Dendrite growth and parasitic reactions with liquid electrolyte are the two key factors that restrict the practical application of the lithium metal anode. Herein, a bis(benzene sulfonyl)imide based single-ion polymer artificial layer for lithium metal anode is successfully constructed, which is prepared via blending the as-prepared copolymer of lithiated 4, 4’-dicarboxyl bis(benzene sulfonyl)imide and 4,4’-diaminodiphenyl ether on the surface of lithium foil. This single-ion polymer artificial layer enables compact structure with unique continuous aggregated Li+ clusters, thus reducing the direct contact between lithium metal and electrolyte, and ensuring Li+ transport fast and homogeneous simultaneously. Based on which, the coulombic efficiency of the Li|Cu half-cell is effectively improved, and the cycle stability of the Li|Li symmetric cell can be prolonged from 160 h to 240 h. Surficial morphology and elemental valence analysis confirm that the bis(benzene sulfonyl)imide based single-ion polymer artificial layer effectively facilitates the Li+ uniform deposition and suppresses parasitic reactions between lithium metal anode and liquid electrolyte in the LFP|Li full-cell. This strategy provides a new perspective to achieve steady lithium metal anode, which can be a promising candidate in practical application.

The new energy structure needs to balance energy security and dual carbon goals, which has brought major challenges to coal-fired power plants, the pollution reduction and carbon emissions reduction of coal-fired power plants will be a key task in the future. This article proposes an optimization operation of electrostatic precipitators(ESP), based on the working mechanism and historical data of ESP, voltage-current characteristic model and outlet dust concentration prediction model are constructed by deep learning algorithm, Particle Swarm Optimization(PSO) is used to achieve the optimal energy consumption while ensuring stable outlet dust concentration. By training with historical data collected on site, accurate prediction of secondary current and outlet dust concentration of ESP has been achieved, the Mean Absolute Percentage Error(MAPE) of secondary current is less than 1.5%, and the MAPE of outlet dust concentration of ESP on the test set is less than 5.2%. Finally, the optimization experiment is carried out in a 330MW coal-fired power plants, the results showed that the fluctuation of the outlet dust concentration is more stable, and the energy saving is about 43% after optimization, according to the annual operation of 300 days, the annual average carbon reduction is approximately 2621.34 tons. This method is effective and can be applied widely.

In this paper, mineralogical and elemental geochemical characteristics of massive sulfide samples collected from Jade hydrothermal field, located in the Izena depression in the central graben of Okinawa Trough, were analyzed by means of optical microscopy, scanning electron microscopy and electron probe. The results show that the sulfide in Jade hydrothermal area can be divided into Zn-Cu-Pb rich massive sulfide and Zn-Fe rich massive sulfide. The former is composed of sphalerite, galena, anglesite, chalcopyrite and pyrite, and its formation stage can be divided into pyrite stage, sphalerite-chalcopyrite stage, anglesite stage and colloidal pyrite stage. The latter is mainly composed of sphalerite, pyrite, marcasite and a small amount of galena, which can be divided into galena stage, pyrite stage, sphalerite stage, pyrite and marcasite stage. Cu and Zn in pyrite may exist in the form of microinclusions, while Ag and Pb may exist in pyrite in the form of fine galena inclusions containing Ag. Fe and Cu may enter sphalerite in the form of ion replacement. Zn may enter chalcopyrite in the form of ion replacement, and As and Pb may be inclusions in chalcopyrite as As-bearing galena inclusions. Consistent with the previous understanding, the metal elements in the hydrothermal liquid system in Jade hydrothermal field mostly migrate with the hydrothermal fluid as sulfur complexes, and when the hydrothermal fluid mixes with seawater, the physical and chemical conditions of the fluid change, resulting in sulfide mineral precipitation. However, the chemical structure of chalcopyrite is still controversial, which restricts the understanding of the substitution mechanism of trace elements during chalcopyrite precipitation.

Soybean is one of the world’s most economically significant crops and is widely utilized as an essential source of vegetable protein and edible oil. Cultivated soybean is domesticated from its annual counterpart, wild soybean, which is considered valuable germplasm for soybean breeding. However, wild soybean accessions generally produce seeds with impermeable coats, a trait known as hard seededness (HS), which is beneficial for long-term seed survival but is undesirable for the uniform water absorption and germination of seeds, thus limiting the utilization of wild soybeans in breeding. However, moderate HS can isolate the embryo from the surrounding environment and is thus beneficial for long-term seed storage and germplasm preservation. The HS trait is primarily associated with the structure and chemical composition of the seed coat. However, its development is also influenced by various environmental conditions, such as water and temperature. Genetic analysis has revealed that HS of soybean is a complex quantitative trait controlled by multiple genes or minor quantitative trait loci (QTL), with many QTLs and several causal genes currently identified. Investigating the physiological and molecular mechanisms underlying this trait is crucial for soybean breeding, production, and food processing. For this article, the literature was reviewed and condensed to create a well-rounded picture of the current understanding of internal and external factors, QTLs, causal genes, and the regulatory mechanisms related to the HS of soybean, with the aim of providing reference for future research and utilization of this trait.

Teaching, learning, research, and development are all supported in a favorable atmosphere at the University of Lagos (UNILAG). The wetland systems made up of freshwater that are extremely biodiverse makeup about 10% of the total land area. Flooding, deforestation, excessive sedimentation, blockages to streams, abuse, overuse, and invasion of wetlands are some of the recent environmental challenges that the university faced. Urban heat island impacts, contaminants in the air, wetland degradation, social issues including stress, and a detachment from nature are all major concerns. With the green corridor behind the faculties of law and management science serving as a model supported by sustainability as a true foundation for UNILAG's campus landscapes, this article investigates the sustainable restoration of wetlands within the boundaries of the university. The use of qualitative techniques was employed, utilizing the Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis. Additionally, a geospatial mapping of the wetlands and tributaries that connect the Lagos Lagoon was conducted to evaluate the intrinsic ecological goods and services through a series of analytical steps, beginning with an analysis of the land area, current biodiversity, hydrology, and its potential through landscape mapping and analysis. The biophysical setup, landscape features, climatic data analysis, the ecological goods and services derived from the wetlands, and the records of flooding and rainfall are all included in the geospatial evaluation and analysis. The educational institution's site planning for the remediation of its wetlands takes into account the actual evolution of the area's drainage network. Throughout the wetlands, low carbon emissions are generated by off-road bike lanes, trails for walking, and raised hardwood platforms. Combining native plant species and park furniture, the academic landscape atmosphere will be improved in each of the wetlands and aesthetic values. the country's "University of First Choice" and its biophysically restored wetlands will help illuminate the landscape while the green corridors have an innate ability to attract human affinity within the academic community. All of these elements are implemented following an environmentally friendly landscape planning, management, design model, and enforcement process.

In the recent decade, Building Information Modelling (BIM) has widely been adopted in the Architecture, Engineering and Construction (AEC) industry and completely upended the way we build. While BIM continues gain momentum in the industry, it has also attracted increasing attentions from researchers. However, most of the current study focuses on reviewing BIM for management, BIM for green building, BIM for infrastructure and BIM for Facilities Management (FM). There are few studies about Global BIM review and to discuss their complex inter-connections. In this study, we adopted a scientometric analysis method to review global BIM research from 2004-2019. A total of 1455 scholarly bibliographic records obtained from Web of Science Core Collection databased were established for the analysis. This study has identified the top productive and influential researchers, research institutes, regions/countries, subject categories and journals in the BIM field. In addition, 11 clusters of Global BIM research were also identified including construction project, green BIM, construction safety planning, automated IFC-based workflow and so on. Authors distinguished 11 clusters of global BIM research into 3 stages, namely formulating stage, accelerating stage and transforming stage. Furthermore, authors reviewed the BIM policy of Singapore and observed there is a co-production relationship between evolution of BIM policy and global BIM research. These findings provide valuable information for researchers, practitioners and policy makers by visualizing the current progress in the research field of BIM and highlighting future research needs.

We derive an ab initio equilibrium statistical mechanics of the gas-liquid-solid contact angle on planar periodic, monodisperse, textured surfaces subject to electrowetting. To that end, we extend an earlier theory that predicts how advance or recession of the contact line amount to distinct first-order phase transitions of the filling state in the ensemble of nearby surface cavities. Upon calculating the individual capacitance of a cavity subject to the influence of its near neighbors, we show how hysteresis, which is manifested by different advancing and receding contact angles, is affected by electrowetting. The analysis reveals nine distinct regimes characterizing contact angle behavior, three of which arise only when a voltage is applied to the conductive liquid drop. As the square voltage is progressively increased, the theory elucidates how the drop occasionally undergoes regime transitions triggering jumps in the contact angle, possibly changing its hysteresis, or saturating it at a value weakly dependent on further voltage growth. To illustrate these phenomena and validate the theory, we confront its predictions with four data sets. A benefit of the theory is to forsake trial-and-error when designing textured surfaces with specific contact angle behavior.

Environmental arsenic exposure is closely related to nerve damage, and chronic arsenic exposure will cause neurotoxicity and damage the nervous system. Recent research suggests miR-27a-3p is required for the progression of certain neurodegenerative and neuropsychiatric disorders. Nonetheless, the precise impact of miR-27a-3p on neuron functioning in the hippocampus remains unclear. In this investigation, models were established using arsenite-treated cells and mice to investigate this aspect. After male C57BL/6J mice were exposed to arsenite (0, 0.5, 5 or 50ppm) in drinking water for 48 weeks, Nissl staining, terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling (TUNEL) assay, and Hematoxylin-Eosin (H&E) stainingrevealed an arsenite-induced neuronal injury and apoptosis. For 6 μmol/L arsenite-treated HT22 cells, arsenite decreases miR-27a-3p levels and activated the FTO/DRP1 pathway. For arsenite-treated HT222 cells, the increases of FTO and DRP1 and p-DRP1 (Ser616) levels induced by arsenite were reversed by miR-27a-3p mimic.Furthermore, the increases of neuronal apoptosis and pro-apoptotic protein (Bax and Cleaved-caspase 3) levels as well as decreased levels of anti-apoptotic proteins Bcl-2 induced by arsenite were reversed by miR-27a-3p mimic in HT22 cells. Moreover,the decreases of MMP induced by arsenitewas reversed by miR-27a-3p mimic. Overall, in HT22 cells exposed to arsenite, miR-27a-3p mitigates neuronal apoptosis, suggesting its potential utility in addressing arsenite accumulation and associated with brain pathologies. Dysregulated expression patterns of miRNAs in the hippocampus have emerged as pivotal elements in neuronal apoptosis linked to neurological dysfunction, with miR-27a-3p specifically implicated in apoptotic pathways.

Remote sensing (RS) as a landscape planning and management tool for socio-cultural diversity and inclusiveness in protected(reserved) areas through monitoring of the land-use changes, settlement/living patterns, predominant trades/socio-economic activities in the urban-rural locations, and the demography in Sub-Saharan Africa (SSA). The eighteen federal governments recognized nature reserves in Nigeria being the giant of Africa because of their green landscapes, rich biodiversity, and human resources. This study aimed to explore the application of remote sensing to assess the extent of land degradation and encroachment in the 18 recognized national parks in Nigeria. A review of the protection of national parks using remote sensing and monitoring the trend of national park invasions which could either be natural or man-made. The study is in line with the United Nations SDG Goal 15: Life on Land- “Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss”. Located in the West Africa subregion lying on Latitude: 9° 04' 39.90" N (9.077899) and Longitude: 8° 40' 38.84" E (8.677599), with an estimated population of over 220,000,000 people. This study through an intensive review of various literature adopted a mixed approach for the analysis and assessment of the geospatial data, the updated aerial photographs obtained through the Landsat imageries (Google Earth Pro, 2023), and the use of GIS for Geospatial analysis which enables the collection and analysis of spatial and geographic data gathering land use/land covers (LULC) maps, soil type, and elevation maps. While exploring the geophysical ecology and biodiversity conservation of some selected national parks in Nigeria, while also providing cost-effective alternatives for biodiversity monitoring and conservation strategy development. A review of national implementation strategies on biodiversity conservation with the deployment of remote sensing technologies, it is now feasible to obtain large details of the surface of the planet without conducting arduous field activities with the assistance of the availability of multi-date, multi-resolution, multi-sensor aerial information to help prevent for encroachment, loss, and degradation of the natural landscapes.

Broadband reverse saturable absorption is systematically investigated via Z-scan, transient absorption spectrum (TAS). The excited state absorption and negative refraction of Orange IV are observed in the Z-scan experiment at 532 nm. Meanwhile, two-photon induced excited-state absorption and pure two-photon absorption are observed at 600 nm and 700 nm with the pulse width of 190 fs, respectively. An ultrafast broadband absorption in visible wavelength region is observed via TAS. The different nonlinear absorption mechanism at multiple wavelengths is discussed and interpreted from the results of TAS. In addition, the ultrafast dynamics of negative refraction in the excited state of Orange IV is investigated via degenerate phase object pump probe, from which the weak long-lived excited state is extracted. All studies indicate that Orange IV has the potential to be further optimized into a superior broadband reverse saturable absorption material and also has certain reference significance for the study of optical nonlinearity in organic molecules containing azobenzene groups.

Reducing the hardness of hard water is of great concern nowadays due to some adverse effects on water pipes, boilers and soap consumption. Using the method of biomineralization to precipitate calcium and magnesium ions to become carbonate minerals was one of the most important innovations for reducing the hardness of hard water. The present study sought to explore the physical and chemical conditions of carbonates bio-precipitation and the potential use of Bacillus licheniformis SRB2 strain (GenBank: KM884945.1) isolated from sludge sample of Moshui River (Shandong University of Science and Technology, Qingdao, China) in reducing the hardness of hard waters by the induction of carbonate minerals. In this study, B. licheniformis SRB2 strain was identified based on the morphological, biochemical and 16S rDNA gene sequence homology analysis. The carbonate minerals induced by B. licheniformis bacteria in the liquid culture medium with 3% NaCl and Mg/Ca molar ratio of 0, 6, 8, 10 and 12 were investigated. The culture medium was inoculated with the bacterial liquid seed was set as the experimental group and the other culture medium was inoculated with the same volume of distilled water was set as the control group. The mineral phases, micromorphologies, and crystal structures were analyzed using X-ray powder diffraction, scanning electron microscope, energy dispersive X-ray detector, high resolution transmission electron microscopy and selected area electron diffraction. The bacterial concentrations and pH values of the solution were measured by a spectrophotometer and a pH meter, respectively. The urease secreted by B. licheniformis SRB2 was found to greatly increase the pH values of the liquid medium, which favored the formation of calcium carbonate.As a result, Mg²⁺ and Ca²⁺ ion concentrations decreased greatly due to the biomineralization of calcium carbonate and nesquehonite minerals in the presence of B. licheniformis SRB2 bacterium. There were only few calcium carbonates and no nesquehonite minerals in the control groups. It was also found that the minerals of nesquehonite induced by B. licheniformis SRB2 had a phenomenon of preferred orientation. What was more, even though Mg²⁺ ions inhibited the precipitation of Ca²⁺ ions, but under the action of B. licheniformis SRB2 bacteria, the inhibition effect was significantly declined. The bio-precipitation of calcium carbonate and nesquehonite minerals may represent a new method of pretreatment for the hardness reduction of hard water. The accomplished study is of certain interest for interpretation of the carbonates biomineralization in natural environment, and maybe also has a certain application value in the former processing of hard water

Digital infrastructure is the basic guarantee for digital transformation, it is of practical significance to discuss how to effectively use digital infrastructure construction to promote the digital transformation of tourism enterprises. This paper examines the impact of digital infrastructure construction on tourism enterprises based on the "Broadband China" policy as a quasi-natural experiment. A-share tourism listed enterprises from 2010 to 2021 are studied using the double difference method. Findings indicate that digital infrastructure construction positively and significantly influences the digital transformation of tourism enterprises, driven by digital leadership and innovation capabilities. State-owned, small-scale, and high-growth tourism enterprises benefit more from this transformation. The results suggested that the state should develop differentiated digital infrastructure plans based on the specific conditions of different tourism enterprises. Additionally, tourism enterprises should enhance digital leadership and innovation capabilities through strategic changes and digital applications to amplify the impact of digital infrastructure on their transformation.

The thesis proposes a argument that a mass point moving in a horizontal circle on the Earth's surface can generate a radial centrifugal force of the Earth's center of mass, thus realizing an unconventional anti-gravity path. And through the theoretical analysis of the difference in the distribution of gravitational acceleration at different latitudes caused by the rotation of the earth, and the centrifugal force of a mass point moving in a horizontal circle on the earth's surface is analyzed, the validity of the argument is demonstrated. At the same time, the paper puts forward two possible basic principles, and makes theoretical analysis and demonstration. Conceive of the concrete experimental verification of principle two is proposed. Four technical schemes for antigravity ascent are proposed and basic analysis is made. On the premise of not fully considering the practical technical ability, it is theoretically proved that three of them have realistic operability and development potential. In theory, this paper opens up a different way of anti-gravity for human beings, which will bring new ideas and prospects for human beings to get rid of the bondage of gravity.

In this paper, the Hafele‐Keating experiment and the geostationary orbit satellite of related physics problems of are analyzed and discussed in detail. If researchers read the paper and think about it, It will be found that the Hafele‐Keating experiment and the geostationary satellite problem prove that some of the core ideas and theories of relativity are seriously wrong. Isnʹt that a very serious problem in physics? Canʹt this cause the academic circles to pay great attention to it? Isnʹt this worthy of in‐depth analysis and research? The core of the paper is to point out that there are problems with the space concept and the reference system theory of classical physics and relativity, And that would bring up a whole host of physics problems. It takes a concerted effort from the academic community, Do furtherin‐depth analysis and research. Strive forthe further discovery and perfection of physics theory.

The degree of ore rock fragmentation of mine blasting is an important index for evaluating the effect of engineering blasting. In order to study the effect of millisecond delayed blasting on the internal fragmentation of the ore rock, LS-DYNA numerical simulation software was used to obtain the damage characteristics of the ore rock in the blasting area using the RHT model. The Mohr-Coulomb strength damage criterion was applied to analyze the internal stress state of the ore rock, and the effects of 25ms, 50ms and 75ms delay time conditions on ore rock fragmentation were studied. The results show that, within a certain range of delay time, the degree of rock fragmentation increases with the increase of delay time. The stress state in the ore rock due to blasting is strengthened with the increase of delay time in the direction of the blast hole, which shows that the stress concentration is strengthened from the excavation face to the interior of the ore rock. The damage and the degree of fragmentation show a characteristic relationship of 25ms＜50ms＜75ms, which is verified by carrying out blasting experiments on site.

To develop a lower-cost, excellent performance, and environmentally friendly phe-nol-formaldehyde (PF) resin, soybean meal was used to modify PF resin, and soybean meal-phenol-formaldehyde (SMPF) resins were prepared. Their physicochemical properties and curing performance were investigated, showing that SMPF resins have higher curing tempera-tures than PF resin. The Fourier transform infrared spectroscopy (FTIR) results indicated that the cross-linking reaction occurred between the amino groups of soybean protein and the hy-droxymethyl phenol. Moreover, with the addition of soybean meal, the viscosity of SMPF in-creased while the gel time decreased. It is worth mentioning that SMPF-2 resin has favorable viscosity, short gel time, low curing temperature (135.78 °C), and high water resistance and bonding strength (1.01 MPa). Finally, all the plywoods bonded with SMPF resins have good water resistance and bonding strength, which could meet the Standard (GB/T 17657-2013, type I) for plywood. The optimized SMPF resins showed the potential application to replace part of PF resin in the wood industry.

In (Semigroup Forum 77: 325-338, 2008) Mahmoudi M. and Renshaw J. solved a study that covers of cyclic $S$-acts over monoids. This article is an attempt to initiate the covers of finitely generated $S$-acts. We give a necessary and sufficient condition for a monoid to have the properties that $n$-generated $S$-acts have strongly flat covers, Condition $(P)$ covers and projective covers. The main conclusions extend some known results. We show also that Condition $(P)$ covers of finitely generated $S$-acts are not unique, unlike the situation for strongly flat covers. Additionally, we demonstrate that the property of Enochs' $\mathcal{X}$-precover of $S$-act $A$, where $\mathcal{X}$ denotes a class of $S$-acts that are closed under isomorphisms.

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.

The COVID-2019 disease caused by the SARS-CoV-2 virus (aka 2019-nCoV) has raised significant health concerns in China and worldwide. While novel drug discovery and vaccine studies are long, repurposing old drugs against the COVID-2019 epidemic can help identify treatments, with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter Phase 3 or 4 or can be used directly in clinical settings. In this study, we presented a novel network based drug repurposing platform to identify potential drugs for the treatment of COVID-2019. We first analysed the genome sequence of SARS-CoV-2 and identified SARS as the closest disease, based on genome similarity between both causal viruses, followed by MERS and other human coronavirus diseases. Using our AutoSeed pipeline (text mining and database searches), we obtained 34 COVID-2019-related genes. Taking those genes as seeds, we automatically built a molecular network for which our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules and finally suggested 78 drugs to repurpose. Following manual filtering based on clinical knowledge, we re-prioritized 30 potential repurposable drugs against COVID-2019 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide) . We hope that this data can provide critical insights into SARS-CoV-2 biology and help design rapid clinical trials of treatments against COVID-2019.

The valley pseudospin properties of electrons in two–dimensional hexagonal materials result in lots of fascinating physical phenomena, which opens up the new field of valleytronics. The valley-contrasting physics aims at distinguishing the valley degree of freedom based on valley–dependent effects. Here, we theoretically demonstrate that both of the valley–selective high harmonic generation and valley–selective electronic excitation can be achieved by using an orthogonal two–color (OTC) laser field in gapped graphene. It is shown that the asymmetry degrees of harmonic yields in the plateaus, cutoff energies of generated harmonics and electron populations from two different valleys can be precisely controlled by the relative phase of the OTC laser field. Thus the selectivity of the dominant valley for the harmonic radiation and electronic polarization can be switched by adjusting the relative phase of the OTC laser field. Our work offers an all–optical route to produce the valley–resolved high harmonic emissions and manipulate the ultrafast valley polarization on a femtosecond timescale in condensed matter.

The intense motion of a ship can greatly impacts the comfort of crew members and the safety of the vessel. Therefore, accurately estimating and predicting ship attitudes has become an important issue. This paper introduces the latest development in functional deep learning model called DeepOnet. It takes wave height as input and ship motion as output, using a cause-to-result prediction approach. The modeling data used in this study is sourced from publicly available experimental data from the Iowa Institute of Hydraulic Research. Firstly, parameters system tuning was conducted for the neural network's hyperparameters to determine the appropriate combination of parameters. Secondly, the DeepOnet model for wave height and multi-degree-of-freedom motion was established, and the influence of increasing time steps on prediction accuracy was examined. Finally, a comparison was made between the DeepOnet model and the classical time series model LSTM. It was found that the DeepOnet model had a 10-fold improvement in accuracy for roll and heave attitudes. Moreover, as the forecast duration increased, the advantage of DeepOnet showed a trend of strengthening. As a functional prediction model, DeepOnet provides a new promising tool for very short-term prediction of ship motion.

A PLS-based quality prediction method is proposed for batch processes using two-dimensional extended windows. To realize the adoption of information in the direction of sampling time and batch, a new definition region of support (ROS), k-i-back-extended region of support (KIBROS), is proposed to establish the extended window, which including the data of the previous sampling times in the same batch, the data of the same sampling time in the historical batches, the data of the previous sampling times in the historical batches and the data of the later sampling times in the historical batches. According to these regions of support, extended windows are established, and different models are proposed based on the extended windows for batch processes quality prediction. Further, using a typical batch process as an example, the injection molding process, the proposed quality prediction method is experimentally verified, proving that the proposed methods have higher prediction accuracy than the traditional method and the prediction stability is also improved.

This study examined the last four decades of the existing academic literature related to the environmental impacts of using cover crops in agricultural production systems. Data were collected from the Web of Science database, resulting in a sample of 3,246 peer-reviewed articles published between 1980 and 2021. We combined two advanced scientometrics analysis software (i.e., CiteSpace 6.0.R1 and Gephi 0.9.2) to identify the trajectory of the literature, hotspots, and frontiers. We developed authorship-, institution-and country-levels networks to examine academic cooperation over the last forty years. Our findings revealed that the number of peer-reviewed outputs documenting the environmental effects of cover crops has consistently increased, with a notable rise in publications between 2015 and 2021. Eighteen salient research topics were identified in the literature, including winter cover crops' effects on soil health, cover crops' effects on nitrous oxide emissions, and the relationship between cover crops and nitrate leaching. Based on the citation-clustering analysis, the trajectory of the literature may be divided into three stages. Studies in Stage 1_A (1980-2000) mainly assessed the role of cover crops in nitrogen management. In Stage 1_B (2001-2010), the research evaluated the impact of using different cover crop mixtures on farming systems. In Stage 2 (2011-2021), studies primarily addressed the environmental impacts of cover crops, particularly their effects on physical and chemical soil properties. Finally, the countries with the most outputs were the United States, Brazil, and Spain. The U.S. Department of Agriculture-Agricultural Research Service was the main contributor to the literature on the environmental impacts of cover crops.

Recently, there has been a growing interest in distributed edge computing resource scheduling. For example, application scenarios such as intelligent traffic systems and Internet of Things(IoT) intelligent monitoring require the scheduling and migration of distributed resources. Distributed resource scheduling needs to consider the cost of resource scheduling, with the primary goal of finding the optimal strategy among various feasible solutions. There are different definitions for optimization objectives in different application scenarios, such as cost, transmission delay, energy consumption, etc. Current research mainly considers the optimization problem of local resource scheduling but needs more consideration of global resource scheduling. This paper defines a global resource scheduling problem for distributed edge computing and proves that the problem is NP-Hard. A heuristic solution strategy based on the Ant Colony Algorithm(ACO) was proposed, and Particle Swarm Optimization(PSO) was used to optimize the parameters of the ACO. Finally, an experimental comparative analysis was conducted to demonstrate that the algorithm proposed in this paper has good accuracy and iteration cost performance.

The environmental policy is compelling industries to treat their wastewater to a level that can be released into the domestic sewer system or even for reuse. However, many industrial branches are lacking space for traditional wastewater plant. Hence, electrokinetics wastewater treatment is a viable alternative as it is fast and does not require large space. However, the electrokinetics wastewater treatment is still mostly tested in the laboratory. In the current study, a prototype of electrokinetics wastewater treatment industrial-size device has been designed, constructed and tested under real conditions. In this paper the device is described and the results obtained from the operation of the device are presented and discussed.

Amid escalating urbanization, devising rational commercial space layouts is a critical challenge. Leveraging machine learning, this study uses a Back-propagation (BP) neural network to optimize commercial spaces in Weinan City's central urban area. The results indicate an increased number of commercial facilities with a trend of multi-centered agglomeration and outward expansion. Based on these findings, we propose a strategic framework for rational commercial space development emphasizing aggregation centers, development axes, and spatial guidelines. This strategy provides valuable insights for urban planners in small and medium-sized cities in the Yellow River Basin and metropolitan areas, ultimately showcasing the power of machine learning in enhancing urban planning.

Classifying network flow subsequences in an Industrial IoT gateway is an effective method for identifying Industrial IoT faults. This paper proposes a subsequence classification algorithm SSGBUL-IKNN based on unsupervised learning encoding to address the problem of low classification accuracy. Firstly, we built a network module based on unsupervised learning to encode the flow sequence of the Industrial IoT gateway. In the encoding module, a subsequence calibration algorithm controls the increasing error during the coding process. Then, the specific fault type is obtained through an improved KNN classification algorithm based on the indication distance source from the integrated coding sequences converted by multi-dimensional network flow sequences. The test result on three Industrial IoT datasets of a sewage treatment plant shows that the accuracy of SSGBUL-IKNN in this paper exceeds 92%, significantly higher than the algorithm DTW and TSF. It reaches the classification requirements of Industrial IoT fault diagnosis.

This study investigates the impact of specimen size on the mechanical properties of wood, specifically focusing on compression strength, elastic modulus, and Poisson's ratio. Compression tests were conducted using three different specimen sizes (20mm×20mm×30mm, 40mm×40mm×60mm, 60mm×90mm×90mm) in the longitudinal, radial, and tangential directions. Mechanical parameters, failure mechanisms, load-displacement curves, and stress-strain relationships were systematically analyzed for each size. The study also evaluated the influence of specimen size on the accuracy of finite element numerical simulations by utilizing the obtained mechanical parameters. The results reveal a significant correlation between compressive strength and specimen size, indicating a decrease in compressive strength with increasing specimen size. Conversely, elastic modulus and Poisson's ratio exhibit less sensitivity to variations in specimen size. Notably, parameters derived from small-sized specimens (20mm×20mm×30mm) exhibited substantial errors, while those obtained from medium-sized (40mm×40mm×60mm) and large-sized specimens (60mm×90mm×90mm) demonstrated greater reliability, providing precise results in finite element numerical simulations.

Mediterranean coastal lagoons and their peripheral areas often provide a collection of habitats for many species, and they often face significant threats from anthropogenic activities. Diverse human activities in such areas directly affect the spatio-temporal dynamic of surface water and its ecological characteristics. Monitoring the surface water dynamic, and understanding the impact of human activities are of great significance for coastal lagoon conservation. The Regional Natural Park of Narbonne includes a typical Mediterranean lagoon complex where surface water dynamic and its potential link with local diverse human activities has not yet been studied. In this context, based on all the available Landsat images covering the study area during 2002-2016, this study identified the water and non-water classes for each satellite observation by comparing three widely used water indices (i.e., NDVI, NDWI and MNDWI) and using the Otsu method. The yearly water frequency index was then computed to present the spatio-temporal dynamic of surface water for each year, and three water dynamic scenarios were also identified for each year: permanent water (PW), non-permanent water (NPW) and non-water (NW). The spatial and inter-annual variation in the patterns of the three water scenarios were characterized by computing the landscape metrics at scenario-level quantifying area/edge, shape, aggregation and fragmentation. Finally, the quantitative link between different land use and land cover (LULC) types derived from the LULC maps of 2003, 2012 and 2015 and the surface water dynamic scenarios was established in each of the 300 m x 300 m grid cells covering the study area to determine the potential impact of human activities on the surface water dynamic. In terms of the inter-annual variation during 2002-2016, PW presented an overall stability, and NPW occupied only a small part of the water surface in each year and presented an inter-annual fluctuation. NPW had a smaller patch size, with lower connectivity degree and higher fragmentation degree. In terms of spatial variation during 2002-2016, NPW often occurred around PW, and its configurational features varied from place to place. Moreover, PW mostly corresponded to natural lagoon, and salt marsh (as a part of lagoons), and NPW had a strong link with arable land (agricultural irrigation) and salt marsh (salt production), sand beach/dune, coastal wetlands and lagoon for the LULC maps of 2003, 2012 and 2015. However, more in-depth analysis is required for understanding the impact of sand beach/dune, coastal wetlands and lagoon on surface water dynamics. This study covers the long-term variations of surface water patterns in a Mediterranean lagoon complex having intense and diverse human activities, and the potential link between LULC types and the water dynamic scenarios was investigated on different dates. The results of the study should be useful for environmental management and protection of coastal lagoons.

Buckling defect will appear on the outer surface of the deformed ring during constrained ring rolling (CRR) of aluminum alloy thin wall conical ring with inner high ribs (AATWCRIHR), if the geometrical dimension of the ribs doesn't match the wall thickness. To avoid the buckling defect, a quantitative method for characterizing the degree of the buckling defect is proposed using the area of buckling profile. Then an orthogonal experimental scheme was designed taking the width of the middle rib, thickness of wall, and height of the middle rib as design variables and defining the area of buckling profile as optimization objective. Subsequently, a quadratic polynomial response surface model was established by combining the optimization algorithm with the finite element method (FEM), and the geometrical dimension of the middle ribs of the deformed AATWCRIHR is optimized. Also the optimal parameter combination to minimize the area of buckling profile is obtained and verified using FE simulation. Results show that the AATWCRIHR after optimization doesn’t generate the buckling defect during constrained ring rolling, and it is proved that the quantitative buckling defect representation method and the optimization design method based on the response surface model and the finite element simulation results are feasible for the constrained ring rolling process of the AATWCRIHR.

To estimate the progressive collapse resistance capacity of a multi-column frame tube structure with the assembled truss beam composite floor (ATBCF), the pushdown analysis, and the nonlinear dynamic analysis as well, are conducted for such a structure by using the alternate load path (ALP) method. The bearing capacities of the remaining structures at three different work conditions, which are the side middle column failure, the edge middle column failure, and the corner column failure, are individually studied, and the collapse mechanism for the remaining structures is analyzed from the aspects of the internal force redistribution and the failure mode of the second defense line. Simultaneously, the influence of the column failure time on the dynamic response of the remaining structure and the dynamic amplification coefficient are discussed. The results show that the residual bearing capacity of the remaining structure with the bottom corner column failure is higher than that of the one with the side or edge middle column failure, while the latter has a stronger plastic deformation capacity. When the ALP method is adopted to operate the progressive collapse analysis, it is reasonable to take the column failure time as 0.1 times of the first-order vertical vibration period of the remaining structure, and it is suitable to set the dynamic amplification coefficient as of 2.0, which is the ratio of the maximum dynamic displacement to the static displacement of the remaining structure under the transient loading condition.

In this study, seventeen faceted gem-quality chrysoberyls exhibiting an attractive canary yellow color were investigated by a series of gemological, spectral, and chemical methods. Microscopic observation reveals distinct growth lines and inclusions, including CO2 fluids, carbon, and mineral crystals such as calcite, quartz, sillimanite, and mica, identified by the Raman spectrum. The FTIR spectrum exhibits the 2405 and 2160 cm-1 feature peaks and a 3223 cm-1 peak in all samples, which can be accompanied by the 3112 cm-1 shoulder, 3301, and 3412 and 3432 cm-1 peaks. The UV-Vis spectrum shows a Fe-related peak at 440 nm, along with the 650–660 nm band and the absorption band in the blue zone of the visible light. The chemical results of EDXRF reveal a V-poor, Cr-poor, and Fe-rich feature. The spectral and chemical results could contribute to explaining the origin of the canary yellow color, which originates from the abundant amount of Fe with very little influence from Cr or V.

Pre-existing fracture and secondary cracks in rock mass are formed by natural power, such as magma condensed to igneous rocks and tectonic movement. The orientation and inclination of these fractures obey certain laws relating to the stress, temperature, minerals, water and so on. Therefore, cracks react differently under the same external loading on the condition of various inclination, fissure apertures, stiffness and joint roughness. To simulate the crack propagation, experiments on hollow cylinder cut by one oblique interface mimicking single fracture accumulated numerous data discovering the failure criterion in accordance with the Mohr-Coulomb criterion. And theory on the Terzaghi’s effective principle take an essential role in controlling the behavior of triggering fault. This paper introduced a series of oblique plane cutting the cylinder regarded as fractures at different inclination to concentrate on how the fracture characteristics effect the stress and strain distribution inside the specimen, especially, the relationship between displacement and water head. The key point of this numerical simulation is coupling the solid phase and the fluid phase, specifically, the mechanic and seepage field. According to the statics, curves referring to deformation and water head could be described as increasing lines. Besides, simulation on coupling solid phase and fluid phase can supply crucial evaluation on activating existing fault, and thus predicting induced seismicity in reservoirs or estimating damage in shale gas exploration.

In this paper, a new axial-type magnetic gear with auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AFS-AMG, it has the higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of proposed AFS-AMG are elaborated. Then, the mapping relation between the radial-type magnetic gears (RMGs) and AMGs are elucidated. Compared to its counterpart in RMGs, AFS-AMGs achieve small size. Then, the geometrical parameters of AFS-AMGs are optimized to obtain the better electromagnetic performances, where the torque density per volume and per PM volume is adopted as the evaluation standard. Finally, three different AMG topologies are constructed in finite element analysis (FEA) software for comparison. It is proven that the AFS-AMG has the largest torque density per volume and per PM volume.

Earth observation satellites can capture images of specific areas in Earth's orbit based on user requirements. Despite the high demand for satellite imagery, satellites remain a scarce resource. When there are many observation tasks that are large and dense, they may interfere with each other due to satellite mobility. To address this issue, a multi-satellite scheduling algorithm based on a task merging mechanism has been proposed. This paper proposes a two-stage approach to the problem: task merging phase and merging task scheduling phase. The task merging phase introduces two methods based on Mean Shift and Complete Graph to generate the merging task set. In the merging task scheduling phase, a multi-satellite scheduling algorithm based on merging tasks is employed to solve the problem. Finally, certain measurement experiments suggest the effectiveness of the algorithm.

Nanoparticle (NP)–surfactants formed by the self-assembly of NPs and end-functionalized polymers at the hydrophilic/hydrophobic interface have a wide range of applications in many fields. In this study, the influence of density of amino groups, NPs dimension and pH on the interaction between end-functionalized polymers and NPs were extensively investigated. Single amino-terminated polystyrene (PS-NH2, Mw ≈ 0.6k, 2.5k, 3.5k, 3.9k) and diamino-terminated polystyrene (H2N-PS-NH2, Mw ≈ 1.1k, 2.8k) were prepared using reversible addition–fragmentation chain transfer polymerization and atom transfer radical polymerization. NPs with different dimensions (zero-dimensional carbon dots with sulfonate groups, one-dimensional cellulose nanocrystals with sulfate groups and two-dimensional graphene with sulfonate groups) in the aqueous phase were added into the toluene phase containing the aminated PS. The influence of pH and the molecular weight of amino-terminated PS on the interfacial tension between two phases were investigated. The results indicate that aminated PS exhibited the strongest interfacial activity after compounding with sulfonated NPs at a pH of 3. Terminating PS with amino groups on both ends leads to better performance in in reducing the water/toluene interfacial tension than modifying the molecular structure of PS on a single end. The dimension of sulfonated NPs also contributed significantly to the reduction of the water/toluene interfacial tension. The minimal interfacial tension was 4.49 mN/m after compounding PS-NH2 with sulfonated zero-dimensional carbon dots. Molecular dynamics simulation on the evolution of the water/toluene interface in the presence of sulfonated carbon dots and H2N-PS-NH2 revealed that these opposite charged substances moved towards the interface in an extreme short time and orderly assembled in a thermodynamic equilibrium.

Inflammation associated endothelial dysfunction represents a pivotal contributor to atherosclerosis. Increasingly evidence has demonstrated that interleukin 1 receptor (IL1-R) / toll-like receptor (TLR) signaling participated in the development of atherosclerosis. Previous studies indicated the therapeutic potential of anti-inflammatory therapy in anti-atherosclerosis. The present study examined the effect of IL-1R-associated kinase 1 and 4 inhibitors (IRAK1/4i) in regulating endothelial dysfunction. IRAK1/4i showed little endothelial toxicity at concentrations from 1 to 10 μM. Inhibition of IRAK1/4 alleviated endothelial activation induced by LPS in vitro evidenced by attenuated monocyte adhesion to the endothelium. Mechanistically, blockade of IRAK1/4 ameliorated the transcriptional activity of NF-κB. Taken together, our findings demonstrated that dual inhibition of IRAK1 and IRAK4 attenuates endothelial dysfunction, suggesting pharmaceutical inhibition of IRAK1/4 might be a potential strategy to combat endothelial dysfunction and atherosclerosis.

The recyclable paper based on photochromic materials not only reduces the pollution in the paper manufacture process, but also reduces the pollution caused by the use of ink, which receives wide attention. In this paper, a serial of PMoA-PWA/ZnO/PVP hybrid films which had different ratio of PMoA/PWA was prepared by the ultrasonic composite method. The results indicated that the hybrid film prepared when the ratio of PMoA to PWA was 3 had the best photochromic performance. In this system, ZnO was the photosensitizer while PMoA/PWA was the chromophore. The photochromic mechanism of PMoA-PWA/ZnO/PVP hybrid film was based on the photogenerated electron transfer mechanism. ZnO generated photoelectron under the excitation of visible light, then PMoA and PWA obtained the photoelectron and produced photoreduction reaction to generate heteropolyblue. The visible light photochromic paper was prepared by loaded PMoA-PWA/ZnO/PVP hybrid film (A3) on A4 paper. Application test showed that the prepared paper had extremely stable, excellent and reversible visible light photochromic properties, whether it was printing patterns or words and could replace the ordinary paper to realize the reuse of paper.

With the aging of China's population, the problem of pension security has become more and more prominent, and whether delayed retirement can effectively alleviate the pension fund gap and ensure the sustainability of the pension fund has become the focus of social concern. This study predicts the income and expenditure of urban workers' basic pension insurance fund from 2021 to 2050 by constructing an actuarial model of pension insurance fund income and expenditure, and simulates the effect of delayed retirement policy. The prediction results show that under the existing system, the basic pension insurance fund for urban workers will have a shortfall for the first time in 2027, and the shortfall will expand year by year. Compared with the non-implementation of delayed retirement policy, the simulation of the implementation of delayed retirementt program delayed the emergence of the fund gap until 2029, and the forecast period of the pension fund gap significantly narrowed, indicating that delayed retirement policy has a certain positive impact on alleviating the pressure of pension payments, but delayed retirementt can not completely eliminate the pension fund gap. In view of this, this paper suggests that a progressive and flexible delayed retirement policy should be introduced as soon as possible to better adapt to the needs of different groups. At the same time, differentiated policies should be formulated for different groups of people and a pension incentive mechanism for delayed retirement should be set up to improve public acceptance of delayed retirement policy. In addition, delayed retirement policy should be combined with other measures, such as lowering the corporate contribution rate and enhancing the value-added capacity of the pension fund, so as to ensure the sustainability of the pension fund.

Improper disposal of waste plastic has caused serious ecological and environmental pollution problems. Transforming plastics into high value-added chemicals can not only achieve efficient recycling of waste plastics, but also an effective way to control white pollution. The catalyst selectively breaks the C-C bond of polyolefin plastic under heat treatment and converts it into liquid fuel, thus realizing sustainable recycling of plastics and has a good development prospect. This review provides a detailed overview of the current development of catalytic pyrolysis, catalytic hydrolysis, solvent decomposition and supercritical hydrothermal liquefaction for cracking plastics to make fuel oil. The reaction mechanism, influencing factors and promoting effects of catalysts in various degradation technologies are analyzed and summarized and the latest proposed tandem reaction for degrading plastics is briefly introduced. Finally, some optimization paths of waste plastic pyrolysis to fuel oil technology are proposed: synergies between mixed raw materials, in-depth exploration of catalysts, design and manufacture of reactors that match the pyrolysis technology. All these are important research directions for promoting the industrialization of plastic pyrolysis to fuel oil.

By using the particle swarm optimization algorithm for crystal structure prediction, we reveal a newly orthorhombic Cmcm structure of HfB4, which is more energetically superior to the previously proposed YB4-, ReP4-, FeB4-, CrB4-, and MnB4-type structures in the considered pressure range. The phonon dispersion and elastic constants calculations confirm that the new phase is dynamically and mechanically stable. The calculated large shear modulus (240 GPa) and high hardness (45.7 GPa) imply that the predicted Cmcm-HfB4 is a potential superhard material. Meanwhile, the directional dependences of the Young's modulus, bulk modulus, and shear modulus for HfB4 are systematically investigated. Further analyses of the density of states and electronic localization function indicate that the strong B-B and B-Hf covalent bonds greatly contribute to its high hardness and stability.

Silicon carbide single crystal (SiC) has been widely used in the field of power devices, while it is difficult to fabricate ultra-flat surface by traditional manufacturing technologies due to its difficult-to-machine property. This paper investigates the interaction process during femtosecond laser ablation of crystalline silicon carbide based on the two-temperature model simulation and experimental study. The findings reveal that parameters such as laser pulse energy, scanning interval, and defocus amount exert significant influence on ablation depth, roughness, and surface morphology. The femtosecond laser proves effective in removing surface defects from cut SiC substrates, albeit resulting in increased surface roughness. However, subsequent polishing treatment of the laser-ablated silicon carbide surface can mitigate this roughness, underscoring the feasibility of laser surface ablation for silicon carbide single crystals.

Soil is an extremely significant resource for human survival, and agglomerates, as the basic unit of soil structure, not only enhance soil fertility and control the biological validity of nutrients, but also strengthen the soil's erosion resistance. The mass application of fertilizers may have a significant impact on crop growth and soil structure, and the rational application and dispensing of fertilizers will be an urgent issue to be addressed. Therefore, the effect of fertilizer application on the stability of water-stable soil aggregates needs to be studied under different meteorological and soil conditions to draw more general and feasible conclusions. Our Meta-analysis of data from 220 of 56 published studies found that fertilizer application increased mean weight diameter (MWD) by an average of 18% compared to the no-fertilizer treatment. Among the nitrogen (N), phosphate (P), and organic (OM) fertilizer treatments, the organic fertilizer treatment had a greater stimulatory effect on MWD (26%). Among the different fertilizer levels, low level of phosphorus (<40kg·hm-2·yr-1), high level of N (>120kg·hm-2·yr-1), and low level of organic fertilizer (<5000kg·hm-2·yr-1) increased MWD by 19%, 14%, and 41% respectively. Across soil types and land use types, the response to MWD was positive for red soils and paddy fields, and the stimulatory effect of organic fertilizer was more significant compared to chemical fertilizer. The regression model showed that the response ratio of MWD was negatively correlated with the response ratio of soil pH and bulk density (BD), and positively correlated with the response ratio of soil organic carbon (SOC) and microbial mass carbon (MBC). Meanwhile, the PLS-SEM model showed that average annual temperature was the main factor affecting the stability of soil aggregates, and the average annual rainfall is the secondary factor. Therefore, this study found that the long-term use of organic fertilizers in place of some chemical fertilizers was more effective than chemical fertilizer alone. Temperature and rainfall have greater effects on the response of fertilizer to soil aggregate stability.

While numerous studies have explored the correlation between the built environment and ride-hailing demand, few have assessed their nonlinear interplay. Utilizing ride-hailing order data and multi-source built environment data from Nanjing, China, this paper uses the machine learning method, eXtreme Gradient Boosting (XGBoost), combined with SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDP) to investigate the impact of built environment factors on ride-hailing travel demand, including their non-linear and threshold effects. The findings reveal that dining facilities have the most significant impact, with a contribution rate of 30.75%, on predicting ride-hailing travel demand. Additionally, financial, corporate, and medical facilities also exert considerable influence. The built environment factors need to reach a certain threshold or within a certain range to maximize the impact of ride-hailing travel demand. population density, land use mix and distance to the subway station collectively influence ride-hailing demand. The results are helpful for TNCs to allocate network ride-hailing resources reasonably and effectively.

Moisture and thermal are the key factors for influencing methane desorption during CBM exploitation. Using high pressure water injection technology into coalbed, new fractures and pathways are formed to methane transport. It is existed a phenomenon of water inhibiting gas flow. This study is focused on various water pressures impacted on gas adsorbed coal samples, then the desorption capacity could be revealed under different conditions. And the results are shown that methane desorption capacity was decreased with water pressure increased at room temperature and the downtrend would be steady until water pressure was large enough. Heating could promote gas desorption capacity effectively, with the increasing of water injection pressures, the promotion of thermal on desorption became more obvious. These results are expected to provide a clearer understanding of theoretical efficiency of heat water or steam injection into coalbed, they can provide some theoretical and experimental guidance on CBM production and methane control.

SOC stock (SOCS) changes caused by land use changes are still unclear, and understanding this response is essential for many environmental policies and land management practices. In this study, we investigated the temporal-spatial and vertical distribution characteristics of SOCS on the Western Sichuan Plateau (WSP) using the sparrow search algorithm-random forest regression (SSA-RFR) models with excellent model applicability and accuracy. The temporal-spatial varia-tions in the SOCS were modeled using 1080 soil samples and a set of nine environmental covariates. We analyzed the effect of land use changes on the SOCS on the WSP. The total SOCS increased by 18.03 Tg C from 1990 to 2020. The results of this study confirmed that the SOCS in the study area has increased significantly since 2010, with an increase of 27.88 Tg C compared to the total SOCS in 2010. We found that the spatial distribution of the SOCS increased from southeast to northwest, and the vertical distribution of the SOCS in the study area decreased with increasing soil depth. Forest and grassland are the main sources of SOCS, the total SOCS in the forest and grassland accounted for 37.53 and 59.39% of the total SOC pool in 2020, respectively. Expansion of the wetlands, forest, and grassland areas could increase SOCS in the study area.

Euler sums are alternating (or level two) extension of multiple zeta values (MZVs). Kaneko and Tsumura initiated the study of multiple T-values (MTVs), another level two generalization, by restricting the summation indices in the definition of MZVs to a fixed parity pattern. In this paper, we shall study finite MTVs and their alternating versions which are level two and level four variations of finite MZVs, respectively. We conjecture that all finite MZVs are in the Q-span of finite MTVs which in turn apparently lie in the span of finite Euler sums, and the inclusions are both proper. We shall first provide some structural results for Euler sums of small weights, guided by the author's previous conjecture that the finite Euler sum space of weight w is isomorphic to a quotient Euler sum space of weight w. Then, by utilizing some well-known properties of the classical alternating MTVs, we shall derive a few important Q-linear relations among the finite alternating MTVs, including the reversal, linear shuffle and sum relations. We then compute the upper bound for the dimension of the Q-span of weight w finite (alternating) MTVs for w<9, both rigorously using the newly discovered relations and numerically aided by computers.

The intestinal microbial community of aquatic animals is closely related to the environment and thus affects the health of aquatic animals. Here we investigated annual variation of intestinal bacteria community structures of Ruditapes philippinarum cultured using two different methods, bottom sown and raft hanging. Bacterial diversity of seawater and sediment in different seasons was examined as well. Correlation between R. philippinarum intestinal bacteria community structures and environmental factors was analyzed. The results showed that in the two aquculture areas where R. philippinarum was differentially cultured, bacteria community structure of seawater and sediment both altered with seasons. However, neither seasonal changes nor difference in culture methods could significantly affect the intestinal bacteria community structures of R. philippinarum. Additionally, in terms of the alpha diversity of intestinal bacteria communities, there was no significant difference in R. philippinarum cultured using the two methods. For benthic cultured clams, alpha diversity of the intestinal bacterial communities was often higher than that of the environmental bacterial communities. For raft hanging cultured calms, Alpha diversity of the intestinal bacterial communities was normally comparable with that of the environmental counterparts. Beta diversity analysis showed that the intestinal bacterial community structure of R. philippinarum was mainly determined by both deterministic and stochastic processes. Correlation analysis showed that the intestinal bacterial community structures of R. philippinarum were determined by a variety of environmental factors. For clams collected from the benthic culture area, the intestinal bacterial structure was more correlated with the physicochemical properties of sediment in comparing with those of seawater. For clams collected from the raft-culture area, the intestinal bacterial structure was mainly determined by the phsicochemical characteristics of seawater. This study helps us to better understand the bacterial community structure in complex aquaculture ecosystems, providing a reference for healthy shellfish aquaculture and ecosystem protection in aquaculture area.

In the fifth generation communication system, millimeter wave (mmWave) networks will coexist with traditional micro wave (μWave) networks, which allows for higher data transmission rate and better user experience. In this paper, we give a comprehensive framework of mathematical models and analytical methods for multi-tier mmWave and μWave hybrid caching networks based on stochastic geometry. We propose an association strategy by assuming average biased-received power association and Rayleigh fading. Accordingly, by using a D-ball approximating blockage model of mmWave networks, expressions of the cell association probability and the coverage probability of the hybrid networks are derived. Also, we use the average successful delivery probability as the performance metric to analyze the existing caching placement strategies. Simulation results validate the accuracy of our analytical conclusions.

Purpose- This study seeks to investigate the collaboration between Digitalization and traditional manufacturing industry and investigate, how digitalized management brings new chances and challenges of management. Design/methodology/approach – The author designed a content analytical study researching the role of digitalization in traditional manufacturing industries. The article presents a selective but systematical review of recent digitalization trend and digital twin to be applied for innovative management in Industry 4.0 era. Findings– Digitalization is highly correlated with traditional manufactory in Industry 4.0 era. The study brings a new outlook on the next wave of Digitalization and review of associated challenges and opportunities for management and innovation in traditional manufacturing industries. Research limitations/implications – The research focuses on two branches of traditional industries only: machine tools building and metalworking industries. Future research needs to examine other traditional industries. The research is limited to 2 high related traditional manufacturing industries, machine tools and metalworking industry. Practical implications – The study and application of digitalization should be highly recommended and launched in traditional manufacturing industries. Universities, institutes and vocational schools should update, optimize their courses systems according to prediction of future industry. Originality/value – The paper enhances understanding about the collaboration between digitalization and traditional manufacturing industry. This paper analyzes an important issue the digitalization serves traditional industries. It is unique in its broad analysis of the related terms – Digitalization, Machines 4.0, Industry 4.0 and innovative management in Industry 4.0 era.

In this study, multilayer composite nanofiber membranes of sodium alginate (SA) /polyethyleneimine (PEI)/polyvinyl alcohol (PVA) was fabricated via electrospinning technique to enhance the adsorption of Cu2+ from wastewater. The preparation and adsorption mechanisms of the SA/PEI/PVA nanofiber membranes were analyzed by utilizing analytical techniques such as SEM, FTIR, EDS, UV-vis, XRD, and TG. The obtained nanofiber membrane characterized by small diameter, high uniformity, and extensive surface area, demonstrate significant potential for heavy metal ion filtration. Optimal spinning parameters were identified, including a voltage of 19.5 KV, a distance of 8 cm, and specific mass ratios (SA: PEI: PVA, 1:2:6) and injection speeds (8 μL/min) and. The resulting nanofibers with an average diameter of 112.5 nm exhibited excellent morphology and high efficiency, retaining over 85% adsorption capacity for Cu2+ in initial tests and maintaining above 80% efficacy through four successive filtration cycles.

Green and low-carbon development has become an important embodiment of China's path to becoming a strong agricultural country. How to enable agricultural enterprises to better adopt green technologies and conduct production and operation with the concept of sustainable development has become a key link. This article utilizes a structural equation model (SEM) to analyze the role paths and mediating effects of organizational learning ability and policy orientation in agricultural enterprises' market orientation and willingness to adopt green technologies[ The definition of green technology in this paper refers to Guo Kesha, Tian Xiaoxiao. Green technology and green transformation of industrial development mode [J]. Tianjin Social Sciences, 2024 (02) :99-107, including green manufacturing (production) technology and green service technology.]. The results show that market orientation, organizational learning ability, and policy effectiveness have significant direct positive impacts on the willingness to adopt; market orientation has a significant positive impact on agricultural enterprises' organizational learning ability, organizational learning ability has a significant positive impact on policy orientation, and market orientation has a significant positive impact on policy effectiveness; the results of mediation analysis also indicate that learning ability has a significant mediating effect between market orientation and willingness to adopt, and policy effectiveness has a significant mediating effect between market orientation and willingness to adopt. Through difference analysis, it is believed that the mediating effects of the three paths are equally important, and organizational learning ability and policy effectiveness play a partial mediating role in agricultural enterprises' willingness to adopt green technologies. Based on this, policy suggestions are proposed to improve enterprises' own organizational learning ability, increase the promotion of policies related to green technologies, improve relevant policies for the application of green technologies, and increase research and development efforts for green technologies.

The hospital indoor environment plays a significant role in shaping the microbial exposures that humans encounter. Resistance to antibiotics is one of the mechanisms employed by bacteria to develop resilience against stress in indoor environments. The extensive usage of antibiotics has been a key factor in driving changes in the ecological function of antibiotic resistance genes (ARGs) and their acquisition by pathogenic bacteria. By integrating the 16S rRNA Illumina sequencing and high throughput-qPCR approaches with water and air dust samples across seven departments at Peking University Shenzhen Hospital, China, this study yielded intriguing findings regarding the department-specific variation, transmission, and correlation of bacteria, ARGs and MGEs within the hospital indoor environment. One notable observation was that the seasonal variation played a vital role in shaping the bacterial composition in the overall hospital indoor environment across seven studied departments. Nevertheless, a similar significant seasonal impact was only observed in the blood test room and emergency departments, rather than in the other five departments. Another intriguing finding was the correlation between ARGs and MGEs abundance. This correlation was evident in the overall hospital indoor environment, which was conversely not found in the emergency, pneumology and gynecology departments. Additionally, while there was no significant relationship that occurred between bacterial communities and ARGs/MGEs within the hospital, the gynecology department demonstrated a close link between bacterial communities and the presence of ARGs/MGEs. Notably, the gynecology department also stood out as an important source of bacteria and ARGs/MGEs for other departments. This study underscores the need for careful surveillance and monitoring of antibiotic resistance, particularly in Legionella spp. in man-made water systems. The findings also show the importance of monitoring and understanding the genetic elements such as Tp614 involved in gene transfer and recombination, as well as their impact on antimicrobial treatment efficacy.

This paper studies the mechanism of how China’s state-owned enterprise (SOEs) reform can influences economic growth, and distinguishes the capital efficiency between state-owned and private enterprises. The results show that: 1) the capital allocation efficiency among state-owned enterprises is lower than private enterprise due to an insufficiently released productivity of state-owned enterprises; 2) although with a higher capital allocation efficiency, the improvement of technology progress of private enterprises at a much slower pace compared to its rapidly increasing share in China’s economy. In case of poor allocation with private sector, blindly reforming ownership of state-owned enterprises cannot effectively alleviate the problem of efficiency losses. State-owned enterprise reform can boost economic growth by increasing capital marginal output, improving capital dynamic allocation efficiency, promoting TFP growth and exerting external spillovers on other firms. At present, China is exploring the endogenous power of economic growth, improving the market institutions and promoting the state-owned enterprises reform with positive and steady pace. By properly re-allocation SOEs into the private sector, which has significant influence on improving economic efficiency and promoting sustained economic growth.

The existing segmentation-based scene text detection methods mostly need complicated post-processing, and the post-processing operation is separated from the training process, which greatly reduces the detection performance. The previous method, DBNet successfully simplified post-processing and integrated the post-processing into a segmentation network. However, the training process of the model took a long time for 1200 epochs and the sensitivity to texts of various scales was lacking, leading to some text instances being missed. Considering the above two problems, we design the text detection Network with Binarization of Hyperbolic Tangent(HTBNet). First of all, we propose Binarization of Hyperbolic Tangent (HTB), optimized along with which, the segmentation network can expedite the initial convergent speed by reducing the amount of epochs from 1200 to 600. Because features of different channels in the same scale feature map focus on the information of different regions in the image, to better represent the important features of all objects in the image, we devise the Multi-Scale Channel Attention(MSCA). Meanwhile considering that multi-scale objects in the image cannot be simultaneously detected, we propose a novel module named Fused Module with Channel and Spatial(FMCS), which can fuse the multi-scale feature maps from channel and spatial dimension. Finally we adopt cross entropy as the loss function, which measures the difference between predicted values and ground truths. The experimental results show that HTBNet compared with lightweight models has achieved competitive performance and speed on Total-Text(F-measure:86.0%, FPS:30) and MSRA-TD500 (F-measure:87.5%, FPS:30).

An innovative superconducting mechanism was developed based on a patented discovery of room temperature superconductivity in several thorium (Th) salts or compounds. The rationale behind this discovery is through the experimental results about the unique electrical and magnetic properties of these Th salts. Accordingly, this new superconducting mechanism for these Th salts was obtained through the analyses of the compounds’ molecular configurations and the packings of their relevant crystal structures. Owing to the distinctive properties of the Th compounds in this discovery, we further established a different electron pairing scheme as opposed to the pairing of the Cooper pairs. Compared to the long distance electron pairing of the Cooper pairs, the new electron pairing in our mechanism is constructed by two closely correlated electrons that reside on the same atomic orbital of the Th cation as an electron lone pair. In this new superconducting mechanism, the Th cation is sitting on a relevant crystallographic lattice arrangement or a network of the relevant Th compounds. This network is constructed by many Th cations along certain crystallographic lattice arrangement where each Th cation contains one electron lone pair. This network allows the electron lone pairs on the Th cations to be delocalized over the network, “in pair”, and thus, reveals the electron lone pair in presence in a long distance fashion. The closely correlated electron lone pairs hop on this network and thus, construct the supercurrent over the network. This explanation about the superconductivity laid the basis for our superconducting mechanism. All these conclusions came from the previous studies about these compounds that illustrated their unusual features of a coexistence of high electrical conductivity and diamagnetism. These electrical and magnetic properties fall in line with that of superconductors but, surprisingly, these Th compounds have such properties at the ambient condition, meaning under room temperature and atmosphere pressure. We expect that this mechanism may be appropriate to be utilized to other superconducting cases, either conventional or unconventional, and therefore, can be adapted to describe the superconducting phenomenon for other superconductors.

The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection which detects the patient's exhaled VOCs combined with sensor arrays of Convolutional Neural Network (CNN) algorithms as a new lung cancer detection is attracting more researchers' attention. However, due to low accuracy, high complexity computation and large number of parameters make the CNN algorithms difficult transplant to the embedded system of POCT devices. A lightweight neural network (LTNet) in this work is proposed to deal with this problem, and meanwhile, achieve high-precision classification of acetone and ethanol gases, which are respiratory markers for lung cancer patients. Compared to currently popular lightweight CNN models such as EfficientNet, LTNet has fewer parameters (32K) and its training weight size is only 0.155 MB. LTNet achieved an overall classification accuracy of 99.06% and 99.14% in the own mixed gas dataset and the University of California (UCI) dataset, which are both higher than that of the five existing models’, and it also offers the shortest training (844.38s and 584.67s) and inference time (23s and 14s) in the same validation set. Compared to the existing CNN models, LTNet is more suitable for resource-limited POCT devices.

Electricity consumption is often the hotspot of life cycle assessment (LCA) of products, industrial activities, or services. The objective of this paper is to provide a consistent, scientific, region-specific electricity-supply-based inventory of electricity generation technology for national and regional power grids. Marginal electricity generation technology is pivotal in assessing impacts related to additional consumption of electricity. China covers a large geographical area with regional supply grids; these are arguably equally or less integrated. Meanwhile, it is also a country with internal imbalances in regional energy supply and demand. Therefore, we suggest an approach to achieve a geographical subdivision of the Chinese electricity grid, corresponding to the interprovincial regional power grids, namely the North, the Northeast, the East, the Central, the Northwest, and the Southwest China Grids, and the China Southern Power Grid. The approach combines information from the Chinese national plans on for capacity changes in both production and distribution grids, and knowledge of resource availability. The results show that nationally, marginal technology is coal-fired electricity generation, which is the same scenario in the North and Northwest China Grid. In the Northeast, East, and Central China Grid, nuclear power gradually replaces coal-fired electricity and becomes the marginal technology. In the Southwest China Grid and the China Southern Power Grid, the marginal electricity is hydropower towards 2030.

In this paper, I present a comprehensive theoretical framework for understanding surface-enhanced Raman scattering (SERS) measurements in both solution and thin film setups, focusing on electromagnetic enhancement principles. Two prevalent types of SERS substrates found in the literature are investigated: plasmonic colloidal particles, including spherical and spheroid nanoparticles, nanoparticle diameters, and thin-film-based SERS substrates like ultra-thin substrates, bundled nanorods, plasmonic, and porous thin films. The investigation explores the impact of analyte adsorption, orientation, and the polarization of the excitation laser on effective SERS enhancement factors. Notably, it considers the impact of analyte size on the SERS spectrum, by examining scenarios where the analyte is significantly smaller or larger than the hot-spot dimensions. The analysis also incorporates optical attenuations arising from the optical properties of the analyte and the SERS substrates. The findings provide possible explanations for many observations made in SERS measurements, such as variations in relative peak intensities during SERS assessments, reductions in SERS intensity at high analyte concentrations, and the occurrence of significant baseline fluctuations. The study offers valuable guidance for optimizing SERS substrate design, enhancing SERS measurements, and improving the quantification of SERS detection.

To evaluate the 2-year efficacy and safety of ab interno trabeculectomy with the Trabectome in Chinese primary open-angle glaucoma (POAG) patients. This was a multicenter, retrospective study and included POAG patients with or without visually-significant cataracts. The primary outcome was intraocular pressure (IOP) reduction. Secondary outcomes included reduction of glaucoma medications, surgical complications, and success at 2-years. Success was defined as: 1) IOP < 21 mmHg and at least 20% IOP reduction from baseline after 3 months at any two consecutive visits, and 2) no additional glaucoma surgery required. A total of 42 patients were enrolled; thirteen had a history of failed glaucoma surgery. Twelve patients underwent Trabectome surgery combined with phacoemulsification while the remainder underwent Trabectome surgery alone. Overall, the mean preoperative IOP was 21.4±1.23 mmHg. The Trabectome lowered IOP to 18.5± 0.94 mmHg at 2 years (P<0.05). The number of glaucoma medications also decreased from a baseline of 2.0±0.9 to 1.2± 0.21 at 2 years (P=0.04). The overall success was 78%, with patients undergoing combined surgery having a higher success than those with Trabectome surgery alone (100% vs. 76%). No major complications were seen. The Trabectome appears to be an efficient and safe procedure in Chinese POAG patients in the long-term.

The paper suggests that the physical priciple of special relativity's space-time transformation effect is wrong, Uniform linear motion without acceleration does not exist objectively, nor does its same reference frames. Therefore, it is inferred that the space-time transformation effect of special relativity is caused by the acceleration of moving objects, special relativity is only a part of general relativity, not a theoretical system that exists independently from general relativity. The corresponding mathematical demonstration and calculation verification are carried out, and the result proves that the inference of the paper is correct. At the same time, it further explains that the concept of absolute airspace is correct. Special relativity has serious errors in the concept of space, the principle of relativity and the physical principle of space-time transformation effect. Therefore, it is necessary to make a series of revisions to the theory of relativity and to reinterpret some related physical problems.

Porous asphalt (PA) pavement systems with and without a geotextile layer were investigated in laboratory experiments to determine the impacts of the geotextile layer on processes leading to lead ion (Pb2+) removal from stormwater runoff. Two types of geotextile membranes placed separately at upper and lower levels within the PA systems were tested in an artificial rainfall experiment using synthetic rainwater. The effect of storage capacity within the system on Pb2+ removal was also investigated. Results indicated that the use of a geotextile layer resulted in a longer delay to the onset of effluent. The non-woven geotextile membrane placed below the reservoir course improved the Pb2+ removal rate by 20% over removal efficiency of the system using a woven geotextile placed just below the surface but before the choker course. Pb2+ ions were reduced by over 98% in the effluent after being held for 24 hours in reservoir storage. Results suggest that temporary storage of stormwater in the reservoir course of a PA system is essential to improving Pb2+ ion removal capability.

Waterbomb structures are origami-inspired deformable structural components used in new types of robots. They have a unique radially deployable ability that enables robots to better adapt to their environment. In this paper, we propose a series of new waterbomb structures with square, rectangle, and parallelogram base units. Through quasi-static axial and radial compression experiments and numerical simulations, we prove that the parallelogram waterbomb structure has a twist displacement mode along the axial direction. Compared with the square waterbomb structure, the proposed optimal design of the parallelogram waterbomb structure reduces the critical axial buckling load-to-weight ratio by 55.4% and increases the radial stiffness-to-weight ratio by 67.6%. The significant increase in the radial stiffness-to-weight ratio of the waterbomb structure and decrease in the critical axial buckling load-to-weight ratio make the proposed origami pattern attractive for practical robotics applications.

The fluorinated organic compounds have superior physicochemical properties than general organic compounds due to the strong C-F single bond, and widely used in medicine, biology, pesticides, and materials science. In order to gain a deeper understanding of the physicochemical properties of fluorinated organic compounds, fluorinated aromatic compounds have been investigated by various spectroscopic techniques. 2-Fluorobenzonitrile and 3-fluorobenzonitrile are important fine chemical intermediates, and their excited state S1 and cationic ground state D0 vibrational features remain unknown. In this paper, we used two-color resonance two photon ionization (2-color REMPI) and mass analyzed threshold ionization (MATI) spectroscopy to study S1 and D0 states vibrational features of 2-fluorobenzonitrile and 3-fluorobenzonitrile. The precise excitation energy (band origin) and adiabatic ionization energy were determined to be 36028 2 cm-1 and 78650 5 cm-1 for 2-fluorobenzonitrile; and 35989 2 cm-1 and 78873 5 cm-1 for 3-fluorobenzonitrile, respectively. The density functional theory (DFT) at the levels of RB3LYP/aug-cc-pvtz, TD-B3LYP/aug-cc-pvtz, and UB3LYP/aug-cc-pvtz were used to calculate the stable structures and vibrational frequencies for the ground states S0, excited state S1, and cationic ground state D0, respectively. Franck-Condon spectral simulations for transitions of S1 S0 and D0 S1 were performed based on above DFT calculations. The theoretical and experimental results are in good agreement. The observed vibrational features in S1 and D0 states are assigned according to the simulated spectra and the comparison with structurally similar molecules. Several experimental findings and molecular features were discussed in detail.

Lignin fibers typically influence the mixture performance of stone matrix asphalt (SMA), such as strength, stability, durability, noise level, rutting resistance, fatigue life, and water sensitivity. However, limited studies were conducted to analyze the influence of fibers on the percent voids in mineral aggregate in bituminous mixture (VMA) during the mixture design. This study analyzed the effect of different fibers and fiber contents on the VMA in SMA mixture design. A surface-dry condition method test and Marshall Stability test were applied on the SMA mixture with four different fibers (i.e., flocculent lignin fiber, mineral fiber, polyester fiber, blended fiber). The test results indicated that the bulk specific gravity of SMA mixtures and asphalt saturation decreased with the increasing fiber content, whilst the percent air voids in bituminous mixtures (VV), Marshall Stability and VMA increased. Mineral fiber had the most obvious impact on the bulk specific gravity of bituminous mixtures, while flocculent lignin fiber had a minimal impact. The mixture with mineral fiber and polyester fiber had significant effects on the volumetric properties, and, consequently, exhibited better VMA over the conventional SMA mixture with lignin fiber. Modified fiber content range was also provided, which will widen the utilization of mineral fiber and polyester fiber in the applications of SMA mixtures. The mixture evaluation suggested no statistically significant difference between lignin fiber and polyester fiber on the stability. The mineral fiber required a much larger fiber content to improve the mixture performance than other fibers. Overall, the results can be a reference to guide SMA mixture design.

Helical (frontier) molecular orbitals [Chem. Sci. 2013, 4, 4278] have been reported almost a decade ago. Yet, helical molecular spin densities [Mol. Phys. 2022, e2157774] have been observed by us only very recently. In this work, we have observed that some chiral boron clusters (B–16, B–20, B–24, and B–28) can simultaneously have helical molecular orbitals and helical spin densities. To our best knowledge, it is the first time we have discovered that inorganic boron clusters assume such an unprecedented property. We have unambiguously unraveled that it is chiral Jahn-Teller distortion of quasi-planar boron clusters that drives the formation of helical molecular spin densities. More interestingly, we have shown that elongation/enhancement of helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity properties of these boron clusters are also discussed. Implication of this work is straightforward that boron clusters may find potential applications in spintronics, such as molecular magnets.

In current transportation hubs, it is a common phenomenon that passengers travel with necessary wheeled-luggage or suitcases. Due to the fact that most luggage occupies certain space within dense passenger crowds with giant mass inertia, its abnormal motions, such as drifting, frequently trig unavoidable local disturbances and turbulence in surrounding pedestrian flows, further increasing security risk. While, current researches primarily concentrate on examining the impact of luggage on crowd evacuation efficiency through scenario-based experiments and analyzing the spatial characteristics of crowd distribution in surveillance videos. There still lacks of the dynamic disturbance mechanisms and crowd stability associated with the combined motion of passengers and luggage. Therefore, this study considers the luggage-laden passenger as a deformable particle, the resulting disturbance on surrounding non-luggage passengers is analyzed and quantified into a nonlinear pressure term. Subsequently, the disturbance propagation model of passenger-luggage is developed by adapting the classical Aw-Rascle traffic flow model with incorporation of the pressure term. Simulation experiments of disturbances caused by luggage drifting and retrograding validate that the proposed propagation model aligns with real-world situations in transportation hubs. Quantitively, when luggage-laden passenger drifted left, the disturbing force of left side crowd can reach a peak of 238N in the passenger density of 3.0 p/m2, and the maximum difference between the left and right sides disturbing force can reach 153N. Furthermore, it is recommended that the proposed model can be applied to crowd flow analysis and risk assessment.

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 mechanism underlying microbiologically induced carbonate precipitation have not been thoroughly characterized, although numerous scholars and experts have specifically investigated questions regarding minerals induced by bacteria. The study of the precipitation of carbonate minerals induced by halophilic bacteria has aroused wide concern. The present study aimed to investigate the characterization and process of biomineralization in high salt systems by a halophilic bacterium, Chromohalobacter israelensis strain LD532 (GenBank: KX766026), which was isolated from the Yinjiashan Saltern in China. Carbonate minerals induced by LD532 were investigated in several sets of comparative experiments that employed magnesium sulfate and magnesium chloride as Mg resources. Magnesium calcite and aragonite were induced by LD532 bacteria, whereas these minerals did not appear in the control group. The mineral phases, micromorphologies, and crystal structures were analysed using X-ray powder diffraction, scanning electron microscopy, and energy dispersive X-ray detection. The carbonic anhydrase and urease secreted by strain LD532 through metabolism increased the pH value of the liquid medium and promoted the process of carbonate precipitation. Further study using high resolution transmission electron microscopy, energy dispersive X-ray detection and analysis of ultrathin slices showed that the nucleation sites of carbonate minerals were located on extracellular polymeric substances and the membranes of intracellular vesicles of LD532 bacteria, which provided favourable conditions for the growth of carbonate mineral crystals. The morphologies and compositions of minerals formed in solutions of MgSO₄ and MgCl₂ display significant differences, indicating that different sources of Mg²⁺ may also affect the physiological and biochemical activities of microorganisms and thus mineral deposition. This study will be of some interest for the interpretation of carbonate biomineralization in natural salt environments and has some value as a reference in understanding sedimentary carbonates in ancient marine environments, such as tidal flats.

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.

Reconfigurable chiral metasurfaces with dynamic polarization manipulation capability are highly required in optical integrated systems. In this paper, we simultaneously realized giant and large-range switchable asymmetric transmission (AT) and circular conversion dichroism (CCD) in a vanadium dioxide (VO2) based metasurface. The AT and CCD of the insulator VO2 based metasurface reach 0.95 and 0.92, respectively. Utilizing the insulator-to-metallic phase transition of VO2, the AT and CCD could be continuously switched to near zero. Furthermore, the physics mechanism of the giant and switchable AT and CCD are analyzed. The proposed metasurface with large-range switchable AT and CCD is promising in the applications of biochemistry detection, chiral imaging and biosensing.

This study aims to examine how the activation of nursing roles and professional identification as a nurse can influence moral judgments in terms of deontological and utilitarian inclinations. In Study 1, a priming technique was used to assess the impact of activating the nursing concept on moral reasoning. Participants were randomly assigned to either a nursing prime or neutral prime condition. By using a scrambled-sentences task, participants were prompted to think about nursing-related or neutral thoughts. Following the priming task, participants were asked to respond to 20 moral dilemmas. The process dissociation approach was employed to measure the degree of deontological and utilitarian tendencies in their moral reasoning. In Study 2, participants completed the nursing profession identification scale and the moral orientation scale before engaging in moral judgments similar to those in Study 1. The findings revealed that priming the concept of nursing roles resulted in an increase in deontological clinical inclinations, while having no significant effect on utilitarian inclinations. Additionally, a positive correlation was observed between identification with the nursing profession and deontological clinical inclinations, whereas a negative correlation was found with utilitarian inclinations. Deliberation orientation acted as a complete mediator in the relationship between nursing professional identification and deontological tendencies, and as a partial mediator for utilitarian tendencies.

In order to create a smart mine, it is necessary to digitize the existing emulsion pumping station. Existing research does not achieve this task, this paper designs and manufactures a high-pressure, high-flow, high-water-based mining digital controlled unloading valve (abbreviated as HLHMDCUV), which achieves good results in both theoretical analysis and experimental testing. In order to obtain the accurate dynamic characteristics, this valve was analyzed by simulation using AMESim. Based on the dynamic performance analysis and the flow field analysis inside the valve body, the structure has been optimized to improve the performance of HLHMDCUV. The results show that the HLHMDCUV has a better dynamic characteristics, which were also demonstrated in the experiment. At the same time, the HLHMDCUV is easy to disassemble and maintain. This paper provides a theoretical basis for the design of such valves, which is conducive to the subsequent promotion of intelligent mine transformation.

It is expected that scholars will continue to strengthen the depth and breadth of theoretical research on RIS, so as to provide a higher theoretical upper bound for the engineering application of RIS. While making breakthroughs in academic research, great progress has been made in engineering application research and industrialization promotion. This article will provide an overview of RIS engineering applications, mainly including the typical features, typical classifications, and typical deployment scenarios of RIS. Then the challenges and candidate solutions of the RIS are systematically and deeply analyzed, involving the cascade channel decoupling for solving the RIS beamforming, the influences and solutions of RIS regulation constraints, RIS system architecture of network controlled mode, the integrated channel regulation and information modulation, TDD mechanism used for RIS. Future trends and challenges are also provided.

The composition and pattern of ecosystems are important factors determining the overall status and spatial differences of ecosystem service functions. However, under the background of differential land policies and ecological protection policies, research on the trend of ecological system pattern changes in the Fenhe River Basin is insufficient. Taking the upper and middle reaches of the Fenhe River Basin as the study area, based on long-term NDVI index and multi-period LUCC remote sensing images, this study used spatial statistics and time trend analysis methods to analyze the spatio-temporal dynamic changes of vegetation, land use, landscape pattern, and explored the impact of major driving factors on ecosystem changes. The results show that: (1) From 2010 to 2020, the vegetation cover in the upper and middle reaches of the Fenhe River Basin increased, with an annual NDVI increment of 0.003 (P<0.001). NDVI showed an increasing trend spatially, with significant statistics (P<0.001) and significant changes (P<0.05) in vegetation in high-altitude mountain areas, and the vegetation cover was mostly forests or grasslands. There was no significant change in vegetation cover in the low-lying urban agglomeration area. (2) From 2010 to 2020, the area of water bodies or wetlands in the study area significantly decreased, with 51.3% converted to arable land and 33.9% transferred to construction land, while only 2.2% remained as water bodies or wetlands. From 2015 to 2020, the trend of water body changes slowed down, with the proportions of conversion to arable land and construction land being 44.0% and 18.4% respectively, while the area of wetlands or water bodies remained at 16.3%. During the period of 2015-2020, the area of water bodies or wetlands converted to other land types increased by more than 14% compared to 2010-2015. This proportion reached more than 30% compared to the 13th Five-year Plan Period. (3) From 2010 to 2020, the spatial changes of landscape diversity (SHDI) and evenness (SHEI) of LUCC showed heterogeneous characteristics. In the high-altitude areas near the river basin boundary, the values of SHDI and SHEI were below 1.0. While in the low-altitude plain areas and urban areas with relatively frequent human activities, the values of SHDI and SHEI were above 1.0, and the values in urban areas could reach above 1.5. The evolution of ecosystem patterns in the upper and middle reaches of the Fenhe River Basin in the past decade has been clarified, providing a scientific basis for the construction and management of ecological environment governance and restoration projects in the Fenhe River Basin, and providing practical references for ecological protection and high-quality development practice in the Yellow River Basin.

Bi1-xSbx crystal is one of the best n-type thermoelectric materials below 200 K, but its weak mechanical strength hinders practical applications for deep refrigeration. Herein, we adopted the mechanical enhancement method of hot extrusion to investigate the comprehensive mechanical and thermoelectric properties of Bi0.905Sb0.095. It revealed that reducing the grain size of the matrix and increasing the extrusion ratio can improve the gain size uniformity and mechanical properties. While the thermoelectric performance depends on the texture, grain size, and local composition. The extruded sample prepared by ingot with the high extrusion ratio of 9:1 generated a high texture degree of (001) plane and small grain sizes between ~4-40 mm, which resulted in the high bending strength of Bi1-xSbx ~130 Mpa and a high-power factor of ~ 68 μW·cm-1·K-2@173 K, as well as the relative high figure of merit of 0.25@173K. This work highlights the importance of the uniform distribution of the grain size and the compositions for Bi1-xSbx, as well as the required universal key parameter for the hot-extrusion method.

The tourism economy plays an essential role in supporting and driving tourism development. Therefore, studying its resilience is crucial for promoting sustainable and high-quality tourism development. Based on the core essentials of economic toughness, this paper constructs the tourism economic toughness evaluation index system, uses the entropy weight TOPSIS method to measure the tourism economic toughness of 10 counties and cities in the Yili River Valley in 2010-2019, analyzes its spatio-temporal evolution characteristics through the standard deviation ellipse, the traditional Markov chain, and the spatial Markov chain, and uses the grey correlation analysis method to analyze the driving factors of the tourism economic toughness. The results show that: (1) the economic resilience of tourism in the Yili River Valley shows a "W"-shaped time-series dynamic development trend with an average index of 0.28394, in which it experienced a decline from 0.28 to 0.27 during 2012-2013 and 2015-2016; (2) Spatial Pattern: The Yili River Valley tourism economic resilience is characterized by a clear uneven spatial distribution. The city of Yining, representing the northwestern region, exhibits a high level of resilience, while the southwestern region, endowed with rich tourism resources, demonstrates a medium level of resilience. Conversely, the central to southeastern counties and cities, such as ChabuchaerXibo Autonomous County and other counties and cities, are characterized by a lack of developed tourism facilities, which has resulted in a lower level of resilience and a weak development situation; (3) In terms of spatial and temporal evolution, the standard deviation ellipse is stabilized year by year pointing to "northwest-southeast", the clustering tendency is gradually enhanced, and five tourism economic resilience convergence clubs are identified, whose internal transition probability is significantly affected by spatial location, and which show obvious stability and neighborhood effects; (4) Regarding the driving factors, the impact of each driving factor on the resilience of the tourism economy reaches the statistical significance threshold of 0.77 or above. Among them, the number of employees in the tertiary industry, especially the input of high-quality talents in the tourism industry, plays a key role in improving the quality of tourism services and strengthening the industry's ability to withstand risks and development potential.

A population dynamics epidemic model is developed that incorporates age of infection and age of vaccination. The model analyzes pre-symptomatic and symptomatic periods of an infected individual in terms of infection age. The model analyzes the efficacy of vaccination in terms of vaccination age. The model is applied to the 2003 SARS epidemic in Taiwan and the current COVID-19 epidemic in New York State.

C-terminal Src kinase (CSK) is the major inhibitory kinase for Src family kinases (SFKs) through phosphorylation of their C-tail tyrosine site, and regulates various cellular activities in association with SFKs functions. As a cytoplasmic protein, CSK need be recruited to the plasma membrane to regulate SFKs activities. The regulatory mechanism for CSK activity and its subcellular localization remains largely unclear. In this work, we developed a genetically encoded biosensor based on fluorescence resonance energy transfer (FRET) to visualize CSK activity in live cells. The biosensor with optimized substrate peptide confirmed crucial Arg107 site in CSK SH2 domain, and displayed sensitivity and specificity to CSK activity while little responses to co-transfected Src and Fyn. FRET measurements showed CSK having relatively mild level of kinase activity in comparison to Src and Fyn ones in rat airway smooth muscle cells. The biosensor tagged with different submembrane-targeting signals detected CSK activity at both non-lipid raft and lipid raft microregions, while showed higher FRET level at non-lipid ones. Co-transfected receptor-type protein tyrosine phosphatase alpha (PTPα) had inhibitory effect on the CSK FRET response. The biosensor didn’t detect obvious changes of CSK activity between metastatic cancer cells and normal ones. In conclusion, a novel FRET biosensor was generated to monitor CSK activity, and demonstrated CSK activity existing in both non-lipid and lipid raft membrane microregions while more present at non-lipid ones.

The advancement in science and technology has led to luffa sponge (LS) being widely used as a natural material in industrial application as its polyporous structure and light texture. In order to enhance the utility of LS fibers as the reinforcement of lightweight composite materials, this study investigate its water absorption, mechanical properties, anatomical characteristic and thermal performance. Hence, moisture regain, tensile properties of LS fiber bundles were measured in accordance with standards and the structural characteristics were investigated via microscopic observation. Scanning electron microscopy (SEM) was used to observe the surface morphology and fracture surface of fiber bundles. Test results shows that the special structure where the phloem tissues degenerate to cavities had a significant influence on the mechanical properties of LS fiber bundles. Additionally, the transverse sectional area occupied by fibers in a fiber bundle (SF), wall thickness and ratio of wall to lumen of fiber cell, and crystallinity of cellulose had an impact on the mechanical properties of LS fiber bundles. Furthermore, the fiber bundles density of LS varies range of 385.46-468.70 kg/m³, much less than that of jute (1360.40 kg/m³) and Arenga engleri (950.20 kg/m³) while LS fiber bundles has superior specific modulus.

The scheme to realize high speed (~250Gb/s) all-optical Boolean logic gates using semiconductor optica amplifiers with quantum-dot (QD-SOA) is introduced and analyzed in this review. Numerical simulation method was presented by solving the rate equation and taking into account nonlinear dynamics including carrier heating and spectral hole-burning. Binary phase shift keyed (BPSK) signal and on-off keyed signal are used to generate high speed all-optical logic gates. The applications based on all-optical logic gates such as, all-optical latches, pseudo random bit sequence (PRBS) generation and all-optical encryption, are also discussed in this review. Results show that the scheme based on QD-SOA is a promising method for the realization of high speed all-optical communication system in the future.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

Early detection of wildfires has been limited using the sun-synchronous orbit satellites due to their low temporal resolution and wildfires’ fast spread in the early stage. NOAA’s geostationary weather satellites GOES-R can acquire images every 15 minutes at 2km spatial resolution, and have been used for early fire detection. However, advanced processing algorithms are needed to provide timely and reliable detection of wildfires. In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R dense time series data. GRU model maintains good performance on temporal modelling while keep a simple architecture, makes it suitable to efficiently process time-series data. 36 different wildfires in North and South America under the coverage of GOES-R satellites are selected to assess the effectiveness of the GRU method. The detection times based on GOES-R are compared with VIIRS active fire products at 375m resolution in NASA’s Fire Information for Resource Management System (FIRMS). The results show that GRU-based GOES-R detections of the wildfires are earlier than that of the VIIRS active fire products in most of the study areas. Also, results from proposed method offer more precise location on the active fire at early stage than GOES-R Active Fire Product in mid-latitude and low-latitude regions.

The development of mobile internet technology has enabled companies to use social media for E-commerce. Some companies use personified images and languages to communicate with consumers in this context. How does personified communication affect consumer behavior in social commerce? Are consumers willing to accept this new form of communication under social commerce? To answer these questions, this paper explores consumers' willingness to take per-sonified communication in the context of social commerce. It investigates the role of cognitive needs in regulating the internal mechanism and proposes some suggestions for enterprises to improve social media communication. Specifically, this paper presents an improved model based on the TAM model. In our model, perceived interaction is introduced as a new independent variable, and cognitive need is added as a regulatory variable, which is more suitable for social commerce. We conduct a questionnaire survey on the Internet and analyze data using AMOS and SPSS. The results show that perceived usefulness and perceived interaction positively im-pact attitude, which influences consumers' willingness to purchase. Furthermore, the cognitive need as the regulatory variable significantly affects the influencing path from perceived use-fulness to attitude and purchase intention.

As a new kind of highly compact and efficient micro-channel heat exchanger, printed circuit heat exchanger (PCHE) is a promising candidate satisfying the heat exchange requirements of liquefied natural gas (LNG) vaporization at low and high pressure. The effects of airfoil fin arrangement on heat transfer an flow resistance were numerically investigated using supercritical liquefied natural gas (LNG) as a working fluid. The thermal properties of supercritical LNG were tested by utilizing a REFPROF software database. Numerical simulation was performed using FLUENT. The inlet temperature of supercritical LNG was 121 K,and its pressure was 10.5MPa. The reference mass flow rate of LNG was set 1.22 g/s for the vertical pitch L_v = 1.67 mm and the staggered pitch L_s = 0 mm, with the Reynolds number of about 3750. The SST k-ω model with enhanced wall treatment was selected by comparing with the experimental data. The airfoil fin PCHE had better thermal-hydraulic performance than that of the straight channel PCHE. Moreover, the airfoil fins with staggered arrangement displayed better thermal performance than that of the fins with parallel arrangement. The thermal-hydraulic performance of airfoil fin PCHE was improved with increasing L_s and L_v. Moreover, L_v affected on the Nusselt number and pressure drop of airfoil fin PCHE more obviously. In conclusion, a sparser staggered arrangement of fins showed a better thermal-hydraulic performance in airfoil fin PCHE.

The COVID-19 pandemic over the past years has shown a great need for rapid, low-cost and on-site detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this paper, an aptamer-based colloidal gold nanoparticle lateral flow test strip was well developed to realize the visual detection of wild type SARS-CoV-2 spike protein (SP) and multiple variants. Under the optimal reaction conditions, a low detection limit of SARS-CoV-2 S protein of 0.68 nM was acquired, and the actual detection recovery was 83.3% to 108.8% for real world samples. This suggests a potential tool for the prompt detection of SARS-CoV-2 with good sensitivity and accuracy, and a new method for the development of alternative antibody test strips for the detection of other viral targets.

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

The testing of high-dimensional normality has been an important issue and has been intensively studied in literatures, it depends on the Variance-Covariance matrix of the sample, numerous methods have been proposed to reduce the complex of the Variance-Covariance matrix. The principle component analysis(PCA) was widely used since it can project the high-dimensional data into lower dimensional orthogonal space, and the normality of the reduced data can be evaluated by Jarque-Bera(JB) statistic on each principle direction. We propose two combined statistics, the summation and the maximum of one-way JB statistics, upon the independency of each principle direction, to test the multivariate normality of data in high dimensions. The performance of the proposed methods is illustrated by the empirical power of the simulated data of normal data and non-normal data. Two real examples show the validity of our proposed methods.

Environmental decentralization (ED), or the allocation of environmental protection affairs and responsibilities among various administrative authorities, affects the effectiveness of environmental regulation in promoting green total factor productivity (GTFP). Based on panel data of 30 Chinese provinces from 2001 to 2015, this paper employs dynamic panel models to test the effects of environmental regulations (environmental protection investment, ENV; pollutant discharge fees, PDF) on GTFP, with or without being influenced by ED. Without the impact of ED, GTFP is significantly inhibited by ENV while significantly promoted by PDF. Considering the impact of ED, with the strengthening of ED, the negative effects of ENV on GTFP is significant; contrarily, the positive effects of PDF on GTFP is significant; improving provincial ED adds negative effects of ENV, while reduces the positive effects of PDF; increasing prefectural ED reduces negative effects of ENV; expanding county-level ED adds the positive effects of PDF. Therefore, to boost GTFP growth, prefectural environmental protection authorities should have more autonomy in ENV, while the county-level should have more autonomy in PDF.

During public health events, Active Mobility (walking and cycling) plays an important role in securing residents' travel. To enhance the resilience of urban transportation, this article integrates the travel environment elements for walking and cycling and constructs a travel environment for Active Mobility evaluation index system. This article uses survey data from the main urban area of Harbin in the context of the COVID-19 pandemic in May 2022, and combines the Gradient Boosting Decision Tree (GBDT) and Impact-Asymmetry Analysis (IAA) methods to analyze the satisfaction of the travel environment for Active Mobility. It proposes strategies for optimizing the travel environment for Active Mobility, ensuring residents' travel during public health events, guiding them to adopt Active Mobility, and improving urban transportation resilience. This research shows that Active Mobility can enhance urban transportation resilience. In addition, there are differences in resident demand for walking and cycling environments in the travel environment for Active Mobility. Residents are more concerned about the comfort of the walking environment, while they prioritize the convenience of the cycling environment.

Project complexity is usually considered as one of main causes of cost overruns, resulting in poor performance and thus project failure. However, empirical studies focused on evaluating its effects on project cost remain lacking. Given this circumstance, this study attempts to develop the relationships between project cost and the multidimensional project complexity elements. We establish complexity as a multidimensional factor including the task, organization, market, legal, and environment complexities. This study uses an empirical evidence-based structural model to account for the relationships between project cost and project complexity. By doing so, a quantitative assessment of multi-dimensional project complexity has been developed. The findings suggest that task and organization complexities have direct effects on project cost, while market, legal and external environment complexities have indirect effects on project cost. The practical contribution is that the findings can improve the understanding of which dimension of complexity significantly influence project cost, and the need to focus efforts on strategically addressing that complexities.

In this paper, we investigate the stabilization of a one-dimensional thermoelastic laminated beam with structural damping, coupled to a heat equation modeling an expectedly dissipative effect through heat conduction governed by Gurtin-Pipkin thermal law. Under some assumptions on the relaxation function g, we establish the well-posedness for the problem. Furthermore, we prove the exponential stability and lack of exponential stability for the problem. To achieve our goals, we make use of the semigroup method, the perturbed energy method and Gearhart-Herbst-Prüss-Huang theorem.

In this paper, we study a generalised CIR process with externally-exciting and self-exciting jumps, and focus on the distributional properties and applications of this process and its aggregated process. The first and second moments of this jump-diffusion process are used to calculate the insurance premium based on mean-variance principle. The Laplace transform of the aggregated process is derived, and this leads to an application for pricing default-free bonds which could capture the impacts of both exogenous and endogenous shocks. Illustrative numerical examples and comparisons with other models are also provided.

This article focuses on artificial intelligence in educational technology, starting with an introduction to educational technology, an interdisciplinary field of study that covers the design, development, utilization, and evaluation of technology and digital tools in educational Settings. A detailed description of its definition in an academic context - a multidisciplinary field of computer science and cognitive science that deals with the development of computational systems that exhibit intelligent behaviour, describing its areas of coverage and scope of application. It then introduces the benefits of AI in education technology, specifically addressing personalized learning, adaptive learning systems, automated scoring and feedback, virtual tutors and chatbots, data analytics, as well as content recommendations and natural language processing, accessibility and inclusion. Then it introduces the main concepts of AI personalized learning: AI personalized learning uses the power of artificial intelligence to meet the unique needs and preferences of individual learners, as well as its key principles and main characteristics. Adaptive learning systems harness the power of artificial intelligence and data analytics to tailor the learning experience to each student's needs and abilities, as well as its core principles and strengths. It also introduces the main operating principles of automated grading and feedback: it uses artificial intelligence and computer algorithms to evaluate and evaluate student assignments, tests and exams without the direct involvement of human graders, and its associated benefits. Secondly, the main concepts of virtual tutor are introduced: Virtual tutor is a computer-based system that uses artificial intelligence and machine learning algorithms to provide students with personalized and interactive educational support and its key characteristics and main advantages, and then the nature and benefits of chatbots and help in the field of education. The final conclusion summarizes the benefits and future challenges of integrating AI into educational technology.

Alzheimer's Disease (AD) is a neurodegenerative disease that is common in the elderly. This paper introduces the overview of Alzheimer's disease and the application of relevant signal processing methods in its detection. Signal processing is a technique that converts raw data into meaningful information and is widely used in the medical field. This paper lists common signal processing techniques, including Fourier transform, time-frequency analysis and statistical signal processing, and discusses their applications in the detection of Alzheimer's disease. Fourier transform can convert time domain signals into frequency domain representations, providing an effective tool for the study of EEG in Alzheimer's disease. Time-frequency analysis can perform a combined time and frequency analysis of the signal to help detect the signal characteristics of Alzheimer's disease. Statistical signal processing methods can be used to identify the features of Alzheimer's disease by building mathematical models. Finally, the challenges of Alzheimer's disease detection are discussed, including signal noise, diversity, and insufficient data volume. Through in-depth research and development of signal processing methods, it is expected to improve the accuracy and efficiency of early detection of Alzheimer's disease.

In this paper, the filtering method of biomedical image denoising is described comprehensively. Firstly, it introduces the biomedical image denoising, describes the relationship between biomedical image denoising and medical care, introduces the filtering methods, the filtering methods of biomedical image denoising, the challenges encountered by the current filtering methods, and other application fields of filtering methods. Firstly, the background of biomedical image denoising is introduced. Biomedical image denoising is a challenge. Different imaging modes have different noise characteristics, and noise levels can vary greatly depending on the specific application. Secondly, it describes that biomedical image denoising plays an important role in medical care, and the biomedical image directly affects the patient's diagnosis, treatment plan and the overall quality of medical care service. Then the filtering method is introduced in detail, describing the core concepts and related features of linear filtering, nonlinear filtering and frequency domain filtering, and then focusing on the adaptive filtering method, describing the characteristics, conditions of use, common algorithms and advantages of adaptive filtering method. Then the filter methods of biomedical image denoising are introduced, and the core concepts of Gaussian filter, median filter, total variation denoising and Wiener filter are introduced respectively. Then, the challenges encountered by filtering methods are described, such as the accurate selection of filters, the balance between noise reduction and image detail preservation are introduced. Finally, the application of filtering method in other fields is mentioned, such as audio processing, speech recognition and so on. In summary, this paper comprehensively expounds the denoising and filtering methods of biomedical images, the filtering methods of medical image denoising, the relationship between medical image denoising and medical care, and the challenges encountered by filtering methods.

This article reviews the introduction of Alzheimer's Disease (AD), neural networks, training and learning of neural networks, applications of neural networks in early diagnosis of AD, applications of neural networks in AD drug discovery, other brain diseases, and challenges faced by AD. First, the paper introduces the background and characteristics of AD. AD is a degenerative neurological disorder characterized by impaired memory, decreased cognitive function, and loss of neurons. These characteristics place a huge burden on the lives and families of patients. Next, the basic principle and structure of neural network are discussed. A neural network is a computational model made up of multiple neurons that can perform tasks by learning and adapting to input data. In particular, the key concepts of neural network hierarchy, activation function and weight adjustment are discussed. Then, the training and learning methods of neural networks are discussed. Common techniques such as backpropagation algorithm and gradient descent optimizer are introduced in detail, as well as the importance of data preprocessing and model evaluation. Next, the paper focuses on the application of neural network in early diagnosis of AD. By extracting features from brain image data, neural networks can automatically identify differences between AD patients and healthy subjects, enabling early diagnosis and intervention. In addition, the application of neural networks in AD drug discovery is also discussed. By analyzing and predicting a database of known drugs, neural networks can help discover potential treatments for AD and speed up the drug discovery process. The paper further explores the application of neural networks in other brain diseases and highlights the challenges faced by AD, such as the lack of reliable biomarkers, complex pathological mechanisms, etc. In summary, this paper presents a systematic overview of AD, neural networks, training and learning of neural networks, applications of neural networks in early diagnosis of AD and drug discovery, and other brain diseases and challenges associated with AD.

Changes in curricula, publication policy and information technology, notably in China have led to concentrations in the role of STEM (science, technology, engineering and mathematics) education in early childhood and applauded to proliferations of imported up-to-date reading materials and mobile apps in English. This paper proposes a longitude study of a Chinese toddler learning STEM by reading picture books and playing with tablet and suggests new horizons in parenting and in STEM education during children's early years. The present study carried out from 2016, when the participant reached one year old, eligible to learn to speak and to concentrate on the picture books read by parents who had filled a language background questionnaire with information on themselves and the participant. Tablet playing brought about for the two-year-old toddler and collections of STEM books in English was added for the second year. Data collection lasted for two years with an iLab video camera, capturing utterances and motions for five minutes per week transcribed by VoiceScript software. Tests were given quarterly at private home by tapping in mobile app "Bilingual Child Learning" which consists of 20 basic STEM themes before scores were collected. Findings indicate that (1) it is accessible for children of very early years to be engaged in English STEM resources, (2) kids' limited English dominance does not impede learning STEM, (3) and to think in English in early STEM contributes to children's English.

Studies in the area of cross-linguistic influence (CLI) have attracted the focus of multi-linguistic learners. However, little research on CLI deals with Asian learners, particularly Chinese-speaker with knowledge of two or more foreign languages. The present study explores CLI in L1 Chinese learners with both English (L2) and Spanish (L3) as foreign languages who are studying in Madrid, a Spanish-speaking community; their studies coincided with data collection. English learners were instructed to speak for analysis purposes, with the following aims: (i) to observe the most frequent category (functional transfer, code-switching, borrowing and coinage) in the CLI instances; (ii) to determine the source language of CLI; (iii) to investigate whether CLI factors, including language distance, L2 status, proficiency and recency of use, intervene in the appearance of CLI instances in the participants. Data was gathered from 16 female Chinese students at Complutense University of Madrid (UCM). These were master students aged 22 to 26, who visited Spain for more than 5 months when they participated in the present study. The instrument used was an English semi-structured interview. Results primarily reveal that (a) borrowing is the most prevalent category, accounting for 70% of the CLI instances; (b) Spanish is the main source language of CLI while Chinese plays a functional role in the transfer process; (c) language distance proves to be the strongest predictor of CLI.

Remote sensing-based models usually have difficulty in generating spatio-temporally continuous terrestrial evapotranspiration (ET) due to cloud cover and model failures. To overcome this problem, machine learning methods have been widely used to reconstruct ET. However, studies comparing and evaluating the accuracy and effectiveness of reconstruction among different machine learning methods remain scarce. In this study, four popular machine learning methods (deep forest, deep neural network, random forest, extreme gradient boosting) were used to reconstruct the ET product, addressing gaps resulting from cloud cover and model failure. The ET reconstructed by four methods were evaluated and compared in Heihe River Basin. The results showed that four methods performed well in the Heihe River Basin, but the RF method was particularly robust. It not only performed well compared with ground measurement (R = 0.73), but also reconstructed ET throughout the basin. Validation based on ground measurement showed that DNN and XGB models performed well (R > 0.70). However, few gaps still existed in the desert after reconstruction, especially for the XGB model. The DF model filled these gaps throughout the basin, but the model had lower consistency compared with ground measurement (R = 0.66) and yielded many low values. The results of this study suggested that machine learning methods had considerable potential in reconstruction of ET at regional scale.