferentially averaged form of the time-dependent Navier-Stokes equations (N-S) as the governing equation. The combustor solver uses the Reynolds Average Navier-Stokes (RANS) method to solve flow and chemical reaction processes by constructing turbulence, combustion, and radiation models. The accuracy of the component solver is validated using Pratt &amp; Whitney’s three-stage axial compressor (P&amp;W3S1) and General Electric’s high-pressure turbine (GE-EEE HPT), and the predicted results are consistent with the experimental data. Finally, the developed throughflow method is applied to simulate the throttling characteristics of the WZ-X turboshaft engine. The results predicted by the throughflow program are consistent with the GasTurb calculations, including the trends of shaft power delivered, specific fuel consumption (SFC), inlet airflow, and total pressure ratio of the compressor. The developed method to perform throughflow simulation of the whole aero-engine eliminates the dependence on a general component map. It can quickly obtain the meridian flow field parameters and overall engine characteristics, which is expected to guide the design and modification of the engine in the future.

To realize structural vibration control,a two parameters H2 optimization design was proposed to optimize the tuning ratio and damping ratio for electromagnetic tuned mass damper (EMTMD). The control effect of this two parameters optimization design is better than that of classical tuned mass damper (TMD).For this two parameters optimization,the most important thing is that the inductance of the coil can be set very small and the external load resistance can be positive ,which can avoid the use of complex negative impedance circuit. If Ref.[6] were designed according to the H2 optimization of two parameters, the EMTMD can be used for multi-modal vibration control of structures without connecting negative inductance and negative resistance spontaneously.

In the current pandemic of COVID-19, students and faculty are subject to social distancing and online learning. How to test students in this unprecedented environment is a new educational challenge with immediate and global impacts. The main contribution of this paper is to establish the feasibility that by a clever design we can control the average gain (which is referred to as the g-factor) from cheating behaviors to a degree as small as pre-specified so that accurate and reliable online exams can be administered. It is underlined that even after the pandemic the methods and systems in the spirit of our proposal are still valuable for cost-effective exams to promote open courses and internet-based education.

In this work, the optoelectronic characteristics of kesterites of the Cu₂NiXS₄ system (X = Si, Ge, Sn) were studied. The electronic properties of the Cu₂NiXS₄ (X = Si, Ge, Sn) system were studied using first-principles calculations within the framework of density functional theory. For calculations, ab initio codes VASP and Wien2k were used. The high-precision modified Beke-Jones (mBJ) functional and the hybrid HSE06 functional were used to estimate the bandgap, electronic and optical properties. Calculations have shown that when replacing Si with Ge and Sn, the band gap decreases from 2.58 eV to 1.33 eV. Replacing Si with Ge and Sn reduces the overall density of electronic states. In addition, new deep (shallow) states are formed in the band gap of these crystals, which is confirmed by the behavior of their optical properties. The obtained band gap values are compared with existing experimental measurements, demonstrating good agreement between HSE06 calculations and experimental data. The nature of changes in the dielectric constant, absorption capacity and optical conductivity of these systems depending on the photon energy has also been studied. The statistical dielectric constant and refractive index of these materials were found. The results will help increase the amount of information about the properties of the materials under study and will allow the use of these compounds in a wider range of optoelectronic devices, in particular, in solar cells and other devices that use solar radiation to generate electric current.

Intelligent Tutoring Systems (ITS) are increasingly popular for online learning. These systems use adaptive algorithms to recommend relevant content based on students' profiles. However, instructors need to periodically assess students' performance to ensure learning outcomes and adjust strategies accordingly. Our objective is to predict students' progress in advance, enabling teachers to make quicker decisions and facilitating the iterative process of adaptive algorithms. For this study, we collected a dataset from ALIN, an online learning platform, consisting of over 5,000 students' learning records and test results. Using this dataset, we conducted experiments employing various machine learning algorithms. The results indicate that learning behavior contributes to improving forecast performance, while students' progress strongly correlates with their previous test results. Additionally, we discovered that students' progress can be indirectly predicted by forecasting their scores. Furthermore, by breaking down overall scores into several distinct components and predicting individual scores for each component, the accuracy of the forecasts can be improved.

Data mining techniques have garnered significant attention within the realm of education. However, the procurement of ample student data poses a formidable challenge. In response to this challenge, we present a student dataset characterized by its size and distinctive attributes. This dataset encompasses various task-related topics interconnected through a learning pathway, thereby enabling researchers to delve into the data from novel perspectives. Moreover, it encompasses extensive longitudinal student behavioral data, a rarity that adds substantial value. Spanning the years from 2010 to 2021, our dataset comprises a cohort of 7,933 students, 64,344 test scores, and 183,390 behavior records, solidifying its status as a valuable resource for educational research. In our experiments, we achieved successful predictions of students' test outcomes based on behavioral learning data. The strengths of our dataset render it apt for analyzing the nexus between student conduct and academic performance, crafting personalized learning recommendations, and pursuing various other research pursuits.

Constructed wetlands (CWs) is a kind of green environmental protection technology, which is widely used in sewage treatment. The traditional CWs is faced with the problem of low treatment effect of high concentration sewage. In recent years, biochar, as a new type of adsorption material, has been used in CWs because of its advantages of large specific surface area, strong adsorption capacity and wide material sources. This paper systematically summarized the characteristics of biochar and the preparation of biochar by studying the changes of microorganisms added to CWs, and compared the effects of different treatment methods coupled with biochar on the treatment performance of CWs, the effects of biochar coupled with CWs on enzyme activity, functional genes, metabolites and microbial communities were investigated. This review summarizes how different preparation methods affect the properties of biochar and how these biochar cause changes in the microorganisms added to CWs.

After long years of development, the technology of analyzing the working condition of power units based on vibration signals has had relatively stable applications, but the accuracy and the degree of automation and intelligence for fault diagnosis are still inadequate due to the limitations of the current development of key technologies. With the development of big data and artificial intelligence technology, the involvement of new technologies will be an important boost to the development of this field. To support the subsequent research, bibliometrics is used as a tool to sort out the development of the technology in this field at the macro level; at the micro level, the classical and key literature is studied to grasp the development status at the technical level and prepare for the selection of entry points to continue in-depth innovation afterwards.

Respiratory Syncytial Virus (RSV) causes severe inflammation and airway pathology in children and the elderly by infecting the epithelial cells of the upper and lower respiratory tract. RSV replication is sensed by intracellular pattern recognition receptors upstream of the IRF and NF-B transcription factors. These proteins coordinate an innate inflammatory response via Bromodomain containing protein 4 (BRD4), a protein that functions as a scaffold for unknown transcriptional regulators. To better understand the pleiotropic regulatory function of BRD4, we examine the BRD4 interactome and identify how RSV infection dynamically alters it. To accomplish these goals, we leverage native immunoprecipitation and Parallel Accumulation – Serial Fragmentation (PASEF) mass spectrometry to examine BRD4 complexes isolated from human alveolar epithelial cells in the absence or presence of RSV infection. In addition, we explore the role of BRD4’s acetyl-lysine binding bromodomains in mediating these interactions by using a highly selective competitive bromodomain inhibitor. We identify 101 proteins that are significantly enriched in the BRD4 complex and are responsive to both RSV-infection and BRD4 inhibition. These proteins are highly enriched in transcription factors and transcriptional coactivators. Among them, we identify members of the AP1 transcription factor complex, a complex important in innate signaling and cell stress responses. We independently confirm the BRD4/AP1 interaction in primary human small airway epithelial cells. We conclude that BRD4 recruits multiple transcription factors during RSV infection in a manner dependent on acetyl-lysine binding domain interactions. This data suggests that BRD4 recruits transcription factors to target its RNA processing complex to regulate gene expression in innate immunity and inflammation.