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

Some researchers in Taiwan argue that the current mechanism by which government subsidies are allocated for smart city demonstration projects warrants improvement. A comprehensive literature review determined that the development potential of smart cities should be prioritized in site selection for such demonstration projects. This study developed an evaluation framework on the basis of multi-criteria evaluation methods to enable the identification of suitable smart community demonstration sites. Evaluation criteria were first identified through the Delphi method. Next, the weights of each criterion were derived through the analytic hierarchy process. Furthermore, the capability of the proposed evaluation model was determined through simulation testing.

In this study, a composite flame retardant was created by combining fish scale (FS), fishery waste, and ammonium polyphosphate (APP), a commercially available flame retardant. The composite flame retardant was added to epoxy resin (EP) to form an EP/APP/FS composite that prevents burns and is environmentally friendly. The use of FS conforms to the concept of circular economy and lowers costs by reducing the consumption of APP. Thermogravimetric analysis (TGA), integral procedural decomposition temperature (IPDT), pyrolysis kinetics, limiting oxygen index (LOI), the Underwriters Laboratories 94 (UL94) flammability test, scanning election microscopy, Raman spectroscopy, and energy-dispersive X-ray spectroscopy were used to determine the thermal properties, flame retardant properties, flame retardant mechanism, char morphology, and composition of the composites. The TGA results indicated that the addition of 40% flame retardant raised the char residue from 16.45 wt% (pure EP) to 36.07 wt%, IPDT from 685.6 °C (pure EP) to 1143.1°C, LOI from 21% (pure EP) to 30%, and UL94 classification from fail (pure EP) to V-0. These results suggest an increase in char residue, which indicates better protection of the polymer matrix material. The improvements in IPDT, LOI, and UL94 classification, which indicate greater thermal stability, lower flammability (from flammable to fireproof), and higher flammability rating (from fail to V-0), respectively, suggest that the composite material has favorable thermal properties and is less inflammable.

This paper takes the VR animation display of the Ming Xiao Mausoleum General stone statue life as an example to study the advantages of VR animation in the display of material heritage. Combined with literature and pictures, the digital restoration of the Ming Xiao Mausoleum stone statue is carried out in MAYA and Z brush, and the construction of the scene and the output of the final effect are realized in UE4.

This study used the sol–gel method to synthesize a non-halogenated hyperbranched flame retardant containing nitrogen, phosphorus and silicon, HBNPSi, which was then added to a polyurethane (PU) matrix to form an organic–inorganic hybrid material. Using 29Si nuclear magnetic resonance, energy-dispersive X-ray spectroscopy of P- and Si-mapping, scanning electron microscopy, and X-ray photoelectron spectroscopy, this study determined the organic and inorganic dispersity, morphology, and flame retardance mechanism of the hybrid material. The condensation density of the hybrid material PU/HBNPSi was found to be 74.4%. High condensation density indicates a dense network structure of the material. The P- and Si-mapping showed that adding inorganic additives in quantities of either 20% or 40% results in homogeneous dispersion of the inorganic fillers in the polymer matrix without agglomeration, indicating that the organic and inorganic phases had excellent compatibility. In the burning test, adding HBNPSi to PU resulted in the material passing the UL-94 standard at the V2 level, unlike the pristine PU, which did not meet the standard. The results demonstrated that after non-halogenated flame retardant was added to PU, the material’s flammability and dripping were lower, thereby proving that flame retardants containing elements such as nitrogen, phosphorus, and silicon exert an excellent flame retardant synergistic effect.

Translational rockslides caused by toe excavation are one of the commonly seen geohazards in mountainous regions due to line traffic construction. Quantifying their failure extension length (FEL) and travel distance are of significant interest as well as huge challenges in landslide hazard assessment. In this paper, a simple criterion is proposed for predicting these two factors based on the principles of rigid body limit equilibrium and kinetic energy theorem. Further, the proposed criterion is validated against the field observations and numerical results with a practical case of the Xinjianan landslide, a medium-sized translational rockslide that occurred in 2013 in Nanchuan District, Chongqing. The findings indicate that a tiny discrepancy can be found in FEL between the field observations and the proposed criteria, while this discrepancy could be considerable in travel distance between different methods. However, the relative discrepancies all fall within 20%, deemed acceptable.

In tobacco plants, symbiont endophytic fungi are widely distributed in all tissues where they play important roles. It is therefore important to determine the species distribution and characteristics of endophytic fungi in tobacco. Here, two parasitic fungi Leptosphaerulina chartarum and Curvularia trifolii were isolated and identified from normal tobacco tissue. We sequenced the mitogenomes of these two species and analysed their features, gene content, and evolutionary histories. The L. chartarum and C. trifolii mitochondrial genomes were 68,926 bp and 59,100 bp long circular molecules with average GC contents of 28.60% and 29.31%, respectively. The L. chartarum mitogenome contained 36 protein coding genes, 26 tRNA genes, and 2 rRNA genes (rrnL and rrnS), which were located on both strands. The C. trifolii mitogenome contained 26 protein coding genes, 29 tRNA genes, and 2 rRNA genes (rrnL and rrnS). The L. chartarum 26 tRNAs ranged from 70 bp to 84 bp in length, whereas the 29 tRNAs in C. trifolii ranged from 71 bp to 85 bp. L. chartarum and C. trifolii mtDNAs had an identical mitochondrial gene order and orientation and were phylogenetically identified as sisters. These data therefore provide an understanding of the gene content and evolutionary history of species within Pleosporales.

Ming-style round-backed armchairs as a classic Chinese chair design are renowned for the blend of ergonomics, practicality, and elegance. Although the Chinese armchair furniture industry has made strides in sustainability, there is still a need for further improvements in material selection, manufacturing processes, and supply chain management to fully support the development of sustainable furniture. Laminated bamboo lumber as new sustainable materials are becoming a popular option for furniture designers in the era of "sustainable design". This research aims to investigate the feasibility and application of laminated bamboo lumber in the design of Chinese armchair furniture and proposes innovative ideas for optimizing the armchair's design. First, an empirical study was conducted to comprehensively understand the classification of Ming-style round-backed armchairs’ structure to develop a 3D model. Secondly, an experimental research method was then employed to explore the parameters of laminated bamboo lumber for future studies. Additionally, a validation experiment was conducted to compare real-world scenarios with simulations using finite element analysis in Ansys. Finally, finite element analysis was used to test the feasibility and application of laminated bamboo lumber in furniture design, focusing on the material’s mechanical properties. Results indicated that laminated bamboo lumber has excellent mechanical properties as furniture design materials, subsequently, using the optimized results, the use of 0.6319 kg of steel was successfully reduced by 23.68% to ensure the armchair’s stability. This provides a reference for the future compter-assist and standardized innovative design of Chinese armchair. By incorporating compter-assist design and lightweight optimization, it is possible to save materials and make more efficient use of resources, thereby contributing to sustainable development goals in the field of furniture design.

Transition metal dichalcogenides (TMDs) monolayers exhibit unique valleytronics properties due to the dependency of the coupled valley and spin state at the hexagonal corner of the first Brillouin zone. Precisely controlling valley spin-polarization via manipulating the electron population enables its application in valley-based memory or quantum technologies. This study uncovered the uncompensated spins of the antiferromagnetic oxide (NiO) serving as the ferromagnetic (FM) order to induce valley spin-polarization in molybdenum disulfide (MoS₂) monolayers via the magnetic proximity effect (MPE). A spin-resolved photoluminescence spectroscopy (SR-PL) was employed to observe MoS₂, where the spin-polarized trions appear to be responsible for the MPE, leading to a valley magnetism. Results indicate that local FM order from the uncompensated surface of NiO could successfully induce significant valley spin-polarization in MoS₂ with the depolarization temperature approximately at 100 K, which is relatively high compared to related literature. This study reveals new perspectives and potential of AFM materials in the field of exchange-coupled van der Waals heterostructures.

The 2019 novel coronavirus (2019-nCoV) causes novel coronavirus pneumonia (NCP). Given that approved drug repurposing becomes a common strategy to quickly find antiviral treatments, a collection of FDA-approved drugs can be powerful resources for new anti-NCP indication discoveries. In addition to synthetic compounds, Chinese Patent Drugs (CPD), also play a key role in the treatment of virus related infections diseases in China. Here we compiled major components from 38 CPDs that are commonly used in the respiratory diseases and docked them against two drug targets, ACE2 receptor and viral main protease. According to our docking screening, 10 antiviral components, including hesperidin, saikosaponin A, rutin, corosolic acid, verbascoside, baicalin, glycyrrhizin, mulberroside A, cynaroside, and bilirubin, can directly bind to both host cell target ACE2 receptor and viral target main protease. In combination of the docking results, the natural abundance of the substances, and botanical knowledge, we proposed that artemisinin, rutin, glycyrrhizin, cholic acid, hyodeoxycholic acid, puerarin, oleanic acid, andrographolide, matrine, codeine, morphine, chlorogenic acid, and baicalin (or Yinhuang Injection containing chlorogenic acid and baicalin) might be of value for clinical trials during a 2019-nCov outbreak.

Photodynamic inactivation (PDI) combines the nontoxic photosensitizer (PS) and visible light to generate reactive oxygen species (ROS), which can cause oxidative damages in (on) microbial organisms. Previously, we have shown that chitosan can augment the bactericidal efficacy mediated by PDI against bacteria and Candida. In this study, we showed that the antimicrobial action of chitosan to augment PDI relates to the enlargement of cell surface destruction. The microbial cell surfaces exhibit severe irregular shapes after PDI in the presence of chitosan. Furthermore, increase in the concentrations or incubation time of chitosan significantly reduce the amounts of photosensitizers TBO required, indicating that chitosan could be a synergistic agent with PDI against human pathogens. A prolonged lag phase was found in PDI surviving microbial cells, in which chitosan can act to synergistically eradicate the cells. Once the impaired cells rebuild their cellular functions from PDI-induced damage, the increased cytotoxic effect of chitosan disappeared. Together, our results suggest that chitosan with an augmented bactericidal activity after PDI is to inhibit the rehabilitation of PDI surviving cells, leading to microbial death.

Polydimethylsiloxane with hydroxy groups was functionalized to form functionalized polydimethylsiloxane, which subsequently underwent an addition reaction with isophorone diisocyanate to form the prepolymer. Next, 3-aminopropyltriethoxysilane (APTS) reacted with 3-glycidoxypropyltrimethoxysilane (GPTS) to produce bridged polysilsesquioxanes, and the sol–gel technology was employed to form hyperbranched polysiloxane nanoparticles with hydroxy groups, which was used as the additive. The hyperbranched polysiloxane and the prepolymer containing NCO functional groups then underwent an addition reaction to produce the hybrid materials. Fourier-transform infrared spectroscopy and 29Si nuclear magnetic resonance were used to characterize the structure of the polyurethane hybrid. Regarding thermal stability, after the hyperbranched polysiloxane nanoparticles was introduced, the integral procedural decomposition temperature increased from 348 ºC for polyurethane matrix to 859 ºC for the hybrid material. The results revealed that the thermal stability of the hybrid material substantially increased by approximately 247%.

The objective of this research is to establish a better understanding of the current landscape of digital learning research and sustainable development by using CiteSpace. First, we retrieved published publications from the Web of Science (2004–2022). Following that, we examined the primary research strengths and important subjects of digital learning from two perspectives: collaboration networks (including collaborative networks across countries, institutions, and authors) and co-citation networks. We examined the co-citation network from three perspectives: cluster analysis, the most active citers, top references. Furthermore, referenced journals, popular themes, and rising trends were examined. These findings indicate the primary study subjects in the field of digital learning, the most intriguing research literature, and each period's emerging research hotspots. Finally, we proposed further study ideas for future paths.

Influenced by geological, climatic, and natural weathering factors, the Great Wall heritage is sus-ceptible to deformations, posing significant challenges to the comprehensive preservation of the Great Wall sites. To investigate techniques for monitoring deformations in extensive linear cultural heritage sites, such as the Great Wall, this study utilizes the SBAS-InSAR technique for deformation monitoring and analysis. A dataset comprising 161 Sentinel-1A images spanning from March 2017 to January 2022 was chosen for SBAS-InSAR processing, yielding a deformation velocity field. To verify result credibility, a typical mountainous segment spanning approximately 896.53 km within the Great Wall landscape corridor underwent analysis. The findings suggest that around 75.8% of the landscape corridor along the Shanxi section of the Ming Great Wall maintain relative stability, displaying deformation rates varying from -10 to 10 mm/year. The remaining 24.2% of the land-scape corridor experiences notable deformations, including a maximum subsidence rate of 33.1 mm/year and a maximum subsidence of 148.6 mm. This study illustrates the potential utility of the SBAS-InSAR technique for monitoring and evaluating surface deformations in extensive linear cultural heritage sites.

The resilience of towns and cities refers to their ability to adapt and recover when confronted with pressures or challenges. This study employs ten variables as indicators to assess the resilience of urban areas by analyzing official data and constructing a multilevel mixed-effects structural equation model. The empirical findings demonstrate that enhancing resilience significantly influ-ences urban service functions, such as strengthening healthcare systems, stabilizing the real estate market, and addressing socio-economic challenges. Specifically, factors such as healthcare re-sources, housing demand, population structure, and social security exhibit varying levels of resil-ience, which profoundly impact the spatial distribution of these factors and socio-economic de-velopment. Disparities in healthcare resource allocation, demographic aging trends, and shifts in the housing market closely correlate with resilience levels in different regions. Additionally, the study emphasizes that improving resilience not only boosts the reliability and security of urban services but also ensures that communities receive necessary support and protection during times of adversity. Consequently, policymakers should recognize the pivotal role of urban resilience in resource allocation and social equity, devising corresponding strategies to enhance the resilience of these areas.

With more companies entering the realm of electric vertical take-off and landing (eVTOL), and governments enacting policies to support the development of low-altitude economies, the commercial potential of eVTOL is being recognized by the public. However, true commercialization is still a long way off. This article analyzes the technologies, product features, potential markets, and government policies related to eVTOL, and constructs a four-stage, four-layer Policy-Technology Roadmap (P-TRM) model to guide the R&D process of eVTOL. Then transform it into a system structural model, and the Decision-making Trial and Evaluation Laboratory (DEMATEL) method is used to identify several key nodes in the R&D process. Utilizing the Technology Adoption Life Cycle (TALC) theory for interpretation and analysis, the article concludes by proposing strategies in product, technology, and policy support for how eVTOL can successfully cross the chasm. This preliminary analysis of the development path, key nodes, and necessary measures for crossing the chasm provides insights for the R&D and commercialization of eVTOL.

Agriculture is an industry that heavily relies on the environment. The increasing frequency of ex-treme disasters attributable to climate change has adversely affected agricultural land and dis-rupted the stability of the supply of agricultural products. Therefore, we implemented a research program focused on current strategies for adapting to agricultural meteorological disasters. The primary goal was to actively promote disaster prevention information and techniques through information platforms and applications and to provide refined forecasting and an early warning system to enhance preparedness for and recovery from agricultural disasters. This initiative can transform passive mitigation into dynamic action by disseminating crucial information to farmers. We integrated meteorological data and crop characteristics to develop disaster prevention strate-gies for the predisaster, during-disaster, and postdisaster stages to empower farmers to implement autonomous disaster prevention, ensuring their profitability and minimizing the impact of disas-ters. This paper presents an agricultural disaster prevention system involving cross-disciplinary collaboration to establish an early warning system for crop disasters. However, the effectiveness of the early warning system relies on the availability of complete meteorological and crop infor-mation, necessitating high-density agricultural meteorological stations, refined weather forecast services, historical crop damage data, and ongoing research and development on disaster preven-tion technology. In the system, a diversified social media interface is used to provide local farmers with weather forecast information. When impending disasters are identified, the platform acti-vates disaster prevention measures to reduce agricultural losses. This article paper introduces Taiwan’s agricultural disaster prevention system as a complete disaster prevention strategy.

Choroidal neovascularization (CNV) is a key pathological feature of several of the leading causes of vision loss including neovascular age-related macular degeneration. Here we show that a calreticulin anti-angiogenic domain (CAD)-like peptide 27, CAD27, inhibited in vitro angiogenic activities, including tube formation and migration of endothelial cells, and suppressed vascular sprouting from rat aortic ring explants. In rat model of laser-induced CNV, we demonstrate that intravitreal injection of CAD27 significantly attenuated the formation of CNV lesions as measured via fundus fluorescein angiography and choroid flat-mounts (19.5% and 22.4% reductions at 10μg and 20μg of CAD27 injected, respectively). Similarly, the reduction of CNV lesions was observed in the groups of rats that had received topical applications of CAD27 (choroid flat-mounts: 17.9% and 32.5% reductions at 10μg/mL and 20μg/mL of CAD27 installed, respectively). Retinal function was unaffected, as measured using electroretinography in both groups received interareal injection or topical applications of CAD27 at least for 9 days. These findings show that CAD27 can be used as a potential therapeutic alternative for targeting CNV in the diseases such as neovascular age-related macular degeneration.

High-spin states of 192Tl are populated by the heavy ion fusion-evaporation reaction 181Ta(16O, 5n)192Tl at 97 MeV beam energy. A new level scheme with eight new levels is constructed and the level spins are tentatively assigned. The negative-parity yrast band is extended up to 23^{-}\hbar. Subsequently, the systematics of signature splitting and signature inversion are discussed for the negative-parity yrast band of odd-odd Tl isotopes including 192Tl, 194Tl, 196Tl, and 198Tl. With the increase of neutron number signature inversion is found in 196,198Tl at high-spin state in these four Tl isotopes. The reason may be due to the competition between neutron-proton interaction and Coriolis force.

The present study analyzed light emitting diodes (LEDs) as an output load and used a Taylor series to describe the characteristic curve based on the exponential characteristic of voltage and current. A prototype circuit of a flyback LED driver system was established to verify whether the theory is consistent with actual results. This study focused on the exponential relationship of LED voltage and current. Conventional simulations usually used linear models to present LED loads. However, the linear model resulted in considerable error between simulation and actual characteristics. Therefore, this study employed a Taylor series to describe the nonlinear characteristic of an LED load. Through precise calculations with Mathcad computation software, the error was effectively reduced. Moreover, the process clarified the influence of temperature on LEDs, which benefited the characteristic analysis of the entire system. Finally, a realized circuit of 120-W flyback LED drivers was established for conducting theory verification, including theoretic analysis and evaluation of the system design process of the flyback converter. The circuit simulation software SIMPLIS was used to demonstrate the system model, which enabled quick understanding of the system framework established in this study. Regarding LEDs, a commercially available aluminum luminaire was used as the output load. The measured results of the actual circuit and the simulation results were remarkably consistent. For the same system at the same temperature, the error between the simulation and actual results was less than 3%, which proved the reliability of the Taylor series simulation.

The article presents a literature review of three Chinese manuscripts containing natural dyes recipes and three containing synthetic dyes from the Ming Dynasty to the Republican Period. The manuscripts mentioned were exclusively used as references and sources. Four databases were used to access the original documents, then, a translation from old mandarin to Spanish was made. For natural dyes, the results show four dyestuffs were commonly used to produce colors, sappanwood (Caesalpinia sappan L.), followed by safflower (Carthamus tinctorius L.), indigo (Indigofera tinctoria L.), and sophora (S. japonicum L.). While the synthetic dyes exported to or produced in China were mainly bluish, greenish, and violet probably because they were difficult to obtain from natural ones. The literature review of the dyes and their recipes can be a key factor in any art history or conservation study, improving the understanding of how the colors were achieved and as complementary information for analytical analyses. It provides useful details that contribute to the preservation of Chinese dye history on silk heritage.

Abstract: NFinFET transistors with fin channel length 90nm and a planar MOSFET transistor with channel length 180nm and 90nm are presented with characteristic curves at various gate biases. A finalized algorithm with kink effects is effectively responsible for addressing the field effect transistors. The algorithm includes the modified conventional current-voltage formula and a nonlinear heat-associated kink solution which is simplified as a Gaussian form. Three parameters in modified model includes kN (related with channel width, channel length, and gate oxide capacitor, and proportional to the mobility of carriers)Vth(Threshold Voltage), and (the inverse of Early Voltage). Those parameters are determined to minimize the discrepancies between the measured data and the fitting values, but leave kinks located at around (VGS－Vth), which are deliberately eliminated by the Gaussian form because of the agitation of thermal kink effects. The whole fitting is made to be as close as the as-measured IDS-VDS. In the mean time, those determined parameters are physically meaningful after the analysis has been done.

Multicellular organisms organize themselves according to two principles; first, the equilibrium between the driving force of unstable state cells and apoptosis or senescence; and second, the mutual equilibrium between the functional requirements of different types of cells. For the first principle, we deduce that stem cells at different levels have their own growth limits, which are determined by two factors: the ability of the stem cells to enter an unstable state (specifically, the ability of cells to divide and differentiate); and the rate of cellular senescence, loss of function, and finally, apoptosis. The superposition of stem cell limits at different levels over each other can amplify small differences at the genetic level. Moreover, the growth limits of different organs are different, which lead to different individuals having completely different appearances. The second principle is that the sum of the specific output functions of an organ must be equal to the overall demand for the function to be provided by the organ. If negative entropy input can meet this equilibrium, defects in certain genes will cause these defective individuals to become larger or develop other morphology.

The bridge crane is often used in a complex environment, often subject to interference of all loads. Some uncertainties factors often have an inevitable impact on its swing. So the force situation of the bridge crane during a working cycle is analyzed, and a three-dimensional dynamic mathematical model of the bridge crane is built. Through the simulation analysis of the model under the action of driving force and wind load, the change law of the swing angle of the bridge crane is studied. Then, the fuzzy control theory is used to determine the control parameter in the anti sway control process. The position, swing angle deviation and deviation rate of the bridge crane are taken as the input, and the parameter correction is obtained after the fuzzification by using the center of gravity method, the anti sway fuzzy control system of the bridge crane is designed and simulated. The research results show that the fuzzy PID anti sway controller can not only improve the adaptability of the control system, but also overcome the large overshoot, quickly restrain the swing, and effectively realize the anti sway function of the bridge crane.

Cs2NaInCl6 double perovskites, which have excellent photoelectric conversion properties and are non-toxic and lead-free, have recently attracted much attention. In particular, double perovskite quantum dots (QDs) are considered to be a promising material for optoelectronic device applications. Ligands such as oleic acid (OA) and oleylamine (OAm) are essential for the synthesis of perovskite QDs, but their roles on double perovskite QDs are not yet clear. In this study, we have investigated the binding of OA and OAm to Cs2NaInCl6 QDs through FTIR and NMR and their effects on the surface defect reduction and stability improvement for Cs2NaInCl6 QDs. We found that only OAm was bound to the QD surfaces while OA was not. The OAm has a great effect on photoluminescence quantum yield (PLQY) improvement by passivate the QD surface defects. The stability of the QDs was also investigated, and it was shown that OA played a significant role in the stability of the QDs. Our findings provide critical insights into the roles of the ligands for photophysical properties and stability of lead-free double perovskite QDs.

Using lightweight fire-rated board (LFRB) presents cost-effective opportunities for various passive fire protection measures. The aim of the project is to develop a LFRB with enhanced fire resistance, acoustic properties, and mechanical properties. These properties were determined using the Bunsen burner, furnace, energy dispersive X-Ray, impedance tube instrument, and Instron universal testing machine. To fabricate the LFRBs, vermiculite and perlite were blended with flame-retardant bind-ers, and four types of LFRBs were produced. A fire test was conducted to compare the fire-resistance performance of the LFRBs with a commercially available flame retardant board. The B2 prototype showed exceptional fire-resistant properties, with a temperature reduction of up to 73.0 °C as compared to the commercially available fire-rated magnesium board. Incorporating nano chicken eggshell into the specially formulated flame-retardant binder preserved the LFRBs’ structural integrity, enabling them to withstand fire for up to 120 minutes with an equilibrium temperature of 92.6 °C. This approach also provided an absorption coefficient of α = 2.0, a high flexural strength of 3.54 MPa, and effective flame retardancy properties with a low oxygen/carbon ratio of 2.60. These results make the LFRBs valuable for passive fire protection applications in the construction and building materials industry.

Flexible capacity applications demands to large energy storage density and high breakdown electric field strength of flexible films. Here, P(VDF-HFP) with ultra-thin Al2O3 nanosheets composite films were designed and fabricated through an electrospinning process followed by hot-pressing in sandwich structured. The results show that the insulating ultra-thin Al2O3 nanosheets and the sandwich structure can enhance the composites' breakdown field (by 24.8%) and energy density (by 30.6%) remarkedly to P(VDF-HFP) polymer matrix. An energy density of 23.5 J/cm3 at the ultrahigh breakdown field of 740kV/mm can be therefore realized. Insulating test and phase-field simulation results reveal that ultra-thin nanosheets insulating buffer layers can reduce the leakage current in composites, thus it effects the electric field spatial distribution to enhance breakdown strength. Our research provides a feasible method to increase the breakdown strength of ferroelectric polymers, which is comparable to those of non-ferroelectric polymers.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

Nutrients are the driving force of plant and herbivore interactions. Different elements and fertilization levels in soil, or artificially fertilized substrates can have a direct impact on plant defense responses. Meanwhile, nutrient levels mediated by root associated microbes can indirectly affect plant-herbivore interactions. Nutrient uptake promoted by beneficial mycorrhizal fungi or rhizobacteria interacting with roots can stimulate plant tolerance to herbivore attack, as evidenced by herbivore performance, plant nutrient status, plant biomass allocation and compensatory growth. In return, herbivory affects nutrient fluxes between plants and their associated beneficial microbes. Furthermore, aboveground and belowground herbivory can affect the nutrient exchange between plants and soil microbial communities, mainly for carbon-and nitrogen-based resources supporting herbivores´ life cycles. These ecological interactions are governed by jasmonic acid (JA) and key enzymes on the molecular level. This review summarizes the current scientific literature on the role of nutrients in plant-herbivore interactions. This will support efforts to optimize plant defense strategy via managing nutrient variance.

The purpose of this paper is to construct an evaluation system for AI painting software based on generative adversarial network technology, which optimizes the performance of the related software in terms of functionality, ease of use, system performance and safety. The results of the questionnaires are statistically analyzed. In addition, exploratory factor analysis was supported to extract the data of the study, which was ultimately used to calculate the weight and importance of each index through fuzzy hierarchical analysis method. The study constructed an evaluation system for AI painting software based on generative adversarial network technology, including 16 indicators of functionality, 16 indicators of ease of use, 7 indicators of system performance, and 8 indicators of safety respectively that their alpha coefficients were 0.882, 0.962, 0.932, 0.932, and 0.932, respectively. In addition, the accumulated explanatory variances of their coefficients were 84.405%, 84.897%, 84.013%, and 72.606%, respectively, 73.013%, and 72.606%, respectively. It is clear that the items included in each of the indicators are homogeneous, with a high degree of internal consistency. This paper suggests that the development of AI painting software focusing on functionality, ease of use, system performance and safety can enhance the market competitiveness of the software.

Spectacular shifts have been led to by The COVID-19 crisis in consumer behavior. Retailers will have to work hard to meet ever-evolving customer service experience with respect to the ways in which it may be differently affected by offline or online transactions in order to win and stay relevant. We suggest an integrative framework and construct customer service experience hypotheses, based on its antecedents and consequences that will contribute to academic study as well as managerial implications. The hypotheses are tested by a simultaneous equation model employing two data sets of the retail industry's offline and online customers. In this study, 571 samples of these businesses, 319 and 252 respondents from offline and online retail channels, respectively, were collected by means of an online web survey of consumers. The results show that the impact of consequences and antecedents of CSX differs based on the media utilized. The integrative framework of CSX in its online medium is far more effective than its explanatory power offline. The outcomes are reasonably counterintuitive in so far as they demonstrate that while most elements of CSX where a service is selected offline is the same in terms of customer loyalty and value equity, the emotional element related to the service provider is higher when the service is selected offline rather than online. These outcomes indicate that, contrary to popular fears, the online medium enables firms to develop a loyal customer foundation. These findings offer perceptivity into how an online channel could be used to better complement the offline channel, contributing towards new knowledge and understanding on CSX and how it may be utilized for managerial decision-making.

Long-span steel structure trusses are widely used in factory buildings, but with the growth of service time and the increase of dynamic load fatigue, a considerable part of the long-span truss with dynamic load appears serious transverse cracks at the bottom of the middle span and oblique deformation of the abdomen in the operation process. The U-shaped cracks at the bottom and belly, as well as the mid-span down deflection of the main truss, reduced the functional function of the factory building truss structure, and had to limit the original crane load, which affected the normal safety and durability of the structure. Therefore, the application principle of the variable axial force cable system in the long-span factory building truss structure and 3D3S software modeling [1] were used. Analyzing and studying the reinforcement method of large-span powerhouse truss can provide practical experience for subsequent similar projects. In view of the above phenomenon, the large-span powerhouse trusses of Hongcheng Powerhouse 1 and No.2 located in Tonglu, Zhejiang Province are used as the research object, and the variable axial force cable method is proposed to strengthen and lift the load. Considering the span of large-span powerhouse truss, the cable system with 22m controlling force of 400kN is proposed to be selected for powerhouse 1, and the cable system with variable axial force of 24m is proposed to be selected for Powerhouse 2. The force model of large-span truss is established by using the finite element method commonly used to analyze the force of truss. Under two working conditions, The influence of reinforcement effect is analyzed and compared from three aspects: stiffness, bearing capacity and stability. And the phenomenon of uneven stress distribution is analyzed. The stress distribution characteristics of each node are understood by simulating the most disadvantageous node plates with the greatest internal force before and after reinforcement.

Background: Functional Movement Screening (FMS) allows for rapid assessment of an individual’s physical activity level and timely detection of sports injury risk. However, traditional functional movement screening often requires on-site assessment by experts, which is time-consuming and prone to subjective bias. Therefore, the study of automated functional movement screening has become increasingly important. Methods: In this study, we propose an automated assessment method for FMS based on the improved Gaussian Mixture Model (GMM). First, the oversampling of minority samples is conducted, the movement features are manually extracted from the FMS dataset collected with two Azure Kinect depth sensors, then we train the Gaussian mixture model with different scores (1 point, 2 points, 3 points) of feature data separately, finally, we conducted FMS assessment by the Maximum Likelihood estimation. Results: The improved GMM has a higher scoring accuracy (Improved GMM:0.8) compared to other models (Traditional GMM=0.38, Adaboost.M1=0.7, Naïve-Bayes=0.75), and the scoring results of improved GMM have a high level of agreement with the expert scoring (kappa=0.67). Conclusions: The results show that the proposed method based on the improved Gaussian mixture model can effectively perform the FMS assessment task and it is potentially feasible to use depth cameras for FMS assessment.

It is desirable to upgrade previous evolutionary theories, which have remained incomplete and controversial for decades. Here we employ the concept of carbon-based entities (CBEs), which include methane, amino acids, proteins, organisms, and other entities containing relatively many carbon atoms. We deduce the driving force, mechanisms, steps, modes, tempos of CBE evolution, through integration of biology, physics, and chemistry using logics for complex issues. We hence establish the Carbon-Based Evolutionary Theory (CBET). The CBET suggests that evolution is the increase in hierarchy, diversity, fitness of CBEs under natural selection and driven by thermodynamics due to the chemical effect of the thermodynamic features of the Earth on CBEs. It provides better explanations for life origin, macroevolution events, natural selection, sympatric speciation, and evolution tempos than previous evolutionary theories. It reveals the evolutionary basis of multiple important social notions, including diversity, collaboration, altruism, obeying rules, and proper increase in freedom. It refutes some wrong notions in thermodynamics, including negative entropy (negentropy) and that biological order is equal to thermodynamic order, which have misled many people. The CBET is supported by its deduction and application. It could be a rare bridge linking laws of thermodynamics, evolution of life, and development of human society, and could have great significance in various sciences.

This paper reports the efforts made and experiences gained in developing the Flood Prevention and Emergency Response System (FPERS) powered by Google Earth Engine, with focus on its applications at the three stages of floods. At the post-flood stage, FPERS integrates various remote sensing imageries, including Formosat-2 optical imagery, to detect and monitor barrier lakes, synthetic aperture radar imagery to derive an inundation map, and high-spatial-resolution photographs taken by unmanned aerial vehicles to evaluate damage to river channels and structures. At the pre-flood stage, a huge amount of geospatial data are integrated in FPERS and are categorized as typhoon forecast and archive, disaster prevention and warning, disaster events and analysis, or basic data and layers. At the during-flood stage, three strategies are implemented to facilitate the access of the real-time data: presenting the key information, making a sound recommendation, and supporting the decision-making. The example of Typhoon Soudelor in August of 2015 is used to demonstrate how FPERS was employed to support the work of flood prevention and emergency response from 2013 to 2016. The capability of switching among different topographic models and the flexibility of managing and searching data through a geospatial database are also explained, and suggestions are made for future works.

The continuous casting process of helical fiber reinforced metal matrix composites was proposed, and the experimental equipment was designed and manufactured. The relationship model be-tween the process parameters and the helical shape of the fibers in the metal matrix is analyzed by differential geometry. Helical carbon fiber reinforced lead matrix composites were prepared under different conditions. When the melting temperature and cooling intensity were increased, the helical radius of helical carbon fiber in lead matrix was increased. When the fiber rotation speed was increased, the helical radius was decreased, and the helical pitch was de-creased proportionally. The experimental results are consistent with the process model. Carbon fiber rein-forced aluminum composites were prepared. Scanning electron microscopy showed that the infiltration between the aluminum matrix and the carbon fiber was not complete. As the volume fraction of carbon fiber which was added in composites is too small, the mechanical properties of the composites have not been significantly improved.

Diagnosing congenital heart disease (CHD) remains challenging because of its complex morphology. Representing the intricate structures of CHD on conventional two-dimensional flat screens is difficult owing to wide variations in the pathologies. Technological advancements, such as three-dimensional printed heart models (3DPHM) and virtual reality (VR), could potentially address the limitations of viewing complex structures using conventional methods. This study aimed to investigate the usefulness and clinical value of four visualization modalities across three different cases of CHD, including ventricular septal defect, double outlet right ventricle, and tetralogy of fallot. Seventeen cardiac specialists were invited to participate in this study, which was aimed at assessing the usefulness and clinical value of four visualization modalities, namely, DICOM images, 3DPHM, VR, and 3D PDF. Of these modalities, 76.4% of the specialists ranked VR as the best for understanding the spatial associations among cardiac structures and for presurgical planning. Meanwhile, 94.1% ranked 3DPHM as the best modality for communicating with patients and their families. Of the various visualization modalities, VR was the best tool for assessing anatomical locations and vessels, comprehending the spatial relationships among cardiac structures, and for presurgical planning. The 3DPHM models were the best tool for medical education as well as communication. In summary, both 3DPHM and VR have their own advantages and outperform the other two modalities, i.e., DICOM images and 3D PDF, in terms of visualizing and managing CHD.

In this paper, we propose a novel approach of video skimming by exploiting the fusion of video temporal information and keyword information representation extracted from multi-model video information including audio, text and visual indices. In addition, we introduce the brand-safe filtering and sentiment analysis in order to only reserve the user-friendly content in the video skim. In the experiment by using the videos from YouTube-8M dataset, we have proved that the semantic conservation in the video skim from the proposed approach highly outperforms the approaches by only partial information of the video in conserving the semantic content of the video.

The increasing residential space differentiation is an important practical problem for Chinese cities. The different choice of living space for urban residents is a concrete reflection of social class divide, which reflects the differences in the choices and demands of different social groups for urban housing. Taking Wuhan, an important city in central China, as an example, this research divides the residential space based on the social resource structure, and analyzes and compares the spatial differentiation and influencing factors of different residential areas and houses with different prices in Wuhan by spatial differentiation indicators and geographic detector. The results show clear differences in resource structure among residential areas, and there are few high-quality residential areas with a concentrated distribution. The spatial differentiation levels of different residential areas are distinct, and the pursuit of high-quality and scarce resources is the key to the residential space differentiation of most large cities in China. In addition, residential space differentiation can lead to inter-generational problems such as housing wealth inequality, resource deprivation and solidified class identity. Exploring the mechanisms and social effect of residential space differentiation in most large cities in China can provide some reference for China's urban space planning and real estate market regulation in the new era.

A case-crossover study examined how PM_2.5 from Asian Dust Storms (ADS) affects the number of emergency room (ER) admissions for cardiovascular diseases (CVDs) and respiratory diseases (RDs). Our data indicated that PM_2.5 concentration from ADS was highly correlated with ER visits for CVDs and RDs. The odds ratios (OR) increased by 2.92 (95% CI: 1.22-5.08) and 1.86 (95% CI: 1.30-2.91) per increase 10 µg/m³ in PM_2.5 levels, for CVDs and RDs, respectively. A 10 µg/m³ increase in PM_2.5 from ADSs was significantly associated with increase in ER visits for CVDs among those 65 years of age and older (an increase of 2.77 in OR) and for females (an increase of 3.09 in OR). In contrast, PM_2.5 levels had a significant impact on RD ER visits among those under 65 years of age (OR=1.77). The risk of ER visits for CVDs increased on the day when the ADS occurred in Taiwan and the day after (lag 0 and lag 1); the corresponding risk increase for RDs only increased on the fifth day after the ADS (lag 5). In Taiwan’s late winter and spring, the severity of ER visits for CVDs and RDs increases. Environmental protection agencies should employ an early warning system for ADS to reduce high-risk groups’ exposure to PM_2.5.

This paper introduces a novel ensemble adjustment Kalman filter (EAKF) that integrates a machine-learning approach. The approach employs nonlinear variable relationships established by a deep neural network (DNN) during the analysis stage of the EAKF. This process nonlinearly projects observation increments into the state variable space. The newly developed DNN-EAKF algorithm can be applied to coupled data assimilation using coupled ocean-atmosphere models. It enhances cross-component updates in strongly coupled data assimilation (SCDA) by diminishing errors in estimating cross-component error covariance arising from insufficient ensemble members, thereby improving the SCDA analysis. This paper employs a conceptual model to conduct twin experiments, validating the DNN-EAKF’s capability to utilize cross-component observation information in SCDA effectively. The approach is anticipated to offer insights for future methodological integrations of machine learning and data assimilation and provide methods for SCDA applications in coupled general circulation models.

On the primitive Earth, both L- and D-amino acids would have been present. However, only L-amino acids are essential blocks to construct proteins in modern life. To study the relative stability of D-amino acid substituted peptides, a variety of computational methods were applied. Ten prebiotic amino acids (Gly, Ala, Asp, Glu, Ile, Leu, Pro, Ser, Thr, and Val) were previously determined by multiple meteorite, spark discharge, and hydrothermal vent studies. Some previously reported early Earth polypeptide analogs were focused on in this study. Tripeptides composed of only Asp, Ser, and Val exemplified that different positions (i.e., N-terminus, C-terminus, and middle) made a difference in the minimal folding energy of peptides, while the chemical classification of amino acid (hydrophobic, acidic, or hydroxylic) did not show a significant difference. Hierarchical cluster analysis for dipeptides with all possible combinations of the proposed ten prebiotic amino acids and their D-amino acid substituted derivatives generated five clusters. Primordial simple polypeptides were modeled to test the significance of molecular fluctuations, secondary structure occupancies, and folding energy differences based on these clusters. We found peptides with α-helices, long β-sheets, and long loops are usually less sensitive to D-amino acid replacements in comparison to short β-sheets. Intriguingly, amongst 129 D-amino acid residues, mutation sensitivity profiles presented that the ratio of more to less stable residues was about 1. In conclusion, some combinations of a mixture of L- and D-amino acids can potentially act as essential building blocks of life.

In the present work, a predictive modelling and optimization with the adaptive network based fuzzy inference system(ANFIS) modelling of mechanical properties of laser-coated NB/SiC/Ni welds was studied based on Taguchi design by laser cladding. An ANFIS model based on a Sugeno type fuzzy inference system was developed for predicting the hardness properties of SiC/BN/Ni welds by laser cladding with experimental data required for network training and prediction. Based on analysis of variance, three important factors were taken as inputs for the fuzzy logic inferences, while the hardness properties was taken as the output of the ANFIS. The microstructure of welds were analysed using scanning electron microscopy with an energy dispersive X-Ray spectrometer. Highly developed leaf-like dendrites and eutectic crystals were found in some areas of the melting zone for the BN/SiC/Ni weld, which was significantly hardened. The ANFIS model based on Taguchi's design provides a better pattern of response because the predicted and experimental values were highly similar. As a result, a satisfactory result was achieved between the predicted and experimental values of hardness in laser-coated NB/SiC/Ni welds, whereby the success and validity of the method was verified.

The Subtropical Front (STF) plays a key role in the ecology of Chilean jack mackerel Trachurus murphyi. Nonetheless, there are few remote sensing studies of the STF in the open Southeast Pacific Ocean, and almost all of them have been conducted by satellite oceanographers in Russia and Ukraine to support respective large-scale fisheries of jack mackerel in this region. We reviewed these studies that documented long-term seasonal and interannual variability of the STF from sea surface temperature (SST) and sea surface height (SSH) data. We also mapped the STF from satellite sea surface salinity (SSS) data of the SMOS mission (2012-2019). The Subtropical Front consists of two fronts -- North and South STF about 500 km apart -- that border the Subtropical Frontal Zone (STFZ) in-between. The STF is density-compensated, with spatially divergent manifestations in temperature and salinity. In the temperature field, the STF extends in the WNW to ESE direction in the Southeast Pacific. In the salinity field, the STFZ appears as a broad frontal zone, extending zonally between 30-35°S across the entire South Pacific. Three major types of satellite data – SST, SSH, and SSS – can be used to locate the STF. The SSH data is most advantageous with regard to the jack mackerel fisheries owing to the all-weather capability of satellite altimetry and the radical improvement of the spatial resolution of SSH data in the near future. Despite the dearth of dedicated in situ studies of the South Pacific STFZ, there is a broad consensus regarding the STFZ being the principal spawning and nursing ground of T. murphyi as well as a major migration corridor between Chile and New Zealand.

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for 15-5PH Stainless steel by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of machining variables such as concentration of cutting fluid , temperature of cutting fluid , feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error and material removal rate, the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is shown that the most significant factor is cutting speed, followed by feed rate, concentration of cutting fluid, radial depth of cut and temperature of cutting fluid. Finally, confirmation tests were carried out to make a comparison between the experimental results and developed model. Experimental results have shown that machining performance in the turn-boring process can be improved effectively through this approach.

Based on collected power generation data associated with solar irradiance, PV system conversion efficiency and cell temperature, an hourly solar PV power estimation model by a parallel artificial neural network (ANN) and particle swarm optimization (PSO) algorithm is proposed. Weight matrices related to different seasons and geographic areas for estimation power generations have been trained by real measured operation data. The parallel PSO algorithm with heuristic global optimization technique assists the ANN training process to get near optimal solutions precisely. The accuracy and reliability of estimation is audited by actual details of photovoltaic power stations in various regions and scales. The results of estimation model can not only assist the electricity dispatcher to explicitly monitor the trend of solar power generation in different areas, but also coordinate with traditional power plants to meet load demand more accurately. The presented model will bring benefits to power dispatching for larger scales of intermittent and unstable solar power generation.

Affective computing has emerged as a prominent technology in recent years, driven by the increasing demand for machines capable of understanding and interpreting emotions. The COVID-19 pandemic has intensified this need by reducing physical interactions and increasing reliance on digital communication, which often involves complex emotional exchanges. To enhance social interactions by identifying and addressing negative emotions, an interactive emotion-perception system based on multi-sensing interfaces and affective computing has been proposed. Integration of gesture, voice, and brainwave sensors is employed to provide users with a rich sensory experience and immersive environment. Design principles and system development processes are derived from the affinity diagram method and prototype development approach. The proposed system was constructed, and experiments were conducted with 60 participants. Interpersonal interaction scenarios were explored to understand emotional transmission mechanisms, aiming to enhance user satisfaction and positive interpersonal experiences. Data were collected through indirect observation and questionnaires, followed by evaluation and statistical analysis. Findings include: (1) The emotion-perception system enhances positive interpersonal interactions by identifying 36 distinct emotions, with overall user emotions being positive but exhibiting notable individual variations; (2) The system effectively stimulates positive emotions and strengthens interpersonal interactions, with affective computing technology fostering enjoyable emotional resonance and high-quality relationships; (3) A positive correlation was observed between semantic analysis and brainwave metrics of relaxation and concentration, showing increased concentration and enhanced positive emotional interactions during message transitions; and (4) The multi-sensing and affective computing technology provides a pleasant and relaxing emotional journey, with interactions shifting from enthusiasm to comfort, demonstrating the system’s capacity for a satisfying and enjoyable experience.

Shrews (Soricidae) are common small wild mammals. Some species of shrews, such as Asian house shrews (Suncus murinus), have a significant overlap in their habitats with humans and domestic animals. Currently, over 190 species of viruses in 32 families, including Adenoviridae, Arenaviridae, Arteriviridae, Astroviridae, Anelloviridae, Bornaviridae, Caliciviridae, Chuviridae, Coronaviridae, Filoviridae, Flaviviridae, Hantaviridae, Hepadnaviridae, Hepeviridae, Nairoviridae, Nodaviridae, Orthoherpesviridae, Orthomyxoviridae, Paramyxoviridae, Parvoviridae, Phenuiviridae, Picobirnaviridae, Picornaviridae, Polyomaviridae, Poxviridae, Rhabdoviridae, Sedoreoviridae, Spinareoviridae, and three unclassified families, have been identified in shrews. Diverse shrew viruses, such as Borna disease virus 1, Langya virus, and severe fever with thrombocytopenia syndrome virus, cause diseases in humans and/or domestic animals, posing significant threats to public health and animal health. This review compiled fundamental information about shrews and provided a comprehensive summary of the viruses that have been detected in shrews, with the aim of facilitating a deep understanding of shrews and the diversity, epidemiology, and risks of their viruses.

The United Nations' sustainable development goals have underscored the importance of enhancing supply chain sustainability while appropriately distributing orders. This study proposes a novel framework involving Z-number, game theory, indifference threshold-based attribute ratio analysis (ITARA), and combined compromise solution method (CoCoSo) to evaluate the sustainability of suppliers and order allocations. To better reflect the decision makers’ current choices for the sustainability of assessed suppliers and order allocations; enhance the comprehensiveness of decision-making, the importance parameter of the supplier is obtained through game theory objectively for transforming supplier performance into order allocation performance. The Z-numbers are involved in ITARA (so-called ZITARA) and CoCoSo (so-called ZCoCoSo) to overcome the issue of information uncertainty in the process of expert evaluation. ZITARA and ZCoCoSo are applied to assess the objective weight of criteria and the ranking of assessed order allocations, respectively. Afterwards, a case study of China’s company is illustrated the utility of the proposed framework and inform their decision-making process regarding the orders to be assigned to the assessed suppliers.

In order to maintain the best conditions of the building from the first day of opening, explorations of office buildings in the world investigated the approaches of optimizing the building operation and property facilities, whereas building managers often have trouble prioritizing improvements toward their sustainable objectives. The challenge is due to numerous equipment types in the building, which has various durability in years and represents users’ different feelings of importance and satisfaction. When faced with multiple improvement projects, building managers are often unable to determine the order of implementation.Hence, this research applies the Analytic Hierarchy Process (AHP) using TAIPEI 101 Tower as a case study to explore the key factors affecting tenants’ willingness to lease office buildings by distributing questionnaires to real estate experts. By filtering out key indicators related to property facilities that users care about, this study used Importance and Satisfaction Analysis (IS Analysis) to identify items that need urgent improvement. The research revealed that air conditioning is the top priority for improvement through empirical evaluation and weight ranking. This study hopes to establish an evaluation model for facility improvements to help clarify the prioritization and defeat limited resources to projects effectively, which is helpful for sustainable property management.

Objective: This study investigated the effect of the hierarchical medical system under the national health insurance program on resident’s healthcare-seeking behavior in Taiwan. Background: Healthcare authorities in Taiwan initiated the allowance reduction of outpatient visits at regional hospitals and higher hierarchical hospitals from 2018. The ultimate goal is to implement a hierarchical medical system and provide the residents accessible as well as consistent medical services. Methods: This research was conducted through the questionnaire survey method and data were collected between August and December 2018 from the records of subjects who had recently sought medical attention. A total of 1,340 valid questionnaires were returned. Results: Regarding the effect on healthcare-seeking behavior, the following factors were significant: being aged between 40 to 49 (p＜.1), subjects with an educational background of junior high school (p＜.05), those who were not aware of the policy (p＜.001), and an awareness about both the hierarchical medical system and the policy to reduce outpatient visits to large hospitals (p＜.001). Conclusion: The public should be made aware about the hierarchical medical system to improve healthcare.

Gastric inflammation-related disorders are commonly observed digestive system illnesses char-acterized by the activation of proinflammatory cytokines, particularly tumor necrosis factor-α (TNF-α). This results in the induction of cyclooxygenase-2 (COX-2)/prostaglandin E2 (PEG2) and matrix metallopeptidase-9 (MMP-9). These factors contribute to the pathogenesis of gastric in-flammation disorders. We examined the preventive effects of Lonicera japonica Thunb. ethanol ex-tract (Lj-EtOH) on gastric inflammation induced by TNF-α in normal GES-1 cells. The GES-1 cell line was used to establish a model that simulated the overexpression of COX-2/PGE2 and MMP-9 proteins induced by TNF-α, to examine the anti-inflammatory properties of Lj extracts. The re-sults indicated that Lj-EtOH exhibits significant inhibitory effects on COX-2/PEG2 and MMP-9 ac-tivity, attenuates cell migration, and provides protection against TNF-α-induced gastric inflam-mation. The protective effects of Lj-EtOH are associated with the modulation of COX-2/PEG2 and MMP-9 through activation of TNFR–ERK 1/2 signaling pathways as well as the involvement of c-Fos and nuclear factor kappa B (NF-κB) signaling pathways. Based on our findings, Lj-EtOH ex-hibits a preventive effect on human gastric epithelial cells. Consequently, it may represent a novel treatment for the management of gastric inflammation.

Ensuring optimal performance and reliability in rotor-bearing systems is crucial for industrial applications. Imbalance and shaft bow in these systems can lead to decreased efficiency and increased vibrations. Early detection and mitigation of a rotor’s faults are essential, and model-based fault identification has gained much attention in the manufacturing industry for years. Over the past two decades, however, the development of fault diagnosis rules with data-driven and artificial intelligence (AI) has become a trend, and in the foreseeable future, AI combined with big data will become mainstream. Nevertheless, the critical role of rotating machinery in manufacturing introduces a challenge, as the availability of fault data is often insufficient. This limitation renders the establishment of diagnostic rules using data-driven methods and AI technologies impractical. In light of these challenges, this study proposes a novel hybrid approach, that combines a physical model with machine learning (ML) techniques for the diagnosis of multi-faults (imbalance and shaft-bow demonstrated) in a Jeffcott rotor. To overcome the lack of real-world faulted, labeled datasets, a physics-based Jeffcott rotor model is first derived and then used to generate abundant fault datasets for ML. Subsequently, simulated data are employed for the training of an artificial neural network (ANN), enabling the network to learn from and analyze the vast array of generated data. The results prove that a well-trained feed-forward neural network (FNN) can accurately isolate and diagnose the imbalance and shaft-bow faults using the simulated data and the real data from the Jeffcott rotor experiment. These physics-based and ML approaches prove effective particularly for multi-fault, offering new possibilities for advanced rotor system monitoring and maintenance strategies in industrial applications.

P-band radar remote sensing applied during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission has shown great potential for estimation of root zone soil moisture. When retrieving the soil moisture profile (SMP) from P-band radar, a mathematical function describing the vertical moisture distribution is required. Because only a limited number of observations are available, the number of free parameters of the mathematical model must not exceed the number of observed data. For example, a second order polynomial that contains 3 free parameters was presumed based on in-situ SMP data. The polynomial is currently parameterized based on 3 backscatter observations provided by AirMOSS (i.e. one frequency at three polarizations of HH, VV and HV). In this paper, a more realistic, physically-based SMP model containing 3 free parameters is derived based on a solution to Richards’ equation for unsaturated flow in soils. Evaluation of the new SMP model based on both numerical simulations and measured data revealed that it exhibits greater flexibility for fitting measured and simulated SMPs than the currently applied polynomial. It is also demonstrated that the new SMP model can be reduced to a second order polynomial at the expense of fitting accuracy.

In Taiwan, remote healthcare was initially limited to telemedicine services, and the systematic development of remote care was relatively delayed. It was not until 2007 that the Department of Health of the Executive Yuan first initiated the 'Remote Care Pilot Program,' followed by the 'Remote Care Service Improvement and Quality Enhancement Plan' in the subsequent year. In 2010, Taiwan officially launched the 'Remote Health Care Services Development Plan' and established a dedicated project office, marking the comprehensive start-up of remote care services. This stage saw significant contributions from artificial intelligence aids and ICT remote transmission technologies, greatly promoting the application of smart healthcare in home care. This study aims to explore the strategic gaps in the application of smart healthcare in home remote care. By analyzing gaps in 'legal regulations,' 'economic factors,' 'user behavior habits,' 'policy and culture,' and 'environment and technology,' this study employs a mixed-methods approach. Particularly, it uses the Analytic Hierarchy Process (AHP) to construct a weighted ranking of these strategic gaps. Through in-depth interviews with doctors and smart healthcare experts and the collection of 16 valid AHP questionnaire samples, which cover both industry and academia with a balanced distribution, the survey results are ensured to be representative and reliable. The findings indicate that 'legal regulations' are considered the most critical strategic gap that needs to be addressed first, followed by 'user behavior habits.' This suggests that when designing smart healthcare applications, greater consideration needs to be given to user acceptance and habits. By systematically analyzing and addressing these strategic gaps, this study not only provides solutions to issues in the application of smart healthcare in home remote care but also offers valuable references for future research and practice, aiming to make home remote care services more comprehensive and efficient.

Based on the perspective of complex directed weighted network analysis, this paper constructs a static resilience evaluation framework for trade networks from two dimensions: structural resilience and node resilience. It studies the evolution of static resilience in the upstream, midstream, downstream, and recycling trade networks of global wood forest products from 2002 to 2021. The study finds that the total trade volume of global wood forest products has increased by 58.0%, 77.3%, 71.2%, and 77.2% in the upstream, midstream, downstream, and recycling sectors, respectively. The downstream trade network exhibits efficient information transmission and resource mobility capabilities. All four types of trade networks exhibit scale-free characteristics, with core countries such as China, the United States, and Germany playing a dominant role in the network and playing a crucial role in network robustness, but also increasing network vulnerability. In terms of unweighted assortativity, all four networks exhibit the characteristic of "small countries relying on hubs," while the weighted assortativity of the downstream network is positive, indicating enhanced network resilience. In terms of node resilience, countries exhibit significant differences and dynamic changes. China demonstrates strong resilience and adaptability, while the United States maintains its core position. China's influence in the downstream network has significantly increased, and India has rapidly emerged in the recycling network. To enhance network resilience, it is necessary to increase diversity and redundancy, establish effective emergency response mechanisms, and promote the diversification and green transformation of the supply chain.

We estimated the daily intakes of chlorpyrifos and cypermethrin via ingestion of indoor dust and outdoor soils using the Stochastic Human Exposure and Dose Simulation Model on a probabilistic approach for Taiwan’s homes. Variable information for the daily intake estimation, such as concentration, ingestion rate, body weight, was adopted from previous studies. Monte Carlo simulation was performed with 1,000,000 iterations to simulate a single daily intake, which was shown in terms of percentage of the Acceptable Daily Intake (ADI) of either insecticide. The daily intakes were minimal with a 99% probability; at 99.9th percentile, however, the total intakes leaped to 13.1% and 20.0% of the respective ADIs of chlorpyrifos and cypermethrin. The sensitivity analysis indicated that concentration was the most determinant variable. Compared to the data of daily intakes via dietary ingestion of vegetables derived from a previous study, the estimated intakes by this study were considerable at the highest percentile, which referred to insecticide residues few days after insecticide application. Consequently, the non-dietary ingestion exposure to either insecticide was negligible in most cases; nevertheless, for those with indoor insecticide applications, the daily intakes for young children could be of concern. Frequently home cleaning is recommended to reduce the exposure.

Background: Lung cancer is one of the leading causes of morbidity and mortality worldwide with 25% of deaths due to lung cancer occurring in Europe. This study therefore sought to assess the burden of lung cancer by country and to evaluate the magnitude of fine Particulate Matter (PM2.5) and cigarette smoking by country in Europe. Methods: An ecological study nested on the World Health Organization air pollution database 2016 was conducted. We sampled 30 European Countries, with a total of 1625 mean annual samples of Particulate Matter (PM2.5) collected from 1625 designated sites (n = 1625). We further used the ‘World Health Disease Rankings’ database to extract Lung Cancer Morbidity and Mortality Rate by country. We used SAS version 9.4 to indicate the distribution of PM2.5 and Lung Cancer Mortality Rate. Results: Lung cancer Relative Risk (RR) was 1.0 in all never- smokers. RR for Ex-smokers for Adeno carcinoma was 3.5 in males and 1.1 in females, small cell carcinoma was 16.2 in males and 3.8 in females. RR for current smokers for Adeno carcinoma was 8.0 in males and 4.1 in females, small cell carcinoma was 57.9 in males and 18.2 in females. Mean annual PM2.5 by country ranged from 6.01 to 37.28µg/m3 whereas lung cancer mortality rate by country ranged from 19.67 to 54.26 deaths per 100,000 population. Conclusion: Cigarette smoking and exposure to both second hand smoke and high concentration of PM2.5 resulted into increased burden of lung cancer in Europe. Countries should re-strategize to reduce the burden of lung cancer in Europe.

This paper uses the complex regression analysis method to establish the customer’s load regression models, which consider economic indicators, temperature and rainfall. Furthermore, the proposed models are used to study the forecasting feasibility of the future energy sales and summer peak load demand. At first, this paper used least-squares techniques to derive regression models for considering economic indicators and temperature of 34 customer energy sales and total energy sales. Besides, the AMI high voltage customer demand data and system generating capacity for 24 hours were adopted to forecast summer peak load. The above-mentioned data analysis tool is used by EViews software to achieve, in order to verify the feasibility of the research framework. The study found that although its forecasting model accuracy is low only when mixed with temperature and high voltage demands. So, when mixed with high voltage demand data and system generating capacity for 24 hours to forecast peak load, the average error is ± 0.87% and in the majority of its energy sales forecasting model of average error is ±3%. This result can provide power company as future reference.

Wind energy is a kind of renewable energy with great potential for development. This study mainly investigated the application of shock waves generated by high-pressure gases (wind energy) for generating energy. In this study, we designed a new supersonic shock wave generator that can be reused without disassembling and assembling bolts and developed a supersonic shock wave monitoring system. This system monitored the velocity of the generated shock waves, which was Mach 3-5, and the output pressure was more than 100 times higher than the input pressure of the shock wave generator tank.Then, we developed a power generation system driven by supersonic shock waves based on the characteristics of the new shock wave generator, which can generate high-pressure and high-speed blast waves and can be reused. The shock wave generator can repeatedly generate high-pressure waves to drive the Tesla turbine and then the magnetic energy generator for power generation. We established a complete control process for power generation driven by shock waves by controlling the valve stem. The system can detect the tank pressure, output pressure, gas flow, rotation speed, voltage, and current during the control process for the performance analysis of power generation.

Teachability has been extensively studied under the context of making industrial robots to be programmable and reprogrammable. However, it is only recently that the artificial intelligence (AI) research community is accelerating the research works with the objective of making humanoid robots and many other robots to be teachable under the context of using natural languages. We human beings spend many years to learn knowledge and skills despite our extraordinary mental capabilities of being teachable with the use of natural languages. Therefore, if we would like to develop human-like robots such as humanoid robots, it is inevitable for us to face the issue of making future humanoid robots to be teachable with the use of natural languages as well. In this paper, we present the key details of a top-down design for achieving a teachable mind which consists of two major processes: the first one is the process which enables humanoid robots to gain innate mental capabilities of transforming incoming signals into meaningful crisp data, and the second one is the process which enables humanoid robots to gain innate mental capabilities of undertaking incremental and deep learning with the main focus of associating conceptual labels in a natural language to meaningful crisp data. These two processes consist of the two necessary and sufficient conditions for future humanoid robots to be teachable with the use of natural languages. In addition, this paper outlines a very likely new finding underlying human brain’s neural systems as well as the obvious mathematics underlying artificial deep neural networks. These outlines provide us the strong reason to separate the study of mind from the study of brain. Hopefully, the content discussed in this paper will help the AI research community to venture into the right direction which is to make future humanoid robots, non-humanoid robots, and many other systems to achieve human-like self-intelligence at cognitive level with the use of natural languages.

The heavy metal lead (Pb) can irreversibly damage the human nervous system. To help understand Pb-induced damage, we applied a genetically encoded Förster resonance energy transfer (FRET)-based Pb biosensor Met-lead 1.44 M1 to two living systems to monitor the concentration of Pb: induced pluripotent stem cell (iPSC)-derived cardiomyocytes as a semi-tissue platform, and Drosophila melanogaster fruit flies as an in vivo animal model. Different FRET imaging modalities were used to obtain FRET signals, which represented the presence of Pb in the tested samples in different spatial dimensions. Using iPSC-derived cardiomyocytes, the relationship between beating activity (20–24 beats per minute, bpm) determined from the fluctuation of fluorescent signals and the concentrations of Pb represented by the FRET emission ratio values of Met-lead 1.44 M1 was revealed from simultaneous measurements. Pb (50 μM) affected the beating activity of cardiomyocytes, whereas two drugs that stop the entry of Pb differentially affected this beating activity: verapamil (2 μM) did not reverse the cessation of beating, whereas 2-APB (50 μM) partially restored this activity (16 bpm). The results clearly demonstrate a potential of this biosensor system as an anti-Pb drug screening application. In the Drosophila model, Pb was detected within the adult brain or larval central nervous system (Cha-gal4>UAS-Met-lead 1.44 M1) using fast epifluorescence and high-resolution two-photon 3D FRET ratio image systems. The tissue-specific expression of Pb biosensors provides an excellent opportunity to explore the possible Pb-specific populations within living organisms. We believe that this integrated Pb biosensor system can be applied to the prevention of Pb poisoning and advanced research on Pb neurotoxicology.

Land engineering is a specific new academic discipline in China. Although the undergraduate major of land engineering was officially approved and established lately since 2017, the birth of land engineering as an academic discipline dates back 40 years ago. It has passed through four development stages: the incubation stage in 1978-1985, the initial stage in 1986-1997, the growth stage in 1998-2011, and the expanding stage from 2012 to present. However, land engineering as an academic discipline remains immature and seriously lags behind practice. There are still no unified academic community and broad academic consensus. After a historical overview of the four development stages, this study gave a strategic consideration to five key questions. We argue that the study object of the discipline is land engineering activity, which is defined as the artificial transformation of a land complex combined by various natural and human elements. The uniqueness of the discipline is rooted in its ability to study the comprehensive and integrated reorganization or rebuilding of various elements of land as a complex, with the theory of land complex reconstruction being the core theory. The discipline of land engineering is based on land pure science and land technology, and is one basis of land management. It consists of two modules (rural land engineering and urban land engineering), five secondary disciplines of each module (land development, land rearrangement, land improvement, land protection, and land remediation), and more than 30 research directions. Various technologies are only instrumental but not essential components of land engineering as an academic discipline.

The chitin synthase B gene is a key enzyme in the chitin synthesis of insect peritrophic matrix (PM), affecting insects' feeding behavior. The chitin synthase B gene has been cloned from the transcription library of Heortia vitessoides Moore. RT-qPCR showed that HvChsb was highly expressed in the larval stage of H. vitessoides, especially on the first day of the prepupal stage, and in the midgut of larvae and the abdomen of adults. After starvation treatment, HvChsb was found to be significantly inhibited with time. After 48 h of starvation, the feeding experiment showed that HvChsb increased with the prolongation of the refeeding time. The experimental data showed that feeding affected the expression of HvChsb. HvChsb was effectively silenced by RNA interference, so its function was lost, significantly decreasing the survival rate of H. vitessoides. The survival rate from larval-to-pupal stages was only 43.33%, accompanied by abnormal phenotypes. It can be seen that HvChsb plays a key role in the average growth and development of H. vitessoides.

A Chinese superalloy GH4099 (~20 vol.% γ' phase), which can operate for long periods of time at temperatures of 1173-1273 K, was fabricated by electron beam melting (EBM). Argon gas atomized (AA) and plasma rotation electrode process (PREP) powders with the similar composition and size distribution were used as raw materials for comparison. Microstructure and mechanical properties of both the as-EBMed and post-treated alloy samples were investigated. The results show that the different powder characteristics resulted in the different build temperatures for AA and PREP samples, which were 1253 K and 1373 K, respectively. With increasing the building temperature, the EBM processing window shifted towards the higher scanning speed direction. Furthermore, intergranular cracking was observed for the as-fabricated PREP sample as a result of local enrichment of Si at grain boundaries. The cracks were completely eliminated by hot isostatic pressing (HIPing) and did not re-open during subsequent solution treatment and aging (STA). Fine spherical γ' phase precipitated uniformly after STA. The tensile strength of the HIP+STA samples was ~920 MPa in the building direction and ~850 MPa in the horizontal direction, comparable with that of the wrought alloy.

In recent years, many molecular and environmental factors have been studied to understand how synaptic plasticity is modulated. Sleep, as an evolutionary conserved biological function, has shown to be a critical player for the consolidation and filtering of synaptic circuitry underlying memory traces. Although sleep disturbances do not alter normal memory consolidation, they may reflect fundamental circuit malfunctions that can play a significant role in exacerbating diseases, such as autism and Alzheimer’s disease. Very recently, scientists sought to answer part of this enigma and they identified p75 neurotrophic receptor (p75NTR) as a critical player in mediating impairments in hippocampal-dependent associative plasticity upon sleep deprivation. This paper will review the role of the p75NTR, critically discuss the impact and implications of this research as the bridge for sleep research and neurological diseases.

Based on stochastic frontier analysis and translog input distance function, this paper examines the total factor energy efficiency of China’s industry using input-output data of 30 sub-industries from 2002 to 2014, and decomposes the changes in estimated total factor energy efficiency into the effects of technical change, technical efficiency change, scale efficiency change and input-mix effect. The results show that during this period the total factor energy efficiency in China’s industry grows annually at a rate of 3.63%, technical change, technical efficiency change and input-mix effect contribute positively to the change in total factor energy efficiency, while scale efficiency change contributes negatively to it.

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

Interferon regulatory factor 5 (IRF5) is known to be involved in the innate immune response and pro-inflammatory cytokines. However, the roles of IRF5 in immune responses in Malabar grouper (Epinephelus malabaricus) have not been extensively explored. In this study, IRF5 gene was identified and characterized from M. grouper. The full-length IRF5 cDNA consisted of a 5’ terminal untranslated region (5’-UTR) of 289 bp and a 3’-UTR of 542 bp, an open reading frame (ORF) of 1500 bp encoding a polypeptide of 499 amino acids with a predicted molecular mass of 56.28 kDa and isoelectric point (pI) of 5.2. The putative MgIRF5 protein consists of four important conserved domains: a helix DNA-binding domain (DBD) at the N-terminus, a middle region, an IRF association domain (IAD) and a virus activated domain (VAD) at the C-terminus. Sequence alignment and phylogenetic analysis showed that highest sequence similarity of IRF5 was observed between the IRF5 genes from Oplegnathus fasciatus and Miichthys miiuy. The mRNA transcripts of IRF5 were detected in a wide range of tissues types from healthy M. grouper with highest expression in muscle, liver and skin. After treatment with poly (I: C), it was significantly up-regulated in spleen and liver tissues. When infected with NNV, the expression level of MgIRF5 was up-regulated in spleen and head kidney and their transcriptional responses to IRF5 increased in the grouper kidney cells. This approach suggests that MgIRF5 is important in the underlying mechanism of the innate immune responses against antiviral response.

Gastric cancer has become one of the most common cancers in the world.Immunotherapy, especially immune point inhibitors targeting programmed cell death 1 or its ligand PD-L1, has been successfully applied in the clinical treatment of GC. However, only a small number of cancer patients experience persistent clinical responses during immunotherapy. In this review, we discussed the current status of immunotherapy for colorectal cancer, elucidated the mechanisms mediating immunotherapy resistance, predicted biomarkers for immunotherapy resistance, and strategies for improving immunotherapy efficacy.

Estimates of extreme water level return periods in river systems are crucial for hydraulic engineering design and planning. Recorded historical water level data of Taiwan’s rivers are not long enough for traditional frequency analyses when predicting extreme water levels for different return periods. In this study, the integration of a one-dimensional flash flood routing hydrodynamic model with the Monte Carlo simulation was developed to predict extreme water levels in the Danshuei River system of northern Taiwan. The numerical model was calibrated and verified with observed water levels using four typhoon events. The results indicated a reasonable agreement between the model simulation and observation data. Seven parameters, including the astronomical tide and surge height at the mouth of the Danshuei River and the river discharge at five gauge stations, were adopted to calculate the joint probability and generate stochastic scenarios via the Monte Carlo simulation. The validated hydrodynamic model driven by the stochastic scenarios was then used to simulate extreme water levels for further frequency analysis. The design water level was estimated using different probability distributions in the frequency analysis at five stations. The design high-water levels for a 200-year return period at Guandu Bridge, Taipei Bridge, Hsin-Hai Bridge, Da-Zhi Bridge, and Chung-Cheng Bridge were 2.90 m, 5.13 m, 6.38 m, 6.05 m, and 9.94 m, respectively. The estimated design water levels plus the freeboard are proposed and recommended for further engineering design and planning.

In the recent past, China has experienced rapid urbanization as a result of diverse growth factors. In such a context, it is crucial to evaluate the expansion of urban entities in order to implement sustainable urban planning strategies in China. Since, urban entities are the spatial reflection of the concentration of human activities, the delineation of urban areas upon the boundaries of built-up surfaces has resulted from inconsistent understanding and identification of urban areas. The study has attempted to extract and evaluate the growth of urban entities in 336 prefecture cities in China mainland (2000-2020) upon a novel approach using consistent night light images. The urban entities were extracted using the light intensities of the SNPP-VIIRS-like data. After extracting urban entities, a rationality assessment was carried out comparing derived urban entities with the LandScan population product, Landsat, and road networks. Also, the results were compared with other physical extents products such as MODIS and the HE. According to the findings, urban entities are basically consistent with the LandScan, road networks, and those with the HE and MODIS. But, urban entities accurately reflect the concentration of human activities than impervious extents of MODIS and the HE. At the prefecture levels, urban entities elevated from 8082 km2 to 74,417 km2 between 2000 and 2020 showing a 10.8% growth rate. By providing a supplementary resource and guide for trustworthy urban mapping, the research will expand new research directions that address the issues of variations of NTL data brightness thresholds dynamics on regional, and global scales.

The rapid development of China's economy has led to a rapid increase in energy production and use. Among them, the excessive consumption of coal in fossil energy consumption is the leading cause of air pollution in China. This paper incorporates renewable energy innovation, fossil energy consumption and air pollution into a unified analysis framework, and uses spatial measurement models to investigate the spatial effects of renewable energy green innovation and fossil energy consumption on air pollution in China, and decomposes the total impact into direct and indirect effects. influences. The empirical results show that China's air pollution, renewable energy green innovation and fossil energy consumption are extremely uneven in geographical space, generally showing the characteristics of high in the east and low in the west, and showing a strong spatial aggregation phenomenon. Fossil energy consumption will lead to increased air pollution, and the replacement of fossil fuels with clean and renewable energy is an important means of controlling pollution emissions. The direct and indirect effects of renewable energy green innovation on air pollution are significantly negative, indicating that renewable energy green innovation not only suppresses local air pollution, but also suppresses air pollution in neighboring areas. The consumption of fossil energy will significantly increase the local air pollution, and the impact on the SO2 and Dust&Smoke pollution in the adjacent area is not very obvious. It is recommended to strengthen investment in renewable energy green innovation, reduce the proportion of traditional fossil energy consumption, and pay attention to the spatial connection and spillover of renewable energy green innovation.

A practical method is presented to estimate rare earth elements (REE) concentrations in magmatic vapour phase (MVP) in equilibrium with water-saturated granitic melts based on empirical fluid-melt partition coefficients of REE (k_P^REE). The values of k_P^REEcan be calculated from a set of new polynomial equations linking to the chlorine molality (m_Cl^v) of the MVP associated with granitic melts, which are established via a statistical analysis on the existing experimental dataset. These equations may be applied to the entire pressure range (0.1 to 10.0 kb) within the continental crust, suggesting that light REEs behave differently in magmatic fluids, i.e. either being fluid compatible with higher m_Cl^v or fluid incompatible with lower m_Cl^v values. In contrast, heavy REEs are exclusively fluid incompatible and partition favourably into granitic melts. Consequently, magmatic fluids tend to be rich in LREE relative to HREE, leading to REE fractionation during the evolution of magmatic hydrothermal systems. Maximum k_P^REEvalue for each element is predicted and presented in a REE distribution diagram constrained by the threshold of m_Cl^v. REE contents of the granitic melt is approximated by whole-rock analysis, so that REE concentrations in the associated MVP would be estimated from the value of k_P^REE given chemical equilibrium retains. Two examples are provided respectively, to show the use of this method as a REE tracer to fingerprint the source of ore-fluids responsible for the Lake George intrusion-related Au-Sb deposit in New Brunswick (Canada), and for the Bakircay Cu-Au (-Mo) porphyry systems in northern Turkey.

Unmanned aerial vehicles (UAVs) have increasingly become integral to multi-access edge computing (MEC) due to their flexibility and cost-effectiveness, especially in the B5G and 6G eras. This paper aims to enhance the Quality of Experience (QoE) in large-scale UAV-MEC networks by minimizing the shrinkage ratio through optimal decision-making in computation mode selection for each user device (UD), UAV flight trajectory, bandwidth allocation, and computing resource allocation at edge servers. However, the interdependencies among UAV trajectory, binary task offloading mode, and computing/network resource allocation across numerous IoT nodes pose significant challenges. To address these challenges, we formulate the shrinkage ratio minimization problem as a mixed-integer nonlinear programming (MINLP) problem and propose a two-tier optimization strategy. To reduce the scale of the optimization problem, we first design a low-complexity UAV partition coverage algorithm based on the Welzl method and determine the UAV flight trajectory by solving a Traveling Salesman Problem (TSP). Subsequently, we develop a coordinate descent (CD) based method and an alternating direction method of multipliers (ADMM) based method for network bandwidth and computing resource allocation in the MEC system. The CD-based method is simple to implement and has a low computational complexity, while the ADMM-based method can further enhance the optimization result through joint optimization. Extensive simulations demonstrate that our proposed algorithms perform well in large-scale edge networks and outperform other representative benchmark methods.

Buckypaper (BP), a flexible and porous material, exhibits photovoltaic properties when exposed to light. In this study, we have employed Radio Frequency (RF) Sputtering of Zinc Oxide (ZnO) followed by rapid thermal annealing to enhance the photovoltaic response of BP. We investigated the impact of various sputtering parameters, such as the gas flow ratio of argon to oxygen and deposition time, on the morphology, composition, resistivity, and photovoltaic characteristics of ZnO-modified BP. Additionally, the photovoltaic performance of the samples under different illumination modes and wavelengths was compared. It was found that optimal sputtering conditions—argon to oxygen flow ratio of 1:2, deposition time of 20 minutes, and power of 100 watts—resulted in a ZnO film thickness of approximately 45 nanometers. After annealing at 400°C for 10 minutes, the ZnO-modified BP demonstrated a significant increase in photocurrent and photovoltage, along with a reduction in resistivity, compared to unmodified BP. Moreover, under gradient illumination, the ZnO-modified BP exhibited a photovoltage enhancement of 14.70 times and a photocurrent increase of 13.86 times, compared to uniform illumination. Under blue light, it showed a higher photovoltaic response than under other colors. The enhancement in photovoltaic response is attributed to the formation of a Schottky junction between ZnO and BP, an increased carrier concentration gradient, and an expanded light absorption spectrum. Our results validate that ZnO sputtering followed by annealing is an effective method for modifying BP for photovoltaic applications such as solar cells and photodetectors.

Pure titanium is limited to be used in biomedical applications due to its lower mechanical strength compared to its alloy counterpart. To enhance its properties and improve medical implants feasibility, advancements in titanium processing technologies are necessary. One such technique is equal channel angular pressing (ECAP) for its severe plastic deformation (SPD). This study aimed to surface modify commercially pure titanium using micro arc oxidation (MAO) technology and mineral solutions containing Ca and P. The composition and shape of the changed surface were characterized using X-ray diffraction (XRD) and scanning electron microscope (SEM), respectively. The weight % of Ca and P in the coating was determined using Energy Dispersive Spectroscopy (EDS), and the corrosion resistance was evaluated through potentiodynamic measurement. The behavior of human dental pulp cell and periodontal cell behavior was also studied through a biomedical experiment over a period of 1-, 3-, and 7-days using trypsin as the culture medium and ELISA as the observation method. This study showed that the mechanical grain refinement method and surface modification significantly improved the biomechanical properties of commercially pure (CP) Titanium. Although the results showed variations in the absorbance values of cells cultured on different surfaces, this study provides valuable insights into pulp cell behavior and advances the field of biomedical research.

Shrews (Soricidae) are common small wild mammals with a significant overlap in their habitats with humans and domestic animals. Currently, viruses from 24 families have been identified in shrews, including Adenoviridae, Arenaviridae, Arteriviridae, Astroviridae, Bornaviridae, Caliciviridae, Circoviridae, Coronaviridae, Filoviridae, Flaviviridae, Hantaviridae, Hepadnaviridae, Hepeviridae, Nairoviridae, Orthoherpesviridae, Paramyxoviridae, Parvoviridae, Phenuiviridae, Picornaviridae, Polyomaviridae, Poxviridae, Rhabdoviridae, Sedoreoviridae, and Spinareoviridae, which pose potential threats to humans and domestic animals. This review compiled fundamental information about shrews and provided a comprehensive summary of the viruses that have been detected in shrews, with the aim to facilitating a deeper understanding of shrews and the diversity and risks of their viruses for researchers and the general public.

The spin-torsion theory is a gauge theory approach to gravity that expands upon Einstein's general relativity (GR) by incorporating the spin of microparticles. In this study, we further develop the spin-torsion theory to examine spherically symmetric and static gravitational systems that involve free-falling macroscopic particles. We posit that the quantum spin of macroscopic matter becomes noteworthy on cosmic scales. We further assume that the Dirac spinor and Dirac equation adequately capture all essential physical characteristics of the particles and their associated processes. A crucial aspect of our approach involves substituting the constant mass in the Dirac equation with a scale function, allowing us to establish a connection between quantum effects and the scale of gravitational systems. This mechanism ensures that the quantum effect of macroscopic matter is scale-dependent and diminishes locally, a phenomenon not observed in microparticles. For any given matter density distribution, our theory predicts an additional quantum term, the quantum potential energy (QPE), within the mass expression. QPE induces time dilation, distance contraction, and thus mimics a gravitational well. When applied to cosmology, our theory yields a static cosmological model. The QPE serves as a counterpart to the cosmological constant introduced by Einstein to balance gravity in his static cosmological model. The QPE also offers a plausible explanation for the origin of the Hubble redshift (traditionally attributed to the universe's expansion). The predicted luminosity distance-redshift relation aligns remarkably well with SNe Ia data from the cosmological sample of SNe Ia. In the context of galaxies, QPE functions as the equivalent of dark matter. The predicted circular velocities align well with the rotation curve data from the SPARC (Spitzer Photometry and Accurate Rotation Curves database) sample. Importantly, our conclusions in this paper are reached through a conventional approach, with the sole assumption of the quantum effects of macroscopic matter on large scales, without the need for additional modifications or assumptions.

In view of the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm all nodes participate in the consensus, the three-stage process has problems such as large communication overhead, random selection of master nodes and lack of reward and punishment mechanism. A Speculative Practical Byzantine Fault Tolerance (SP-PBFT) is proposed. Firstly, the consensus protocol was optimized, and a timeout mechanism was proposed to divide the consensus process into optimistic mode and pessimistic mode, which reduced the communication overhead under the premise of resisting Byzantine node attacks .Secondly, a node evaluation mechanism was proposed to calculate the node reputation value according to the node's historical behavior and give the corresponding reward or punishment, which reduced the possibility of malicious nodes participating in the consensus process. Finally, the Fibonacci grouping mechanism was used to reduce the number of nodes participating in the consensus process, fundamentally improving the consensus efficiency, avoiding the problem of centralization of the consensus process caused by the cumulative reputation value of nodes, and improving the enthusiasm of consensus nodes. Simulation experiments using Docker containers to simulate multiple nodes show that the SP-PBFT consensus algorithm proposed in this paper has better performance than PBFT consensus algorithm and other improved algorithms in terms of consensus delay, throughput, fault tolerance and communication complexity.

In this paper, we extend the KdVSKR equations in (1+1)-dimension and (2+1)-dimension to fractional KdVSKR equations with modified Riemann-Liouville derivative. The (2+1)-dimensional KdVSKR equation, which is a recent extension of (1+1)-dimensional KdVSKR equation, can model the resonances of solitons in shallow water. By means of the Hirota bilinear method, finite symmetry group method and consistent Riccati expansion method, many new interaction solutions have been derived. Soliton-cnoidal interaction solution of the (1+1)-dimensional fractional KdVSKR equation has been derived for the first time. For the (2+1)-dimensional frac-tional KdVSKR equation, two-wave interaction solutions and three-wave interaction solutions, including dark-soliton-sine interaction solution, bright-soliton-elliptic interaction solution, and lump-hyperbolic-sine interaction solution, have been derived. Impact of the fractional order on the shapes of these solutions has been illustrated by figures. Three-wave interaction solutions of fractional systems have not been reported in the existing references. The research idea in this paper can be applied to other fractional differential equations.

This paper aims the automatic ball balancers (ABBs) used in passive balancing devices for suppressing vibration of the eccentric rotor. The system model describes which equipped with a skew-mounted ABB with angular deviation. The dynamic equilibrium equations of the system are deduced from the perspective of three-dimensional (3D) dynamics. The results obtained are consistent with those derived from the Euler-Lagrange equations. It is exciting that the spatial dynamics method reveals the spatial geometric characteristic of dynamic balance positioning of the balls when the system is balanced with vibration suppression. The spatial property emerges the perpendicular line from each ball to the rotating spindle of the system must pass through the central axis of the orbit perpendicular to the ABB plane. This characteristic is a general rule that can be used to explain the phenomenon of the stable equilibrium positions of the balls in all previously studied cases.

In recent years, the taxonomy of the families of Phenuiviridae, Nairoviridae, and Peribunyavidae in Bunyavirales was updated frequently, because many novel viruses in these families have been identified and the species demarcation criteria of these families have been changed. As per these criteria and sequence analysis, we found that the taxonomy of 19 species in these families should be revised. We presented six proposals for optimizing virus species taxonomy using the examples from these families. First, the species demarcation criteria for the same family (e.g., Peribunyavidae) should be unified. Second, the methods and parameters for the taxonomic calculation in the same order (e.g., Bunyavirales) should be unified. Third, virus species taxonomy should be based on phylogenetic relationships, rather than a cutoff value of sequence identities that is a self-contradictory demarcation criterion, although sequence identities aid virus taxonomy greatly. Fourth, virus species taxonomy should be based on the phylogenetic relationship of a key viral gene (e.g., the RdRp gene of Bunyavirales), which is important for the taxonomy of virus recombinants or reassortants. Fifth, a virus can be demarcated without a species before its biomedical significance has been revealed. Sixth, names of all viruses and virus species should be constituted exclusively with common characters (English letters and Arab numbers), to minimize difficulty in spelling and communication. These proposals are rational, flexible, and can accommodate all known viruses. They can also bridge the taxonomy history and the future demands due to their flexibility.

Revealing the spatial distribution mechanism of the coupling effect between soil water and salt is essential for managing saline-alkali farmland. This study utilized the multifractal method to analyze soil water and salt under varying water content levels in arid saline-alkali farmland. Soil samples were collected on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after a rainfall event. The findings showed that a significant decrease in soil water content, contrasting with an increase in soil salt content throughout the soil layers post-rainfall. As water content decreased, the spatial variability of soil water initially increased from S1-3 and then decreased, while the spatial variability of soil salt decreased. The spatial distribution between soil water and salt exhibited a high correlation at S3-4 (with relative water content of soil ranging from 0.52 to 0.75) due to their coupling effect. However, soil salt was unevenly leached by rainfall at high water content levels (S1-2) and precipitated at low water content levels (S5), resulting in low spatial variability correlations between soil water and salt. This study elucidated the coupling process of soil water and salt, identifying their spatiotemporal distribution mechanism in dryland agricultural areas.

In all areas of medicine, especially in radiology, computers are increasing year by year. Filmless radiology, speech recognition software, electronic application forms, and teleradiology are recent developments that have greatly improved radiologists' performance. This research explores radiology software trends, predictions, and the challenges posed by informatics and historical trend analysis. The rationale behind this research is that information technology (IT) is overgrowing almost every day. We must continuously seek new ways to apply IT to make more use of resources. Consequently, IT becomes increasingly crucial to radiology organizations' innovative thinking, workflow, and business models. This study aimed to analyze all radiology software publications in the Science Citation Index (SCI). From 1991 to July 2021, SCI was used to search for publications systematically. We have also widely used this historical method in radiology software research. The findings and discussions are base on an assessment of trends, predictions, contributions, and challenges in radiology software, and we are exploring radiology software with six evolutionary stages. The gift of this research is that radiology managers realize that the use of new information technologies is closely related to survival in a competitive environment. Radiology companies can review these new technologies to develop more innovative business models and services to improve operational deficiencies.

This paper revisits the analytical theory of fractional vibrations with the highlights in five aspects. First, we address the cases of structures with frequency dependent mass or damping or stiffness in Sections 2-4. Second, we introduce the theory based on the general second-order vibration motion equation with frequency dependent elements (mass, damping, stiffness) in Sections 5-7. Third, we present the analytical theory of seven specific classes of second-order vibration systems with frequency dependent mass or damping or stiffness in Sections 8 and 9. Fourth, we bring forward the analytical theory of seven classes of fractional vibration systems in Sections 10-12. Finally, as an application, we give the closed form expression of the forced response to multi-fractional Euler-Bernoulli beam in Section 13. The explanation of the nonlinearity of fractional vibrations is given in Section 14.

The objective of person re-identification (ReID) tasks is to match a specific individual across different times, locations, or camera viewpoints. The prevalent issue of occlusion in real-world scenarios affects image information, rendering the affected features unreliable. The difficulty and core challenge lie in how to effectively discern and extract visual features from human images under various complex conditions, including cluttered backgrounds, diverse postures, and the presence of occlusions. Some works have employed pose estimation or human keypoint detection to construct graph-structured information to counteract the effects of occlusions. However, this approach introduces new noise due to issues such as the invisibility of keypoints. Our proposed module, in contrast, does not require the use of additional feature extractors. Our module employs multi-scale graph attention for the reweighting of feature importance. This allows features to concentrate on areas genuinely pertinent to the re-identification task, thereby enhancing the model's robustness against occlusions. To address these problems, a model that employs multi-scale graph attention to re-weight the importance of features is proposed in this study, significantly enhancing the model’s robustness against occlusions. Our experimental results demonstrate that, compared to baseline models, the method proposed herein achieves a notable improvement in mAP on occluded data sets, with increases of 0.5%, 31.5%, and 12.3% in mAP scores.

This paper considers the Hermitian solutions of a new system of commutative quaternion matrix equations, we establish both necessary and sufficient conditions for the existence of solutions. Furthermore, we derive an explicit general expression when it is solvable. To illustrate our main findings, we present two numerical algorithms and examples in this paper.

This study employs the phase-field regularized cohesion model (PF-CZM) to simulate crack propagation and damage behavior in porous granite. We investigate how pore radius (r), initial crack-pore distance (D), and pore-crack angle (θ) impact crack propagation. The simulation findings reveal that, with a fixed deflection angle and initial crack-pore distance, larger pores are more likely to induce crack extension under identical loading conditions. Moreover, with r and θ keeping constant, the crack extension can be divided into two stages: from its initiation to the lower edge of the pore and then from the lower edge to the upper boundary of the model. By varying the values of D and r, we derive multiple combinations of different D/r ratios and pore radii. These results demonstrate that with constant r, cracks tend to deflect toward the pore closer to the initial crack. Conversely, when D is maintained constant, cracks will preferentially deflect toward pores with a larger r. In summary, the numerical simulation of rock pores and initial cracks, based on the PF-CZM, exhibits remarkable predictive capabilities and holds significant potential in advancing rock fracture analysis.

Image segmentation is the process of partitioning an image into multiple segments where the goal is to simplify the representation of the image and make the image more meaningful and easier to analyze. In particular, semantic segmentation is an approach of detecting the classes of objects, based on each pixel. In the past, most semantic segmentation models were for only one single style, such as urban street views, medical images, or even Manga. In this paper, we proposed a semantic segmentation model called Dual-Pyramid Wide Residual Network (DPWRN) to solve the segmentation for cross-style datasets, which is suitable for diverse segmentation applications. The DPWRN integrated the Pyramid of Kernel paralleled with Dilation (PKD) and Multi-Feature Fusion (MFF) to improve the accuracy of segmentation. To evaluate the generalization of the DPWRN and its superiority over most state-of-the-art models, three datasets with completely different styles are tested in the experiments. Finally, the DPWRN verified its generalization and also showed its superiority over most state-of-the-art models.

This review will serve as an entry point for international researchers who would like to tap into the vast scientific potential of Chinese-language literature on oceanic fronts. We focused on observational studies in descriptive physical oceanography of marine fronts. A thorough bibliographic search netted 93 papers published in 1982-2023, with a sharp increase of the total number of papers after 2010. This trend continued unabated through the early 2020s. Regionally, the overwhelming majority of papers is focused on the China Seas, particularly the East China Seas (Bohai, Huanghai, and Donghai, especially the Yangtze River Plume) and northern South China Sea (Guangdong Shelf). Elsewhere, a number of papers were dedicated to the Southern Ocean and North Atlantic. Thematically, papers on remote sensing of ocean fronts dominate, with special attention to the development of new advanced front-detection algorithms applied to satellite data on sea surface temperature and chlorophyll. Numerous papers on marine fronts in the China Seas present important results that have to be considered by international researchers. Overall, this review emphasizes the significant contributions made by Chinese oceanographers, particularly to the frontal oceanography of the China Seas.

The purpose of interdisciplinary communication during the early architectural design stage is to achieve the early integration of knowledge in different professional fields, which can help architects to choose correct design development strategies during the early architectural design stage. However, because there is too little information at the early design stage, and design solutions are still rapidly changing and developing, the uncertainties at this stage make it difficult for consultants in other disciplines to provide their views and analysis. In spite of this situation, the emergence of generative modeling is changing design procedures and methods of communication and cooperation for architectural teams, and has brought about a shift in the way architects transmit design information from "what" (declarative information) to "how" (procedural information). Generative modeling is like an aircraft's dashboard: It can provide a basis for interdisciplinary communication, provide interdisciplinary knowledge packages, and bring about a shift in interdisciplinary communication that will reduce the architectural team's communication needs and cost. This study uses a real design case to show the feasibility of generative modeling. Employing generative modeling as a basis, architects can enhance the efficiency of design change and multi-disciplinary communication during the early design stage, integrate specialized knowledge in relevant fields, use this knowledge to formulate design criteria for the next stage, and effectively transmit design decisions. As a consequence, the changes to the cost structure of design revisions and communication between different disciplines has initiated a paradigm shift toward multi-disciplinary communication in architectural design.

Distributed deformation based on Fiber Bragg Grating sensors or other kinds of strain sensors can be used to evaluate safety in operating periods of bridges. However, most of the published researches about distributed deformation monitoring are focused on solid rectangular beam rather than box girder—a kind of typical hollow beam widely employed in actual bridges. Considering that the entire deformation of a single-cell box girder contains not only bending deflection but also two additional deformations respectively caused by shear lag and shearing action, this paper again revises the improved conjugated beam method (ICBM) based on the LFBG sensors to satisfy the requirements for monitoring two mentioned additional deformations. The best choice for the LFBG sensor placement in box gilder is also proposed in this paper due to strain fluctuation on flange caused by shear lag effect. Results from numerical simulations show that most of the theoretical monitoring errors of the revised ICBM are 0.3%~1.5%, and the maximum error is 2.4%. A loading experiment for a single-cell box gilder monitored by LFBG sensors show that most of the practical monitoring errors are 6%~8%, and the maximum error is 11%.

The signal processing technique is one of the principal tools for diagnosing power quality (PQ) issues in electrical power systems. The Discrete Fourier Transform (DFT) is a frequency analysis technique used to process power system signals and identify PQ problems. However, the DFT algorithm may lead to spectral leakage and picket-fence effect problems for asynchronously sampled signals that contain harmonic, inter-harmonic, and flicker components. To resolve this shortcoming, a hybrid method for frequency estimation based on a second-level DFT approach and a frequency-domain interpolation algorithm to obtain the accurate fundamental frequency of a power system is proposed in this paper. This method uses a second-level DFT to compute the cosine and sine parts for the fundamental frequency components of the acquired signals. Then, a frequency-domain interpolation approach is adopted to determine the amplitude ratio for the cosine and sine parts of the system's fundamental frequency. To demonstrate the performance of the proposed frequency estimation method, the observation window used by this paper to evaluate different estimation algorithms is 200 ms. According to the IEC standards, a 200 ms acquisition window is recommended for power system quality assessment. A set of mixed signals with harmonic, inter-harmonic, and flicker components with the fundamental frequency deviation is used. The evaluation results demonstrate the superiority of the new method over other approaches for assessing asynchronously sampled signals contaminated with noise, harmonic, inter-harmonic, and flicker components.

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for AA7050-T7451 by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of cutting variables such as, feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error, material removal rate and power consumption the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is proved that the most significant factor is cutting speed, followed by feed rate, radial depth of cut. Finally, confirmation tests were performed to make a comparison between the experimental results. Experimental results have shown that machining performance in precision turn-boring process can be improved effectively through this approach

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for Ti-6Al-4V by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of machining variables such as, feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error, material removal rate and power consumption the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is shown that the most significant factor is cutting speed, followed by feed rate, radial depth of cut. Finally, confirmation tests were carried out to make a comparison between the experimental results. Experimental results have shown that machining performance in the turn-boring process can be improved effectively through this approach.

Skeletal muscle atrophy is one of the major side effects of high dose or sustained usage of glucocorticoids. Pyroptosis is a novel form of pro-inflammatory programmed cell death that may contribute to skeletal muscle injury. Trimetazidine, a well-known anti-anginal agent, can also improve skeletal muscle performance both in human and mice. We here showed that dexamethasone induced atrophy, evidenced by the increase of muscle atrophy F-box (Atrogin-1) and muscle ring finger 1 (MuRF1) expression , and the decrease of myotube diameter in C2C12 myotubes. Dexamethasone also induced pyroptosis, indicated by upregulated pyroptosis-related protein NLRP3, Caspase-1 and GSDMD. Knockdown of NLRP3 or GSDMD attenuated dexamethasone-induced myotube pyroptosis and atrophy. Trimetazidine administration ameliorated dexamethasone-induced muscle atrophy both in vivo and in vitro. Moreover, trimetazidine improved exercise tolerance, as evidenced by increased running distance and running time, as well as increased skeletal muscle mass in dexamethasone-treated mice. Mechanically, trimetazidine could reverse dexamethasone-induced activation of pyroptosis both in C2C12 myotubes and in mice. Taken together, our present study demonstrated that NLRP3/GSDMD pathway-mediated pyroptosis was involved in dexamethasone-induced skeletal muscle atrophy. Trimetazidine could partially alleviate dexamethasone-induced skeletal muscle atrophy, and increase the diameter of C2C12 myotubes via inhibiting pyroptosis. Thus, trimetazidine might be a potential therapeutic compound for the prevention of muscle atrophy in glucocorticoid-treated patients.

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

Microcystis aeruginosa is a common cyanobacteria found in water blooms and often causes ecological harm. Antibiotics are also increasingly used for the prevention and treatment of bacterial infections in aquaculture. However, since most antibiotics cannot be fully metabolized, they enter the water environment and cause ecological impacts. In this paper, the effects of the two quinolone antibiotics (enrofloxacin and ciprofloxacin) on the population density and microcystins (MCs) production of Microcystis aeruginosa were studied. It is of great significance for the ecological risk assessment of antibiotics to the water environment. The results showed that the 96h EC50 values of enrofloxacin and ciprofloxacin to Microcystis aeruginosa were 56.10mg/L and 49.80mg/L respectively, and the toxicity of ciprofloxacin to Microcystis aeruginosa was slightly stronger than that of enrofloxacin. With the increase of the two quinolone antibiotic concentration, the growth inhibition rate (IR) increased, but when the concentration reached a certain height, the IR would reach its threshold. Long-term exposure to low concentrations of these two quinolone antibiotics is not only more likely to lead to the outbreak of Microcystis aeruginosa, but also increase its toxin production capacity. The highest contents of MCs in enrofloxacin and ciprofloxacin groups were 95.539 μg/g and 93.720 μg/g, respectively. The MCs value of these three enrofloxacin treatment groups was more than above 51.8 times that of control group (CK) on the 4th day; from 8th day to 14th day, the MCs value of these three enrofloxacin treatment groups was more than above 3.2 times that of CK group. For another ciprofloxacin, the MCs value of the treatment group was more than 64.98 times that of the CK group on the 4th day, and from 8th day to 14th day, the MCs value of the treatment group was more than 2.7 times that of the CK group. These findings provide crucial management rationale.

AgW materials exhibit excellent properties and are widely used as contact materials in low- and medium-voltage switches. In this study, a pre-sintering and infiltration method was employed to pre-sinter W powder with Cu, Ni, and (Cu+Ni) addition in the low temperature range of 950–1050 °C. The low-temperature sintering behaviours of W skeletons with different additives were investigated. Subsequently, AgW70, AgW75, AgW80, and AgW85 materials were prepared through infiltration at 1050 °C. The microstructure morphology and physical properties of high-W contact materials were investigated using a metallographic microscope and scanning electron microscope. The mechanism of low-temperature sintering-infiltration of high-W contact materials was elucidated. The results indicated that pure W and 1% Cu-added W skeletons experience minimal linear shrinkage within the temperature range of 950–1050 °C. The linear shrinkage curves of W skeletons with different additives coincided under the conditions of 950–1000 °C/90 min. At 1050 °C, after sintering for 150 min, the particle boundaries in the W skeleton were fully spheroidised, with a dihedral angle of 120°. At 1050 °C and after 150 min of infiltration, cross-sectional micrographs of the AgW material revealed the presence of irregular Ni layers, where Ni spatially enveloped/encapsulated Ag. With an increase in the W content, the electrical conductivity and relative density of AgW(70–85) materials decreased, whereas the hardness of the materials increased.