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

This study examines the influences of live streaming servicescape on Chinese consumers' luxury purchase intention. Interestingly, for the sample without luxury purchase experience, the mediating effect of the perceived value of luxury goods is significant but effect of consumer trust is not. For the sample with luxury purchase experience, the result of mediating effect is just the opposite. The interaction between conspicuous consumption and live streaming servicescape plays a certain role in regulating the perceived value of luxury goods. These results show that luxury brands can adopt innovation in the live streaming servicescape for different types of consumers to promote live streaming marketing. This study enriches the servicescape theory of live streaming.

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

A large body of research has examined people’s attitudes toward mandatory vaccination to cope with the COVID-19 pandemic. However, studies have yet to explore how Chinese people view the COVID-19 vaccine mandates, let alone placing such views in the country’s highly politicized context. On the other hand, facing the high pressure of loosening its zero-COVID policies amidst the worldwide practices of co-existing with the COVID-19 virus, the country has to improve its vaccination coverage quickly. In this situation, it is more than necessary to systematically investigate the Chinese public’s attitude to mandatory vaccination against the virus and the underlying determinants. The current study utilizes data from a national survey adopting quota sampling to analyze the Chinese public’s medical and non-medical considerations when judging compulsory COVID-19 vaccination. The study reveals that thanks to China’s successful lockdown policies, personal risk, and benefit perceptions did not dominate their views regarding vaccination mandates. Instead, conspiracy beliefs regarding the pandemic outbreaks, conspiratorial thinking, and nationalism more strongly predicted their willingness to accept mandatory vaccination. Given the potentially massive impacts of the COVID-19 infection, if China opens its door and loosens its strict quarantine restrictions, the Chinese public needs to be educated with more medically valuable and relevant information to improve their vaccination protection against COVID-19.

The effects of various drawing parameters and annealing processes on the structure and properties of Cu-Ag wires, containing 1 wt% silver, were investigated using specialized equipment including fine wire drawing machines, very fine wire drawing machines, heat treatment equipment, tensile testing machines, microcomputer-controlled electronic universal testers, resistance testers, and scanning electron microscopes. The results revealed that continuous drawing of Cu-1%Ag alloy wires led to elongation of the grains, resulting in a uniform and tightly fibrous microstructure. Moreover, the tensile strength of the alloy wire increased from 670 MPa to 783.9 MPa after a single-pass with a deformation of 14%. Subsequently, when the wire was drawn at a speed of 500 m/min, the tensile strength further increased to 820.1 MPa. After annealing the Փ0.08 mm Cu-1% Ag alloy wire, an increase in annealing temperature up to 500°C resulted in the wire's tensile strength decreasing from 820.1 MPa to 377.5 MPa. Simultaneously, the elongation increased from 1.94% to 15.21%, and the resistivity decreased from 1.931×10-8Ω·m to 1.723×10-8Ω·m. Additionally, when annealing was conducted at a rate of 80 m/min, the wire resistivity dropped to 1.635×10-8Ω·m.

The combination of wet-lab experimental data on multi-site combinatorial mutations and machine learning is an innovative method in protein engineering. In this study, we present an improved innovative sequence–activity relationship (innov'SAR) methodology based on novel descriptors and digital signal processing (DSP) to construct a predictive model. In this improved approach, 21 experimental (R)-selective amine transaminases from Aspergillus terreus (AT-ATA) were used as an input to predict higher thermostability than that predicted using the existing data. We successfully improved the determination coefficient (R2) of the model from 0.66 to 0.92. In addition, root mean square deviation (RMSD) and root mean square fluctuation (RMSF) were estimated and conformation analysis based on molecular dynamics simulations was performed to verify the enhanced thermal stability of the screened mutants. The improved innov'SAR algorithm enhanced the predictive accuracy, suggesting a method for modifying the stability of AT-ATA, which may help in directed evolutionary screening and open up new avenues for protein engineering.

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

Juvenile idiopathic arthritis (JIA) is a disease with unknown causes within all forms of arthritis in children under 16 years of age. The diagnosis is made when another joint pathology is excluded. Difficulties in early and differential diagnosis lead to the rapid disability of patients and an unfavourable life prognosis. Therefore, timely diagnosis is necessary to prevent irreversible damage to the joints and preserve their function. Due to the widespread use of new technologies, modern multimodal imaging has gained recognition, which includes X-ray, ultrasound, and MRI. The combination of methods plays a key role in confirming the diagnosis, monitoring disease activity, prognosis during the course, and outcome in children with JIA. Each method has its own advantages and disadvantages. The introduction of the method of passive microwave radiometry (MWR), in combination with other imaging methods, makes it possible to expand the possibilities of screening the disease in the preclinical and early clinical phases.

Honeycomb-like CO₃O₄ nanosheets with high specific surface area were successfully synthesized on porous nickel foam by the facile hydrothermal method followed by an annealing treatment (300 °C), which were used as high-performance supercapacitor electrodes. The effects of mole ratio of hexamethylenetetramine (HMT) and Co(NO₃)₂ (1:1, 2:1, 3:1, 4:1, 5:1 and 6:1）as the reactants on morphological evolution and electrochemical performance of the electrodes were investigated in detail. X-ray diffractometry, transmission electron microscopy, X-ray photoelectron spectroscopy and scanning electron microscopy were applied to characterize the structure and morphology of the products. The electrochemical performance was measured by cyclic voltammetry (CV) and galvanostatic charge/discharge. The results indicated that phase constituents were almost unaffected with the change in mole ratio of HMT and Co(NO₃)₂. However, the significant morphological evolution of Co₃O₄ was observed with increasing the mole ratio, which was described as followed: the nanosheets accompanied with a large number of spherical nanoparticles→the formation of some strip-like particles due to the agglomeration of spherical nanoparticles→the formation of new nanosheets resulting from the growth of strip-like particles→the formation of coarse flower-like particles owing to the connection among the nanosheets→the nanosheets gradually covered with flower-like particles. Accompanied with the change, the specific surface area was increased firstly, and then decreased. A maximum was obtained in the HMT and Co(NO₃)₂ mole ratio of 4:1, which was further validated by CV and galvanostatic charge/discharge tests. The specific capacitance value was 743.00 F·g^-1 at 1 A·g^-1 in the galvanostatic charge/discharge test, which was apparently higher than those in the other mole ratios (139.11 F·g^-1 in 1:1, 280.46 F·g^-1 in 2:1, 503.29 F·g^-1 in 3:1, 463.75 F·g^-1 in 5:1 and 363.74 F·g^-1 in 6:1). The change was also observed in the CV test with a scanning rate of 5 mV·s^-1 (121.32 F·g^-1 in 1:1, 217.33 F·g^-1 in 2:1, 559.86 F·g^-1 in 3:1, 693.56 F·g^-1 in 4:1, 423.35 F·g^-1 in 5:1 and 321.64 F·g^-1 in 6:1). Co₃O₄ synthesized in the mole ratio of 4:1 also demonstrated an excellent cyclic performance, in which about 97% of the initial specific capacitance was remained at 1 A·g^-1 for 500 cycles in the galvanostatic charge/discharge test. This excellent electrochemical performance was ascribed to high specific surface area of Co₃O₄ nanosheets that provide enough channels and space for ions transportion.

Taiwan’s Chi Mei Medical Center has a vision of becoming a sustainable organization. They found they violated the sustainable development goal (SDG) 13 (“Climate Action”) since its workflows consume excessive tangible resources and waste much operation time. To fulfill the vision, the Chi Mei Medical Center first introduced electronic invoicing. Implementing this electronic invoicing included adopting cloud E-invoice data and creating a software robot for auditing them. This study presents this software robot and its contributions. The software robot replaces an internal auditor to log into Taiwan’s E-invoice platform, download cloud E-invoice data, and detect the inconsistency between these cloud and on-premise data. Internal auditors of the Chi Mei Medical Center only needed to confirm the detection results. They welcome this software robot since it significantly reduces their work burdens. They approved more software robots for assisting other workflows. Besides, the Chi Mei Medical Center earned profits after eliminating paper invoices. This elimination helped release less carbon. This study concludes that chasing a sustainable organization is unnecessarily equivalent to the requirement of more costs. A software robot represents the last puzzle for constructing a paperless workflow since it can resolve the resistance of existing workers to a new workflow.

Due to wood’s susceptibility to fire, it is crucial to treat wood-based materials with flame retardants, especially in construction applications. This study investigated the effectiveness of various grooving types, including transverse, longitudinal, both transverse and longitudinal, and surface grooving, in enhancing larch's vacuum pressure impregnation process. The results revealed that transverse grooving provided a slightly greater impregnation advantage than longitudinal grooving. Moreover, exceptional impregnation performance was observed in larch samples subjected to both longitudinal and transverse grooving and surface grooving, exhibiting a remarkable improvement of 214,7 % compared to untreated larch.

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

The four-way reversing valve is a key component determining whether a heat pump air conditioning system can work. Studying the four-way reversing valve is of great significance for improving the performance of the heat pump air conditioning system. In this paper, the control equation of the sliding block movement process is constructed to simulate the reversing process of the four-way reversing valve in fluid mechanics, and a detailed study is carried out from the sliding block speed, sliding block acceleration, sliding block force, refrigerant leakage, and other aspects. Research has shown that optimizing the structure of the slider can greatly improve the working performance of the four-way reversing valve. Increasing the height of the slider not only improves the pressure relief ability of the four-way reversing valve and prevents the slider from being damaged by high-pressure gas impact, but also reduces the leakage of refrigerant during the directional process; When reducing the length of the slider, although it will improve the pressure relief capacity of the four-way reversing valve, it also increases the amount of refrigerant leakage. The research results provide a theoretical basis and improvement direction for designers to improve the performance of four-way reversing valves.

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

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

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

In the context of the rural revitalization strategy, it is urgent to accurately grasp the spatial differentiation characteristics and influencing factors of rural settlements in underdeveloped arid inland river basins. Taking the Shiyang River Basin as an example, the rural settlements from 2000 to 2019 were obtained by visual interpretation using satellite remote sensing data and official statistical data. Following the logical of "state characteristics - evolutionary patterns - influence factors - layout optimization", the average nearest index, gravity-center migration model, spatial statistical analysis and other methods were used combine with GIS. The spatiotemporal pattern evolution characteristics of rural settlements in the past 20 years have been analyzed. The results revealed the following: 1) The distribution pattern of rural settlements in the study area is sheet-like and strip-shaped. The projects in the southeast are mostly distributed in a patchy pattern with high density, while the characteristics in the west and north are exactly opposite. The objects in the south are distributed in the alluvial area of rivers, while settlements in the north are located in the oasis area. 2) From 2000 to 2019, the scale of rural settlements in the Shiyang River Basin, where simultaneous occurrence of new-built and disappearing phenomena, shows an expansion trend that fast firstly and then slow. Spatially, rural settlements in the basin show a trend of clustering towards the southwest. 3) The distribution characteristics of rural settlements are close to water and roads, greatly influenced by urban-rural integration and ecological migration. The results will provide scientific basis for accelerating the modernization of rural areas, and the construction of new rural areas according to local conditions.

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

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

The sexual reproduction of ascomycetes is controlled by the mating-type(MAT) locus. (Pseudo)homothallic reproduction has been hypothesized based on genetic data from Hirsutella sinensis (Genotype #1 of Ophiocordyceps sinensis). In this study, the differential occurrence of the mating-type genes in the MAT1-1 and MAT1-2 idiomorphs, which constitute the genetic control of O. sinensis reproduction, was analyzed in 237 strains and 5 genomes of H. sinensis. The mating-type genes were differentially transcribed in H. sinensis Strain L0106, and the MAT1-2-1 transcript in H. sinensis Strain 1229 was alternatively spliced, with an unspliced intron I containing stop codons; these findings constitute O. sinensis reproduction controls at the transcriptional and coupled transcriptional-translational levels. The occurrence of the mating-type genes and a-/α-pheromone receptor genes differed among the 5 H. sinensis genomes. The differential occurrence and transcription of these genes are inconsistent with self-fertilization under (pseudo)homothallism but suggest self-sterility of H. sinensis, which therefore needs a mating partner to achieve sexual outcrossing under heterothallism or hybridization. Consistent occurrence and transcription of the mating-type genes of both the MAT1-1 and MAT1-2 idiomorphs have been reported in natural and cultivated Cordyceps sinensis, but these findings are insufficient to determine the reproduction mode(s) because of the co-occurrence of >90 fungal species and multiple genomically independent genotypes of O. sinensis. The mutant MAT1-1-1 and α-pheromone receptor transcripts in natural C. sinensis result in the N-terminus or middle-truncated proteins, with changes in hydrophobicity and secondary structures of the proteins, suggesting heterogeneous fungal source(s) of the proteins and hybridization reproduction.

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

The ketogenic diet and walking exercise training activity are two key public health lifestyle factors. The potential of combined lifestyle factors interventions focused on getting to compliance in forced exercise. A balanced ketogenic diet and regular exercise activity is a key modifiable factor to the prevention and management of chronic diseases. Influence health across the lifespan and reduction of the risk of premature death through several biological mechanisms. Community older group’s lifestyle factors interventions contribute identity in their natural living environment. While the older health benefits of walking exercise training strategies are commonly to study, combined ketogenic diet and walking exercise interventions have induced greater benefits in community older groups.

In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to intricate coupled conditions, this distribution strategy inevitably results in increased inconsistency and hastened system aging. This paper presents a novel differentiated power distribution strategy comprising three control variables: the rotation status, the operating boundaries for both Depth of Discharge (DOD) and C-rates (C) within a control period. The proposed strategy integrates an aging cost prediction model developed to express the mapping relationship between these control variables and aging costs. Additionally, it incorporates the multi-colony particle swarm optimization (Mc-PSO) algorithm into the optimization model to minimize aging costs. The aging cost prediction model consists of three functions: predicting health features (HFs) based on the cumulative charge/discharge throughput quantity and operating boundaries, characterizing HFs as comprehensive scores, and calculating aging costs using both comprehensive scores and residual equipment value. Further, we elaborated on the engineering application process for the proposed control strategy. In the simulation scenarios, this strategy prolonged the service life by 14.62%, reduced the overall aging cost by 6.61%, and improved module consistency by 21.98%, compared with the traditional equalized distribution strategy. In summary, the proposed strategy proves effective in elongating service life, reducing overall aging costs, and increasing the benefit of energy storage systems in particular application scenarios.

The nuclear factor-ĸB (NF-ĸB) transcriptional system is a major effector pathway involved in inflammatory responses. Previous studies found that a Gardenia decoction (GD) inhibited the expression of NF-κB in a lipopolysaccharide (LPS)-stimulated mouse intestinal injury model. Herein, we hypothesized that geniposide (GE), a component of Gardenia jasminoides Ellis, also exerts anti-inflammatory effects and inhibits NF-ĸB activity in LPS-induced intestinal epithelial cells (IEC-6). IEC-6 cells were stimulated with LPS, following which the effects of GE on NF-ĸB signaling in the IEC-6 cells were examined by western blotting to detect IĸB phosphorylation/degradation. The expression of NF-κB was determined by immunofluorescence assay (IFA). Enzyme-linked immunosorbent assay (ELISA) was used to detect the inhibitory effect of GE on the release of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-1β (IL-1β) activated by LPS in IEC-6 cells. In addition, the migration ability of IEC-6 cells was observed by the scratch method. These results showed that GE dose-dependently downregulated levels of the proinflammatory cytokines TNF-α, IL-6 and IL-1β that had been upregulated by LPS and suppressed the phosphorylation of IĸB and NF-ĸB induced by LPS. Our findings indicated that GE could reduce LPS-induced NF-ĸB signaling and proinflammatory expression in IEC-6 cells and significantly enhance the migration of IEC-6 cells. Moreover, GE inhibited the expression of NF-κB, nuclear transfer, and transcriptional activity in IEC-6 cells. GE could block the synthesis of inflammatory factors of IEC-6 cells by inhibiting activation of the IĸB/NF-κB signaling pathway induced by LPS.

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

Digital technology makes energy systems more dynamic, efficient, reliable and sustainable. Promoting the digital governance of renewable energy is not only a key part of energy transformation, but also an important initiative to cope with the global energy crisis, which provides a new impetus for realizing the goal of net-zero emissions. In order to achieve the "dual-carbon" goal, China has been actively promoting energy reform and enhancing the wide application of digital technologies in the development and utilization of renewable energy. The digital governance system and governance capacity of renewable energy is an important support for the modernization of the national governance system and governance capacity. Although the digital governance of renewable energy in China has better policy support and advantages, the dilemmas it faces are still relatively prominent, including unsound laws and policies, insufficient governance capacity, and security loopholes in digital technology, etc. Therefore, this paper proposes a problem-oriented approach to the digital governance of renewable energy. Therefore, this paper puts forward problem-oriented optimization suggestions to innovate the legal system of renewable energy digital governance, promote the digital transformation of China's renewable energy industry, provide development space for renewable energy digital governance in a diversified mode, and enhance the digital governance capacity by improving the renewable energy security system.

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

The vibration signal of the engine contains strong background noise and many kinds of modulating components, which is difficult to diagnose. Variational mode decomposition (VMD) is a recently introduced adaptive signal decomposition algorithm with a solid theoretical foundation and good noise robustness compared with empirical mode decomposition (EMD). VMD can effectively avoid endpoint effect and modal aliasing. However, VMD cannot effectively eliminate the random noise in the signal, so the random decrement technique is introduced to solve the problem. Based on the crankshaft bearing fault simulation experiment, the four kinds of wear state vibration signals are decomposed by VMD, and the modal components with smaller permutation entropy are selected as fault components. Then the fault component is processed by the random decrement technique, and the Hilbert envelope spectrum of the fault component is obtained. Compared with the fault feature extraction method based on EMD and EEMD, the feature extraction results of the proposed method are better than those of the above two methods. The simulation analysis and the simulation test of the crankshaft bearing fault verify the effectiveness of the proposed method.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

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

To address the insufficient mechanical properties of calcined phosphogypsum, this research aims to investigate the utilization of basalt fiber and calcium carbonate whiskers as reinforcing agents. The study examines their impact on the flexural and compressive strength, toughness, water resistance, and tensile strength of calcined phosphogypsum. In the individual tests, basalt fibers with different lengths (3 mm, 6 mm, 9 mm, and 18 mm) were added at dosages of 0%, 0.5%, 1.0%, and 1.5% respectively. The findings demonstrate that basalt fiber effectively enhances the flexural and compressive strength, toughness, and tensile strength of calcined phosphogypsum, albeit potentially compromising water resistance. Among the various fiber lengths, the 6 mm fibers exhibit the most advantageous influence on the performance of calcined phosphogypsum. A subsequent test was conducted to investigate the impact of cross-scale fibers on the properties of calcined phosphogypsum by mixing 6 mm basalt fibers and calcium carbonate whiskers. The results illustrate that calcium carbonate whisker refines the pores, thereby improving the flexural strength and toughness of calcined phosphogypsum. Furthermore, it compensates for the water resistance limitations associated with the sole utilization of basalt fiber while further augmenting the tensile strength and strain capacity. However, it should be noted that increasing the dosage of both calcium carbonate whiskers and basalt fibers concurrently leads to increased porosity of phosphogypsum and reduced compressive strength.

Pancreatitis and alcoholic pancreatitis are serious health concerns, and there is an urgent need for effective treatment strategies. Alcohol is a known etiological factor for pancreatitis, including acute pancreatitis (AP) and chronic pancreatitis (CP). Excessive alcohol consumption induces many pathological stress responses; of particular note is endoplasmic reticulum (ER) stress and adaptive unfolded protein response (UPR). ER stress results from the accumulation of unfolded/misfolded protein in the ER and is implicated in the pathogenesis of alcoholic pancreatitis. Here we summarize the possible mechanisms by which ER stress contributes to alcoholic pancreatitis. We also discuss potential approaches targeting ER stress and UPR for developing novel therapeutic strategies for the disease.

With the increasingly stringent airworthiness standards, the noise generated during the rotorcraft flight is gradually attracting people’s attention. It widely operated helicopters at low altitudes because of their maneuverability. The way to reduce the noise caused by the complex airflow of the helicopter rotor system has progressively become a hot topic for researchers. Using a hybrid acoustic analysis method, this paper investigates the improvement of the noise and thrust of the helicopter’s tail rotor through the tail rotor structural parameters. For the basic model, the turbulence simulation is performed using an incompressible detached eddy simulation (DES) method, and the Lighthill acoustic analog equation is calculated using the finite element method (FEM). We verified the accuracy of the method through wind tunnel tests. We chose a series of structural parameters for sound simulation and fluid simulation calculations. The results indicate that the modified tail rotor noise reduced by 16.5 dBA and the total thrust increased by 19.9% from the prototype model. This work can enhance the duct tail rotor design to improve aerodynamic and aeroacoustic performance.

Achieving the dual development of rural revitalization and urbanization is an important strategic goal of China’s current modernization. Rural population and settlements are the main components of the countryside in traditional agricultural areas, and play an important role in the development of the countryside itself in terms of urban and rural land use and in the formation of urban and rural development patterns. This study analyzes the spatial and temporal changes in rural populations and settlements at the township level, as well as the degree and type of coupled development. A framework for urban–rural development relationships based on different types of coupled development is proposed, and a model of urban–rural forces is constructed to derive the spatial pattern of urban–rural development at the township level that may be formed in the future. Our study shows that the rural population and settlements in the study area are characterized by significant spatial and temporal dynamics, indicating that traditional rural areas are in a process of rapid development and change. The results of the township-level coupling measurements present four types of development in terms of the spatial pattern of urban–rural development: A-type is most likely to produce new cities or satellite towns in the Jixi–Harbin–Qiqihar area in the future; B-type is the fastest dying area in the future, located in the Harbin and Qitaihe clusters, with a tendency to merge into Harbin; C-type is the area to be focused on in the future to attract population and strictly control the growth of the rural settlement area to avoid it turning into B-type; D-type may develop regional township centers in the future in the combined area of Jiamusi City, Suihua City and Mudanjiang City. The results of the study provide experience in realizing rural revitalization according to local conditions. The new spatial pattern of urban–rural development provides an important reference for formulating land use policies, optimizing urban–rural land allocation and realizing integrated urban–rural development strategies.

This study presented a novel and sustainable method for producing chitin nanocrystals (PA-ChNCs) using phosphoric acid hydrolysis. The produced PA-ChNCs were used as stabilizers for Pickering emulsions and their physicochemical properties as well as stabilization mechanisms were systematically investigated. The PA-ChNCs exhibited small particle sizes and high surface areas, enabling an effective adsorption at the oil/water interface, which prevented coalescence in Pickering emulsions. The particle size and surface charge PA-ChNCs were strongly pH-dependent, which were critical factors for stabilizing Pickering emulsions. The study showed that emulsions with higher O:W ratios (50%) exhibited larger droplets but greater viscosity, forming a stable gel-like matrix that was more stable than emulsions with other O:W ratios after storage for 30 days. Emulsions with higher PA-ChNCs concentrations (2.0 wt%) and higher pH values (pH 10) showed small droplets and high viscosity, leading to stable emulsions. This research contributes to the development of sustainable and effective emulsifiers for use in the food industry, making utilization of seafood waste in an eco-friendly manner possible. Overall, this study highlights the potential of using newly developed PA-ChNCs as stabilizers for Pickering emulsions in food products.

Nuclear magnetic resonance (NMR) techniques are widely used to identify pure substances and probe protein dynamics. Edible oil is a complex mixture composed of hydrocarbons, which have a wide range of molecular size distribution. In this research, low field NMR (LF-NMR) relaxation characteristic data of various sample oils were analyzed. We also suggest a new method for prediction size of edible oil molecules using LF-NMR relaxation time distributions. According to the relative molecular mass, carbon chain length, transverse relaxation time of different sample oils, combined with oil viscosity and other factors, the relationship between carbon chain length and transverse relaxation time rate was analyzed. Various oils and fats in the mixed fluid are displayed, reflecting the composition information of different oils. To study the correlation between the rotation correlation time and molecular information of oil molecules. The molecular composition of the resulting fluid determines its properties, such as viscosity and phase behavior. The results show that low-field NMR can obtain information on the composition, macromolecular aggregation, and molecular dynamics of complex fluids. Measurements of grease in the free fluid state show that the relaxation time can reflect the intrinsic properties of the fluid. It is shown that the composition characteristics and states of complex fluids can be measured by low-field nuclear magnetic resonance.

Ocean surface waves have been utilized as fundamental information in various fields of oceanic research. In this paper, we suggest a simulation and modelling technique for generating an ocean surface wave using an inverse Fast Fourier Transform (iFFT), and we subsequently verify the wave’s accuracy. The conventional method, linear superposition, requires recursive calculation because of the double summation and the time variable; to circumvent this issue, the new algorithm is presented. The Joint North Sea Wave Project (JONSWAP) spectrum is utilized for the ocean surface wave simulation example, and the parameters are the significant wave height (HS) and the zero-crossing wave period (TZ). A coordinate transform for the wavenumber domain was used to apply the inverse FFT algorithm. To verify the accuracy of the simulation result, the relative error between the input condition and the analysis result was calculated. The result for TZ is below 4% relative error, and the maximum relative error for HS is 7%. To avoid the Nyquist frequency for wave-field analysis and simulation, the minimum grid size was calculated by twice applying the maximum wavenumber.

With superior optical properties, high flexibility in engineering its material properties, and strong capability for large-scale on-chip integration, graphene oxide (GO) is an attractive solution for on-chip integration of two-dimensional (2D) materials to implement functional integrated photonic devices capable of new features. Over the past decade, integrated GO photonics, representing an innovative merging of integrated photonic devices and thin GO films, has experienced significant development, leading to a surge in many applications covering almost every field of optical sciences. This paper reviews the recent advances in this emerging field, providing an overview of the optical properties of GO as well as methods for the on-chip integration of GO. The main achievements made in GO hybrid integrated photonic devices for diverse applications are summarized. The open challenges as well as the potential for future improvement are also discussed.

The intricate relationship between physical and social environments within organizations plays a pivotal role in shaping sustainable innovation endeavors. This paper presents a comprehensive analysis of two key dynamics that have garnered substantial scholarly attention for promoting sustainable innovation: the physical environment and the organizational climate. To elucidate the intricate interplay between these dynamics, we propose a novel three-dimensional framework that guides the modeling of the intricate processes through which the physical environment and innovation climate synergistically influence innovation outcomes. Building on this framework, we delve into an in-depth literature review concerning physical environments that exert a significant impact on innovation. Through this review, we identify and elaborate on four pivotal elements of the physical environment: communality, personalization, comfort, and healthiness. Leveraging insights gleaned from this review, we outline two promising avenues for future research in the realm of the physical environment's interaction with the innovation climate. Furthermore, we underscore the critical importance of adopting an interdisciplinary approach that seamlessly integrates insights from both the physical and social domains to comprehensively understand the sustainable innovation landscape.

Weeds that infest crops are a primary factor limiting agricultural productivity world-wide. Weedy rice, also called red rice, has experienced independent evolutionary events through gene flow from wild rice relatives and de-domestication from cultivated rice. Each evolutionary event supplied/equipped weedy rice with competitive abilities that allowed it to thrive with cultivated rice and severely reduce yields in rice fields. Under-standing how competitiveness evolves is important not only for noxious agricultural weed management but also for the transfer of weedy rice traits to cultivated rice. Molec-ular studies of weedy rice using simple sequence repeat (SSR), restriction fragment length polymorphism (RFLP) and whole genome sequence have shown great genetic variations in weedy rice population globally. These variations are evident both at whole genome and at single allele level, including Sh4 (shattering), Hd1 (heading and flower-ing), and Rc (pericarp pigmentation). The goal of this review is to describe the genetic diversity of current weedy rice germplasm and the significance of weedy rice germplasm as a novel source of disease resistance. Understanding these variations, es-pecially at an allelic level, is also crucial as individual locus that control important traits can be of great target to rice breeders.

Insulated Gate Bipolar Transistor (IGBT) may convey high current and sustain high breakdown voltages; it may provide high power control. In a sense, how IGBT demonstrates the capability of power control was not specifically described, and the equivalent bipolar junction transistors (BJT) activated by an applied bias to the insulated gate is intriguing. As seen in Figure 1, IGBT shows an equivalent circuit structure containing two types of BJT, (NPN-type Bipolar transistor and PNP-type Bipolar transistor), which can be modeled as diode-associated transistor. Apparently, as a bias applies to the controlling gate, the channel beneath the gate oxide gets strongly inversed and turns out to be conductive just like what happens on metal-oxide-silicon field effect transistor (MOSFET), which provides necessary igniting currents to both BJTs and thus causes high current gain flowing through them-selves from the bottom. A proposed and renewed formula provides addressing the above scenario and successfully fitting the measured data that forms the characteristic curves. Some parameters in the proposed formula, which includes size and mobility associated constant, threshold voltage, and Early-Voltage-related lambda for MOSFET, explain and explore the underlying physics. IGBT thus enjoy high input impedance and high current gain due to MOSFET (Insulated Gate) and BJT, respectively. This formula combines both merits of MOSFET and BJT in order to fit the measured data. Indeed, the formula intimately fits IGBT electrical characteristic curves, and thus may be qualified and served as a model. The new model is then advisable for designing power integrated circuit to exactly achieve power saving, power control, and power efficiency.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.

Variational mode decomposition (VMD) is a recently introduced adaptive signal decomposition algorithm with a solid theoretical foundation and good noise robustness compared with empirical mode decomposition (EMD). There is a lot of background noise in the vibration signal of diesel engine. To solve the problem, a denoising algorithm based on VMD and Euclidean Distance is proposed. Firstly, a multi-component, non-Gauss, and noisy simulation signal is established, and decomposed into a given number K of band-limited intrinsic mode functions by VMD. Then the Euclidean distance between the probability density function of each mode and that of the simulation signal are calculated. The signal is reconstructed using the relevant modes, which are selected on the basis of noticeable similarities between the probability density function of the simulation signal and that of each mode. Finally, the vibration signals of diesel engine connecting rod bearing faults are analyzed by the proposed method. The results show that compared with other denoising algorithms, the proposed method has better denoising effect, and the fault characteristics of vibration signals of diesel engine connecting rod bearings can be effectively enhanced.

In February 2004, the Food and Drug Administration (FDA) was the first to approve the combination of cisplatin (CDDP) and pemetrexed (PEM) as standard first-line chemotherapy for untreated, unresectable malignant pleural mesothelioma (MPM). However, after that approval, no progress was made in the standard first-line treatment of MPM for almost 15 years. Positive results from a phase 3 study (Mesothelioma Avastin Cisplatin Pemetrexed Study: MAPS) verifying the effect of bevacizumab, an anti-angiogenesis agent added to CDDP/PEM for unresectable MPM, were published in The Lancet in December 2015; however, this did not lead to approval by national drug regulatory agencies. Furthermore, no second-line treatment was established for cases refractory to CDDP/PEM. In August 2018, the Pharmaceuticals and Medical Devices Agency of Japan was the first in the world to approve monotherapy with nivolumab, an immune checkpoint inhibitor (ICI), for previously unresectable, advanced, or recurrent MPM. Following Japan, in October 2020, the FDA approved the combination of nivolumab and ipilimumab for the treatment of previously untreated, unresectable MPM. In this article, we review the transition of drug treatment for MPM, in light of the historical background, focusing on the benefits of ICIs.

The genetic diversity of coronavirus (CoV) is high, and its infection in animals has not yet been fully revealed. By RT-PCR detection of partial RNA dependent RNA polymerase (RdRp) gene of CoV, we screened a total of 502 small mammals belonging to 18 species in 12 genera and 4 orders collected in Dali and Nujiang Prefecture of Western Yunnan Province, China. The prevalence of β-CoV in Chevrieri's field mouse (Apodemus chevrieri) and Lancangjiang field mouse (A. ilex) were 3.54% (4/113) and 6.67% (6/90), respectively; the prevalence of α-CoV in White-footed Indochinese rat (Rattus nitidus) and long-tailed red-toothed shrew (Episoriculus leucops) was 75% (3/4) and 5.88% (1/17), respectively. The co-infection rates of β-CoV and α-CoV in Kachin red-backed vole (Eothenomys cachinus), Norway rat (R. norvegicus) were 2.22% (2/90), 3.85% (1/26) respectively. The identity of the partial RdRp genes obtained of 13 strains of β-CoV was 83.42%-99.23% at nucleotide level, and it is worth noting that the two strains from Kachin red-backed vole showed highly homology to BOV-36/IND/2015 from Indian bovine and DcCoV-HKU23 from one-humped camel (Camelus dromedarius) in Morocco, the nucleotide similarity between 97.86%-98.33%. Similarly, the identity of the 7 strains of α-CoV among the partial RdRp sequences was 94.00%-99.18% at nucleotide levels. The viral load in different tissues was measured by quantitative RT-PCR (qRT-PCR). The average CoV viral load in small mammalian intestinal tissue was 1.25×106copies/g, differently, the mean CoV viral load in liver, heart, lung, spleen and kidney tissue was from 1.29×103 to 4.02×103copies/g, which revealed that CoV has extensive tropism of intestinal tissue in small mammals (P < 0.0001). This result revealed the genetic diversity, epidemiology, and infective tropism of α-CoV and β-CoV in small mammals from Dali and Nujiang, which deepens the comprehending of the retention and infection of coronavirus in natural hosts.

Effective prediction of wastewater treatment is beneficial for precise control of wastewater treatment processes. The nonlinearity of pollutant indicators such as COD and TP makes the model difficult to fit and has low prediction accuracy. The classical deep learning methods have been shown to perform nonlinear modeling. However, there are enormous numerical differences between multi-dimensional data in the prediction problem of wastewater treatment, such as COD above 3000 mg/L and TP around 30 mg/L. It will make current normalization methods challenging to handle effectively, leading to the training failing to converge and the gradient disappears or exploding. This paper proposes a multi-factor prediction model based on deep learning. The model consists of a combined normalization layer and a codec. The combined normalization layer combines the advantages of three normalization calculation methods: z-score, Interval, and Max, which can realize the adaptive processing of multi-factor data, fully retain the characteristics of the data, and finally cooperate with the codec to learn the data characteristics and output the prediction results. Experiments show that the proposed model can overcome data differences and complex nonlinearity in predicting industrial wastewater pollutant indicators and achieve better prediction accuracy than classical models.

A robust guaranteed cost preview repetitive controller is proposed for a class of polytopic uncertain discrete-time systems. In order to improve the tracking performance, the repetitive controller combined with preview compensator is inserted in the forward channel. By using the L-order forward difference operator, an augmented dynamic system is constructed. Then, the guaranteed cost preview repetitive control problem is transformed into the guaranteed cost control problem for the augmented dynamic system. For given performance index, the sufficient condition of asymptotic stability for the closed-loop system is derived by combining parameter-dependent Lyapunov function method with linear matrix inequality (LMI) techniques. By incorporating the controller obtained into the original system, the guaranteed-cost preview repetitive controller is derived. A numerical example is also included to show the effectiveness of the proposed method.

Types of DNA recombination include homologous recombination and nonhomologous recombination. Homologous DNA recombination is a general term that includes exchange of information between chromatids: (reciprocal) crossing-over, gene conversion, and post-meiotic segregation. Gene conversion is now thought to be a type of non-Mendelian segregation of heterozygous markers near the recombination initiation site. Thus, it includes both gene conversion and post-meiotic segregation previously described. DNA non-HR including transpositional recombination and site-specific recombination. Our understanding of the molecular mechanism by which DNA recombination occurs has significantly increased in the past decades. Currently The synthesis-dependent strand annealing model is now thought to give rise to most or all noncrossovers, with the double-strand-break repair model forming mainly crossovers. The Shapiro model proposed by Dr. J. Shapiro explains the molecular mechanism of transpositional recombination. Site-specific recombination results from another distinct model. We previously proposed a novel theory which can provide a more reasonable and simpler explanation accounting for DNA HR including the 3 classes of recombinogenic events described above. In the new supplementedly molecular model, DNA meiotic recombination can be initiated by a copy choice mechanism, that is, copying part of 1 single-stranded DNA template, followed by DNA polymerase switching to another single-stranded DNA template, and then resuming the following DNA synthesis along the new template. The current review suggests that transpositional recombination and site-specific recombination should be initiated by copy choice during DNA synthesis rather than break/join mechanism. The work indicates that review of DNA nonhomologous recombination are very necessary. The novel theory would challenge earlier models accounting for transpositional recombination and site-specific recombination and would be critical to the understanding of the mechanisms. We hope copy choice initiating DNA nonhomologous recombination will be one of the concepts that are explored. Proper and specific experiments are required to reconstruct the detailed mechanism described here.

Nicotine exposure may affect NSCLC is associated with lung cancer in humans. Whether nicotine exhibits carcinogenesis promoted activities in tumor growth still unknown. Nicotine is known to have dichotomous effects on cancer biology, acting like a pro- or anti-carcinogenesis agent. There are different functions between adenocarcinoma and squamous NSCLC cancer cells. Excess generation of nicotine may inhibit mitochondrial metabolism, protein modification, and DNA cleavage. Materials and Methods: We used the H520 NSCLC line obtained from human lung epithelial cells to detected nicotine growth and toxicity using MTT assay and western blotting. The concentration of nicotine stimulated cell growth to correspond to low concentration, while high concentration was cytotoxic. Results: According to MTT assay results, at 1.0 μM nicotine has significantly enhanced the H520 cell viability (%). Nicotine induced lung cancer carcinogenesis through mechanisms of α7nAchR, EGFR, HDAC2/4/5, Cyclin D/Cyclin E, Bcl-2, p-Akt, and inflammatory proteins of NF-KappaB and COX2 increases at 1.0 μM. Apoptosis proteins were decreases at 1.0 μM nicotine by p21, p27, c-jun, and p38α using western blotting. Nicotine stimulates tumor growth is mediated through α7nicotinic-acetylcholine receptors (α7nAChR), possibly involving inflammation. On the other hand, at high nicotine concentrations (> 1.0 μM) with consistent cytotoxic effects and appeared to be due to direct cell kill. Nicotine can prevent apoptosis induced by NSCLC. Conclusion: Therefore, the effects on chemotherapeutics by NSCLC malignant cell lines, nicotine in concentrations as low as 1.0 μM decreased. These mechanisms are responsible for the genotoxic effects caused by nicotine. This leads to downstream effects on decreased apoptosis, increased cell proliferation and transformation. The malignant NSCLC cells respond to the treatment with nicotine in lung cancer, the nicotine-mediated induction of growth may provide one of its links to α7nAchR or EGFR.

Blood image intensity has been used to detect erythrocyte sedimentation rate (ESR). However, it does not give an information on biophysical properties of blood sample under continuous ESR. In this study, three physical properties, including, τ₀, ESR_τ, and AI_I, are suggested to quantify mechanical variations of blood under continuous ESR. To demonstrate the proposed method, blood sample is loaded into a driving syringe. The blood flow rate is set in a periodic on–off pattern. Blood sample is then supplied into a capillary chip, and microscopic blood images are captured at specific intervals. Blood shear stress is quantified from the interface of blood stream in the coflowing channel. Both τ₀ and ESR_τ are then obtained by analyzing the blood shear stress. Simultaneously, the AI_I is evaluated by analyzing the image intensity of blood flow. According to the experimental results, the τ₀ exhibits consistent trends with respect to hematocrit as well as diluent. The ESR_τ and AI_I showed a reciprocal relationship each other. Three suggested properties represented substantial differences for suspended blood samples (i.e., hardened red blood cells, different concentration of dextran solution and fibrinogen). In conclusion, the present method can detect variations of blood sample under continuous ESR effectively.

The Doppler band compensated by the keystone transform (KT) is limited. Therefore, it needs to be used in conjunction with the Doppler ambiguity compensation function to correct the range migration (RM) caused by maneuvering targets with Doppler ambiguity. However, the KT implemented by sinc interpolation suffers from significant performance loss at boundaries of compensation Doppler bands. Additionally, in a multi-target scenario, KT implementation methods occupy high complexity when the Doppler range of targets spans over two compensation Doppler bands. To address aforementioned issues, this study presents a variable Doppler starting point keystone transform (VDSPKT) method, where a new form of ambiguity compensation function is constructed, turning the Doppler starting point of the compensation band in KT variable. Firstly, the position of the compensation Doppler band is changed from fixed to adjustable as needed, enhancing the flexibility of KT. Crucially, the connection points of the compensation Doppler bands in sinc interpolation are reset, avoiding the performance loss at their boundaries. Also, the compensation band is adjusted to cover the narrow Doppler frequency range caused by targets, significantly improving the computational efficiency. Finally, the simulation results demonstrate that the proposed approach effectively addresses the performance degradation and high computational complexity of KT in the aforementioned scenarios, resulting in a computational load reduced by approximately 50% compared to traditional methods.

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

We research the interaction between six representative carbon-based nanoparticles (CBNs) and 20 standard amino acids through all-atom molecular dynamics simulations. The six carbon-based nanoparticles are fullerene(C60), CNT55L3, CNT1010L3, CNT1515L3, CNT2020L3, and two-dimensional-graphene(Graphene33). Their curvatures decrease sequentially, and all of CNT are single-walled carbon nanotubes. We have observed that as the curvature of CBNs decreases, the adsorption effect of 20 amino acids with them has an increasing trend. In addition, we also used multi-dimensional clustering to analyze the adsorption effects of 20 amino acids on six carbon-based nanoparticles. We observed that the π-π interaction still plays an extremely important role in the adsorption of amino acids on carbon-based nanoparticles. Individual long-chain amino acids and “Benzene-like” Pro also have a strong adsorption effect with carbon-based nanoparticles.

Searching over a sorted list is a classical problem in computer science. Binary Search takes at most log2n+1 tries to find an item in a sorted list of size n. Interpolation Search achieves an average time complexity of Ο(loglogn) for uniformly distributed data. Hybrids of Binary Search and Interpolation Search are also available to handle data with unknown distributions. This paper analyzes the computation cost of these methods and shows that interpolation can significantly affect their performance — accordingly, a new method, Interpolation Once Binary Search (IOBS), is proposed. The experimental results show that IOBS outperforms the hybrids of Binary Search and Interpolation Search for nonuniformly distributed data.

We report a large third-order nonlinear optical response of palladium diselenide (PdSe₂) films – a two-dimensional (2D) noble metal dichalcogenide material. Both open-aperture (OA) and closed-aperture (CA) Z-scan measurements are performed with a femtosecond pulsed laser at 800 nm to investigate the nonlinear absorption and nonlinear refraction, respectively. In the OA experiment, we observe optical limiting behaviour originating from large two photo absorption (TPA) in the PdSe₂ film of β = 3.26 ×10^-8 m/W. In the CA experiment, we measure a peak-valley response corresponding to a large and negative Kerr nonlinearity of n₂ = -1.33×10^-15 m²/W – two orders of magnitude larger than bulk silicon. We also characterize the variation of n₂ as a function of laser intensity, observing that n₂ decreases in magnitude with incident laser intensity, becoming saturated at n₂ = -9.96×10^-16 m²/W at high intensities. These results verify the large third-order nonlinear optical response of 2D PdSe₂ as well as its strong potential for high performance nonlinear photonic devices.

Considering the spectrum shortage problem of IoT devices, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources, so that IoT devices can access it and meanwhile avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of the PU’s signal detection in IoT devices, the issue about the stopping time and decision cost arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the stopping time and cost function for IoT devices, and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal stopping time problem as a finite horizon problem, and solve the threshold of the optimal decision rule by dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various cost of each observation taken and thresholds.

Background and Objectives: Cancer as the second leading cause of death in the United States poses a huge healthcare burden. Barriers to access to advanced therapies influence the outcome of cancer treatment. In this study, we examined whether insurance types affect the quality of cancer clinical care regarding access to an important monoclonal antibody, ramucirumab. Materials and Methods: Data for 13,340 cancer patients with Purchased or Medicaid insurance from the All of Us Database were collected for this study. The Chi-square test of proportions was employed to determine the significance of patient cohort characteristics and ramucirumab usage between Purchased and Medicaid insurance groups. The independent t-test was utilized to assess the influences of other determinants on insurance types. Results: Cancer patients who are African American, with lower socioeconomic status, or with lower educational attainment are more likely to be insured by Medicaid. Analysis of survey questions demonstrated the relationship between income and education level with insurance type as Medicaid cancer patients were less likely to receive primary care and specialist physician access and more likely to request lower cost medications. In addition, those with Medicaid insurance were identified to have poorer access to expensive therapeutics like ramucirumab compared to those with Purchased insurance.  Conclusions: The inequities of the US healthcare system are observed for cancer patient care; access to physicians and therapeutics are highly varied and dependent on insurance types. Socioeconomic status determines insurance type, which unfortunately generates a significant impact on cancer treatment and disease outcome.

Oleuropein, glycosylated secoiridoid present in olive leaves is known to be an important antioxidant phenolic compound. We studied the antioxidant effect of low doses of oleuropein aglycone (3,4-DHPEA-EA) and oleuropein aglycone peracetylated (3,4-DHPEA-EA(P)) in murine C2C12 myocytes treated with hydrogen peroxide (H2O2). Both compounds were used at a concentration of 10 μM and were able to inhibit cell death induced by the H2O2 treatment, with 3,4-DHPEA-EA(P) being more. Under our experimental conditions, H2O2 efficiently induced the phosphorylated-active form of JNK and of its downstream target c-Jun. We demonstrated, by Western blot analysis, that 3,4-DHPEA-EA(P) was efficient in inhibiting the phospho-active form of JNK. This data suggests that the growth arrest and cell death of C2C12 proceeds via the JNK/c-Jun pathway. Moreover, we demonstrated that 3,4-DHPEA-EA(P) affects the myogenesis of C2C12 cells; because MyoD mRNA levels and the differentiation process are restored with 3,4-DHPEA-EA(P) after treatment. Overall, the results indicate that 3,4-DHPEA-EA(P) prevents ROS-mediated degenerative process in a genomic and epigenomic manner by functioning as an efficient antioxidant.

Oleuropein, glycosylated secoiridoid present in olive leaves is known to be an important antioxidant phenolic compound. We studied the antioxidant effect of low doses of oleuropein aglycone (3,4-DHPEA-EA) and oleuropein aglycone peracetylated (3,4-DHPEA-EA(P)) in murine C2C12 myocytes treated with hydrogen peroxide (H2O2). Both compounds were used at a concentration of 10 μM and were able to inhibit cell death induced by the H2O2 treatment, with 3,4-DHPEA-EA(P) being more. Under our experimental conditions, H2O2 efficiently induced the phosphorylated-active form of JNK and of its downstream target c-Jun. We demonstrated, by Western blot analysis, that 3,4-DHPEA-EA(P) was efficient in inhibiting the phospho-active form of JNK. This data suggests that the growth arrest and cell death of C2C12 proceeds via the JNK/c-Jun pathway. Moreover, we demonstrated that 3,4-DHPEA-EA(P) affects the myogenesis of C2C12 cells; because MyoD mRNA levels and the differentiation process are restored with 3,4-DHPEA-EA(P) after treatment. Overall, the results indicate that 3,4-DHPEA-EA(P) prevents ROS-mediated degenerative process in a genomic and epigenomic manner by functioning as an efficient antioxidant.

A switchable and tunable terahertz (THz) metamaterial based on photosensitive silicon and Vanadium dioxide (VO2) was proposed. By using finite-difference time-domain (FDTD) method, the transmission and reflective properties of the metamaterial were investigated theoretically. The results imply that, the metamaterial can realize a dual electromagnetically induced transparency (EIT) or two narrow-band absorption depending on the temperature of the VO2. Additionally, the magnitude of the EIT and two narrow-band absorption can be tuned by varying the conductivity of photosensitive silicon (PSi) via pumping light. Correspondingly, the slow light effect accompanying the EIT can also be adjusted.

In order to overcome the limitation of the traditional adaptive Unscented Kalman Filtering (UKF) algorithm in noise covariance estimation for statement and measurement, we propose a hybrid adaptive UKF algorithm based on combining Maximum a posteriori (MAP) criterion and Maximum likelihood (ML) criterion, in this paper. First, to prevent the actual noise covariance deviating from the true value which can lead to the state estimation error and arouse the filtering divergence, a real-time covariance matrices estimation algorithm based on hybrid MAP and ML is proposed for obtaining the statement and measurement noises covariance, respectively; and then, a balance equation the two kinds of covariance matrix is structured in this proposed to minimize the statement estimation error. Compared with the UFK based MAP and based ML, the proposed algorithm provides better convergence and stability.

The multidrug resistance transporter NorM is an important drug resistance pump and plays a critical role in multidrug resistance in bacteria and mammals. In this study we carried out molecular dynamics simulation to study the mechanism of Na+ binding and dynamical structures of two long loops in the substrate-releasing process in substrate binding NorM. Our simulation study identified several key residues (D41, E261 D377) along the Na+ binding pathway and a multi-state ion-binding mechanism is proposed based on the simulation study. In this proposed model, the transport of Na+ is a multi-stage process with D41 being the first station for binding to Na+, followed by Na+ binding to the second station E262 and finally to the cation-binding site of E262 and D377. During the transport of Na+, the transmembrane components TM1, TM7 and TM2 are rearranged to facilitate the ion transport as well conformational changes of NorM to a closed state. Further, substrate-bound simulation revealed that Loop3-4 and Loop9-10 control the substrate-releasing process.

Density distribution function of classical statistical mechanics is generally generalized as a product of a general complex function and its complex Hermitian conjugate function, and the average of classical statistical mechanics is generalized as the average of the quantum mechanics. Furthermore, this paper derives three ones of the five axiom presumptions of quantum mechanics, e.g., deduces Schrȍdinger equation by two general ways, makes the three axiom presumptions into three theorems of quantum mechanics, not only solves the crisis to hard understand, but also gets new theories and new discoveries, e.g., this paper solves the crisis of the origin of the wave-particle duality, derives operators, eigenvalues and eigenstates, deduces commutation relations for coordinate and momentum as well as the time and energy, and discovers quantum mechanics is just a generalization ( mechanics ) theory of the complex square root of ( real density function of ) classical statistical mechanics. Quantum mechanics being just a generalization theory of the complex square root of classical statistical mechanics is both new physics and revolutionary discovery, which are affecting people’s deep philosophical thinking for modern physics development, solve all the crisises of quantum mechanics, quantum information and so on, and make quantum mechanics have scientific solid bases being checked and both no basic axiom presumption and no all the quantum strange incomprehensible properties, because classical statistical mechanics and the complex square root of classical statistical mechanics have the scientific solid bases being checked. In addition, this paper discovers the reason no taking the time derivative of space coordinates in Schrȍdinger equation. Therefore, this paper gives solution to the crisis of the first quantization origin, and mainly deduces quantum physics no all the quantum current strange incomprehensible properties.

This study aimed to evaluate a cantilever beam-type piezoelectric energy harvester operating on train-induced vibrations for powering Wireless Sensor Networks (WSNs) used in railway track monitoring systems. The harvester's behaviors under different conditions are simulated in MATLAB using the analytical model. Natural frequency, maximum deflection, and stress were calculated with greater precision using eigenfrequency and stationary analysis using COMSOL Multiphysics. At a base excitation of 2 g and a resonant frequency of 4.38 Hz, the simulated results showed that the developed energy harvester prototype could generate up to 14 V of AC output voltage and 550 mW of output power. These findings highlight the promising potential of the proposed energy harvester for transforming train mechanical energy into electrical power. This energy harvester's viability and dependability for real-world applications in monitoring railway tracks are supported by developed analytical and simulation models.

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

Facing the charging difficulties of free-floating shared electric vehicle and the high cost of mobile charging for single demand, this article proposes a collaborative charging planning method based on the complementary advantages of fixed charging stations and mobile charging vehicles, which can charge shared electric vehicles more efficiently and reduce the charging cost at the same time. A bi-level programming model for fixed and mobile cooperative charging is constructed. The upper level of the model is the minimization model of system charging total cost, seeking the optimal charging scheme and the number of mobile charging vehicles. The lower model is a fixed and mobile cooperative charging path planning model, which calculates the optimal routes for mobile charging vehicles and the shared electric vehicles that need to be transferred to the fixed charging station. The example results show that the cost of the proposed fixed-mobile cooperative charging scheme is reduced by 12.6% compared with the pure fixed charging scheme and 14.9% compared with the pure mobile charging scheme

Manual interpretation of these huge amounts of image volumes are susceptible to inter-reader variability and human error. Thus, accurate automated CAD scheme is highly desirable in clinical pathological diagnosis. In this research, plethora of machine learning paradigms (e.g. feature extraction, dimensionality reduction and supervised classification methods) were explored, evaluated, compared and analyzed to identify the optimal pathway for brain MR images (normal vs neoplastic) binary classification task. External validation dataset was used to test the generalizability of the optimal predictive models implemented. Relevant and informative features were selected to construct cross-validated decision tree and eventually simple rule set was built based on the decision tree. The experimental results show that almost all pattern recognition paradigms achieve high accuracy with careful selection of number of attributes. LDA+ELM with 55 features are the optimal pipelines which achieve perfect classification when training and test data are of same source; and achieving (accuracy=97.5%, AUC=0.989, sensitivity=95% and specificity=100%) under balanced test dataset; (accuracy=99.5%, AUC=0.988, sensitivity=95% and specificity=100%). Cross-validated decision tree model also shows comparable performance: accuracy=98.8%, AUC=99.1%, sensitivity=99.6% and specificity=98.2%. Three highly relevant and robust attributes are visualized and selected for construction of decision tree models and finally a rule sets are read directly off the decision tree. This rule sets can potentially serve as fast and accurate classification algorithm.

Most of existing fuzzy forecasting models partition historical training time series into fuzzy time series and build fuzzy-trend logical relationship groups to generate forecasting rules. The determination process of intervals is complex and uncertainty. In this paper, we present a novel fuzzy forecasting model based on high-order fuzzy-fluctuation trends and the fuzzy-fluctuation logical relationships of the training time series. Firstly, we compare each data with the data of its previous day in historical training time series to generate a new fluctuation trend time series(FTTS). Then, fuzzify the FTTS into fuzzy-fluctuation time series(FFTS) according to the up, equal or down range and orientation of the fluctuations. Since the relationship between historical FFTS and the fluctuation trend of future is nonlinear, Particle Swarm Optimization (PSO) algorithm is employed to estimate the required parameters. Finally, use the acquired parameters to forecast the future fluctuations. In order to compare the performance of the proposed model with that of the other models, we apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) time series datasets. The experimental results and the comparison results show that the proposed method can be successfully applied in stock market forecasting or such kinds of time series. We also apply the proposed method to forecast Shanghai Stock Exchange Composite Index (SHSECI) to verify its effectiveness and universality.

Oleuropein, glycosylated secoiridoid present in the olive leaves, is known as an important antioxidant phenolic compound. We studied the antioxidant effect of low dose of oleuropein aglycone (3,4-DHPEA-EA) and oleuropein aglycone peracetylated (3,4-DHPEA-EA(P)) in murine C2C12 myocytes treated with hydrogen peroxide (H2O2). Both compounds were used at a concentration of 10 μM and were able to inhibit cell death induced by H2O2 treatment, with 3,4-DHPEA-EA(P) being more. Under our experimental conditions H2O2 efficiently induced the phosphorylated-active form of JNK and of its downstream target c-Jun. We demonstrated, by Western blot analysis, that 3,4-DHPEA-EA(P) was efficient in inhibiting the phospho-active form of JNK. This data suggest that growth arrest and cell dead of C2C12 proceeds via the JNK/c-Jun pathway. Moreover, we demonstrated that 3,4-DHPEA-EA(P) affects myogenesis of C2C12 cells; because the MyoD mRNA levels and the differentiation process are restored after treatment with 3,4-DHPEA-EA(P). Overall, the results indicate that 3,4-DHPEA-EA(P) prevents ROS-mediated degenerative process by functioning as an efficient antioxidant.

For a comprehensive exploration of the Bimolecular Fluorescence Complementation (BiFC) approach, we critically assess whether protein pairs establish direct or indirect interactions within this context. Emphasizing the multifaceted nature of protein interactions, this review underscores the imperative of delineating macromolecular complex characteristics across five distinct levels: composition, stoichiometry, copy number, topology, and dynamics. A pivotal discussion revolves around the challenges introduced by the overexpression of target proteins and the potential artificial ramifications of fusion proteins. The significance of stoichiometry in protein interactions is illuminated, with the HOXA9/PBX1 interaction serving as a pertinent case study. The research identifies and elaborates on the inherent limitations of prevailing large-scale BiFC screenings, advocating for the incorporation of rigorous negative controls. A novel proposition is introduced in the form of a high-throughput multicolor BiFC strategy, exemplified using the HOXA9 and PBX1 proteins. The paper culminates with an insightful discourse on the implications of tags within the BiFC system, presenting the TriFC (Tripartite Fluorescence Complementation) assay as a promising alternative.

We study L_2-approximation problems in the weighted Hilbert spaces in the worst case setting. Three interesting weighted Hilbert spaces appear in this paper, whose weights are equipped with two positive parameters $\ga_j$ and $\az_j$ for $j=1,\,2,\dots,\,d$. We consider the worst case error of algorithms that use finitely many arbitrary continuous linear functionals. We discuss the exponential convergence-(t,s)-weak tractability (EC-(t,s)-WT) of these L_2-approximation problems under the absolute or normalized error criterion. In particular, we obtain the sufficient and necessary conditions for EC-(1,1)-WT and EC-(t,1)-WT with t

We investigate \texorpdfstring{$L_2$}{}-approximation problems in the worst case setting in the weighted Hilbert spaces \texorpdfstring{$H(K_{R_{d,\a,\g}})$}{} with weights \texorpdfstring{$R_{d,\a,{\bm \ga}}$}{} under parameters \texorpdfstring{$1\ge \ga_1\ge \ga_2\ge \cdots\ge 0$ and $1<\az_1\le \az_2\le \cdots$}{}. Several interesting weighted Hilbert spaces \texorpdfstring{$H(K_{R_{d,\a,\g}})$}{} appear in this paper. We consider the worst case error of algorithms that use finitely many arbitrary continuous linear functionals. Multivariate approximation; information complexity; tractability; weighted Hilbert spacesWe discuss tractability of \texorpdfstring{$L_2$}{}-approximation problems for the involved Hilbert spaces, which describes how the information complexity depends on \texorpdfstring{$d$}{} and \texorpdfstring{$\va^{-1}$}{}. As a consequence we study the strongly polynomial tractability (SPT), polynomial tractability (PT), weak tractability (WT), and \texorpdfstring{$(t_1,t_2)$}{}-weak tractability (\texorpdfstring{$(t_1,t_2)$}{}-WT) for all \texorpdfstring{$t_1>1$}{} and \texorpdfstring{$t_2>0$}{} in terms of the introduced weights under the absolute error criterion or the normalized error criterion.

The poor conductivity and instability of layered dihydroxides (LDHs) limit their widespread application in oxygen evolution reaction (OER). In this study, the composite electrode of NiMn-LDHs, reduced graphene oxide (rGO) and nickel foam (NF), i.e., NiMn-LDHs/rGO/NF, was prepared by a hydrothermal method. When subjected to oxygen evolution reaction (OER) catalytic performance in a solution of 1 M KOH, the NiMn-LDHs/rGO/NF composite catalyst exhibited an overpotential of only 140 mV at a current density of 10 mA cm-2 and a Tafel slope of 49 mV dec-1, which is not only better than the comparing RuO2/NF catalyst, but also better than most of the Mn-based and the Ni–Fe containing bimetallic OER catalysts reported in the literature. The excellent electrocatalytic performance is ascribed to the efficient integration of ultrathin NiMn-LDHs sheets, thin-layered rGO and NF, contributing a lot to the decrease in charge transfer resistance and the increase in electrochemically active surface area. Moreover, NF plays a role of current collector and a role of rigid support for the NiMn-LDHs/rGO composite, contributing extra conductivity and stability to the NiMn-LDHs/rGO/NF composite electrode.

Using DCC-GARCH and EGARCH model, this paper finds that since 1990, the relationship between crude oil prices and the US dollar index is time-varying, demonstrating a process of “very weak correlation—negative correlation—enhanced negative correlation—weakening negative correlation”, but the existing research does not provide enough reasonable explanation. Therefore, this paper proposed a “key mediating factors” hypothesis which points out that whether there is a common “key mediating factor” is important source of the time-varying relationship between two assets. We argue that market trend and financial market sentiment undertook the role of “key mediating factor” during the period of “2002 to the financial crisis” and “financial crisis to 2013”, while other periods lack the “key mediating factors”.

The Kerr nonlinear optical performance of silicon nanowire waveguides integrated with 2D layered graphene oxide (GO) films is theoretically studied and optimized based on experimentally measured linear and nonlinear optical parameters of the GO films. The strong mode overlap between the silicon nanowires and highly nonlinear GO films yields a significantly enhanced Kerr nonlinearity for the hybrid waveguides. A detailed analysis for the influence of waveguide geometry and GO film thickness on the propagation loss, nonlinear parameter, and nonlinear figure of merit (FOM) is performed. The results show that the effective nonlinear parameter and nonlinear FOM can be increased by up to ≈52 and ≈79 times relative to bare silicon nanowires, respectively. Self-phase modulation (SPM)-induced spectral broadening of optical pulses is used as a benchmark to evaluate the nonlinear performance, examining the trade-off between enhancing Kerr nonlinearity and minimizing loss. By optimizing the device parameters to balance this, a high spectral broadening factor of 27.6 can be achieved ‒ more than 6 times that achieved in previous experiments. Finally, the influence of pulse chirp, material anisotropy, and the interplay between saturable absorption and SPM is also discussed. These results provide useful guidance for optimizing the Kerr nonlinear optical performance of silicon waveguides integrated with 2D layered GO films.

Deep convolutional neural network (CNN) has shown their great advantages in the single image deraining task. However, most existing CNN-based single image deraining methods still suffer from residual rain streaks and details lost. In this paper, we propose a deep neural network including the Multi-scale feature extraction module and the channel attention module, which are embed in the feature extraction sub-network and the rain removal sub-network respectively. In the feature extraction sub-network, the Multi-scale feature extraction module is constructed by a Multi-layer Laplacian pyramid, and is then integrated multi-scale feature maps by a feature fusion module. In the rain removal sub-network, the channel attention module, which assigns different weights to the different channels, is introduced for preserving image details. Experimental results on visually and quantitatively comparison demonstrate that the proposed method performs favorably against other state-of-the-art approaches

Bartonella species, intracellular parasitic zoonotic pathogens, has drawn increasing attention for their diverse host range and associated human diseases. This study investigates Bartonella infection in small mammals in Yunnan Province, China, focusing on tissue tropism. 333 small mammals were sampled from 13 species, 3 orders, 4 families, and 4 genera in Heqing and Gongshan Counties. Conventional PCR and real-time quantitative PCR (qPCR) were utilized for detection and quantification, followed by bioinformatic analysis of obtained DNA sequences. Results show a 31.5% detection rate, varying across species. Notably, Apodemus chevrieri, Eothenomys eleusis, Niviventer fulvescens, Rattus tanezumi, Episoriculus leucops, Anourosorex squamipes, and Ochotona Thibetana exhibited infection rates of 44.4%, 27.7%, 100.0%, 6.3%, 60.0%, 23.5%, and 22.2%, respectively. Genetic analysis identified 30, 10, and 5 strains based on ssrA, rpoB, and gltA genes, with nucleotide identities ranging from 92.1% to 100.0%. Bartonella strains were assigned to B. grahamii, B. rochalimae, B. sendai, B. koshimizu, B. phoceensis, B. taylorii, and a new species identified in the Episoriculus leucops (GS136). Tissue distribution analysis revealed varied copy numbers across different tissues, with the highest load in spleen. These findings underscore Bartonella's diverse species and host range in Yunnan Province, highlighting its broad tissue tropism in small mammals.

Tulou dwellings in Southeast China have captivated global interest due to their distinctive appearance, sustainable construction materials and technologies, and their defensive and collective housing functions. Despite several recognized as World Cultural Heritage sites, the vast majority of tulou buildings are undergoing irreversible decline and destruction, necessitating a comprehensive and systematic study. Taking 83 Tulou buildings in Raoping County, Chaozhou City, Guangdong Province as the research object, this study reconstructs the historical scenes and systematically reveals the emergence, popularity, and consolidation process of tulou dwellings as integrated defensive and residential buildings for ordinary people by conducting a comprehensive analysis of historical documents and local chronicles. Based on an extensive field investigation, the study systematically analyzes the geospatial distribution and the spatial characteristics of Raoping tulou and its residential unit. The results demonstrate the adaptability and flexibility of tulou dwellings, showcasing their developmental process and revealing the inclusive nature of these traditional residences, as well as the initiative of those who reside within them. The research findings contribute to a more dynamic, comprehensive, and authentic understanding of tulou and Chinese traditional residences, providing valuable references for the preservation and sustainable development of tulou architectural heritage.

In order to better realize rural revitalization, this paper analyzes the spatial and temporal char-acteristics and influencing factors of agricultural surface source pollution in the Yangtze River Economic Belt from the three perspectives of government, enterprise and agriculture by using the spatial Durbin model and the dynamic GMM method in the period of 2006-2021, and further re-searches the threshold characteristics of the distortion of the factor market on the agricultural surface source pollution under the different strengths of environmental regulation. The results show that there is a positive spatial correlation between agricultural surface pollution in the Yangtze River Economic Belt, and government environmental regulation, input factor market distortion and labor force transfer all have a significant impact on agricultural surface pollution. Among them, factor market distortion has a significant spatial spillover effect on agricultural surface pollution in the Yangtze River Economic Zone, and has a significant single-threshold ef-fect on environmental regulation. Accordingly, the government should strengthen environmental regulation, continuously improve the agricultural factor market mechanism, and pay attention to the construction of talents to provide support for rural revitalization.

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

In this paper, we propose a partial differential equation model based on phase-field for sentiment analysis in the field of hotel comment texts. The comment texts are converted into word vectors using the Word2Vec tool, and then we utilize the multifractal detrended fluctuation analysis (MF-DFA) model to extract the generalized Hurst exponent of the word vector time series to achieve dimensionality reduction of the word vector data. The dimensionality reduced data is represented in a two-dimensional computational domain, and the modified Allen-Cahn (AC) function is used to evolve the phase values of the data to obtain a stable nonlinear boundary, thereby achieving automatic classification of hotel comment texts. The experimental results show that the proposed method can effectively classify positive and negative samples and achieve excellent results in classification indicators. We compared our proposed classifier with traditional machine learning models and the results indicate that our method possesses a better performance.

With heat treatments to control drywood termites (Blattodea: Kalotermitidae), the presence of heat sinks causes heat to be distributed unevenly throughout the treatment areas. Drywood termites may move to galleries in heat sink areas to avoid exposure to lethal temperatures. Our studies were conducted in Crytotermes brevis-infested condominiums in Honolulu, Hawaii to reflect real-world condominium scenarios; either a standard heat treatment performed by a heat remediation company or an improved heat treatment was used. For improved treatments, heated air was directed into the toe-kick voids of C. brevis infested cabinets to reduce heat sink effects and increase the heat penetration into these difficult-to-heat areas. Eight thermistor sensors placed inside toe-kick voids, treatment zone, embedded inside cabinets’ sidewalls, and in a wooden cube recorded target temperatures of above 46 °C or 50 °C for 120 minutes. A pretreatment and follow-up inspections were performed at 6 months posttreatment to monitor termite inactivity using visual observations and by recording the numbers of spiked peaks on a microwave technology termite detection device (Termatrac). In improved treatment condominiums, significantly higher numbers of spiked peaks were recorded at pretreatment as compared to 6 months posttreatment. Efficacious heat treatment protocols using the improved methods are proposed.

The fluid seepage in local-saturated zone of subgrade promotes the migration of fine particles in the filler, resulting in the change of pore structure and morphology of the filler and the deformation of solid skeleton, which affects the fluid seepage characteristics. Repeatedly, the muddy interlayer, mud pumping and other diseases are finally formed. Based on the theory of two-phase seepage, the theory of porous media seepage, and the principle of effective stress in porous media, a two-phase fluid-solid coupling mathematical model in local-saturated zone of subgrade considering the effect of fine particles migration is established. The mathematical model is numerically calculated with the software COMSOL Multiphysics○R, the two-phase seepage characteristics and the deformation characteristics of the solid skeleton in local-saturated zone of the subgrade are studied. The research results show that due to the continuous erosion and migration of fine particles in local-saturated zone of the subgrade, the volume fraction of fine particles first increases then decreases and finally becomes stable with the increase of time. And the volume fraction of fine particles for the upper part of the subgrade is larger than that for the lower part of the subgrade. The porosity, the velocity of fluid, the velocity of fine particles, and the permeability show a trend of increasing first and then stabilizing with time; the pore water pressure has no significant changes with time. The vertical displacement increase first and then decrease slightly with the increase of time, and finally tend to be stable. For a filler with a larger initial volume fraction of fine particles, the maximum value of the volume fraction of fine particles caused by fluid seepage is larger, and the time required to reach the maximum value is shorter. It can be concluded that in actual engineering, the volume fraction of fine particles in the subgrade filler should be minimized on the premise that the filler gradation meets the requirements of the specification.

The purpose of this study is to examine the relationship between the institutional investors which can affect financial performance for corporate sustainability on the income smoothing. Therefore, this study focus on the connection between the nature of stock rights and income smoothing in China. For this study, hypotheses were established on the relationship each state-controlled companies, income smoothing, and information equilibrium of individual investors, and empirical analysis was conducted through related variables. The analysis results are summarized in three categories as follows. First, this research finds that state-controlled firms (CONTs) prefer income smoothing activities compared to non-state-controlled firms for the long-term sustainable development of firms using data from 2011 to 2019. Second, this study found out that Institutional investors support the behavior of CONTs to smooth their earnings because this behavior is seen as an attempt by CONTs to convey valuable private information to other investors. Third, we was able to discover that institutional investors' monitoring effect is predominantly driven by pressure-resistant institutional investors. This research complements the lack of empirical research on income smoothing and enable to give a guideline that the type of stock rights is a critical key determinant of participation in income smoothing activities for stable growth and sustainability in the future.

Technology development changes society and society demands new and innovative technology development. We analyze technology to understand society and technology itself. Many researches have been introduced in various fields. Most of them were about patent analysis. This is because detailed and accurate results of research and development are patented. In this paper, we study on new patent analysis method based on count data model and Bayesian regression analysis. Using count data model, we analyze the technological keywords extracted from the collected patent documents. We use the posterior distribution of Bayesian statistics to reflect the experience and knowledge of the relevant technological experts in the analysis model. Moreover, we apply the proposed model to finding sustainable technologies. Finding and developing sustainable technologies is an important activity for companies and research institutes to maintain their technological competitiveness. To illustrate how our modeling could be applied to real domain, we carry out a case study using the patent documents related to artificial intelligence.

Our understanding of pull-apart basins and their fault systems has been enhanced by analog experiments and simulations. However, there has been no opportunity to compare the faults that constitute pull-apart basins with surface ruptures during earthquakes. In this study, we investigated the effects of a 2018 earthquake (Mw 7.5) on a pull-apart basin in the Palu-Koro fault system, Sulawesi Island, Indonesia, using geomorphic observations in digital elevation models, optical correlation with pre- and post-earthquake satellite images. A comparison of active fault traces determined by geomorphology with the locations of surface ruptures from the 2018 earthquake shows that some of the boundary faults of the basin are inactive and that active faulting has shifted to basin-shortcut faults and relay ramps. We also report evidence of lateral spreading, in which alluvial fan materials moved around the end of the alluvial fan. These phenomena may provide insights for anticipating the location of future surface ruptures in pull-apart basins.

The dilatometer curves of continuous cooling transformation of 12Mn steel were measured with Formastor-FⅡthermal mechanical simulator．The steel's undercooled austenite phase continuous cooling transformation curves ( CCT curves) were established by means of the dilatometer method and the metallographic-hardness measurement method． The effect of cooling rate on microstructure and hardness of the steel was studied． CCT curve of test steel was simulated by JMatPro. The results show that the Ac1 and Ac3 of the experimental steel are 692 ℃ and 855 ℃ ; the microstructure obtained is made of ferrite，pearlite and bainite．The ferrite transformation and pearlite transformation occur at a slower cooling rate，in which the ferrite is dominant. When the cooling rate is greater than 4.25 ℃ / s bainite transformation happens．As the cooling rate increases，microstructure or grains become finer．The hardness of the tested steel with increasing cooling rate shows a trend of first fast increase and soon decrease．The simulation results are consistent with the measured CCT law. The high temperature mechanical properties of 12mn steel round billet were tested by gleeble-1500d thermal / mechanical simulator. The tensile strength, reduction of area and stress-strain curves of the billet were obtained in the range of 600-1300 ℃.

Thin people who undergo implant insertion into the chest wall face a high risk of implant exposure to the external environment. Five months after an 8-year-old boy underwent implantable cardioverter-defibrillator (ICD) implantation in a subcutaneous pocket in the left anterolateral chest wall to manage long QT syndrome, ICD replacement became necessary owing to exposure risk from distal and lateral thinning of the ICD pocket. Pocket rupture and exposure would increase the risk of infection; therefore, we performed ICD removal and primary pocket closure. Two weeks later, a new suprafascial pocket was created, acellular dermal matrix (ADM) was attached to the inner wall to prevent ICD protrusion, and a new ICD was inserted. One year postoperatively, the ADM was engrafted, and no complications were observed. A thin subcutaneous layer increases the risk of ICD implantation complications. Inner wall strengthening with ADM can help prevent pocket rupture.

Sensory descriptive analysis was used to evaluate the aged Feng-flavored baijiu. The results indicated that there are notable differences in the samples of different ages. The samples with shorter storage times and fresh distilled Baijiu present bran flavor, and fresh green flavor. with the increase of storage time, the fragrance of honey, sweetness, flowers, and aging gradually increases. The samples of Feng-flavored baijiu were dected by Headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC–TOFMS) , in total, 496 sustances were identified in all samples, mainly containing 14 types of substances, such as esters, aldehydes etc., of which 42 substances were found in Feng-flavored baijiu for the first time. Chemometrics was used to analyze the key differential compounds. 143 differential compounds closely related to aging were preliminarily screened, and principal component analysis revealed that these samples were separated by year. 65 differential compounds were selected out by partial least squares discriminant analysis(PLS-DA). Furthermore, 43 key differential compounds were selected from the aged Feng-flavored baijiu combined with variable importance in projection and Pearson correlation coefficients. Partial least squares regression (PLSR) was used to research the correlation of sensory properties and key differential compounds, and the results indicated that most compounds were closely related to the aged Baijiu . This study afford theoretical basis and reference for flavor research of Feng-flavored baijiu.

Lodging is a common problem in maize production that seriously impacts yield, quality, and the capacity for mechanical harvesting. Evaluation of site-specific lodging risks requires establishment of a method for multi-year monitoring. In this study, spectral images collected by the Sentinel-2 satellite were processed to obtain three types of data: gray-level co-occurrence matrix texture (GLCM), vegetation indices (VIs), and spectral reflectance (SR). Lodging classification models were then established with Random Forest (RF) using each of the three data types separately (the GLCM, VI, and SR models) and in combination (SR+VI model, SR+GLCM model, VI+GLCM mod-el, and SR+VI+GLCM model). By gradually removing features with low importance scores from the SR+VI+GLCM model and analyzing the changes in the overall accuracy (OA), the optimal set of predictive variables was identified and used to construct the optimal model. A model built us-ing data from a single timepoint in 2021 was tested on data collected at a similar timepoint in 2019 and vice versa to assess interannual model generalizability. The results of this study demon-strate that for monitoring maize lodging, models constructed with a single feature type, the GLCM model had significantly lower accuracy compared to the VI and SR models. During certain growth stages, the model constructed with combined features had significantly higher accuracy in monitoring maize lodging compared to models constructed with a single feature. During the pro-cess of selecting the optimal predictive variables, it was found that the accuracy of the model did not increase as the number of predictive variables increased. The results show that the positive and negative validation models had an accuracy of 96.55% and 95.18%, with kappa values of 0.93 and 0.83, respectively. This indicates that the model has strong generality for the same repro-ductive stage between years. This study provides a detailed method for large-scale maize lodging monitoring, allowing for identification of optimal planting practices to reduce the probability of lodging and ultimately improving regional maize yield and quality.

Building Information Modeling (BIM) has been one of the overwhelming trends in the worldwide. In Korea, from 2012, BIM application to the public construction projects worth more than $40 million was mandated. However, despite the policy, many public owners have hesitated to apply BIM to their projects. They generally view BIM very complex to manage and difficult to understand. While there have been diverse BIM guides as a reference, most of them have developed from BIM suppliers’ perspective involving certain deficiency in meeting the public owners’ taste. The public owners have addressed the necessity for developing an owner-oriented BIM guide on which they can understand the overall BIM procurement process thereby efficiently preparing their BIM service contracts. The main objective of this study is to develop the structure and contents guidance of the new guide to be developed that follows the public business process and mitigates the deficiency. To meet the research objective, a number of domestic and international BIM guides were analyzed and workshops were operated twice with the 12 BIM experts from the Korean construction industry. As a result of the study, a four-staged guide structure was developed consisting of the BIM service Scoping, Tendering, Executing, and Wrapping-up (STEW) guides.

In mathematics, one always aims to obtain new frameworks from specific ones. This also stratified to the regality of graphs, where one can produce numerous new graphs from a specific set of graphs. In this work we define some classes of pyramid graphs created by a gear graph and we derive straightforward formulas of the complexity of these graphs, using linear algebra matrix analysis techniques and employing knowledges of Chebyshev polynomials.

Synthesis of natural products with complicated architecture often requires segments having the functional groups that can be structurally transformed with the desired stereogenic centers. Bicyclic ?-lactones have a great potential for a suitable segment for natural product synthesis. However, the stereoselective construction of such functionalized bicyclic ?-lactones is not as straightforward as one might expect. On the other hand, the Lewis acid template-mediated Diels-Alder reaction is one of the most powerful and versatile methods for providing bicyclic ?-lactones with high regioselectivity and stereoselectivity. In this reaction, the Lewis acid template activates the dienophile as well as linking the diene and dienophile by a temporary tether. Therefore, Diels-Alder reaction smoothly proceeds in a stereocontrolled manner, allowing a simple access to bicyclic ?-lactone as a valuable building block for the synthesis of complicated natural products. In this review, some highlights of the Lewis acid-mediated Diels-Alder reaction, along with its application to the synthesis of biologically active compounds are discussed.

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

Flammability was evaluated and the results showed the values of critical flux at extinguishment (CFE) as 49.5kW/㎡ on average, total heat release (Qt) as 0.21MJ on average, and peak heat release rate (Qp) as 0.66kW on average, which satisfied all of the thresholds presented by the IMO. Therefore, flame-retardant plywood, of which the flame-retardant performance was evaluated, was determined to be an applicable finishing material that satisfies fire safety standards.

Managing epidemics need to unite each individual of the nations. Lockdown is an essential strategy to fatal and threatening epidemic. All of the citizens should realize that each of people has a responsibility to support the public health crisis. How to organize individual to fight against the epidemic plaque depends each of them. This essay discussed the COVID-19 pandemic relevant self-governance of community from a historical perspective in China. Self-governance of neighborhood committee and community residential office in urban and rural helped to control the COVID-19 pandemic in the communities in China. Co-operation and collective responsibility of citizens and community support is a critical condition to prevent epidemic. The community self-governance can track back Qin Dynasty in China history. It established baojia system to maintain social control for thousand years. Now, the community-based system, baojia system is becoming more autonomous for local citizenship and socialized governance in China. We reviewed a historical pneumonia plaque in North China in 1911. Chinese doctor, Wu Lien-teh (伍連德) confronted the epidemic crisis with many measures such as lockdown, quarantine, the wearing of mask, setup mobile hospitals, travel restriction, the cremation of victims, and border control. Dr. Wu made effort to establish the modern public health service in China. We think that the combination of culture background of China community with modern public healthcare system determinedly played important role to control the COVID-19 pandemic.

This study analyzes the influence of CEO types on corporate governance, focusing on de facto (substantial) CEOs. We examine how substantial CEOs impact ESG activities (Hypothesis 1) and corporate value (Hypothesis 2). Data were collected from KIS-VALUE and DART (Electronic Disclosure System) of the Financial Supervisory Service, defining substantial CEOs as highest remuneration recipients exceeding the representative director of the company pay. Results sup-port Hypothesis 1, showing companies with substantial CEOs are more engaged in ESG activities, potentially to improve public image while concealing self-serving behaviors. Hypothesis 2 is validated, indicating lower corporate value in companies with substantial CEOs due to prioritizing personal interests over long-term profit maximization. Despite limitations in exploring governance relationships beyond remuneration data, the study offers key contributions. It expands research on corporate governance and ESG activities by identifying substantial CEOs through objective remuneration data. It highlights the importance of an independent board for transparent governance and positive corporate value. Lastly, empirical evidence shows the negative impact of misdirected ESG activities on corporate value. By using remuneration as an indicator, this study illuminates substantial CEOs' influence on corporate value and ESG activities, providing insights for future research in corporate governance and ESG.

Porous tantalum (Ta) is a promising biomaterial and has been applied in orthopedics and dentistry for nearly two decades. The high porosity and interconnected pore structure of porous Ta promise fine bone ingrowth and new bone formation within the inner space, which further guarantee rapid osteointegration and bone-implant stability in long term. Porous Ta has high wettability and surface energy that can facilitate adherence, proliferation and mineralization of osteoblasts. Meanwhile, low elastic modulus and high friction coefficient of porous Ta can effectively avoid stress shield effect, minimize marginal bone loss and ensure primary stability. Accordingly, the satisfactory clinical application of porous Ta based implants or prostheses are mainly derived from its excellent biological and mechanical properties. With the advent of additive manufacturing, personalized porous Ta based implants or prostheses have shown their clinical value in the treatment of individual patient who need specially designed implant or prosthesis. In addition, many modification methods have been introduced to enhance the bioactivity and antibacterial property of porous Ta with promising in vitro and in vivo research results. In any case, choosing suitable patients is of great importance to guarantee surgical success after porous Ta insertion.

The photoelectrochemical (PEC) conversion of organic small molecules offers a dual benefit of synthesizing value-added chemicals and concurrently producing hydrogen (H2). Ethylene glycol, with its dual hydroxyl groups, stands out as a versatile organic substrate capable of yielding various C1 and C2 chemicals. In this study, we demonstrate that pH modulation markedly enhances the photocurrent of BiVO4 photoanodes, thus facilitating the efficient oxidation of ethylene glycol while simultaneously generating H2. Our findings reveal that in a pH=1 ethylene glycol solution, the photocurrent density at 1.23 V vs. RHE can attain an impressive 7.1 mA cm−2, significantly surpassing the outputs in neutral and highly alkaline environments. The increase in photocurrent is attributed to the augmented adsorption of ethylene glycol on BiVO4 under acidic conditions, which in turn elevates the activity of the oxidation reaction, culminating in the maximal production of formic acid. This investigation sheds light on the pivotal role of electrolyte pH in the PEC oxidation process and underscores the potential of the PEC strategy for biomass valorization into value-added products alongside H2 fuel generation.

We experimentally demonstrate enhanced spectral broadening of femtosecond optical pulses after propagation through silicon-on-insulator (SOI) nanowire waveguides integrated with two-dimensional (2D) graphene oxide (GO) films. Owing to the strong mode overlap between the SOI nanowires and the GO films with a high Kerr nonlinearity, the self-phase modulation (SPM) process in the hybrid waveguides is significantly enhanced, resulting in greatly improved spectral broadening of the femtosecond optical pulses. A solution-based, transfer-free coating method is used to integrate GO films onto the SOI nanowires with precise control of the film thickness. Detailed SPM measurements using femtosecond optical pulses are carried out, achieving a broadening factor of up to ~4.3 for a device with 0.4-mm-long, 2 layers of GO. By fitting the experimental results with theory, we obtain an improvement in the waveguide nonlinear parameter by a factor of ~3.5 and the effective nonlinear figure of merit (FOM) by a factor of ~3.8, relative to the uncoated waveguide. Finally, we discuss the influence of GO film length on the spectral broadening and compare the nonlinear optical performance of different integrated waveguides coated with GO films. These results confirm the improved nonlinear optical performance for silicon devices integrated with 2D GO films.