System-of-systems (SoS) evolution is a complex and unpredictable process. Although various principles to facilitate collaborative SoS evolution have been proposed, there is a lack of experimental data validating their effectiveness. To address these issues, we present an Agent-Based Model (ABM) for SoS evolution in the Internet of Vehicles (IoV) , serving as a quantitative analysis tool for SoS research. By integrating multiple complex and rational behaviors of individuals, we aim to simulate real-world scenarios as accurately as possible. To simulate the SoS evolution process, our model employs multiple agents with autonomous interactions and incorporates external environmental variables. Furthermore, we propose three evaluation metrics: evolutionary time, degree of variation, and evolutionary cost, to assess the performance of SoS evolution. Our study demonstrates that enhanced information transparency significantly improves the evolutionary performance of distributed SoS. Conversely, the adoption of uniform standards only brings limited performance enhancement to distributed SoSs. Although our proposed model has limitations, it stands out from other approaches that utilize Agent-Based Modeling to analyze SoS theories. Our model focuses on realistic problem contexts and simulates realistic interaction behaviors. This study enhances the comprehension of SoS evolution processes and provides valuable insights for the formulation of effective evolutionary strategies.

Evaluating soil quality across various altitudinal gradients, both with and without vegetative cover, is crucial for the proper functioning of soil and optimal crop growth, thereby contributing to the sustainability of agroecosystems. Although the altitudinal gradient significantly influences soil quality, the ability to predict this quality, expressed through an index, in soils with and without vegetative cover, is still insufficiently explored. This study aimed to assess soil quality in the Jun Jun micro-watershed, located in the Tungurahua region, Ecuador. To achieve this objective, three categories of altitudinal gradients were selected: less than 2800 meters above sea level (masl), between 2800 and 2900 masl, and greater than 2900 masl. A total of 24 soil samples were collected in the mentioned gradients, considering both areas with and without vegetative cover. The indicators used included chemical and biological parameters such as soil organic carbon (OC), earthworm density (WD), earthworm biomass (WB), organic matter (OM), pH, total nitrogen (TN), and organic carbon (OC). The results revealed that in areas with altitudinal gradients below 2800 masl, soil quality index values were higher compared to other altitudes. In vegetated areas, a decrease in index values was observed as the altitudinal gradient increased, indicating a deterioration in soil quality with altitude. These findings are significant in providing a quantitative assessment of the effects of altitudinal gradient and vegetative cover influence on soil quality.

Previous research has shown that the effectiveness of selecting filter set from a large set of commercial broadband filters by vector analyzing method based on maximum linear independence (MLI). However, the traditional MLI is suboptimal due to predefining the first filter of the selected filter set being the maximum ℓ2 norm among all those of the filters. An exhaustive imaging simulation is conducted to investigate the features of the most competent filter set. In the simulation, every filter in a subset of all the filters is selected serving as the first filter in turn. From the results of the simulation, we found there are remarkable characteristics for the most competent filter set. Besides smaller condition number, the geometric features of the best-performed filter set comprise the distinct peak of the transmittance of the first filter, the generally uniform distributing of the peaks of the transmittance curve of the filters, the substantial overlapping of the transmittance curves with those of the adjacent filer sets. Therefore, the best-performed filter sets can be decided intuitively by simple vector analyzing and just a few experimental verifications. This work would be useful for optimizing spectral sensitivity of broadband multispectral imaging sensors or SFA sensors.

This study investigates the transformative impact of ChatGPT, a cutting-edge AI language model developed by OpenAI, on the financial sector. We explore ChatGPT's applications in financial analysis, focusing on its ability to perform tasks traditionally handled by human analysts. By creating a set of multi-step and advanced reasoning financial tasks, and establishing several task-specific evaluation metrics, our experimental results demonstrate that ChatGPT-4o can effectively perform both basic and some complex financial analysis tasks comparable to those executed by humans. However, our empirical evaluation reveals limitations in its performance on complex tasks that require comprehensive understanding and critical thinking. The study highlights the necessity for meticulous task formulation and robust evaluation to achieve consistent functionality. While ChatGPT enhances efficiency in financial analysis, its integration with human expertise remains crucial for effective decision-making. This study contributes to the understanding of AI's role in finance and provides insights into its potential and constraints, guiding future integration of AI technologies in financial practices.

This paper first discusses a fractional-order Liu system of order as low as 2.7 and shows its chaotic characteristics by carrying out numerical simulations such as Lyapunov exponents, bifurcation diagrams and phase portraits. Then, by using the topological horseshoe theory and computer-assisted proof, the existence of chaos in the system is verified theoretically. Finally, the fractional-order system is implemented on a Field Programmable Gate Array (FPGA) and the results obtained show that the fractional-order Liu system is indeed chaotic.

Flexible implementations of Monte Carlo Tree Search (MCTS), combined with domain specific knowledge and hybridization with other search algorithms, can be a very powerful for the solution of problems in complex planning. We introduce mctreesearch4j, a standard MCTS implementation written as a standard JVM library following key design principles of object oriented programming. We define key class abstractions allowing the MCTS library to flexibly adapt to any well defined Markov Decision Process or turn-based adversarial game. Furthermore, our library is designed to be modular and extensible, utilizing class inheritance and generic typing to standardize custom algorithm definitions. We demon- strate that the design of the MCTS implementation provides ease of adaptation for unique heuristics and customization across varying Markov Decision Process (MDP) domains. In addition, the implementation is reasonably performant and accurate for standard MDP’s. In addition, via the implementation of mctreesearch4j, the nuances of different types of MCTS algorithms are discussed.

We investigated the response of leaf photosynthetic capacity to climate warming and its variation among provenances of Larix gmelinii (Dahurian larch). Seedlings of 11 L. gmelinii provenances were transplanted into two common gardens with different climate conditions (control and warming climate). We measured the leaf photosynthetic capacity and explored its influencing factors. The warming treatment significantly increased the maximum net photosynthetic rate (Pmax-a), photosynthetic nitrogen use efficiency (PNUE), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), triose phosphate utilization rate (TPU), mesophyll conductance (gm), leaf nitrogen content (Narea), and chlorophyll content (Chlm). The Pmax-a was significantly positively associated with Vcmax, Jmax, TPU, gm, and Narea, and the slope of the correlations between Pmax-a and Vcmax, Jmax, and TPU was steeper in the warming treatment. The responses of Pmax-a, PNUE, Vcmax, Jmax, TPU, Narea, and Chlm to warming differed among provenances. The effects of warming on Pmax-a, Vcmax, Jmax, and TPU increased and then decreased as the aridity index of the original site increased. Overall, the warming treatment improved the photosynthetic capacity of L. gmelinii, but the extent of the improvement varied among provenances. These findings provide insights into the mechanisms underlying the responses of L. gmelinii to climate warming.

Cold stress is a major environmental factor affecting the growth, development, and productivity of various crop species. With the current trajectory of global climate change, low temperatures are becoming more frequent and can significantly decrease crop yield. Wheat (Triticum aestivum L.) is the first crop to be domesticated and is the most popular cereal crop in the world. Due to a lack of systematic research on cold response pathways and gene regulatory networks, the underlying molecular mechanisms of cold signal transduction in wheat are poorly understood. This study reviews recent progress in wheat, including the ICE-CBF-COR signaling pathway in cold stress and the effects of cold stress on hormonal pathways, reactive oxygen species (ROS), and epigenetic regulation. This review also highlights outstanding issues that are crucial for understanding the interactions between wheat and low-temperature conditions.

Due to the uniqueness of the underwater environment, traditional data aggregation schemes face many challenges. Most existing data aggregation solutions do not fully consider node trustworthiness, which may result in the inclusion of falsified data sent by malicious nodes during the aggregation process, thereby affecting the accuracy of the aggregated results. Additionally, because of the dynamically changing nature of the underwater environment, current solutions often lack sufficient flexibility to handle situations such as node movement and network topology changes, significantly impacting the stability and reliability of data transmission. To address the aforementioned issues, this paper proposes a secure data aggregation algorithm based on a trust mechanism. By dynamically adjusting the number and size of node slices based on node trust values and transmission distances, the proposed algorithm effectively reduces network communication overhead and improves the accuracy of data aggregation. Due to the variability in the number of node slices, even if attackers intercept some slices, it is difficult for them to reconstruct the complete data, thereby ensuring data security.

A multiscale model that enables quantitative understanding and prediction of the size effect on scattering properties of micro- and nanostructures is crucial for the design of LED surface textures optimized for high light extraction efficiency (LEE). In this paper, a hybrid process for combining full-wave finite-difference time-domain simulation and a ray-tracing technique based on a bidirectional scattering distribution function model is proposed. We apply this method to study the influence of different pattern sizes of a patterned sapphire substrate on GaN-based LED light extraction from the microscale to the nanoscale. The results show that near-wavelength–scaled patterns with strong diffraction are not expected to enhance LEE. By contrast, microscaled patterns with optical diffusion behavior have the highest LEE at a specific aspect ratio, and subwavelength-scaled patterns that have antireflection properties show marked enhancement of LEE for a wide range of aspect ratios.

Abstract: The population issue has been increasingly urgent in China in recent years. Fertility desire is an essential component of fertility research. Studies on fertility desire mainly contain two aspects: socio-economic structure and individual family[1]. The psychological structure of individuals in individual families is the primary factor of fertility desire. Based on the parasocial relationship theory, this study analyzed the changes in real behavioral intention achieved by players through the identification and attachment to avatars while constructing parasocial relationships[2]. The results indicate that character attachment can significantly enhance the variables of game concentration and player self-identity, actively mediates parasocial emotions and parasocial cognition, and ultimately increases fertility desire. As a theoretical contribution, this study provides a comprehensive interpretation of the psychology of Chinese players in a Simulation Game and explores the theoretical connections among role attachment, role identity, and parasocial relationships in virtual game players.

Surface water plays a crucial role in climate change, human production, and life, making accurate monitoring and observation of surface water particularly important. However, due to the significant diversity and complexity of water distribution in surface space, accurate mapping of surface water faces considerable challenges. When extracting water bodies from medium-resolution satellite remote sensing images, CNN methods may suffer from limitations in receptive fields and insufficient context modeling capabilities, leading to the loss of water body boundary details and poor fusion of multiscale features. Currently, there is relatively little research on this issue; therefore, it is necessary to explore new combinations of deep learning networks to address these challenges. The purpose of this study is to address the above issues. We propose a new combination of deep learning networks that fully utilize multiscale information to enhance water features. Specifically, we first combine deformable convolutions with the Swin Transformer to increase effective receptive fields while better integrating global semantic information. This combination can capture features of water bodies at different scales, improve the accuracy and integrity of water extraction, and provide reliable technical support for detailed water body extraction. We tested the newly constructed model using Sentinel-2 satellite images. Our model achieved results of over 90%, with an average accuracy of 97.89%, average precision of 94.98%, average recall of 90.05%, and an average F1 score of 92.33%. In addition, our model achieved an accuracy of 98.03% in mountainous areas. Our experiments and results validate the potential of combining the Swin Transformer and deformable convolutions in detailed water body extraction.

Objective: To explore the efficacy and safety of breathing exercises for pain management in cancer survivors. Design: A systematic review. Data sources: Thirteen databases, including PubMed, EMBase, CENTRAL, Medline, CINAHL, JBI, Science Direct, Scopus, SocINDEX, Web of Science, PsycINFO, CNKI, and Wan Fang, were searched from inception to May 24, 2021. Review/analysis methods: Studies that focused on the efficacy of breathing exercises for pain management in cancer survivors were included. Cochrane tools were used for the quality appraisal of the included studies. Due to the heterogeneity of the studies, descriptive data analysis was used to summarize the results. Results: A total of 10 studies were included in this systematic review. Slow pursed lip breathing showed benefits for post-surgical pain. Contradictory findings were identified in the Enhanced Recovery After Surgery breathing exercise for post-surgical pain. Slow deep breathing and Hey-Hu regular breathing techniques were effective for pain management in pediatric cancer patients. The Active Cycle of Breathing Technique and five-minute mindful breathing did not have any statistically significant effects on pain relief. Quality of life was measured in three studies, with some improvement. Only one study addressed adverse events and reported that no adverse events associated with the breathing exercises occurred during the study. Conclusion: This review found some evidence of positive effects of breathing exercises for pain relief in cancer survivors. However, the unsatisfactory methodological quality of the studies prevents its generalizability. More large-scale studies are needed to assess the efficacy and safety of breathing exercises for pain relief in cancer survivors.

Background: A growing number of clinical practice guidelines (CPGs) with regards to non-pharmacological interventions for breast cancer survivors are available. However, given the limitations in guideline development methodologies and inconsistency of recommendations, it remains uncertain how best to design and implement such non-pharmacological strategies to tailor interventions for breast cancer survivors with varied health conditions, healthcare needs, and preferences. Aim: To critically appraise and summarise available non-pharmacological interventions for symptom management and health promotion that can be self-managed by breast cancer survivors based on the recommendations of the CPGs. Methods: Clinical practice guidelines which were published between January 2016 and September 2021 and described non-pharmacological interventions for breast cancer survivors were systematically searched in six electronic databases, nine relevant guideline databases, and five cancer care society websites. The quality of the included CPGs was assessed by four evaluators using the Appraisal of Guidelines for REsearch and Evaluation, second edition tool. Content analysis was conducted to synthesise the characteristics of the non-pharmacological interventions that were recommended by the included CPGs, such as the intervention’s form, duration and frequency, level of evidence, grade of recommendation, and source of evidence. Results: Fourteen CPGs were identified and analysed. Of the 14 CPGs appraised, only five were rated as high quality. The domain with the highest standardised percentage was “scope and purpose” (84.61%), while the “applicability” domain had the lowest standardised percentage (51.04%). Five guidelines were assessed as “recommended”, seven were rated as “recommended with modifications”, and the remaining two were considered “not recommended”. Regarding the content analysis, physical activity/exercise, meditation, hypnosis, yoga, music therapy, stress management, relaxation, massage, and acupressure were the common self-managed non-pharmacological interventions recommended by the 14 CPGs. Physical activity/exercise was the only self-managed non-pharmacological intervention that was mostly recommended for psychological and physical symptom management by the included CPGs. However, there were significant disparities in terms of level of evidence and grade of recommendation in the included CPGs. Conclusion: The recommendations for the self-managed non-pharmacological interventions were varied and limited among the 14 CPGs, and some were based on medium- and low-quality evidence. More rigorous methods are required to develop high-quality CPGs in order to guide clinicians in offering high-quality and tailored breast cancer survivorship care.

Arylsulfatase and β-glucuronidase are two important enzymes in human, which play important role on dynamic equilibrium of steroidal estrogens. This work probably for the first time reported that hydrogen peroxide (H2O2), hypochlorite and peracetic acid (PAA) could effectively inhibit the activities of arylsulfatase and/or β-glucuronidase. The 50 percent of inhibitions (IC50) of H2O2, and PAA on arylsulfatase were found to be 142.90±9.00, 91.83±10.01, and 43.46±2.92 μM, respectively. The corresponding respective IC50 of hypochlorite and PAA on β-glucuronidase were 704.90±41.40 and 23.26±0.82 μM, while H2O2 showed no inhibition on β-glucuronidase. It was further revealed that the inhibition of hypochlorite on both arylsulfatase and β-glucuronidase was irreversible. On the contrary, the inhibition by H2O2 and PAA was reversible. Moreover, it was found that the inhibitions of arylsulfatase and/or β-glucuronidase by these three chemicals were pH-dependent, among which the inhibition by H2O2 was competitive and non-competitive for PAA. In general, H2O2 and hypochlorite can be endogenously produced in human, which suggested that the two compounds are potential endocrine disruption compounds (EDCs) as they can cause endocrine disruption via inhibition of arylsulfatase and β-glucuronidase. This work further indicated that any agent that can induce production of H2O2 or hypochlorite in human is potential EDC, which explains why some EDCs with very weak or no estrogenic potency can cause endocrine disruption that confirmed in epidemiological studies.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Knowledge graphs (KGs) play a crucial role in many applications, such as question answering, but incompleteness is an urgent issue for their broad application. Much research in knowledge graph completion (KGC) has been performed to resolve this issue. The methods of KGC can be classified into two major categories: rule-based reasoning and embedding-based reasoning. The former has high accuracy and good interpretability, but a major challenge is to obtain effective rules on large-scale KGs. The latter has good efficiency and scalability, but it relies heavily on data richness and cannot fully use domain knowledge in the form of logical rules. We propose a novel method that injects rules and learns representations iteratively to take full advantage of rules and embeddings. Specifically, we model the conclusions of rule groundings as 0-1 variables and use a rule confidence regularizer to remove the uncertainty of the conclusions. The proposed approach has the following advantages: 1) It combines the benefits of both rules and knowledge graph embeddings (KGEs) and achieves a good balance between efficiency and scalability. 2) It uses an iterative method to continuously improve KGEs and remove incorrect rule conclusions. Evaluations on two public datasets show that our method outperforms the current state-of-the-art methods, improving performance by 2.7% and 4.3% in mean reciprocal rank (MRR).

Craters are the most prominent geomorphological features on the surface of celestial bodies, which is playing a crucial role in studying the formation and evolution of celestial bodies, as well as in landing and planning for surface exploration. Currently, the main automatic crater detection models and datasets focus on the detection of large and medium craters. In this paper, we created 23 small lunar crater datasets for model training based on the Chang’E-2 (CE-2) DOM, DEM, Slope, and integrated data with 7 kinds of visualization stretching methods. And then, we proposed the YOLO-Crater model for Lunar and Martian small crater detection by replacing EioU and VariFocal loss to solve the crater samples imbalance problem and introducing a CBAM attention mechanism to mitigate interference from the complex extraterrestrial environment. The results show that the accuracy (P = 87.86%, R = 66.04%, and F1 = 75.41%) of the Lunar YOLO-Crater model based on the DOM-MMS (Maximum-Minimum Stretching) dataset is the highest and better than that of YOLOX model. And the Martian YOLO-Crater, trained by the Martian dataset from the 2022 GeoAI Martian Challenge, achieves good performance with P = 88.37%, R = 69.25%, and F1 = 77.65%. It indicates that the YOLO-Crater model has a strong transferability and generalization capability, which can be applied to detect small craters on the Moon and other celestial bodies.

CuO/ZnO/Al2O3 catalyst is a commonly used catalyst for rea methanol steam reforming reaction. Oxalic acid was as precipitant in preparing oxalate precursor of CuO/ZnO/Al2O3 catalyst by co-precipitation, deionized water and ethanol were as solvents, microwave irradiation and water bath were as aging heating manner respectively. It indicated that ethanol selected crystal phase composition of oxalate precursors and restricted their growth. Microwave irradiation prompted the isomorphous substitution between Cu2+ of CuC2O4 and Zn2+ of ZnC2O4 in mother liquid, forming the master phase (Cu,Zn)C2O4 in precursor, the solid solution Cu-O-Zn formed after calcination, which exhibited nano-fibriform morphology. It possessed small CuO grains, large surface area and strong synergy between CuO and ZnO, which is beneficial to improve the catalytic performance of methanol steam reforming, the STY of H2 reached 516.7 mL·g-1·h-1, and the selectivity of CO was only 0.29%.

The connexin gene family is the most prevalent gene that contributes to hearing loss. Connexins 26 and 30, encoded by GJB2 and GJB6 respectively, are the most abundant expressed connexins in the inner ear. Connexin 43 which is encoded by GJA1 appears to be widely expressed in various organs, including the heart, skin, brain, and inner ear. The mutations that arise in GJB2, GJB6 and GJA1 can all result in comprehensive or non-comprehensive genetic deafness in newborns. As it is predicted that connexins include at least 20 isoforms in humans, the biosynthesis, structural composition, and degradation of connexins must be precisely regulated so that the gap junctions can operate properly. Certain mutations result in connexins possessing a faulty subcellular localization, failing to transport to the cell membrane and preventing gap junction formation, ultimately leading to connexin dysfunction and hearing loss. In this review, we provide a discussion of the transport models for connexin 43, connexins 30 and 26, mutations affecting trafficking pathways of connexin 26, the existing controversies in trafficking pathways of connexins, and the molecules involved in connexin trafficking and their functions. This review can contribute to a new way of understanding the etiological principles of connexin mutations and finding therapeutic strategies for hereditary deafness.

To ensure the security of highly sensitive remote sensing images (RSI) during their transmission, it is essential to implement effective content security protection methods. Generally, secure distribution schemes for remote sensing images often employ cryptographic techniques. However, sending encrypted data exposes communication behavior, which poses significant security risks to the distribution of remote sensing images. Therefore, this paper introduces deep information hiding to achieve secure distribution of remote sensing images, which can serve as an effective alternative in certain specific scenarios. Specifically, the Deep Information Hiding for RSI Distribution (hereinafter referred to as DIH4RSID) based on encoder-decoder network architecture with Parallel Attention Mechanisms (PAM) by adversarial training was proposed. Our model is constructed with four main components: a preprocessing network (PN), an embedding network (EN), a revealing network (RN) and a discriminating network (DN). The PN module is primarily based on Inception to capture more details of RSI and targets of different scales. The PAM module obtains features in two spatial directions to realize feature enhancement and context information integration. The experimental results indicate that our proposed algorithm achieves relatively higher visual quality and secure level compared to related methods. Additionally, after extracting the concealed content from hidden images, the average classification accuracy is unaffected.

Microbial community succession in raw milk determines its quality and storage period. In this study, carbon dioxide (CO2) at 2000 ppm was used to treat raw milk to investigate the mechanism of extending the shelf life of raw milk by CO2 treatment from the viewpoint of microbial colonies and metabolites. The results showed that the shelf life of CO2-treated raw milk was extended to 16 days at 4 ℃, while that of the control raw milk was only 6 days. Microbiomics analysis identified 221 Amplicon Sequence Variants (ASVs) in raw milk, and the alpha diversity of microbial communities increased (P < 0.05) with the extension of storage time. Among them, Pseudomonas, Actinobacteria and Serratia were the major microbial genus responsible for the deterioration of raw milk, with a percentage of 85.7%. A combined metagenomics and metabolomics analysis revealed that microorganisms altered the levels of metabolites, such as pyruvic acid, glutamic acid, 5'- cmp, arginine, 2-propenoic acid, and phenylalanine in the raw milk through metabolic activities, such as ABC transporters, pyrimidine metabolism, arginine and proline metabolism and phenylalanine metabolism, and reduced the shelf life of the raw milk. CO2 treatment prolonged the shelf life of the raw milk by inhibiting the abundance of Gram-negative aerobic bacteria, such as Acinetobacter guillouiae, Pseudomonas fluorescens, Serratia liquefaciens and Pseudomonas simiae.

Digital health has gained widespread adoption across various disciplines. Within the field of sport science, there is growing interest in digital health, leading to a surge in research activities. The objective of this study is to conduct a comprehensive bibliometric and visualization analysis, tracing the evolutionary trajectory, identifying research hotspots, and uncovering emerging trends in digital health within the domain of sport science. By doing so, this research aims to offer scholars a systematic and comprehensive understanding of the dynamic landscape in this field. To achieve this, the Web of Science core collection was chosen as the primary database. A thorough literature search was performed, focusing on digital health and sport science, resulting in the screening of 1870 English-language documents. The findings revealed a consistent upward growth trend in the annual publication count from 2010 to 2023. Notably, the United States, specifically the Commonwealth of Pennsylvania System of Higher Education, and John B. Cronin, emerged as the most prolific contributors in terms of publications. Collaborative efforts among countries, institutions, and authors were also observed. The research hotspots identified encompassed several areas, including the evaluation of digital health technologies' effectiveness, exploration of the relationship between digital health technologies and physical activity/exercise performance, and the use of digital health technologies in assessing and rehabilitating sports injuries. Among the prominent digital health technologies employed in these studies were virtual reality, social media, and wearable devices. The predominant types of studies utilized meta-analysis, randomized controlled trials, and cross-sectional studies. Looking towards the future, the study identified several key research trends. These include the exploration of telemedicine, artificial intelligence-based machine learning, therapeutic interventions, and physical therapy within the realm of digital health. These emerging areas signify promising directions for future investigation and development in the field of digital health within sport science.

Despite their anti-icing ability, hydrophobic coatings have the disadvantages of easy falling off and poor wear resistance, resulting in insufficient durability of ice/snow melting. To improve the surface stability and durability of superhydrophobic coatings, nanoparticle/epoxy coatings were prepared with three types of nanoparticles, two types of dispersion methods, three types of application methods and two types of introduction methods of epoxy resin. Water contact angles, ice adhesion force and icing rate of asphalt concrete coated with hydrophobic coatings were tested. The molecular structures of coatings were analyzed by Fourier transform infrared spectroscopy. The surface morphology of hydrophobic coatings was observed using Scanning electron microscopy. Results indicated that nano-ZnO, TiO2 and SiO2 particles can be modified into hydrophobicity by stearic acid. The hydrophobic coating could improve the hydrophobicity of concrete, reduce the adhesion strength of ice and asphalt concrete and delay the beginning icing time. Moreover, The dosages of stearic acid, nanoparticle and epoxy resin need to be in a certain range to ensure the best hydrophobicity and durability of coatings.

Transient receptor potential melastatin-8 (TRPM8) is a cation channel that is activated by cold and “cooling agents” such as menthol and icilin, which induce a cold sensation. Stimulation of TRPM8 activates an intracellular signaling cascade that ultimately leads to a change in the gene expression pattern of the cells. Here, we investigated the TRPM8-induced signaling pathway that links TRPM8 channel activation to gene transcription. Using a pharmacological approach, we show that inhibition of phosphatidylinositol 4-phosphate 5 kinase alpha (PIP5K), an enzyme essential for the biosynthesis of phosphatidylinositol 4,5-bisphosphate, attenuated TRPM8-induced gene transcription. Analyzing the link between TRPM8 and Gq proteins, we show that pharmacological inhibition of the beta gamma subunits impairs TRPM8 signaling. In addition, genetic studies showed that TRPM8 requires an activated Galpha subunit for signaling. In the nucleus, the TRPM8-induced signaling cascade triggers an activation of the transcription factor AP-1, a complex consisting of a dimer of basic region leucine zipper (bZIP) transcription factors. Here, we identified the bZIP protein c-Jun as an essential component of AP-1 within the TRPM8-induced signling cscade. In summary, with PIP5K, Gq subunits and c-Jun we have identified key molecules in the TRPM8-induced signaling from the plasma membrane to the nucleus.

In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes.A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m³ and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31m³/t. These results demonstrate that the unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines.

Pandemics caused by viruses have threatened lives of thousands of people. Viral infection is a complex and diverse process, and substantial studies have been complemented in understanding the biochemical and molecular interactions between viruses and hosts. However, the physical microenvironment where infections implement is often less carefully considered, and the role of mechanobiology in viral infection remains elusive. Mechanobiology focuses on sensation, transduction and response to intracellular and extracellular physical factors by tissues, cells and extracellular matrix. The intracellular cytoskeleton and mechanosensors have been proved to be extensively involved in virus life cycle. Furthermore, innovative methods in vivo and in vitro are being utilized to elucidate how extracellular factors including stiffness, forces and topography in regulating viral infection. Our current review covers how physical factors from different sources coordinate virus infection. We further discuss how this knowledge can be harnessed in future research on cross-fields of mechanobiology and virology.

Medium-deep Borehole Heat exchanger (MBHE) has been widely paid attention for building heating. In order to avoid the thermal interference of adjacent MBHEs, temperature distribution characteristics of medium-deep rock-soil was investigated in this work. The evolution on maximum rock-soil thermal affected radius (MTAR) in full life cycle was further analyzed. The results showed that the rock-soil thermal affected area (RTAA) continuously expands in both radial and vertical directions during a heating season. Several factors of thermal extraction load, fluid velocity, geothermal gradient and pipe length have main impacts on the RTAA in vertical direction. Rock-soil thermal conductivity affects the RTAA in both radial and vertical directions. In non-heating season, temperature difference of rock-soil in radial direction dominates the temperature recovery in the first year while geothermal flow nearly dominates temperature recovery after 20 years. The thermal affected radius (TAR) in the 30 th year could be determined as an effective MTAR in full life cycle. In order to decrease installed distance of adjacent MBHEs, a new well layout form by deflecting borehole was proposed. The recommended deflection angle is equal to or larger than 4 times TAR angle. This work provides scientific reference for promoting application of multiple MBHE arrays.

Aborycin is a type I lasso peptide with a stable interlocked structure, offering a favorable framework for drug development. The aborycin biosynthetic gene cluster gul from marine sponge-associated Streptomyces sp. HNS054 was cloned and integrated into the chromosome of S. coelicolor hosts with different copies. The 3-copy gul-integration strains S. coelicolor M1346::3gul showed better production than one-copy or 2-copy gul-integration strains, and the total titer reached approximately 10.4 mg/L, i.e., 2.1 times that of the native strain. Then, five regulatory genes, phoU (SCO4228), wblA (SCO3579), SCO1712, orrA (SCO3008) and gntR (SCO1678), which were reported to have negative effects on secondary metabolism, were further knocked out from the M1346::3gul genome by CRISPR/Cas9 technology. While the ΔSCO1712 mutant showed a significant decrease (4.6 mg/L) and the ΔphoU mutant showed no significant improvement (12.1 mg/L) in aborycin production, the ΔwblA, ΔorrA and ΔgntR mutations significantly improved the aborycin titers to approximately 23.6 mg/L, 56.3 mg/L and 48.2 mg/L, respectively, which were among the highest heterologous yields for lasso peptides in both Escherichia coli systems and Streptomyces systems. Thus, this study provided important clues for future studies on enhancing antibiotic production in Streptomyces systems.

Mesozoic-Palaeozoic marine carbonate rocks are important hydrocarbon reservoirs in the Central Uplift area of the South Yellow Sea Basin (SYSB). Due to the lack of boreholes and the great heterogeneity of carbonate reservoirs, the distribution of porous carbonate reservoirs and their related key controlling factors remain unclear. Based on seismic inversion and isotope analysis, this study explores the factors affecting the distribution of porous Carboniferous-Early Permian carbonate reservoirs in the SYSB. In this study, the log-seismic characteristics of porous carbonate reservoirs, sensitive lithology parameters, and physical property parameters are extracted and analyzed. The pre-stack simultaneous inversion technique is applied to predict the lithology properties and physical properties of the porous carbonate reservoirs. Moreover, the sedimentary of carbonate is analyzed using isotopes of carbon, oxygen, and strontium. The results indicate that porous carbonate reservoirs with porosities of 3%~5% mainly occur at the paleo-highland (Huanglong Formation and Chuanshan Formation) and the slope of paleo-highland (Hezhou Formation). The porous carbonate reservoirs of the Qixia Formation are only locally developed. In addition, the study area was dominated by a warm and humid tropical climate from the Carboniferous to Early Permian, with four sea-level eustatic fluctuation indicated by the negative and positive δ13C excursions. When the sea level fell, the study area was exposed and denuded, and the supply of terrigenous detrital was dominated, which significantly influenced the carbonate deposit and diagenesis. This study highlights that sedimentation was a key factor in controlling the quality of Carboniferous-Early Permian carbonate reservoirs. The methods proposed in this study can be used in other carbonate-dominated strata worldwide.

Codon use bias is an important characteristic in the process of genetic information transmission of species. With the publication of the genome of C. panzhihuaensis, it is of great significance to investigate the codon use bias for understanding the genetic evolution of this species and for molecular breeding. In this study, Perl language and CodonW 1.4.2 software was used to systematically analyze the coding gene sequences of the C. panzhihuaensis genome, obtain the characteristics of codon use, and identify the sources of variation affecting codon use. The results showed that GC3s content, GCall content, and ENC value were 46.75%, 47.67%, and 52.8 respectively. As the first seed plant, the GC3 content of Cycas is similar to that of most gymnosperms and most dicotyledons, but considerably different from that of monocotyledons.RSCU value was greater than 1, among which 21 codons ended in U or A. Enc-plot analysis, PR2-plot neutral plot analysis, and correlation coefficient analysis of Axis1 with GC3s and CAI revealed that the codon bias was mainly affected by natural selection, but also by mutation pressure and other factors. Thirty-one optimal codons of Cycas genes were screened. This research can provide a reference for the phylogeny and genome codon evolution of Cycas.

Dissolved organic matter (DOM) derived from organic fertilizers may increase soil phosphorus (P) availability. However, the frequently observed correlation between soil P availability and dissolved organic carbon (DOC) content has led to an excessive focus on DOC content at the expense of DOM properties. The present study investigated the influence of DOM characteristics on soil P availability by using a 6-year field experiment and microcosms of P sorption in paddy soil. Our results showed that partial replacement of chemical P fertilizer with manure or crop straw increased P fertilizer-use efficiency, even when decreasing chemical P input by 34 %, compared to normal chemical fertilization. The microcosm experiment demonstrated that DOM properties, rather than total DOC content, determine soil P sorption capacity, despite the significant correlation between DOC content and P availability observed in the field experiment. Manure-DOM exerted stronger inhibitory effects on P sorption than straw-DOM, and high molecular weight (HMW)-fractionated DOM exerted stronger inhibitory effects on P sorption than low-molecular-weight-fractionated DOM by 16-20%. The mechanism was rooted in the HMW DOM with unique characteristics (e.g., strong aromaticity, hydrophobicity, abundant humic-like components, carboxyl groups, and benzene ring structures) competing for soil P sorption sites (e.g., reduction in specific surface area and micropore volume), decreasing the soil surface charge (e.g., zeta potential), and thereby suppressing P sorption in paddy soil. Our study points out a promising avenue for regulating organic matter properties with organic fertilization to improve P use efficiency in agricultural soils.

The mechanism of anionic/cationic combination collector ST-8 for the efficient separation of spodumene and feldspar was investigated by flotation tests, surface tension measurements, zeta potential measurements and infrared spectroscopy analysis. The flotation results indicated that when the optimum molar combination of sodium oleate and dodecylamine was 6:1-10:1 and pH=8.5 or so, the recovery of spodumene reached a maximum of 80% and that of feldspar reached about 24.5%. Zeta potential measurements showed that the negative shift of the kinetic potential on the surface of spodumene was much stronger than that on the surface of feldspar, indicating that the adsorption capacity of the combined collector on spodumene surface and feldspar surface was greatly different. From the surface tension as well as the synergistic parameters, there was a strong mutual attraction between dodecylamine and sodium oleate, and there was a significant synergistic effect between them. Infrared spectroscopy indicated that the combined collector chemisorbed on the mineral surface, and the intensity of the absorption peak after the action of spodumene was much stronger than that after the action of feldspar. The solution chemistry of the combined collector revealed that at pH 8.5, the positively charged ions RNH3+ and (RNH3+)22+ in dodecylamine and the negatively charged RCOO- and (RCOO-)22- ions in oleic acid form highly reactive complexes to interact with the mineral surface by electrostatic gravitation, thus achieving efficient separation of spodumene and feldspar. Finally, from the closed circuit test results, a flotation index of 6.34% Li2O grade and 88.51% Li2O recovery was obtained.

The COVID19 coronavirus SARS-CoV2 spreading in Wuhan and now worldwide has been shown to use angiotensin-converting enzyme 2 ACE2 as its host cell receptor, like the severe acute respiratory syndrome coronavirus (SARS-CoV). Epidemiology studies found different sex and age groups have different susceptibility to infection, and very skewed severity and mortality of the virus infection, with male, old age, and comorbidity being the most inflicted. Here by analyzing GTEx and other public data in 30 tissues across thousands of individuals, we found significantly higher expression in Asian females compared to males and other ethnic groups, an age dependent ACE2 expression decrease and a highly significant decrease in type II diabetic patients. Consistently, the most significant expression quantitative loci (eQTLs) contributing to high ACE2 expression are close to 100% in East Asians, >30% higher than other ethnic groups. Together with the shockingly common enrichment of viral infection pathways among ACE2 anti-expressed genes, binding of virus infection-related transcription factors at ACE2 regulatory regions, the repression of ACE2 expression by inflammatory cytokines and by type 2 diabetes, and the induction by estrogen and androgen (both decrease with age) established a negative correlation between ACE2 expression and CovID19 fatality at both population and molecular levels. Our results will be instrumental when designing potential prevention and treatment strategies for ACE2 binding coronaviruses in general.

Due to the special characteristics of the shooting distance and angle of remote sensing satellites, the pixel area ratio of ship targets is small and the feature expression is insufficient, which leads to unsatisfactory ship detection performance and even situations such as missed detection and false detection. In this study, we propose an improved-YOLOv5 algorithm. The improvement strategies mainly include: (1) Add the Convolutional Block Attention Module (CBAM) into the Backbone to enhance the extraction of target-adaptive optimal features; (2) Introduce cross-layer connection channel and lightweight GSConv structure into the Neck to achieve higher-level multi-scale feature fusion and reduce the number of model parameters; (3) The Wise-IoU loss function is used to cal-culate the localization loss in the Output, and assign reasonable gradient gains to cope with dif-ferences in image quality. In addition, during the preprocessing stage of experimental data, a me-dian and bilateral filter method is used for noise reduction to reduce interference from ripples and waves and highlight the information of ship features. The experimental results show that Im-proved-YOLOv5 has a significant improvement in recognition accuracy compared to various mainstream target detection algorithms; Compared to the original YOLOv5s, the mean Average Precision (mAP) has improved by 3.2% and the Frames Per Second (FPN) has accelerated by 8.7%.

Heavy metals are compounds that can be hazardous and impair growth of living organisms. Bacteria have evolved the capability not only to cope with heavy metals but also to detoxify polluted environments. Three heavy metal-resistant strains of Mucilaginibacer rubeus and one of Mucilaginibacter kameinonensis were isolated from the gold/copper Zijin mining site, Longyan, Fujian, China. These strains were shown to exhibit high resistance to heavy metals with minimal inhibitory concentration reaching up to 3.5 mM Cu(II), 21 mM Zn(II), 1.2 mM Cd(II), and 10.0 mM As(III). Genomes of the four strains were sequenced by Illumina. Sequence analyses revealed the presence of a high abundance of heavy metal resistance (HMR) determinants. One of the strain, M. rubeus P2, carried genes encoding 6 putative P1B-1-ATPase, 5 putative P1B-3-ATPase and 4 putative Zn(II)/Cd(II) P1B-4 type ATPase, and 16 putative RND-type metal transporter systems. Moreover, the four genomes carry a high abundance of genes coding for putative metal binding chaperones. Analysis of the close vicinity of these HMR determinants uncovered the presence of clusters of genes potentially associated with mobile genetic elements. These loci include genes coding for tyrosine recombinases (integrases) and subunits of mating pore (type 4 secretion system) respectively allowing integration/excision and conjugative transfer of numerous genomic islands. Further in silico analyses revealed that their genetic organization and gene products resemble the Bacteroides integrative and conjugative element CTnDOT. These results highlight the pivotal role of genomic islands in the acquisition and dissemination of adaptive traits, allowing for rapid adaption of bacteria and colonization of hostile environments.

Background: Micronutrients has roles in strengthening and maintaining immune function, but its supplementation and/or deficiency effects on respiratory tract infections are inconclusive. This review aims to systematically assess the associations between micronutrient supplementation or deficiency, with novel coronavirus incidence and disease severity. Methods: Systematic literature searches conducted in 5 electronic databases identified 751 unique studies, of which 33 studies (5 supplementation studies, 1 supplementation and deficiency study, and 27 deficiency studies) were eventually included in this review. Proportions of incidence and severity outcomes in each group, and adjusted summary statistics with their relevant 95% confidence intervaIs (CI) were extracted. Data from 19 studies were pooled in meta-analysis using the generic inverse variance method. Findings: A total of 360,346 patients across 16 countries, with a mean age between 32 and 87.7 years, were involved across 33 studies. All studies were on COVID-19 infections. In individuals without micronutrient deficiency, there was a significant reduction on odds of COVID-19 incidence (pooled OR: 0.37, 95% CI: 0.18, 0.78), and ICU admissions or severe/critical disease onset (pooled OR: 0.26, 95% CI: 0.08, 0.89). Insignificant protective effects were observed on other outcome measures – mortality, ICU admission, progression to respiratory-related complications, severe/critical disease onset or requiring respiratory support and hospitalization rate. Conclusion: The absence of micronutrient deficiency significantly reduced COVID-19 incidence and clinical deterioration in hospitalized patients. Usage of micronutrients as prophylaxis and complementary supplement in therapeutic management of COVID-19 patients may be a promising and cost-effective approach warranting in-depth investigation.

Previous studies have demonstrated that cold pools play a pivotal role in the initiation and organization of convection, yet their influence on the evolution of GFs remains inadequately understood. A destructive wind event associated with a rearward gust front (RGF, 8 grade gale appeared after passing GF) and a prior gust front (PGF, 10 grade gale appeared before passing GF) over the north coast of China on 10 June 2016 was analyzed. Using multiple observation data as well as the four-dimensional Variational Doppler Radar Data Assimilation System (VDRAS), we found that the intensity of the GFs increased with increasing cold pool strength, depth and propagation speed. Two schematic models were proposed to explain the discrepancy between GFs and associated cold pools. The depth and intensity of the cold pool in RGF are found to be relatively shallower and weaker, leading to a correspondingly reduced strength in both outflow and convergence. In contrast, the enhanced vertical shear and boundary northeaster inflow of PGF generate intensified and more organized downdrafts, resulting in a deeper cold pool, robust outflow, and convergence. These findings offer novel insights into the diversity of GFs and associated cold pools.

The exploitation of bio-based foams implies an increase in the use of renewable biological resources to reduce the rapid consumption of petroleum-derived resources. Both tannins and furfuryl alcohol are derived from forestry resources and are therefore considered as attractive precursors for the preparation of tannin-furanic foams. In addition, toughening modification of tannin-furanic foams using polyvinyl alcohol (PVOH) resulted in a more flexible network-like structure, which imparts excellent flexibility to the foams with acquirement of relative properties that are even close to those of polyurethane foams, which are the most used polymers for fabrication of insoles for athletes. In addition, the addition of PVOH did not affect the thermal insulation of the foams, resilience and elongation at break, while reducing the brittleness of the samples and improving the mechanical properties. Also the observation of the morphology of the foam indicated that the compatibility between PVOH and tannin-furanic resin is good, and the cured foam does not show fragmentation or collapse, while the bubble pore structure is uniform. The developed flexible foam derived from biomass resources endowed the foam good thermal insulation properties and high mechanical properties, and the samples exhibited suitable physical parameters to be used as flexible insoles for athletes.

Astragalus membranaceus (AM) and Panax ginseng (PG) are two herbal products with a long history of clinical usage in traditional Chinese medicine (TCM), used in treating a variety of diseases especially in stimulating or inhibiting the immune system. To elucidate the immunity effect of these two traditional Chinese medicine on animal model, four pharmacodynamic indexes (spleen index, thymus index, splenic lymphocyte proliferation and cytotoxic activity of natural killer (NK) cells) were observed on mice. Furthermore, metabolic profiles of plasma were also analyzed by ultra-performance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF-MS, LC-MS) method. All mice were intragastric administrated at three doses (low dose, moderate dose and high dose) once daily for 30 days. Principal components analysis (PCA) and orthogonal projection to latent structure discriminant analysis (OPLS-DA) were performed on LC-MS spectra of plasma, showing that all administration groups developed the disturbance of internal milieu, compared to the blank control (BC) group. Besides, correlation analysis was conducted between pharmacodynamic index and metabolic index. It indicated that uracil, lysoPC(18:3(6Z,9Z,12Z)), sphinganine, LPA(0:0/16:0), UDP-glucuronate, PC(14:0/18:0) were five main endogenous substances, much closely related to four immunological indexes. Glycerophospholipid metabolism was found in both AM and PG groups. Pyrimidine metabolism and sphingolipid metabolism were closely regulated in AM groups. Energy metabolism (starch and sucrose metabolism, Pentose and glucuronate interconversions, together with glycerolipid metabolism) and glycerolipid metabolism were found in PG groups. These findings could contribute to the understanding of mice plasmatic metabolic profiling after long-term administration. Comparative immune-related metabolomic analysis of AM and PG was obtained on the base of pathway analysis of immune-related biomarkers. PG groups trended to have effect on cytotoxic activity of NK cells. AM groups trended to effect thymus index. Our work provides a detailed interpretation of immunological characteristics in different traditional Chinese medicine on metabonomic level.

Two reversible furan-maleimide resins, in which there are rigid -Ph-CH2-Ph- structure and flexible -(CH2)6- structures in bismaleimides, were synthesized from furfuryl glycidyl ethers (FGE), 4,4′-diaminodiphenyl ether (ODA), N,N'-4,4'-diphenylmethane-bismaleimide (DBMI) and N,N'-hexamethylene-bismaleimide (HBMI). The structures of the resins were confirmed by Fourier transform infrared analysis, and the thermoreversibility was evidenced by differential scanning calorimetry (DSC) analysis as well as sol-gel transformation process. Mechanical properties and recyclability of the resins were preliminarily evaluated by the flexural test. The results show the Diels-Alder (DA) reaction occurs at about 90°C and reversible DA reaction does at 130-140°C for the furan-maleimide resin. Thermally reversible furan-maleimide resins have high mechanical properties. The flexural strength of cured FGE-ODA-HBMI resin arrives at 141 MPa. The resins have a repair efficiency of over 75%. After being hot-pressed for three times, two resins display higher flexural strength than 80 MPa.

The target of an antibody plays a significant role in the success of antibody-based therapeutics and diagnostics, and to an extent, that of vaccine development. This importance is focussed on the target binding site – epitope, where epitope selection as a part of design thinking beyond traditional antigen selection using whole cell or whole protein immunisation can positively impact success. With purified recombinant protein production and peptide synthesis to display limited/selected epitopes, intrinsic factors that can affect the functioning of resulting antibodies can be more easily selected for. Many of these factors stem from the location of the epitope that can affect accessibility of the antibody to the epitope at a cellular or molecular level, direct inhibition of target antigen activity, conservation of function despite escape mutations, and even non-competitive inhibition sites. Through the incorporation of novel computational methods for predicting antigen changes to model-informed drug discovery and development, superior vaccines and antibody-based therapeutics or diagnostics can now be more easily designed to mitigate failures. With detailed examples, this review highlights the new opportunities, factors and methods of predicting antigenic changes for consideration in sagacious epitope selection.

Sunflower is one of the oil crops and its planting areas was listed behind Soybean, peanut and rapeseeds in China. It will encounter different kind of diseases during planting, thus limited the seeds yield. Fusarium species are the major threat to different crops nowadays, it is very important to identify the species caused diseases on different hosts, so that the potential control measures may be explored. In Inner mongolia, Sunflower Disk Rot (SDR) was found in different sunflower planting field, the average infection ratio around 8.50%, typically in some verieties, its infection ratio reach to 11.67%. The diseased receptacle were collected from different locations and Koch’s postulate was conducted. The results showed that Fusarium verticillioides was the main causal agent caused SDR. Fungicide toxicity tests shown that Fludioxonil and Flutolanil were screened out from six fungicides for controlling F. verticillioides, with EC50 values of 0.05 µg/mL (R = 0.9825) and 0.96 µg/mL (R = 0.9964) , respectively. This is the first report of SDR caused by F. verticillioides, and it will alert sunflower reseachers to include SDR in the disease list, so as to control sunflower diseases with integrated management strategy successfully.

The nature of the fracture and fragmentation process of concrete medium under blast loading is the transformation process of the medium from continuum to discontinuity, coupled with the significant rate correlation of concrete medium, its mechanical behavior presents a high degree of complexity. Problems such as grid distortion and even negative volume are often encountered in the finite element method and others when solving this problem, while the material point method can effectively avoid these problems. In addition, the widely used HJC concrete constitutive model does not take into account the segmented characteristics of the calculation function for dynamic increasing factor. Therefore, in this paper, firstly, the calculation function for dynamic increasing factor in the HJC concrete model is modified by SHPB experiment, and the improved HJC concrete model is proposed; secondly, the material point method simulation program is developed, and the improved HJC concrete model is embedded into the simulation program; finally, the simulation program is verified by numerical examples, and the results show that the developed simulation program can better simulate the fracture and fragmentation process of concrete medium under blast loading, especially the pulverization characteristics of the medium in the near zone of the load.

Satellite scene classification is challenging because of the high variability inherent in satellite data. Although rapid progress in remote sensing techniques has been witnessed in recent years, the resolution of the available satellite images remains limited compared with the general images acquired using a common camera. On the other hand, a satellite image usually has a greater number of spectral bands than a general image, thereby permitting the multi-spectral analysis of different land materials and promoting low-resolution satellite scene recognition. This study advocates multi-spectral analysis and explores the middle-level statistics of spectral information for satellite scene representation instead of using spatial analysis. This approach is widely utilized in general image and natural scene classification and achieved promising recognition performance for different applications. The proposed multi-spectral analysis firstly learns the multi-spectral prototypes (codebook) for representing any pixel-wise spectral data, and then based on the learned codebook, a sparse coded spectral vector can be obtained with machine learning techniques. Furthermore, in order to combine the set of coded spectral vectors in a satellite scene image, we propose a hybrid aggregation (pooling) approach, instead of conventional averaging and max pooling, which includes the benefits of the two existing methods but avoids extremely noisy coded values. Experiments on three satellite datasets validated that the performance of our proposed approach is much more accurate than even the deep learning framework for spatial analysis.

Understanding the distribution in drought and floods plays an important role in disaster risk management. The present study aims to explore the trends in the standardized precipitation index and extreme precipitation days in China, as well as to estimate the economic losses they cause. We found that in the Northeast China, northern of North China and northeast of Northwest China were severely affected by drought disasters (average damaged areas were 6.44 million hectares) and the most severe drought trend was located in West China. However, in the north of East China and Central China, the northeastern of the Southwest China was severely affected by flood disasters (average damaged areas were 3.97 million hectares) and the extreme precipitation trend is increasing in the northeastern of the Southwest China. In the Yangtze River basin, there were increasing trends in terms of drought and extreme precipitation, especially in the northeastern of the Southwest China, where accompanied by severe disaster losses. By combining the trends in drought and extreme precipitation days with the distribution of damaged areas, we found that the increasing trend in droughts shifted gradually from north to south, especially in the Southwest China, and the increasing trend in extreme precipitation gradually shifted from south to north.

In this paper, a novel permanent magnet-assisted synchronous reluctance machine (PMASynRM) with rare-earth PMs and ferrite magnets is proposed. The performance of PMASynRM is discussed with respected to the different magnet ratio of rare-earth PMs and ferrite magnets. Some characteristics including the flux density, output torque, cogging torque, output power, power factor, torque ripple, loss, efficiency, and demagnetization are calculated by 2-D finite element analysis (FEA). The analysis results show that the excellent performance can be obtained by using hybrid magnet of rare-earth PMs and ferrite magnets with the suitable magnet ratio, and provide some desirable cost-performance trade-off.

Natural products are an important source of antibacterial agents. Canthin-6-one alkaloids have displayed potential antibacterial activity based on our previous work. In order to improve the activity, twenty-two new 3-N-benzylated 10-methoxy canthin-6-ones were designed and synthesized through quaternization reaction. The in vitro antibacterial activity against three bacteria was evaluated by double dilution method. Four compounds (6f, 6i, 6p and 6t) displayed 2-fold superiority (minimum inhibitory concentration (MIC) = 3.91 µg/mL) against agricultural pathogenic bacteria R. solanacearum and P. syringae than agrochemical propineb. Moreover, the structure–activity relationships (SARs) were also carefully summarized in order to guide the development of antibacterial canthin-6-one agents.

This study aimed to investigate the relationship between sleep duration, dementia severity, age, and ANS regulation. This cross-sectional pilot study included 27 older patients with probable Alzheimer’s disease, hospitalized at a psychiatric center. We measured heart rate variability to assess ANS regulation at night, evaluated dementia severity using the Clinical Dementia Rating scale, and obtained sleep duration data from sleep diaries maintained by psychiatric nurses. The data were analyzed using repeated-measures generalized linear models with age, sex, dementia severity, and medication (antipsychotics) as covariates. A sleep duration of 7–8 h per night was associated with better ANS regulation than other sleep durations, as indicated by sympathovagal balance (p = 0.005). ANS dysregulation was characterized by a 20.7% increase in sympathetic nervous system activity and a 14.8% decrease in parasympathetic nervous system (PSNS) activity. We found a significant correlation between dementia severity and PSNS activity (p = 0.04) and observed an inverted U-shaped association between sleep duration and ANS regulation. This pilot study demonstrated that a sleep duration of 7–8 h per night may be critical in maintaining optimal ANS regulation. Bidirectional associations between sleep duration, inadequate sleep duration, aging, and ANS regulation warrant further investigation.

In order to improve the operation performance of the multi-stage double-suction centrifugal pump and reduce the internal energy loss of the pump, this paper proposes a single-objective optimization design method based on non-hierarchical response surface model (RSM) and the multi-island genetic algorithm (MIGA). Nine parameters, such as the blade outlet width and blade wrap angle, were used as design variables, and the optimization objective was the efficiency under design conditions. In total, 149 sets of valid data were obtained under the latin hypercube sampling method (LHS), the corresponding thresholds were set for efficiency and head, and 99 sets of valid data were obtained. A cross-validation analysis of the sieved data was carried out based on non-hierarchical RSM, global optimization of the efficiency was carried out using MIGA, and numerical verification was carried out via CFD. The research results show that compared with hierarchical RSM, non-hierarchical RSM can approximate the nonlinear relationship between the objective function and the design variables with higher accuracy, and the model fitting R2 value was 0.919. The efficiency was improved by 3.717% after optimization. The overall prewhirl of the impeller inlet after optimization decreased, the internal speed of the volute significantly improved, the large-area vortex at the volute and the outlet pipe was eliminated, the impact loss at the volute separating tongue disappeared, and the overall hydraulic performance of the pump was improved. The total entropy output value of the optimized pump was reduced by 4.79 (W/K), mainly concentrated in the reduction in the entropy output value of the double volute, and the overall energy dissipation of the pump was reduced.

Water pollution, intensified by the release of hard-to-degrade pollutants, poses severe threats to ecosystems, human health, and economic development. The existing advanced oxidation processes often involve high operational costs and may result in secondary pollution, highlighting the necessity for innovative and more sustainable solutions. To address these challenges, our study introduces a cost-effective and eco-friendly corona discharge barrier plasma discharger for wastewater treatment. Through the central composite design/response surface methodology, a high decolorization rate of 98% of methylene blue (MB) within 10 minutes was achieved by optimizing parameters such as pH and voltage. Furthermore, the mechanisms of the generation of reactive oxygen species via this device was discussed in detail and the degradation pathways of MB were described. Moreover, this device is also very energy-efficient, with a low energy density and electrical energy per order of 0.15 watt/mL and 5.79 kWh/m³/order, respectively. In conclusion, the plasma discharger developed in this study provides a cost-effective and environmentally sustainable solution for dye wastewater treatment. This research contributes significantly to the advancement of sustainable dye wastewater management practices, offering an innovative method that meets both environmental and economic objectives.

Glioma accounts for the highest proportion of primary intracranial malignant tumors. Microenvironment enormously influences the process of glioma progression. Our study is to establish an individualized prognostic nomogram for glioma patients with microenvironment signature. Glioma samples of Chinese Glioma Genome Atlas (CGGA) were grouped by the immune and stromal score based on ESTIMATE algorithm. Microenvironment-related genes (MRGs) in glioma were analyzed by R. To determine the best prognostic correlation genes, univariate and multivariate Cox regression analysis were used to analyze MRGs. Use the selected genes (CHI3L1, SOCS3, SLC47A2, COL3A1, SRPX2 and SERPINA3), we established the prognostic risk score model (microenvironment signature) and validated it. Gene Set Enrichment Analysis (GSEA) showed that the high-risk group was mainly enriched in immune and stromal function KEGG pathways. Finally, the nomogram was constructed and evaluated. The receiver operating characteristic (ROC) curve, Calibration plots and decision curve analysis (DCA) of training and validation set indicated the excellent predictive performance of nomogram. In conclusion, the 6-gene microenvironment signature can not only provide directions for the basic research of glioma, but also can be included as an independent prognostic index in nomogram for individual prediction to guide clinical treatment.

Dendrobium Sw have multiple photosynthetic pathways but due to the lack of identification, the influence of CAM pathway on the plastid genomic evolution of Dendrobium and the origin of CAM pathway are still poorly understood. In this study, based on the results of δ13C, net photosynthetic rates (Pn) and titratable acid value, we identified Dendrobium species into three photosynthetic pathways. Then the chloroplast whole genome characteristics of 10 Dendrobium species were analyzed with next-generation sequencing technology. The quadripartite-structure plastomes ranged from 151,673 bp to 160,375 bp and included 127 to 132 genes. Five noncoding mutational hotspots (rbcL-accD, atpB-rbcL, rbcL, trnLUAA, accD, Pi &gt; 0.10) were identified. A total of 41–60 SSRs were recognized, the average trinucleotide content was only about 4%, which is probably due to a more conserved SSR. Among multiple photosynthetic pathways, the apparent differences in IR junctions of SSC/IRB junctions (JSBs) were measured within chloroplast genomes, and the chloroplast genome size of constitutive CAM plants is shorter because of their ndh gene loss or pseudogenization, and this phenomenon accounts for a decreasing proportion of constitutive CAM, facultative CAM, and obligate C3 plants, so that the loss of the ndh gene may be speculated to be closely related to the CAM pathway. Phylogenetic analyses showed that there are multiple independent CAM origins in selected Dendrobium species, and the ancestral Dendrobium plastome possessed full ORFs for all ndh genes. The study aims to clarify the chloroplast genomic features of different photosynthetic pathways, enrich the genomic data of CAM plants, and provide genetic information from different perspectives for further systematic study of Dendrobium.

Coptisine (Cop) exerts a neuroprotective effect in central nervous system disease, particularly ischemic stroke. However, its protective mechanism is still unclear. This study aimed to investigate the protective effect of Cop on cerebral ischemia-reperfusion (IR) rats with a middle cerebral artery occlusion model by integrating a gas chromatography-mass spectrometry (GC-MS) based metabolomics approach with biochemical assessment. Our results showed that Cop could improve neurobehavioral function and decrease the ischemia size in IR rats. In addition, Cop was found to decrease inflammatory mediators (e.g., prostaglandin D2 (PGD2) and tumor necrosis factor-α (TNF-α) and attenuate oxidative stress response (e.g., increase the superoxide dismutase (SOD) expression and decrease 8-iso-PGF2α level). Furthermore, GC-MS based cerebrospinal fluid (CSF) metabolomics analysis indicated that Cop influenced the level of glycine, 2,3,4-trihydroxybutyric acid, oleic acid, glycerol, and ribose during IR injury. Cop exhibited a good neuroprotective effect against cerebral IR injury and metabolic alterations which might be mediated through its antioxidant and anti-inflammatory property.

In China, the majority of mountainous regions are characterized by complex topography and a delicate, sensitive geological environment. Coupled with a generally underdeveloped infrastruc-ture and numerous unreasonable human engineering activities, these regions are often highly susceptible to geological disasters. Geological hazards can cause significant damage to human lives and property, impeding the development of mountainous areas. Consequently, researching the assessment of geological hazard vulnerability is crucial for disaster prevention, emergency management, and economic development in these regions. This study focuses on Xuanwei City and selects eight factors for evaluation, including elevation, gradient, slope aspect, normalized vegetation index, stratigraphic lithology, distance from faults, distance from rivers, and distance from roads. These factors are chosen based on a comprehensive analysis of the spatial and tem-poral distribution of geological hazards and disaster incubation conditions. Two paired models, the deterministic coefficient model + logistic regression model (CF+LR) and the information quan-tity model + logistic regression model (I+LR), were employed to quantitatively assess the study ar-ea. The accuracy of these models was evaluated using ROC curves and AUC values. The results indicate that: (1) The AUC values for the CF+LR and I+LR coupled models are 0.799 and 0.772, respectively, demonstrating that both models can objectively and reliably assess the vulnerability to geological hazards in the study area; (2) Based on the CF+LR model calculations, the geological hazard susceptibility of Xuanwei City can be categorized into four zones: extremely high suscepti-bility (6.09%), high susceptibility (31.08%), medium susceptibility (32.26%), and low susceptibility (30.57%); (3) The CF+LR model more accurately represents the evaluation results and offers a strong reference value.

Rapid and accurate detection of road cracks is of great significance for road health monitoring, but currently this work is mainly completed through manual site surveys. Low-altitude UAV remote sensing can obtain images with centimeter or even subcentimeter ground resolution, which provides a new efficient and economical approach for rapid crack detection. Nevertheless, crack detection networks face challenges such as edge blurring and misidentification due to the heterogeneity of road cracks and the complexity of the background. To address these issues, we propose a real-time edge reconstruction crack detection network (ERNet) which adopts multi-level information aggregation to reconstruct crack edges and improve the accuracy of segmentation between the target and background. To capture global dependencies across spatial and channel levels, we propose an efficient bilateral decomposed convolutional attention module (BDAM) that combines depth separable convolution and dilated convolution to capture global dependencies across spatial and channel levels. To enhance the accuracy of crack detection, we use a coordinate-based fusion module that integrates spatial, semantic, and edge reconstruction information. In addition, we propose an automatic measurement of crack information for extracting the crack trunk and its corresponding length and width. Experimental results demonstrate that our network achieves the best balance between accuracy and inference speed.

Streptomyces sp. HNS054, which was previously isolated from a marine sponge, demonstrates vigorous growth and facile genetic modification. This study explores its potential as a marine ac-tinomycete chassis through complete genome sequencing and genetic engineering. With a 7.5 Mb genome containing 6678 predicted genes, 21 secondary metabolic biosynthetic gene clusters (BGCs), and 8 common site-specific recombination (SSR) system attB loci, HNS054 shows a close phylogenetic relation to S. griseoincarnatus strain RB7AG. Utilizing multiplexed site-specific ge-nome engineering (MSGE) and the CRISPR/Cas9 method, engineered strains derived from HNS054 (with three copies of the target BGCs) produce higher amounts of aborycin and ac-tinorhodin than S. coelicolor M1346 (containing three copies of the same BGCs). HNS054 stands out for its remarkable characteristics, including salt tolerance, rapid growth, and compatibility with synthetic biology tools, and positions it as a promising candidate for developing marine ac-tinomycete hosts to enhance secondary metabolite production.

In this paper, a semi-empirical model of air waves induced by falling rock is described. The model is composed of a uniform motion phase (velocity close to 0 m·s^-1) and an acceleration movement phase. The uniform motion phase was determined based on experimentally and the acceleration movement phase was derived by theoretical analysis. A series of experiments were performed to verify the semi-empirical model and elucidated the law of the uniform motion phase. The acceleration movement phase accounted for a larger portion with a greater height of the falling rock. Experimental results of different falling heights of the goaf showed close agreement with theoretical analysis values. The semi-empirical model could accurately and conveniently estimate the velocity of air wave induced by falling rock. Thus, the semi-empirical model can provide a reference and basis for estimating the speed of air waves and designing protective measures in mines.

Saikosaponin (SS) a is a compound with various pharmacological properties and easily degraded into SSb1 and SSg in acid condition. In present work another two new degradation products of SSa formed under acid hydrolytic condition were detected and isolated by analytical and semi-preparative liquid chromatography technology, furthermore their structures were characterized as hydroxyl-saikosaponin a and SSb2 by spectral analysis, which is not only essential in stability-indicating method development and validation but also could be used as a worst case to assess the analytical method performance of SSa. Moreover their structural transformation pathways were also proposed.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

Calcareous sand deposits are widely distributed along the shoreline in ropical and subtropical regions. Microbially induced calcite precipitation treatment (MICP) is a relatively new method to improve the stiffness and strength of the soil. Little is known about the small-strain shear modulus and damping ratio of MICP-treated calcareous sand, which are two crucial parameters for the prediction of the dynamic behavior of soil. A series of resonant column tests are performed to investigate the dynamic performance of MICP-treated calcareous sand, with special attention paid to the influence of treatment duration and confining stress on the stiffness and damping characteristics. The relationship between the initial dynamic shear modulus and unconfined compressive strength is analyzed. Additionally, the empirical equations of the reference shear strain between treatment duration and confining stress are given. The G/G0 of MICP-cemented calcareous sand presents a higher strain sensitivity than that of untreated sand, and its attenuation pattern can be described by Hardin-Drnevich model. The σc has an apparent effect on the degradation characteristics of the dynamic shear modulus of MICP-treated calcareous sand with a low cementation level, however, its effect decreases with the increasing treatment duration. The relationship between the reference shear strain and the treatment duration and confining stress can be described by a power and a linear formula, respectively.

Although the spanwise periodicity within the gap between two tandem circular cylinders has been observed by some researchers, there is a lack of systematic study on the properties of this pe-riodicity. For the spanwise periodicity within the gap, this study aims to ascertain its characteris-tics, its influences on the flow field, and its variation trend with increasing spacing ratio. By nu-merically simulating the flow around two tandem circular cylinders with a diameter ratio of d/D=0.6 and seventeen spacing ratios (L/D=1.00~6.00) at Re=3900, this study shows four flow re-gimes: Reattachment Flow (L/D=1.00~3.15), Bi-stable Flow (L/D=3.24), Intermittent Lock-in Co-shedding (L/D= 3.30~3.50) and Subharmonic Lock-in Co-shedding (L/D=4.00~6.00). Further, de-pending on the spanwise periodicity length of the time-averaged flow structures (i.e. Pz) within the gap, Reattachment Flow is, for the first time, subdivided into three new sub-flow regimes: Small-scale Periodic Reattachment (L/D=1.00~1.50, Pz/D=(0, 4]), Large-scale Periodic Reattachment (L/D=2.00~2.25, Pz/D>4) and Non-periodic Reattachment (L/D=2.50~3.15, no spanwise periodicity). The formation mechanisms are elaborated by analyzing the combined effect of both the L/D value and the spanwise-averaged time-averaged reattachment angle of the downstream cylinder. Moreover, this study proves that the newly-defined Small-scale Periodic Reattachment and Large-scale Periodic Reattachment are responsible for the pronounced asymmetry of the flow along the transverse direction within the gap. In addition, detailed flow properties and statistical pa-rameters are provided for each flow regime, such as velocity, vorticity, force coefficient, separa-tion/reattachment angle, Strouhal number and Q-criterion.

Surface velocity is traditionally measured with in situ techniques such as velocity probes (in shallow rivers) or Acoustic Doppler Current Profilers (in deeper water). In the last years, researchers have developed remote sensing techniques, both optical (e.g., image-based velocimetry techniques) and microwave (e.g., Doppler radar). These techniques can be deployed from Unmanned Aerial Systems (UAS), which ensure fast and low-cost surveys also in remotely-accessible locations. We compare the results obtained with a UAS-borne Doppler radar and UAS-borne Particle Image Velocimetry (PIV) in different rivers, which presented different hydraulic–morphological conditions (width, slope, surface roughness and sediment material). The Doppler radar was a commercial 24 GHz instrument, developed for static deployment, adapted for UAS integration. PIV was applied with natural seeding (e.g., foam, debris) when possible, or with artificial seeding (woodchips) in the stream where the density of natural particles was insufficient. PIV reconstructed the velocity profile with high accuracy typically in the order of a few cm s⁻¹ and a coefficient of determination (R²) typically larger than 0.7 (in half of the cases larger than 0.85), when compared with acoustic Doppler current profiler (ADCP) or velocity probe, in all investigated rivers. However, UAS-borne Doppler radar measurements show low reliability because of UAS vibrations, large instrument sampling footprint, large required sampling time and difficult-to-interpret quality indicators suggesting that additional research is needed to measure surface velocity from UAS-borne Doppler radar.

Real-time tracking is one of the most challenging problems in computer vision. Most Transformer-based trackers usually require expensive computational and storage power, which leads to the inability of these robust trackers to achieve real-time performance in resource-constrained devices. In this work, we propose a lightweight tracker, AnteaTrack. To localize the target more precisely, we develop a scaling-invariant max-filtering operator employing a sliding window combined with local max-pooling, which filters out the suspected target from the feature and performs an augmented representation while suppressing the background. For a more tight bounding box, we employ Pixel-Shuffle to increase the resolution of the feature map and get a more fine-grained representation of the target. In addition, AnteaTrack can run in real-time at 47 frames per second(FPS) on the CPU. We tested AnteaTrack on 5 datasets, and a large number of experiments have shown that AnteaTrack provides the most efficient solution compared to the same type of CPU real-time trackers. The code will be available at https://github.com/cnchange/AnteaTrack.

The Gurney flap (GF) is a miniature lift-enhancement device and is usually mounted at the trailing edge of an airfoil. The GF and has been successfully applied to isolated airfoils, multi-element airfoils, and aircraft wings as well as helicopter rotor due to its attractive features of simplicity, cost-effective and separation control. The GF also has aroused the attention of researchers in the turbomachinery industry. However, limited studies are currently available on the application of a GF to an axial fan.Hence, in this paper, we conduct a wind tunnel and computational fluid dynamic (CFD) investigation on an axial fan profiled with a NACA 65-(12)10 airfoil to evaluate the effect of the GF on the performance of the fan. We also present the detailed flow features of the fan with and without the GF after validating the simulation results with the experimental results. The experimental results show that as the GF is installed higher on the fan blade, it can produce a higher total pressure rise accompanied with a greater loss of efficiency. The installation of the GF also enlarges the work capacity of the fan. Detailed flow field analysis, including the surface pressure distribution, vorticity distribution at the trailing edge and streamline distribution of the fan, is carried out to understand the mechanisms of the effect of the GF on the performance of the fan.

Background: Pittosporum tobira (Thunb.) Aiton is an aromatic medicinal plant widely cultivated in the world. However, the essential oils (EOs) from P. tobira flowers for anti-cancer potential is still not systematically studied. The present aim to elucidate the phytochemical composition of the EOs and to explore mechanism of anticancer action. Methods: The EOs were extracted and analyzed by headspace solid-phase microextraction (HS-SPME) with gas chromatography-mass spectrometry (GC-MS). Volatile components were identified according to Kovats retention index (KI) and NIST database. The anti-neoplasm mechanisms of the EOs was comprehensively investigated in lung carcinoma A549 and H460 cells. Results: A total of 47 secondary metabolites representing 94.18% of the EOs were successfully identified: monoterpenes and sesquiterpenes were the dominant terpenoids. The EOs exhibited antiproliferative activity on A549 and H460 lung carcinoma cells. Hoechst 33324 fluorescent staining indicated the typical characteristics of apoptosis and induced cycle phase arrest. AnnexinV/PI staining revealed that the number of apoptotic cells was increased. Furthermore, the EOs also induced the caspase-mediated mitochondrial apoptosis pathway. Conclusions: Findings suggest that the full-scale chemical composition and first characterization of anticancer activities of the EOs, it could be used for integrative natural anti-cancer agents in health care should be pay more attention.

The task of weakly supervised point cloud semantic segmentation has received widespread attention and also has been widely used in autonomous driving, robotics, and modern industries. Due to the high dimensionality and large volume of point cloud data, many technical difficulties appeal to weakly supervised semantic processing, especially segmentation. However, weakly-supervised schemes usually provide only partial labelling information of the underlying point cloud data and thus need to effectively extract local features, geometric information, and contextual relationships only using these limited labelled data for supervised learning. To improve weakly-supervised semantic segmentation, we propose a novel segmentation network through the boundary-based feature aggregation based on a K-NN algorithm with down-sampling operation, and also introduce the smoothness loss and Siamese loss for effective segmentation. The experiments on public datasets demonstrate that our presented segmentation method exceeds most of the existing fully supervised and weakly-supervised methods in terms of mIoU. Specifically, our network has high segmentation accuracy on the labels of objects with similar geometrical structures, such as ceiling, wall, floor, chair and table, reaching 91.2%, 98.8%, 83.3%, 75.3% and 80.2%, respectively. Extensive experiments also illustrate its robustness, effectiveness, and generalization of the proposed weakly supervised segmentation network.

In this paper, a distributed algorithm is proposed to solve a consensus convex optimization problem. It is a Jacobi-proximal alternating direction method of multipliers with a damping parameter $\gamma$ in the iteration of multiplier. Compared with existing algorithms, it has the following nice properties: (1) The restriction on proximal matrix is relaxed substantively, thus alleviating the weight of the proximal term. Therefore, the algorithm has a faster convergence speed. (2) The convergence analysis of the algorithm is established for any damping parameter $\gamma\in(0,2]$, which is larger ones in the literature. In addition, some numerical experiments and an application to a logistic regression problem are provided to validate the effectiveness and the characteristics of the proposed algorithm.

Gas flaring is commonly used by industrial plants for processing oil and natural gases in the atmosphere, and hence is an important anthropogenic source for various pollutants including CO₂, CO, and aerosols. This study evaluates the feasibility of using satellite data to characterize gas flaring form space by focusing on the Khanty Mansiysk Autonomous Okrug in Russia, a region that is well known for its dominatingly gas flaring activities. Multiple satellite-based thermal anomaly data products at night are inter-compared and analyzed, including MODIS (Moderate Resolution Imaging Spectroradiometer) Terra level-2 Thermal Anomalies product (MOD14), MODIS Aqua level-2 Thermal Anomalies product (MYD14), VIIRS (Visible Infrared Imaging Radiometer Suite) Active Fires Applications Related Product (VAFP), and VIIRS level-2 data based Nightfire product (VNF). The analysis compares and contrasts the efficacy of these sensor products in detecting small, hot sources like flares on the ground in extremely cold environments such as Russia. We found that the VNF algorithm recently launched by NOAA has the unprecedented accuracy and efficiency in characterizing gas flares in the region owing primarily to the use of Shortwave Infrared (SWIR) bands. Reconciliation of VNF’s differences and similarities with other nighttime fire products is also conducted, indicating that MOD14/MYD14 and VAFP data are only effective in detecting those gas flaring pixels that are among the hottest in the region. Validation of VNF product of gas flaring location with Google Earth images are made. It is shown that that VNF’s estimates of gas flaring area (the area of gas flaming) agree well the counterparts from Google images with a linear correlation of 0.91, highlighting its potential use for routinely monitoring emissions of gas flaring from space.

Recently, research on ultra-high-performance concrete (UHPC) with the characteristics of ultra-high strength, high toughness, and high durability has been actively conducted from materials to actual structural applications. However, research on experimental methods that reflect the unique characteristics of UHPC, which are different from those of normal concrete, is insufficient. To solve the difficulties in applying the compressive creep test method for normal concrete to UHPC and to verify the validity of the recently proposed ASTM C 1856 standard test method, this study performed compressive creep tests on UHPC with variables of specimen size, sustained load intensity, fiber length, and strain measuring method. Two types of cylindrical specimens of ϕ100 × 200 mm and ϕ75 × 150 mm were used for a specimen size variable. The sustained load intensities of 10% to 40% based on the specified compressive strength of 150 MPa were applied. Two types of steel fiber lengths of 13 mm and 19.5 mm in the UHPC mix were used as a variable, and three strain measuring methods of the embedded strain gauge method, the attached strain gauge method, and the strain meter with stud measured the change in length of the UHPC specimens. The experimental results showed that the strain meter method using the standard rod had limitations due to the error in the verification process using the standard rod and the observation error of the measurer, and the sustained load intensity is preferable to 15% to 40% of the actual compressive strength. It was found that it is possible to perform a compressive creep test for UHPC using a specimen with a size of ϕ75 mm or more, and the fiber length did not affect the creep behavior of UHPC up to 19.5 mm. As a result of comparing the UHPC creep test results with the creep prediction model, the B3 model was found to most accurately predict the UHPC creep behavior. The creep coefficient pattern of the B3 model was very similar to the measured results, and well reflected the effects of the mixing ratio and compressive strength of UHPC.

With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n-distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2.

Silver ion (Ag+) are recognized for their potent antibacterial properties; however, their utilization in food preservation is restricted by factors such as inadequate stability, a transient antibacterial impact, and the potential for human absorption. Hydrogel-based antibacterial agents are capable of exerting their antibacterial effects by establishing appropriate microenvironments, which facilitate the efficient delivery of antimicrobial molecules to the contaminated regions of food. In previous studies, we observed that chitosan (CS) and silver nitrate (AgNO3) were able to reduce Ag+ to silver nanoparticles (AgNPs) with enhanced antibacterial properties. This not only significantly extended the stability of the antibacterial agent but also demonstrated exceptional inhibitory capabilities against pathogenic bacteria, including common grape contaminants such as P. expansum, A. niger, and B. cinerea. Utilizing ultrasound-induced complexation technology, this study has successfully synthesized a chitosan-silver (CS-AgNPs) hydrogel. The efficacy of this hydrogel against the pathogenic fungus responsible for jujube black spot disease has been thoroughly investigated. The morphology structures of CS-AgNPs hydrogels were characterized by TEM, FTIR and UV-vis. The results indicated that AgNPs ranging from 80 to 110 nm were uniformly dispersed within the gel matrix and remained stable for extended periods at room temperature. In vitro antibacterial assays and fractional inhibitory concentration index (FICI) studies revealed that the pronounced antibacterial efficacy of the CS-AgNPs hydrogel was primarily attributed to the additive antibacterial effect of CS and AgNPs. These insights underscore the significant potential of CS-AgNPs hydrogels in combating fungal diseases of jujube, offering innovative strategies and materials for the management of agricultural pathogens.

Exposure to psychosocial stress is a risk factor for cardiovascular disease, including vascular aging, angiogenesis, and atherosclerosis-based cardiovascular disease (ACVD). Dipeptidyl peptidase-4 (DPP-4) is a complex enzyme (also called CD26) that acts as a membrane-anchored cell surface exopeptidase. DPP4 is upregulated in metabolic and inflammatory cardiovascular disorders. The widespread expression of DPP4 macrophages and immune cells and the noncatalytic function of DPP4 (also called CD26) as a signaling and binding protein across a wide range of species suggest a teleological role for DPP4 in inflammation and immune response. DPP-4 exhibits many physiological and pharmacological functions by regulating its extremely abundant substrates [e.g., stromal cell-derived factor-1α/ C-X-C chemokine receptor type-4, glucagon-like peptide-1 (GLP-1), etc.]. Over last ten year, emerging data demonstrated unexpected roles for GLP-1 and DPP-4 in extracellular and intracellular signaling, immune activation, inflammation, oxidative stress production, cell apoptosis, insulin resistance, and lipid metabolism,. This mini review has focuses on recent novel findings in this field, highlighting an imbalance between GLP-1 and DPP4 as a potential therapeutic molecular target in treatments of chronic psychological stress-related atherosclerotic cardiovascular disease in humans and animals.

The origin of the nucleus remains a great mystery in life science, although nearly two centuries have passed since the discovery of nuclei. To date, studies of eukaryogenesis have focused largely on micro-evolutionary explanations. Here, we examined macro-patterns of C-values (the total amount of DNA within the haploid chromosome set of an organism) for over 110,000 species and the chromosome numbers for over 11,000 species and their potential links with the state of atmospheric oxidation over geological time. Eukaryogenesis was in sync with an over 2.5 order-of-magnitude increase in genome size from prokaryote to eukaryote, and also with a rapid rise of atmospheric oxidation, suggesting that eukaryogenesis would have resulted from a regime shift of genomes driven by the oxidation-driven complexification and structuralization (e.g. chromatin packing).

Resection of malignant lesions in the oral and maxillofacial area causes functional and morphological defects. To recover from these defects, reconstruction surgery is needed such as a primary closure or a flap. There are advantages and disadvantages to the method of using the primary closure and the flap, and the choice of procedure is entirely up to a surgeon. The purpose of this study is to evaluate availability of primary closure in patients. For 10 years from January 2010 to May 2020, patients who recovered using flaps after removing malignant lesions from the oral cavity and those who closed the lesion using primary closure were investigated. The investigation was conducted by searching the database of the hospital. There were 85 patients who removed malignant lesions in the oral and maxillofacial area, and among them 16 patients closed the soft tissue defects using primary closure. Operation time, histologic types, stages, wound status, and period of hospitalization according to the patients' medical records were investigated retrospectively. Between the staging and the primary closure, statistically significant differences were observed between stage I and stage II patients in 13 patients using the primary closure. (P=0.046). Statistically significant differences were identified between operation time and primary closure, with an average of 4.02 hours (P=0.015). The average period of hospitality for patients who underwent primary closure was 13.4 days, compared to 26.7 days for those who underwent flap surgery. This difference was statistically significant (P=0.0003). This study evaluated the use of primary closure in patients who underwent resection of malignant lesions in the oral and maxillofacial area. Although the majority of patients underwent reconstruction with flaps, our results showed that primary closure can be a viable option for certain patients with early-stage lesions. Therefore, oral and maxillofacial surgeons should carefully consider various evaluation criteria and select appropriate reconstruction methods to optimize functional and aesthetic outcomes for each patient.

A 'little brother' of pain, itch is an unpleasant sensation that creates a specific urge to scratch. To date, various machine-learning based image classifiers (MBICs) have been proposed for quantitative analysis of itch-induced scratch behaviour of laboratory animals in an automated, non-invasive, inexpensive and real-time manner. In spite of MBICs' advantages, the overall performances (accuracy, sensitivity and specificity) of current MBIC approaches remains inconsistent, with their values varying from ~50% to ~99%, for which the reasons underlying have yet to be investigated further, both computationally and experimentally. To look into the variation of the performance of MBICs in automated detection of itch-induced scratch, this article focuses on the experimental data recording step, and reports here for the first time that MBICs' overall performance is inextricably linked to the sharpness of experimentally recorded video of laboratory animal scratch behaviour. This article furthermore demonstrates for the first time that a linearly correlated relationship exists between video sharpness and overall performance (accuracy and specificity, but not sensitivity) of MBICs, and highlight the primary role of experimental data recording in rapid, accurate and consistent quantitative assessment of laboratory animal itch.

Photovoltaic(PV) power generation is highly nonlinear and stochastic. Accurate prediction of PV power generation plays a crucial role in grid connection as well as the operation and scheduling of power plants. To predict the PV power combination model, this paper suggests a method based on Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Nonlinear Auto-Regressive Neural Networks with Exogenous Input (NARXNN), Long Short Term Memory (LSTM) Neural Network, and Light Gradient Boosting Machine (LightGBM) algorithms. To attempt to reduce the non-smoothness of PV power, the weather variable features with the greatest effect on PV power are first identified by correlation analysis. Following this, the PV power modal decomposition is split and reorganized into a new feature matrix. Finally， a NARX is used to obtain preliminary PV power components and residual vector features， and the PV power is predicted by combining three models of LightGBM， LSTM, and NARX and then the final prediction results are obtained by combining the PV power prediction results using error inverse method weighted optimization. The prediction results demonstrate that the model put forth in this paper outperforms those of other models and validate the model's validity by utilizing real measurement data from Andre Agassi College in the United States.

In this study, we investigate the magnetization behavior of coaxial nanowires fabricated through the sol-gel electrospinning method. Our analysis uncovers a significant reduction in coercivity for CoFe2O4 nanowires when BaTiO3 is used as the shell material, effectively transforming them from hard to soft magnetic. This intriguing behavior is attributed to the magnetization reversal effect at the interface between ferromagnetic and paramagnetic regions, and it is also observed in NiFe2O4 and Fe2O3 nanowires. Surprisingly, introducing a GdBa2Cu3O7 shell induces a similar effect. Additionally, we employ magnetic impedance measurements on the coaxial nanowires, unveiling their potential for magnetic field sensing applications.

Kombucha is a popular sparkling sugared tea, fermented by a symbiotic culture of acetic acid bacteria (AAB) and yeast. The demand for Kombucha is increasing worldwide mainly due to its perceived health benefits and appealing sensory properties. This study isolated and characterised the dominant AAB and yeast from starter culture and Kombucha broth after 0, 1, 3, 5, 7, 9, 11, and 14 days of fermentation at ambient temperature (~22°C). Changes in the microbial composition were associated with variations in the physico-chemical characteristics of Kombucha tea, such as pH, titratable acidity, and total soluble solids (TSS). During fermentation, the acidity increased, and TSS decreased. The yield, moisture content and water activity of the cellulosic pellicles which had developed by the end of fermentation were attributed to the presence of AAB. Yeast and AAB were isolated from the Kombucha samples using glucose yeast extract mannitol ethanol acetic acid (GYMEA) and yeast extract glucose chloramphenicol (YGC) media respectively, using serial dilutions. Phenotypic and taxonomic identification of AAB and yeast were determined by morphological and biochemical characterisation, followed by sequence analysis of the ribosomal RNA gene (16S rRNA for AAB and ITS for yeast). The dominant AAB species in the cellulosic pellicle and Kombucha broth was identified as Komagataeibacter rhaeticus. The yeast isolates belonged to Debaryomyces prosopidis and Zygosaccharomyces lentus.

In this paper, we study the well-posedness and asymptotics of a one-dimensional thermoelastic laminated beam system either with or without structural damping, where the heat conduction is given by Fourier's law effective in the rotation angle displacements. We show that the system is well-posed by using Lumer-Philips theorem, and prove that the system is exponentially stable if and only if the wave speeds are equal, by using the perturbed energy method and Gearhart-Herbst-Prüss-Huang theorem. Furthermore, we show that the system with structural damping is polynomially stable provided that the wave speeds are not equal, by using the second-order energy method.

In this study, based on a new quantum integral identity, the authors establish some quantum estimates of Hermite-Hadamard type inequalities for convex functions. These results generalize and improve some known results given in literatures.

Lithium-rich layered oxides is one of the most perspective candidates for cathode materials of lithium ion battery, because of its high discharge capacity. However, there are some disadvantages of uneven composition, voltage decay, and poor rate capacity, which are closely related to the preparation method. Here, 0.5Li2MnO3·0.5LiMn0.8Ni0.1Co0.1O2 were successfully prepared by sol-gel and oxalate co-precipitation methods. A systematic analysis of the materials shows that the 0.5Li2MnO3·0.5LiMn0.8Ni0.1Co0.1O2 prepared by the oxalic acid co-precipitation method has the most stable layered structure and the best electrochemical performance. The initial discharge specific capacity is 261.6 mAh·g-1 at 0.05 C, and the discharge specific capacity is 138 mAh·g-1 at 5 C. The voltage decay is only 210 mV, and the capacity retention is 94.2% after 100 cycles at 1 C. The suppression of voltage decay can be attributed to the high nickel content and uniform element distribution. In addition, tightly packed porous spheres help to reduce lithium ion diffusion energy and improve the stability of the layered structure, thereby improving cycle stability and rate capacity. This conclusion provides a reference for designing high energy density lithium-ion batteries.

Concrete is more stable than filler as a false roof in a downward approach type infill quarry, but the mechanical model of a concrete false roof is not clear. As a result, there has been limited application. Therefore, it is necessary to establish the mechanical model of a concrete artificial false roof to enhance the stability of the downward approach infill quarry. This paper combines theoretical analysis, model derivation, finite element analysis and field application methods. Firstly, the basic assumptions of thin plate theory and elasticity mechanics are used as the premise to establish the differential equations of the deflection curve of the concrete thin plate false roof. Then, the three types of bending moment generation of the concrete thin plate false roof are explored. Secondly, the relationship between the location of dangerous surface and dangerous point in hard-supported weak-slab structure and soft-supported weak-slab structure is analyzed, and the type of uniform load and calculation model of concrete thin-slab false roof are improved. Finally, according to the established mechanical model of thin slab false roof, finite element analysis and field application were carried out. The results show that there are three types of deflection curve differential equations in the concrete thin slab false roof perpendicular to the strike, and three extreme points exist in the middle section of the thin slab and on both sides of the surrounding rock. The hazardous surface of the hard-supported weak-slab structure is present at the intersection of the encircling rock and the thin-slab fake ceiling, with the perilous point situated on the top of this surface. The hazardous surface of the soft-supported weak-slab structure can be found in the centre section of the thin-slab fake ceiling, with the perilous point being located at the bottom of this surface. Moreover, the damage mode for both structures is that of maximum tensile stress damage. Upon conducting a finite element analysis, the results indicate that the concrete's maximum tensile stress is significantly high.

Temperature is a crucial environmental factor that affects embryonic development, particularly for marine organisms with long embryonic development periods. However, the sensitive period of embryonic development and the role of autophagy/apoptosis in temperature regulation in cephalopods, enigmatic creatures, remain unclear. In this study, we cultured embryos of Sepiella japonica, a typical species in the local area of the East China Sea, at different incubation temperatures (18 ℃, 23 ℃, and 28 ℃) to investigate various developmental aspects, including morphological and histological characteristics, mortality rates, the duration of embryonic development, and expression patterns of autophagy-related genes (LC3, BECN1, Inx4) and apoptosis marker genes (Cas3, p53) at 25 developmental stages. Our findings indicate that embryos in the high-temperature (28 ℃) group had significantly higher mortality and embryonic malformation rates than those in the low-temperature (18 ℃) group. Furthermore, high temperature (28 ℃) shortened the duration of embryonic development by 7 days compared to the optimal temperature (23 ℃), while low temperature (18 ℃) caused a delay of 9 days. Therefore, embryos of S. japonica were more intolerant to high temperatures (28 ℃), emphasizing the critical importance of maintaining an appropriate incubation temperature (approximately 23 ℃). Additionally, our study observed, for the first time, that the Early blastula, Blastopore closure, and Optic vesicle to Caudal end stages were the most sensitive stages. During these periods, abnormalities in the expression of autophagy-related and apoptosis-related genes were associated with higher rates of mortality and malformations, highlighting the strong correlation and potential interaction between autophagy and apoptosis in embryonic development under varying temperature conditions.

Brucella abortus is a facultative intracellular Gram-negative bacterium that causes chronic persistent infections in humans and livestock. In this study, conventional bio-typing, multiple-locus variable-number tandem repeat analysis (MLVA), and whole-genome sequencing-single-nucleotide polymorphism (WGS-SNP) were used to investigate the molecular epidemiology characteristics of Brucella abortus strains in China and their relationships to world lineages. A total of 100 strains were collected from 1953 to 2013, suggesting that B. abortus circulated in China in the past five decades. Moreover, most strains were mainly distributed in the northwest area. During this period, seven biovars were found, indicating that B. abortus displayed a high diversity of biovars and that the main epidemic areas are in the northern provinces. Strains have high genetic diversity, and bruce07 is the most helpful locus for genotyping of this population. Moreover, 17 MLVA-11 genotypes were found; 13 of them are of known genotypes and four are unassigned genotypes, indicating that B. abortus in this study had several geographic origins. Still, strains from unassigned genotypes may originate from China. Many shared MLVA-16 genotypes were observed in strains from the same provinces in Northern China, which confirmed a brucellosis outbreak within northern regions. WGS-SNP analysis showed that eight Chinese strains formed a ladder-like phylogram (C. Ⅶ) with strains from nine countries, including Uganda, Iraq, Russia, Georgia, Spain, Italy, Egypt, Mongolia, and China; strains were introduced to these countries from a single source. Notably, Chinese strains were closely related to strains from Russia and Mongolia; frequent animal (cattle) trade and exchanges may promote this process. We will provide new and insightful information for strength surveillance and control of B. abortus brucellosis in China.

Practical applications of CsPbX3 nanocrystals (NCs) are limited by their poor stability. The formation of heterojunction between CsPbX3 NCs and oxides is an effective means to protect perovskite from polar solvents and other external factors. Significantly improving the stability and photocatalytic properties of the core/shell perovskite is very important for its application in photoelectric and photocatalytic technology. Here, we report the synthesis of asymmetrical CsPbBr3/TiO2 core-shell heterostructure NCs at single particle level by hot injection liquid phase synthesis and sol-gel method, where each CsPbBr3 NCs is partially covered by titanium dioxide. It is shown that the type II arrangement is generated at the heterogeneous interface, which greatly facilitates the separation of electron-hole pairs and increases the carrier transport efficiency. More crucial, due to the protection of titanium dioxide shell, the product has higher long-term stability in humid air compared with bare CsPbBr3 NCs. The asymmetrical core-shell heterostructure prepared in this study not only improves the stability of CsPbX3 NCs, but also provides some ideas for optoelectronic device applications and TiO2-based photocatalysts.

With the rapid development of MEMS (Micro-electro-mechanical Systems) fabrication technologies, manifolds microelectrodes with various structures and functions have been designed and fabricated for applications in biomedical research, diagnosis and treatment through electrical stimulation and electrophysiological signal recording. The flexible MEMS microelectrodes exhibit multi-aspect excellent characteristics beyond stiff microelectrodes based on silicon or SU-8, which comprising: lighter weight, smaller volume, better conforming to neural tissue and lower fabrication cost. In this paper, we mainly reviewed key technologies on flexible MEMS microelectrodes for neural interface in recent years, including: design and fabrication technology, flexible MEMS microelectrodes with fluidic channels and electrode-tissue interface modification technology for performance improvement. Furthermore, the future directions of flexible MEMS microelectrodes for neural interface were described including transparent and stretchable microelectrodes integrated with multi-aspect functions and next-generation electrode-tissue interface modifications facilitated electrode efficacy and safety during implantation. Finally, the combinations among micro fabrication techniques with biomedical engineering and nanotechnology represented by flexible MEMS microelectrodes for neural interface will open a new gate to human lives and understanding of the world.

Stabilization of a G-quadruplex (G4) in the promotor of the c-MYC proto-oncogene leads to inhibition of gene expression, and it thus represents a potentially attractive new strategy for cancer treatment. However, most G4 stabilizers show little selectivity among the many G4s present in the cellular complement of DNA and RNA. Intriguingly, a crescent-shaped cell-penetrating thiazole peptide, TH3, preferentially stabilizes the c-MYC G4 over other promotor G4s, but the mechanisms leading to this selective binding remain obscure. To investigate these mechanisms at the atomic level, we performed an in silico comparative investigation of the binding of TH3 and its analogue TH1 to the G4s from the promotors of c-MYC, c-KIT1, c-KIT2, and BCL2. Molecular docking and molecular dynamics simulations, combined with in-depth analyses of non-covalent interactions and bulk and per-nucleotide binding free energies, revealed that both TH3 and TH1 can induce the formation of a sandwich-like framework through stacking with both the top and bottom G-tetrads of the c-MYC G4 and the adjacent terminal capping nucleotides. This framework produces enhanced binding affinities for the c-MYC G4 relative to other promotor G4s, with TH3 exhibiting an outstanding binding priority. Van der Waals interactions were identified to be the key factor in complex formation in all cases. Collectively, our findings fully agree with available experimental data. Therefore, the identified mechanisms leading to specific binding of TH3 towards the c-MYC G4 provide valuable information to guide the development of new selective G4 stabilizers.

Different inlet structures have a significant impact on the internal flow characteristics of a solid-magnesium powder water ramjet engine. Based on the magnesium-water reaction model, a computational fluid dynamics (CFD) method is applied to establish a numerical simulation method for the internal flow field of the engine, and the internal flow characteristics of the engine under different inlet structure conditions are studied. The simulation results show that high-temperature gas can effectively promote the ignition of magnesium powder at the top of the combustion chamber, while accelerating the evaporation of the first inlet water and increasing the combustion rate of magnesium powder. The secondary inlet has the most significant effect on the temperature inside the combustion chamber. When the secondary inlet flow rate increases towards the top of the combustion chamber, it increases the amount of heat absorbed by the evaporating water at the top of the chamber, thereby reducing the temperature at the top of the combustion chamber. However, when the flow rate is low, it results in insufficient oxidizer at the top of the combustion chamber, which is unfavorable for the combustion of magnesium powder.

In order to develop novel botanical insecticides, the joint action of Ligusticum chuanxiong oil (LCO) and lemongrass oil (LO) against Aphis citricola van der Goot was determined systematically indoors and outdoors. The chemical profiles of LCO and LO as determined by gas chromatography- mass spectrometry analysis revealed that main compounds from LCO were Z-Ligustilide (44.58%) and Senkyunolide A (26.92%), and that of LO were geranial (42.16%) and neral (32.58%), respectively. The mixture of LCO and LO showed significant synergy against A. citricola, with a common-toxicity coefficient (CTC) value of 221.46 at the optimal ratio of LCO to LO (4: 1, w/w). Based on the results of solvents and emulsifiers screening, L. Chuanxiong oil · Lemongrass oil 20% emulsifiable concentrate (20% LCO · LO EC) was developed, which was confirmed to meet the requirements of a commercial pesticide by quality test. Field trials indicated that the insecticidal activity of the diluted 20% LCO · LO EC (1000 fold dilution) was comparable to conventional pesticide (20% imidacloprid EC) on A. citricola 7 days after application. Thus, the mixture of LCO and LO has the potential to be further developed as a botanical pesticide.

In this paper, we consider a fourth-order suspension bridge equation with nonlinear damping term |u_t|^m-2u_t and source term |u|^p-2u. We give necessary and sufficient condition for global existence and energy decay results without considering the relation between m and p. Moreover, when p>m, we give sufficient condition for finite time blow-up of solutions. The lower bound of the blow-up time T_max is also established. It worth to mention that our obtained results extend the recent results of Wang (J. Math. Anal. Appl., 2014) to the nonlinear damping case.

Artificial intelligence algorithms have gained widespread adoption in the field of air conditioning load prediction. However, their prediction accuracy is substantially influenced by the quality of training samples. Training samples that lack relevance to the predicted moments can introduce interference into the neural network's learning process, potentially leading to a state of local convergence during its iterative process. This, in turn, diminishes the robustness and generalization capabilities of the prediction model. To enhance the prediction accuracy of air conditioning load prediction models based on artificial intelligence algorithms, this study presents an artificial intelligence algorithm prediction model based on the method of sample similarity sample screening. Initially, the comprehensive similarity coefficient between samples is computed using the gray correlation analysis method, enriched with enhancements in information entropy. Subsequently, a subset of closely related samples is extracted from the original dataset and employed as the training dataset for the artificial intelligence prediction model. Finally, the trained artificial intelligence algorithm prediction model is deployed for air conditioning load prediction. The results illustrate that the method of screening training samples based on sample similarity effectively improves the prediction accuracy of BP neural network (BPNN) and extreme learning machine (ELM) prediction models. However, it is important to note that this approach may not be suitable for genetic algorithm BPNN (GABPNN) and support vector regression (SVR) models.

Currently, in some domestic and foreign mines, the backfill drilling pipeline experience a rupture phenomenon even when the wear degree is low. This results in a delay in production due to the filling becoming 'sick'. This paper presents, for the first time, the damage mechanism from a mechanical perspective and re-derives the anti-extrusion strength model of the backfill drilling pipeline. We investigate the influence of law on the anti-extrusion strength of pipelines from the perspective of stratum and cement ring. We then verify the theoretical and simulation results through engineering examples. The results demonstrate that the Mises stress criterion is a suitable modification principle for the anti-extrusion strength model of the backfill drilling pipeline. The anti-extrusion strength of the pipeline is related to the elastic modulus and Poisson's ratio of the stratum, and the thickness of the cement ring. It is negatively affected by the depth of the stratum. For hard strata, a cement ring with a smaller elastic modulus is suitable, while for soft stratum, a cement ring with a larger elastic modulus is recommended. When the missing angle of the cement ring is less than 60°, the stress concentration factor increases up to 2.2. The stress unloading capacity of the cement ring ranges from 32.7% to 37.8%, and optimal performance of the cement ring is achieved when it has high strength and low rigidity. The backfill filling pipeline of a copper mine abroad was destroyed due to external extrusion force exceeding its anti-extrusion strength value. The modified pipeline anti-extrusion strength model is 18.2% higher than the casing API strength value. This finding can inform the design of the backfill filling pipeline for China's kilometer-deep wells in the future.

Close to half (45.4%) of 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined on the level of broad geographic regions, literature on more in-depth coverage of the individual countries and subregions of the Asian continent is lacking. This review examines the breast cancer burden in 47 Asian countries. Breast cancer screening guidelines and risk-based screening initiatives are discussed.

This paper addresses the input coupling problem for the shape memory alloy (SMA) actuated parallel platform with completely unknown nonlinear dynamics. The problem means that in a parallel platform with multiple SMA actuators acting together, the displacement of one of the actuators will simultaneously affect the remaining actuators to change. Due to the coupling problem and nonlinear characteristics of the SMA actuators, it is not easy to control the platform to achieve bi-directional swing with completely unknown nonlinear dynamics. Therefore, a model-free adaptive sliding mode control method is proposed to improve the control accuracy of the complex motion of the platform, avoiding the complex modeling process of the SMA actuated parallel platform. Based on the model-free adaptive control (MFAC) theory, a multiple input and multiple output (MIMO) dynamic linearized mathematical model of the parallel platform is established using the online input and output data of the system. Then, a sliding mode controller is designed based on the dynamic model. A rigorous theoretical analysis proves that the proposed model-free adaptive sliding mode controller is able to stably control the SMA actuated parallel platform, and its tracking error is uniformly ultimately bounded (UUB). Finally, experiments are conducted on the established SMA actuated parallel platform. The results show that the proposed model-free controller is feasible and effective, and can control the system well to achieve the complex motion of bi-directional swing.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

The low-altitude quasi-periodic (LQP) E-region echoes observed with the upgraded HCOPAR located in Hainan Island of China (19.5°N, 109.1°E) are presented. With the interferometry technique, the interferometry equations can be developed to investigate the structures of the irregularities. The results show that the plasma structures of the LQP echoes with negative slope mainly drift southwestward almost horizontally, but they also drifted southeastward in some striations. According to the movement of the plasma structures, we find strong wind shear in the region where the LQP echoes are produced. Meanwhile, The periodicity of the LQP echoes may be related to the strength of the wind shear. It is proposed that the plasma structures are most likely produced by the Kelvin-Helmholtz instability.

Abstract- Cognitive radio (CR) play an important role in improving spectral efficiency (SE) of wireless communication, meanwhile, intelligent reflecting surface (IRS) is an effective technology to improve the secrecy performance of wireless communication system by adjusting the phase shift and amplitude of channel. Thus, we consider an IRS-aided multiple-input single-output (MISO) CR systems to enhance secrecy rate, which is consists of a single eavesdropping link, a primary network containing the primary receiver (PR), and secondary network including secondary receiver (SR) and the SR transmitter (SR-TX). Specifically, we minimize the transmit power of SR subject to secrecy capacity constraint and interference temperature (IT) constraint on PR, by jointly optimizing the beamforming vector and artificial noise (AN) constraints matrix at SR-TX as well as the phase shift matrix of IRS. Numerical results show that the different values of transmit antennas at the SR-TX and the number of IRS elements can significantly decrease the transmit power under the condition of ensuring secure communication.

Light trapping in single nanowires (NWs) are of vital importance for photovoltaic applications. However, circular NWs (CNWs) can limit its light-trapping ability due to high geometrical symmetry. In this work, we present a detailed study of light trapping in single NWs with an elliptical cross-section (ENWs). We demonstrate that the ENWs exhibit significantly enhanced light trapping compared with the CNWs, which can be ascribed to the symmetry-broken structure that can orthogonalize the direction of light illumination and the leaky mode resonances (LMRs). That is, the elliptical cross-section can simultaneously increase the light path length by increasing the vertical axis and reshape the LMR modes by decreasing the horizontal axis. We found that the light absorption can be engineered via tuning the horizontal and vertical axes, the photocurrent is significantly enhanced by 374.0% (150.3%, 74.1%) or 146.1% (61.0%, 35.3%) in comparison with that of the CNWs with the same diameter as the horizontal axis of 100 (200, 400) nm or the vertical axis of 1000 nm, respectively. This work advances our understanding of how to improve light trapping based on the symmetry breaking from the CNWs to ENWs and provides a rational way for designing high-efficiency single or self-assembled NW photovoltaic devices.

The complete genomic sequence of a Cassava common mosaic virus Linggao isolate (CsCMV-LG) was determined from cassava (Manihot esculenta Crantz) with mild leafy mosaic symptom to no symptom in China. Excluding the poly(A) tail, the CsCMV-LG genome (GenBank accession No. MT038420) is 6374 nucleotides (nts) in length, with five major open reading frames encoding a 1450-amino acids (aa) RNA-dependent RNA polymerase (RdRp), three triple gene block (TGB) proteins (231-aa, 110-aa and 95-aa), and a 229-aa coat protein (CP). Phylogenetic analysis indicated that the complete genome of the CsCMV-LG is closely related to that of CsCMV-Brazilian which has been assigned to the genus Potexvirus, but the sequence identity shared only 88.0%. Notable, the mild CsCMV-LG isolate can also infect Nicotiana benthamiana in laboratory through rub inoculation causing mild vein yellowing at 15-day post inoculation. This is the first full-length genome sequence of a distinct isolate of Cassava common mosaic virus (CsCMV) infecting cassava in Hainan, China.