Predicting and evaluating the vitality level of public spaces of urban design is crucial before new construction and renewal, especially for developing countries, to avoid failures like "ghost neighborhood" and reduce resource waste. However, existing assessment methods for the urban vitality are either static and ignore changes in the time dimension, or rely on historical big data and are unable to predict unbuilt projects. This study combines previous methods and crowds’ characteristics observation in public space, puts forward the crowd-frequency hypothesis and constructs an algorithm, and establishes a time-dimensional urban vitality dynamic prediction model. Taking the Rundle Mall neighborhood in Adelaide, Australia, as an example, the effec-tiveness of the prediction model was proved through on-site observation sampling comparative verification method. In addition, the decision tree model was used to conduct machine learning on the case data, and a set of algorithm programs were obtained that can directly input some basic information to obtain the urban vitality level (high-medium-low) in a certain period. It can be used as a tool to support the design and decision-making processes of urban planners and government officials, providing a low-cost way to achieve sustainable urban vitality construction of late-developing cities directly.

Aspergillus montevidensis is an important domesticated fungus that has been applied to produce many traditional fermented foods under high osmotic conditions. However, the detailed mechanisms of tolerance to osmotic stress remain largely unknown. Here, we construct a target-deleted strain (ΔLeuRS) of A. montevidensis and found that the ΔLeuRS mutants grew slowly and suppressed the development of the cleistothecium compared to the wide-type strains (WT) under salt-stressed conditions. Furthermore, differentially expressed genes (P<0.0001) governed by LeuRS were involved in salt tolerance, ABC transporter, amino acid metabolism, sugar metabolism, and reproduction process. The ΔLeuRS strains compared to WT strains under short- and long-term salinity stress especially altered accumulation levels of metabolites, such as amino acids and derivatives, carbohydrates, organic acids, and fatty acids. The study provides new insights into the underlying mechanisms of salinity tolerance and lays a foundation for favor improvement of foods fermented with A. montevidensis.

Saliency detection in synthetic aperture radar (SAR) image is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR image. Firstly, we extract four features of SAR image as the input of the MSD model, which include the intensity, orientation, uniqueness and global contrast. Then, the saliency map is generated by the multitask sparsity pursuit (MTSP) which integrates the multiple features collaboratively. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps of the source images, an image fusion method is proposed for the SAR and color optical image fusion. The experimental results of real data show the proposed image fusion method is superior to the presenting methods in terms of several universal quality evaluation indexes, as well as in the visual quality. The salient areas in the SAR image can be highlighted and the spatial and spectral details of color optical image can also be preserved in the fusion result.

China is in the climbing phase of the "Inverted U" environmental Kuznets curve, from excessive environmental consumption to the development stage of governance and protection, and green innovation. It is the most complex period of environmental quality. Environmental and policy regulation are very important. Select panel data of 29 provinces of China (excluding Hong Kong, Macau, Taiwan, Hainan and Tibet) from 2008 to 2017, construct a nonlinear two-threshold regression model, empirically analyse the impact of environmental tax and government innovation subsidies to green processes innovation, and attempt to explore whether the implementation of these two policies at the same time can make enterprises more inclined to green process innovation and whether there is an optimal space for policy implementation. It is proposed that the synergy effect of environmental tax and government innovation subsidy policies on enterprise green process innovation should be fully utilized, and the enterprise green process innovation environment and incentive mechanism should be improved to promote the green transformation and sustainable development of enterprises.

In this paper, we study the well-posedness and asymptotic behaviour of solutions to a laminated beam in thermoelasticity of type III. We first give the well-posedness of the system by using the semigroup method. Then, we show that the system is exponentially stable under the assumption of equal wave speeds. Furthermore, it is proved that the system is lack of exponential stability for case of nonequal wave speeds. In this regard, a polynomial stability result is proved.

The outbreak of recently identified 2019 novel coronavirus (2019-nCOV) infection has become a world-wide health threat. Currently, more information is needed for further understanding the transmission, clinical characteristics, and infection control procedures of 2019-nCOV. Recently, the role of the eye in transmitting 2019-nCOV has been intensively discussed. Previous investigations about other high infectious human COVs, that is, severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV), may provide helpful information. In this review, we describe the genomics and morphology of human CoVs, the epidemiology, systemic and ophthalmic manifestations, mechanisms of human CoVs infection, and infection control procedures. The role of the eye in the transmission of SARS-CoV and 2019-nCOV is discussed. Although the conjunctiva is directly exposed to extraocular pathogens, and the mucosa of ocular surface and upper respiratory tract is connected by nasolacrimal duct and share same entry receptors for some respiratory viruses. The eye is rarely involved in human CoVs infection, conjunctivitis is quite rare in patients with SARS-CoV and 2019-nCoV infection, and COV RNA positive rate by RT-PCR test in tears and conjunctival secretions from patients with SARS-CoV and 2019-nCoV infection is also very low, which imply that the eye is neither a preferred organ of human COVs infection, nor is a preferred gateway of entry for human COVs to infect respiratory tract. However, pathogens exposed to the ocular surface might be transported to nasal and nasopharyngeal mucosa by constant tear rinsing through lacrimal duct, and then cause respiratory tract infection. Considering close doctor-patient contact is quite common in ophthalmic practice which are apt to transmit human COVs by droplets and fomites, hand hygiene and personal protection are still highly recommended for health care workers to avoid hospital-related viral transmission during ophthalmic practice.

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

Fire is a common natural disturbance in forest ecosystems and plays an important role in subsequent vegetation patterns. Based on the spatial sequence method instead of the time successional sequence method, this study selected burned areas in different locations in the Anning River Basin, which contains typical dry valleys. Quadrat surveys and quantitative classification were used to identify the vegetation classification, distribution pattern, and environmental interpretation during the natural restoration process after forest fire. The results showed that: (1) the vegetation community in the early stage of natural recovery after forest fire disturbance could be divided into seven community types, and Quercus guyavaefolia H. Leveille (Qg) was the dominant species in the community; (2) vegetation samples could be divided into five ecological types, and the classification and distribution pattern of community types in this region changed most obviously with altitude; and (3) detrended correspondence analysis could clearly classify vegetation community types, and detrended canonical correspondence analysis could well reveal the relationships between species and environmental factors. This study provides a scientific basis guiding the restoration of ecosystem structural stability and biodiversity in burned areas.

Cellular senescence has recently been recognized as a hallmark of cancer, reflecting its association with aging and inflammation, its role as a response to deregulated proliferation and oncogenic stress, and its induction by cancer therapies such as radiation, chemotherapy, and targeted agents. While such therapy-induced senescence (TIS) has been linked to resistance, recurrence, metastasis and normal tissue toxicity, TIS has the potential to enhance therapy response and stimulate anti-tumor immunity. In this review, we examine the Jekyll and Hyde nature of senescent cells (SnCs), with a particular focus on how their persistence while expressing the senescence-associated secretory phenotype (SASP) modulates the tumor microenvironment through autocrine and paracrine mechanisms. Via the SASP, the formation of SnCs may alternately mediate resistance or response to conventional therapy. Further, toward fulfilling the unmet potential of cancer immunotherapy, we consider how SnCs may influence tumor inflammation and serve as a source of antigen to potentiate anti-tumor immunity. This new view suggests treatment strategies based on inducing TIS to enhance immune checkpoint blockade. Finally, we describe strategies for mitigating the detrimental effects of senescence, such as modulating the SASP or targeting SnC persistence, toward enhancing the benefits of cancer treatment.

The Danxia landform area of Jingbian Wave Valley is located in the central part of Ordos Basin. The near-red Danxia landform consisting of sandstone in this area is a new discovery in geological circles at home and abroad, and its depositional age and genesis remain a hot topic of discussion at present. As the material basis for its development, red sandstone is of great importance to the in-depth study on its formation date and origin. The paper explores the origin, tectonic significance and paleogeographic pattern of the red sandstone through field geological investigation and zircon U-Pb dating analysis of the red sandstone of the Luohe Formation. The results show that the original materials of the red sandstone was formed in three main age intervals, 252~456 Ma, 1657~2084 Ma, and 2129~2538 Ma, and regional tectonothermal events in the origin area during the three periods were recorded, among which the events in Mesoproterozoic and Paleoproterozoic periods were the most active. The comparative analysis of zircon U-Pb age spectra shows that for the sediment of red sandstone, the early origin is near-origin and late origin is distant-origin. The main origin areas in the study area are the Xingmeng orogenic belt, the North China massif and the Alashan massif; the vertical section reflects that the origin area has the strongest erosion and transport in the upper deposition period, the smallest erosion and transport in the middle deposition period, and the moderate erosion and transport in the lower deposition period. With origins system dominated by the northern origins and the paleogeographic pattern of multi-period and cyclonic, the area mainly experienced four tectonic movement cycles, such as Wutai, Lvliang, Caledon and Haixi.

A novel starch stabilized Mg/Al LDHs material (S-LDH) was prepared in a facile approach and its fluoride ion removal performance was developed. Characterization of S-LDH was employed by using XRD, FTIR and particle size distribution. The adsorption property was studied through the assessment of adsorption isotherms, kinetic models, thermal dynamics and pH influence. The result shows that a low loading of starch of 10 mg onto LDH could obviously improve fluoride removal rate. The S-LDH had 3 times higher adsorption capacity to fluoride than that of Mg/Al LDH to fluoride. The particle size was smaller and the particle size distribution was narrower for S-LDH than that for Mg/Al LDH. Langmuir adsorption isotherm model and pseudo-second-order kinetic model fitted well with the experimental data. In thermodynamic parameters, the enthalpy (△H0) value was 35.63 kJ mol-1 and the entropy (△S0) value was 0.0806 kJ mol-1K-1. The values of △G0 were negative, implying the adsorption process is spontaneous. S-LDH reveals stable adsorption property in a wide pH range from 3 to 9. The mechanism for fluoride adsorption on S-LDH included surface adsorption and interaction ion exchange.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

This study aimed to evaluate the effects of a palygorskite-based antibacterial agent (PAA) as an alternative to antibiotics on growth performance, blood parameters, rumen fermentation, and rumen microbiota in sheep. A total of 120 sheep were randomly divided into five groups of six replicates with four sheep each. Sheep were fed a basal diet, an antibiotic diet supplemented with 500 g/t chlortetracycline (CTC), and a basal diet supplemented with 500, 1,000, and 2,000 g/t PAA for 80 d, respectively. Supplementation with 2,000 g/t PAA and 500 g/t CTC increased the average daily gain (ADG) of sheep compared with the control group (P < 0.05). Diets supplemented with 2,000 g/t PAA and 500 g/t CTC reduced (P < 0.05) the feed: gain (F/G ratio) in the overall periods. Dietary Supplementation with 1,000 g/t PAA significantly increased albumin and total protein (P < 0.05). A significant positive correlation was found between growth hormone concentration and PAA supplementation (P < 0.05). In addition, compared to the control group, the CTC group had higher growth hormone concentration and lower lipopolysaccharide concentration (P < 0.05). No dif-ference was observed between the five groups in terms of rumen fermentation characteristics (P > 0.05). At the phylum level, the relative abundance of Proteobacteria was lower in the PAA 2000 and CTC 500 groups than that in the control and PAA 500 groups (P < 0.05). At the genus level, a sig-nificant decrease (P < 0.05) in the relative abundance of RuminococcaceaeUCG-010 was observed in the PAA 1000, PAA 2000, and CTC 500 groups compared with that in the control group. In addition, the relative abundance of Prevotella1 (P < 0.05) was higher in the PAA 2000 group than that in the control group. These findings indicate that dietary supplementation with PAA has ameliorative effects on growth performance, blood parameters, and rumen microbiota, with an optimal dosage of 2,000 g/t for sheep.

The combustion of fuel oil releases sulfur compounds, which react to form sulfur oxides that are harmful to the environment and pose a threat to human health. To mitigate these negative effects, it is crucial to pretreat fuel oil through desulfurization processes. One promising approach involves the use of deep eutectic solvents (DESs), carbon nanotubes (CNTs), and their composites (DESs/CNTs) to effectively reduce sulfur content in fuel oil.However, the conventional methods of DES-based extraction desulfurization and CNT-based adsorption desulfurization suffer from low desulfurization rates. Additionally, the composite material DESs/CNTs is in a semi-solidified form, resulting in high viscosity, complex operation procedures, and increased waste and environmental pollution. To address these challenges, this study focused on the preparation of CNTs/PEG-PVA hydrogel. This hydrogel not only maintains the high desulfurization rate observed in the DESs/CNTs composite material but also possesses several advantages. Firstly, it is convenient to use, offering ease of handling and application. Secondly, it is biodegradable, meaning it can break down naturally over time, reducing its impact on the environment. Lastly, the hydrogel is reusable, allowing for repeated use, thereby minimizing material waste. The desulfurization rate achieved with the CNTs/PEG-PVA hydrogel is remarkably high, reaching up to 99.8%. Moreover, the material utilization rate is close to 100%, meaning that almost all of the hydrogel is utilized in the desulfurization process, reducing unnecessary material consumption. In summary, the innovative CNTs/PEG-PVA hydrogel presents a highly efficient and environmentally friendly solution for desulfurization in fuel oil. Its superior desulfurization rate, alongside its convenience, biodegradability, and reusability, positions it as a promising alternative that not only ensures effective desulfurization but also contributes to sustainable practices in the energy industry.

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

In the process of metal cutting, the anti-wear performance of the tool determines the life of the tool and affects the surface quality of the workpiece. The finite element simulation method can directly show the tool wear state and morphology, but due to the limitations of the simulation time and complex boundary conditions, it has not been commonly used in tool life prediction. Based on this, a tool wear model was established on the platform of a finite element simulation software for the cutting process of titanium alloy TC4 by end milling. The key technique is to embed different types of tool wear models into the finite element model in combination with the consequent development technology. The effectiveness of the tool wear model is validated by comparing the experimental results with the simulation results. At the same time, in order to quickly predict the tool life, an empirical prediction formula of tool wear was established, and the change course of tool wear under time change was obtained.

In light of the current situation where no testing equipment is available for measuring thermal deformation of objects, this paper proposes a novel method for accurate and precise measurement. The method overcomes the limitations of previous approaches that relied on pitch angle. By utilizing the principle of biplane multiple reflections, a bivariate laser spot displacement analysis algorithm is devised to attain highly precise measurements of bivariate angles. Additionally, a temperature gradient comparison algorithm is introduced to calculate the indicator test results under specific temperature conditions. To validate the effectiveness and reliability of this method, a testing system is constructed and utilized. The results demonstrate that the thermal deformation angle change test achieves an impressive accuracy of 0.015″ and a rate of thermal deformation angle change of 0.3247″/°C. These values are in close agreement with the previously simulated analysis result of 0.359″/°C, with only a relative error of 9.55%. Therefore, the test results confirm the efficacy and reliability of this testing method along with the feasibility of the algorithm processing.

The statistical technique, the multiple regression model, is employed to analyze the relationship between the dependent variable and several independent variables. The multicollinearity problem is one of the assumptions in the multiple regression model that occurred in the relationship among independent variables. The ordinal least square is the standard method to evaluate parameters in the regression model, but the multicollinearity problem affects the unstable estimator. The Liu regression is proposed to approximate the Liu estimators based on the Liu parameter to overcome multicollinearity. For this paper, we have proposed the modified Liu parameter to estimate the biasing parameter in scaling options to compare the ordinal least square estimator with two modified Liu parameters and six standard Liu parameters. The performance of the modified Liu parameter is considered with the generating independent variables from the multivariate normal distribution in the Toeplitz correlation pattern as the multicollinearity data, where the dependent variable is obtained from the independent variable multiplied with a coefficient of regression and with the error from the normal distribution. The mean absolute percentage error is computed as an evaluation criterion of estimation. For application, the Hepatitis C patients dataset is a real dataset to investigate the benefit of the modified Liu parameter. Through the simulation and real dataset, it can be seen from the results that the modified Liu parameter outperforms the other Liu parameters and the ordinal least square estimator. It can recommend the user for estimating parameters by using the modified Liu parameter when the independent variable exits the multicollinearity problem.

The plate embedded with acoustic black hole (ABH) indentations is potential for structural vibration and noise control. This work focuses on the mid- and low-frequency performance of plates embedded with the array of ABH for energy focalization and vibration &amp; noise suppression. Plates embedded with two-dimensional ABHs are modelled with detailed Finite Element (FE) models, and the power flow method is introduced to analyze the energy propagation characteristics arising from ABH effect. Then the distribution of average vibration power density along ABH radius is studied. Next, the energy dissipation effects of the plate model embedded with ABH array with two types of damping layers are investigated. Finally, the sound pressure levels of the ABH structure are calculated and discussed. This work is helpful to understand the characteristics of plates embedded with ABH array in reducing vibration and noise radiation. Results show the tremendous potential of ABH array for vibration and noise control.

Consumer preference for products made from transgenic technology has been widely studied, yet few studies exist exploring the factors influencing producers’ adoption of transgenic technology. Based on field surveys in Chinese provinces of Shanxi, Henan and Shandong, we employed a gambling experiment to capture producers’ risk preferences by estimating their risk aversion coefficients. We further estimated producers’ risk amplification and risk perception of GM technology. Using ordered logit model and Poisson model we identified the major factors influencing producers’ adoption of transgenic technology. We found the factors impacted the decision of producers from different regions in different ways. The results showed that over 60% of participants amplified the risk of transgenic crops. When there was potential risk, producers might not be rational even if they had high level of knowledge and cognition about the technology. Our results shed light on government policies aiming to increase the adoption of new technologies by producers.

This experiment aimed to investigate the impact of malic acid (MA) and citric acid (CA) on the nutritional composition, fermentation quality, rumen degradation rate, and microbial diversity of a mixture of apple pomace and corn protein powder during ensiling. The experiment used apple pomace and corn protein powder as raw materials, with four groups: control group (CON), malic acid treatment group (MA, 10g/kg), citric acid treatment group (CA, 10g/kg), and citric acid + malic acid treatment group (MA, 10g/kg + CA, 10g/kg), subjected to mixed ensiling for 60 days. The results indicated: (1) Compared to the CON group, the crude protein content significantly increased in the MA, CA, and MA+CA groups (p < 0.05), with the highest content observed in the MA+CA group. The addition of MA and CA effectively reduced the water-soluble carbohydrate (WSC) content (p < 0.05). Simultaneously, the CA group showed a decreasing trend in NDFom and hemicellulose content (p = 0.08; p = 0.09). (2) Compared to the CON group, the pH significantly decreased in the MA, CA, and MA+CA groups (p < 0.01), and the three treatment groups exhibited a significant increase in lactic acid and acetic acid content (p < 0.01). The quantity of lactic acid bacteria increased significantly (p < 0.01), with the MA+CA group showing a more significant increase than the MA and CA groups (p < 0.05). (3) Compared to the CON group, the in situ dry matter disappearance (ISDMD) significantly increased in the MA, CA, and MA+CA groups (p < 0.05). All three treatment groups showed highly significant differences in in situ crude protein disappearance (ISCPD) compared to the CON group (p < 0.01). (4) Good's Coverage for all experimental groups was greater than 0.99, meeting the conditions for subsequent sequencing. Compared to the CON group, the Shannon index significantly increased in the CA group (P < 0.01), and the Simpson index increased significantly in the MA group (p < 0.05). However, there was no significant difference in the Chao index among the three treatment groups and the CON group (p > 0.05). At the genus level, the abundance of Lentilactobacillus in the MA, CA, and MA+CA groups was significantly higher than in the control group (p < 0.05). PICRUSt prediction results indicated that the metabolic functional microbial groups in the CA and MA treatment groups were significantly higher than in the CON group (p < 0.05), suggesting that the addition of MA or CA could reduce the loss of nutritional components such as protein and carbohydrates in mixed ensilage. In conclusion, the addition of malic acid and citric acid to a mixture of apple pomace and corn protein powder during ensiling reduces nutritional losses, improves fermentation quality and rumen degradation rate, enhances the diversity of the microbial community in ensiled feed, and improves microbial structure. The combined addition of malic acid and citric acid demonstrates a superior effect.

This is a brief critique of the functions—particularly olfactory functions—specified for the “Chemosensory Protein” (CSPs) molecule family. On the basis of these proteins’ presence in the sensory antennal lymph of locusts, odor chemosensory ligand binding functions have been hypothesized. According to this hypothesis, the entire protein molecule superfamily is referred to as “CSPs”. However, new information and developments in the field of CSP molecular research, such as the expression of CSP genes in the gut, brain, fat body, epidermis, and pheromone gland, as well as gene expression profiling from most early developmental stages—that is, CSP expression well in advance of the appearance of chemical sense nerve cells—strongly suggest that the protein molecule has other roles that are unrelated to chemosensing. Moreover, CSPs are found in bacterial microbial prokaryote organisms in addition to insects. Thus, we examine the molecule’s name, definition, RNA editing, protein structure, lipid binding properties, DNA interaction, and evolutionary characteristics in brief before referring to this protein family as “Chemosensory Proteins”. This article tries to compel and discuss the most recent information as a way to rename this protein family. Because of its highly conserved molecular distinctive feature (four adjacent cysteines), we propose renaming “CSPs” as “4CSPs” (4 Cysteines Soluble Proteins).

In this study, we improved the photovoltaic (PV) properties and storage stabilities of inverted perovskite solar cells (PVSCs) based on methylammonium lead iodide (MAPbI3) by employing bathocuproine (BCP)/poly(methyl methacrylate) (PMMA) and BCP/polyvinylpyrrolidone (PVP) as hole-blocking and electron-transporting interfacial layers. The architecture of the PVSCs was indium tin oxide/poly(3,4-ethylenedioxythiophene):polystyrenesulfonate/MAPbI3/[6,6]-phenyl-C61-butyric acid methyl ester/BCP:PMMA or BCP:PVP/Ag. The presence of PMMA and PVP affected the morphological stability of the BCP and MAPbI3 layers. The storage-stability of the BCP/PMMA-based PVSCs was enhanced significantly relative to that of the corresponding unmodified BCP-based PVSC. Moreover, the PV performance of the BCP/PVP-based PVSCs was enhanced when compared with that of the unmodified BCP-based PVSC. Thus, incorporating hydrophobic polymers into BCP-based hole-blocking/electron-transporting interfacial layers can improve the PV performance and storage stability of PVSCs.

The energy E takes the place of the gravitational mass m_G to produce gravity [1]. We wonder whether the inertial mass m_i in the inertial force is also replaced by E. The experiments to measure the inertial force and weight of a carrier are presented. Now we can test the principle of equivalence and study foundations of physics in condensed matter.

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.

Accurate determination of protein localization, levels, or protein-protein interactions is pivotal for the study of their function, and in situ protein labeling via homologous recombination has emerged as a critical tool in many organisms. While this approach has been refined in various model fungi, the study of protein function in most plant pathogens has predominantly relied on ex-situ or overexpression manipulations. To dissect the molecular mechanisms of development and infection for Verticillium dahliae, a formidable plant pathogen responsible for vascular wilt diseases, we have established a robust, homologous recombination-based in situ protein labeling strategy in this organism. Utilizing Agrobacterium tumefaciens-mediated transformation (ATMT), this methodology facilitates the precise tagging of specific proteins at their C-termini with epitopes, such as GFP and Flag, within the native context of V. dahliae. We demonstrate the efficacy of our approach through the in situ labeling of VdCf2 and VdDMM2, followed by subsequent confirmation via subcellular localization and protein-level analyses. Our findings confirm the applicability of homologous recombination for in situ protein labeling in V. dahliae and suggest its potential utility across a broad spectrum of filamentous fungi. This labeling method stands to significantly advance the field of functional genomics in plant pathogenic fungi, offering a versatile and powerful tool for the elucidation of protein function.

MicroRNA plays a critical role in regulating gene expression post-transcriptionally. Variations in mature microRNA sequences, known as isomiRs, arise from imprecise cleavage and nucleotide substitution or addition. These isomiRs can target different mRNAs or compete with their canonical counterparts, thereby expanding the scope of miRNA post-transcriptional regulation. Our study investigated the relationship between cis-acting single nucleotide polymorphisms (SNPs) in precursor miRNA regions and isomiR composition, represented by the ratio of a specific 5’-isomiR subtype to all isomiRs identified for a particular mature miRNA. Significant associations between 95 SNP-isomiR pairs were identified. Of note, rs6505162 was significantly associated with both 5’-extension of hsa-miR-423-3p and 5’-trimming of hsa-miR-423-5p. Comparison of breast cancer and normal samples revealed that expression of both isomiRs was significantly higher in tumors than in normal tissues. This study sheds light on the genetic regulation of isomiR maturation and advances our understanding of post-transcriptional regulation by microRNA.

The South-to-North Water Transfer Jiangsu Water Supply Area (JWSA) is a mega inter-basin water transfer area (water source) that provides water resources from JiangHuai, combines drainage and flooding management, and regulates nearby rivers and lakes. Analyzing the spatiotemporal soil moisture dynamics in the area will inform agricultural drought and flood disaster assessment and early warning studies. Therefore, we evaluated the quality of European Space Agency Climate Change Initiative Soil moisture (ESA CCI_SM) data in the South-North Water Transfer JWSA. Then, we used ensemble empirical modal decomposition, Mann-Kendall tests, and regression analysis to study the spatiotemporal variation in soil moisture for the past 29 years. The CCI _SM data showed a high correlation with local soil measurements at nine sites. We then analyzed the CCI_SM data from three pumping stations (the Gaogang, Hongze, and Liushan stations) in the South-North Water Transfer JWSA. These stations had similar periodic characteristics of soil moisture, with significant periodic fluctuations around 3.1 d. The overall soil moisture at the three typical pumping stations showed an increasing trend. We then investigated whether there were abrupt soil moisture changes at each station. The spatial distribution of soil moisture in the South-North Water Transfer JWSA was characterized by “dry north and wet south”, with higher soil moisture in winter, followed by autumn, and low soil moisture in spring and summer. Although the linear trend of soil moisture in the South-North Water Transfer JWSA varied in significance, the overall soil moisture in the JWSA has increased over the past 29 years. The areas with significantly enhanced soil moisture are mainly distributed in the Yangzhou and Huai'an areas in the southeastern part of the study area. The areas with significantly decreased soil moisture are small in size and mainly located in northern Xuzhou.

The Arbas cashmere goat is a unique biological resource that plays a vital role in livestock husbandry in China. LCDM is a medium with special small molecules (consisting of human LIF, CHIR99021, (S)-(+)-dimethindene maleate, and minocycline hydrochloride) for generation pluripotent stem cells (PSCs) with bidirectional developmental potential in mice, humans, pigs, and bovines. However, there is no report on whether LCDM can support for generation of PSCs with the same ability in Arbas cashmere goats. In this study, we applied LCDM to generation goat induced PSCs (giPSCs) from goat fetal fibroblasts (GFFs) by reprogramming. The derived giPSCs exhibited stem cell morphology, expressing pluripotent markers, and could differentiate into three germ layers. Moreover, the giPSCs differentiated into the trophectoderm lineage by spontaneous and directed differentiation in vitro. The giPSCs contributed to embryonic and extraembryonic tissue in preimplantation blastocysts and postimplantation chimeric embryos. RNA-sequencing analysis showed that the giPSCs were very close to goat embryos at the blastocyst stage and giPSCs have similar properties to typical extended PSCs (EPSCs). The establishment of giPSCs with LCDM provides a new way to generate high quality of PSCs from domestic animals and lays the foundation for basic and applied research in biology and agriculture.

In the evolving landscape of Portfolio Management (PM), the fusion of advanced machine 1 learning techniques with traditional financial methodologies has opened new avenues for innovation. 2 Our study introduces a cutting-edge model combining Deep Reinforcement Learning (DRL) with 3 a Non-stationary Transformer architecture. This model is specifically designed to decode complex 4 patterns in financial time series data, enhancing portfolio management strategies with deeper insights 5 and robustness. It effectively tackles the challenges of data heterogeneity and market uncertainty, 6 key obstacles in PM. Our approach integrates key macroeconomic indicators and targeted news 7 sentiment analysis into its framework, capturing a comprehensive picture of market dynamics. This 8 amalgamation of varied data types addresses the multifaceted nature of financial markets, enhancing 9 the model’s ability to navigate through the complexities of asset management. Rigorous testing 10 demonstrates the model’s efficacy, highlighting the benefits of blending diverse data sources and 11 sophisticated algorithmic approaches in mastering the nuances of PM.12

Thermal safety of lithium-ion traction batteries is a highly concerned issue in the field of electric transportation. The large amount of gas emission during the thermal runaway process of batteries has highly safety hazards such as fire and explosion. Quantitative analysis of emission is one of the important challenges for testing and evaluating battery safety. Focus on quantifying the gas emission through large-scale thermal propagation in battery modules and packs, based on the idea of cell result multiplication, this article conducts thermal runaway emission analysis on single cell and modules, and compares the behavior of thermal runaway and gas emission of the cell and module from the aspects of temperature, pressure, gas composition and battery morphology. The feasibility of the cell result multiplication method was verified from the perspective of experimental data.

Glycosaminoglycans (GAGs) with unique structures from marine animals show intriguing pharmacological activities and negligible biological risks, providing more options for us to explore safer agents. Swim bladder is a tonic food and folk medicine, and its GAGs show good anticoag-ulant activity. In this study, two GAGs SJG-1.0 and GMG-1.0 have been extracted and isolated from the swim bladder of Sphyraena jello and Gadus morhua. The physicochemical properties, pre-cise structural characteristics, and anticoagulant activities of these GAGs were determined. The analysis results of the SJG-1.0 and GMG-1.0 showed that they were chondroitin sulfate (CS)/dermatan sulfate (DS) hybrid chains with molecular weights of 109.32 kDa and 123.13 kDa, respectively. They were mainly composed of the repeating disaccharide unit of -{IdoA-α1,3-GalNAc4S-β1,4-}- (DS-A). The DS-B disaccharide unit of -{IdoA2S-α1,3-GalNAc4S-β1,4-}- also existed in both SJG-1.0 and GMG-1.0. SJG-1.0 had a higher proportion of CS-O disaccharide unit -{-GlcA-β1,3-GalNAc-β1,4-}-, while GMG-1.0 contained higher proportion of CS-E disaccha-ride unit -{-GlcA-β1,3-GalNAc4S6S-β1,4-}-. The disaccharide compositions of the GAGs varied in a species-specific manner. Anticoagulant activity assay revealed that both SJG-1.0 and GMG-1.0 had potent anticoagulant activity, which can significantly prolong activated partial thrombosis time. GMG-1.0 also can prolong the thrombin time. SJG-1.0 showed no intrinsic tenase inhibition ac-tivity, while GMG-1.0 can obviously inhibit intrinsic tenase with EC50 of 58 nM. Their significantly different anticoagulant activities may be due to their different disaccharide structural units and proportions. These findings suggested that the swim bladder CS/DS hybrid chains with well-defined structure may be safer anticoagulants with low bleeding risk.

Digital twin technology, a cutting-edge approach that creates dynamic digital replicas of physical systems, is increasingly integral to various industrial applications. However, the effective deployment of digital twins often faces challenges associated with data availability, quality, and interoperability, which can impede the development and operational efficacy of these virtual counterparts. This paper presents a systematic review of the application of artificial intelligence (AI) in enhancing and managing digital twin technologies across multiple domains such as industry, healthcare, urban planning, business, education, technology, and others. It specifically examines how machine learning models, particularly neural networks and deep generative models, are being employed to optimize the creation, maintenance, and functionality of digital twins. The review explores the role of artificial intelligence in overcoming data-related limitations by providing robust, scalable data solutions for digital twins. Additionally, it addresses critical considerations of real-time data processing and system interoperability within these applications. This survey not only identifies the prevailing challenges and opportunities within this emerging field but also highlights potential future research directions that could further the integration of AI with digital twin technology. Through a detailed exploration of the intersection between AI and digital twins, this paper aims to contribute significantly to the knowledge base and encourage further innovations in this interdisciplinary area.

Litter decomposition is a crucial biochemical process regulated by microbial activities in forest ecosystem. However, the dynamic response of fungal community during litter decomposition to vegetation changes is not well understood. Here, we investigated the litter decomposition rate, extracellular enzyme activities, fungal community, and nutrient cycling-related genes in leaf and twig litters over a three-year decomposition period in a pure Liquidamabar formosana forest and a mixed L. formosana / Pinus thunbergii forest. The result showed that during the three-year decomposition, twig litter decomposed faster in the mixed forest than that in the pure forest. In both leaf litter and twig litter, β-cellobiosidase, N-acetyl-glucosamidase exhibited higher activities in the mixed forest, whereas phosphatase, β-glucosidase and β-xylosidase were higher in the pure forest. The fungal α-diversity were higher in both litters in the pure forest compared to mixed forest, with leaf litter showing higher α-diversity than twig litter. Fungal species richness and α-diversity within leaf litter increased as decomposition progressed. Within leaf litter, Basidiomycota dominated in the mixed forest while Ascomycota dominated in the pure forest. Funguild analysis revealed that symbiotroph and ectomycorrhizal fungi were more abundant in the mixed forest compared to the pure forest. In the third-year decomposition, genes related to phosphorus cycling was most abundant in both forests, with the pure forest having a higher abundance of cex and gcd genes. Fungal community structure, predicted functional structure, and gene composition differed between the two forest types and between the two litter types. Notably, the fungal functional community structure during the first-year decomposition was distinct from that in the subsequent two-year. These findings suggest that both dominant tree species, litter quality and decomposition time significantly influence the litter decomposition by recruiting different fungal community, thereby affecting the entire decomposition process.

This paper describes the formulations for viscoplasticity of metals based on the Chaboche and Delobelle model. The implementations of the viscoplastic models were detailed herein and then implemented via user subroutines for material models (UMAT) in ABAQUS. Two typical metals, i.e., 316 Stainless Steel and Zircaloy-4, were chosen as examples and their viscoplastic behaviors were captured. Numerical simulations are compared to reported experiments to validate the models and the UMAT codes. Typical viscoplastic behaviors of both metals, such as stress relaxation and creep, were captured well against available experiments. We publicize all the data and codes via: https://github.com/XJTU-Zhou-group/ABAQUS_UMAT_316ss_Zr4.

Glycoside Hydrolase 3 (GH3) is a phytohormone-responsive family of genes that has been found in many plant species. It is implicated in the biological activity of indolacetic (IAA) and jasmonic acids (JA), and also affects plant growth and developmental processes and some stresses. In this study, GH3 genes were identified in 48 plants, which belong to algae, moss, fern, gymnosperm and angiosperm. No GH3 representative gene has been found in algae, and our research identified 4 genes in mosses, 19 in ferns, 7 in gymnosperms, and numerous in Angiosperms. The results showed that GH3 genes mainly occur in seed plants. Phylogenetic analysis of all GH3 genes showed three separate clades. Group I was related to JA adenylation, group II was related to IAA adenylation, and group III was separated from group II but the function was not clear. The structure of GH3 protein indicated highly conserved sequence in the plant kingdom. The analysis of JA-adenylation related to gene expression of GH3 in potato (Solanum tuberosum) showed that StGH3.12 highly responded to Methyl Jasmonate (MeJA) treatment. Expression levels of StGH3.1, StGH3.11, and StGH3.12 were high in flower and StGH3.11 expression was also high in stolon. Our research revealed the evolution of the GH3 family, which is useful for studying the precise function about JA-adenylation GH3 genes in S. tuberosum under development and biotic stresses.

Exposure to cadmium sulfate (CdSO4) can lead to neurotoxicity. Nevertheless, the precise molec-ular mechanisms underlying this phenomenon remain unclear, and effective treatment strategies are scarce. This study explored the protective effects of ellagic acid (EA), a natural polyphenolic compound, against CdSO4 exposure-induced neurotoxicity in HT22 cells. Additionally, the inves-tigation sought to elucidate the molecular mechanisms underlying this phenomenon. Our findings demonstrated that exposure of HT22 cells to CdSO4 resulted in apoptosis, which was effectively reversed by EA supplementation. EA supplementation also decreased reactive oxygen species (ROS) and mitochondrial ROS productions, reduced malondialdehyde (MDA) levels, and restored the activities of superoxide dismutase (SOD) and catalase (CAT). Additionally, EA supplementation at 5–20 μM significantly counteracted Cd-induced mitochondrial membrane potential and ATP losses and reduced the ratio of Bax/Bcl-2 and cleaved-caspase-3 protein expression. Furthermore, EA supplementation upregulated Nrf2 and HO-1 protein expression while downregulating the phosphorylation of JNK and p38 proteins. Pharmacological inhibition of JNK partially inhibited CdSO4-induced Nrf2/HO-1 activation and exacerbated its cytotoxicity. In conclusion, our results indicate that EA supplementation provides protection against CdSO4-induced cell apoptosis in HT22 cells by inhibiting oxidative stress and activating the Nrf2 pathway. Activation of the JNK pathway plays a protective role in CdSO4-induced cell apoptosis in HT22 cells.

Three new cembranoids (1–3) and a new casbanoid (4), along with three known analogues (5–7), have been isolated from the soft coral Sinularia nanolobata collected off Ximao Island. The structures including the absolute configurations of new compounds were established by extensive spectro-scopic data analysis, time-dependent density functional theory/electronic circular dichroism (TDDFT-ECD) calculations and the comparison with spectroscopic data of known compounds. In in vitro bioassay, compounds 1 and 5 exhibited moderate cytotoxic activities against human erythroleukemia (HEL) cells line with IC50 values of 37.1 and 42.4 uM, respectively.

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

Type 2 diabetes mellitus(T2DM) is an increasingly prevalent and serious health problem. Its onset is typically associated with metabolic disorders and disturbances in the gut microbiota. Previous studies have reported the anti-T2DM effects of Pueraria thomsonii Radix as a functional food. However, the mechanism of action is still unknown. In this study, the effects of Pueraria thomsonii Radix water extract(PTR) on db/db mice were evaluated by pharmacology, metabolomics, and 16S rRNA gene sequencing. The results showed that PTR could improve the body weight of mice, reduce fasting blood glucose(FBG), urinary glucose(UGLU), homeostasis model assessment insulin resistance(HOMA-IR), urinary albumin/creatinine ratio(UACR), and reduce pancreatic tissue damage. Metabolomics showed that the Model group produced 109 differential metabolites, of which 74 could be regulated by PTR. 16S rRNA sequencing was done in fecal samples and results showed that PTR could reduce the Firmicutes/Bacteroidetes ratio(F/B) associated with obesity and regulate 3 beneficial bacteria and 1 harmful bacteria. In conclusion, the results showed that PTR could ameliorate T2DM symptoms, metabolic disorder, and gut microbiota imbalance of db/db mice, and it was superior to metformin in some aspects. We suggested for the first time that γ-aminobutyric(GABA) may be involved in the regulation of the microbiota-gut-brain axis(MGB) and thus affect the metabolic disorders associated with T2DM. This study will provide a scientific basis for the development of functional food with PTR.

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

The largest gene families in plants were found to be Glutathione transferase (GSTs), which played significant roles in regulating plant growth, development, and stress response. Within the GSTs gene family, members were found to play a crucial role in the low-temperature response process of plants. A comprehensive study identified a total of 70 BraGSTs genes. Cluster analysis results demonstrated that the BraGSTs in Brassica rapa(B.rapa) could be categorized into eight sub-families and were unevenly distributed across ten chromosomes. The 39 BraGSTs genes were found to be organized into 15 tandem gene clusters, with the promoters containing multiple cis-elements associated with low-temperature response. Cold stress was observed to stimulate the expression of 15 genes, with the BraGSTF2 gene exhibiting the highest level of expression, sug-gesting its significant involvement in winter B.rapa's response to low-temperature stress. Sub-cellular localization analysis of the BraGSTF2 protein indicated its potential expression in both the cell membrane and nucleus. The analysis of stress resistance in BraGSTF2 transgenic Arabidopsis thaliana lines emon-strated that the over-expression of this gene resulted in significantly elevated levels of SOD, POD activity, and SP content compared to the wild type following exposure to low temperatures. These levels reached their peak after 24 hours of treatment. Conversely, the MDA content was lower in the transgenic plants compared to the wild type. Additionally, the survival rate of BraGSTF2 transgenic Arabidopsis thaliana was higher than that of the wild type, suggesting that the BraG-STF2 gene may play a crucial role in enhancing the cold stress tolerance of winter B. rapa. This study lay a foundation for further study on the role of BraGSTs gene in the molecular regulation of cold resistance in winter B.rapa.

The gravitational charge should be the energy instead of mass. This modification will lead to some different results and the experiments to test are also presented. Especially, we propose a scheme to achieve the negative energy and gravitational repulsive force in the lab.

Silicon has been proved to be one of the most promising anode materials for the next generation of lithium-ion battery. For the application in batteries, Si anode should have high capacity and must be industrially scalable. In this study, we have designed and synthesised a hollow structure to meet these requirements. All the processes are carried out without special equipment. The Si nanoparticles that are commercially available are used as the core sealed inside TiO₂ shell, with rationally designed void space between the particles and shell. The Si@TiO₂ are characterised using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscope (SEM). The optimised hollow structured silicon nanoparticles, when used as anode in lithium-ion battery, exhibit a high reversible specific capacity over 600 mAhg-1. This excellent electrochemical property of the nanoparticles can be attributed to their optimised phase and unique hollow nanostructure.

Mineral prospectivity mapping (MPM), aiming to outline and prioritize mineral exploration targets, has been spurred by data-driven machine learning algorithms. Supervised data-driven MPM is a typical few-shot task, suffering from the scarcity of labeled data, over-fitting of models and uncertainty of predictions. The main objective of this contribution is to propose a robust framework of few-shot learning (FSL) combining data augmentation and transfer learning, which enables generation of prospectivity models with excellent predictive efficiency and low uncertainty. The mineral systems approach was used to transfer a conceptual mineral system into mappable exploration criteria. Synthetic minority over-sampling technique (SMOTE) was employed to augment and balance the labeled dataset, allowing for model pre-training with a large synthetic training dataset of source domain. The knowledge derived from pre-trained models was then transferred to the target domain by fine-tuning, and the prospectivity model was generated in light of over-fitting and uncertainty assessment. The proposed FSL framework was applied to tungsten prospectivity mapping in southern Jiangxi Province. The results indicate that the SMOTE-ed balanced dataset boosts the classification accuracy in the training process. The FSL models yield an arch-shaped prediction point pattern favorable for focusing potential targets with high probability and low uncertainty. The FSL models achieve a high predictive performance (test AUC=0.9172) and the lowest quantitative over-fitting value, compared to the models derived from the benchmark algorithms of random forest and support vector machine. Four levels of potential targeting zones, considering both predictive efficiency and uncertainty, are extracted from the resulting FSL prospectivity map. The final high-potential and low-risk exploration targets only cover 4.27% of the area, but capture 41.53% known tungsten deposits, achieving superior predictive performance. This study highlights the capability of FSL framework for controlling over-fitting and generating high-confidence exploration targets with low uncertainty.

The quantified residence time distribution (RTD) provides a numerical characterization of mixing in the continue casting tundish, thus allowing the engineer to better understand the metallurgical performance of the reactor. This paper describes a computational fluid dynamic (CFD) modelling study for analyzing the flow pattern and the residence time distribution in a five-strand tundish. Two passive scalar transport equations are applied to separately calculate the E-curve and F-curve in the tundish. The numerical modelling results are compared to the water modelling results for the validation of the mathematical model. The volume fraction of different flow regions (plug, mixed and dead) and the intermixing time during the ladle changeover are calculated to study the effects of the flow control device (FCD) on the tundish performance. The result shows that a combination of the U-baffle with deflector holes and the turbulence inhibitor has three major effects on the flow characteristics in the tundish: i) reduce the extent of the dead volume; ii) evenly distribute the liquid streams to each strand and iii) shorten the intermixing time during the ladle changeover operation.

Fruit cracking or splitting, a severe physiological disease that highly affects appearance and quality, compromise the commodity value of fruit and also causes huge economical losses to the producers of several fleshy fruit crops. The growth-promoting phytohormone gibberellic acid (GA) and growth-inhibiting phytohormone abscisic acid (ABA) antagonistically regulate numerous developmental processes throughout the plant life cycle. Homeostasis of endogenous GA and ABA play a significant role in the normal growth of fruits, and its imbalance may lead to the occurrence of cracking or splitting during the process of fruit growth, development, ripening and postharvest storage. The pathways of GA and ABA metabolism and signaling have been studied widely, and the major components were well characterized, which including the genes encoding major biosynthesis and catabolism enzymes and the key signaling components. Nevertheless, our knowledge of the mechanisms of GA and ABA governing fruit cracking is not comprehensive enough. In this review, we not only focus on the scenarios of effects of endogenous GA and ABA contents in the fruit and exogenous plant growth regulators GA and ABA treatments, but also endeavor to provide some genetic cues on the function of GA and ABA responsible for fruit cracking modulation. Information from this review aims to strengthen the understanding of potential molecular bases underlying GA and ABA in fruit cracking control and provide guidance in breeding of fruit cultivars with cracking-resistant ideotypes, and also make great theoretical significance in guiding the establishment of integrated prevention and control measures to fruit cracking or splitting.

Although crop conversion from annual to perennial crops has been considered as one path towards climate-smart and resource-efficient agriculture, the effects of this conversion on soil multifunctionality and biomass yields remain unclear. Here, we investigated the effects of one annual and three perennial crops (a grass (Lolium perenne), a legume (Medicago sativa), and their mixture) on soil multifunctionality and biomass yield on the Yellow River floodplain. Soil multifunctionality was assessed by the capacity of water regulation and the multifunctionality of carbon (C), nitrogen (N), and phosphorus (P) cycles. Results showed that perennial crops enhanced soil multifunctionality by 207% for L. perenne, 311% for M. sativa, and 438% for L. perenne + M. sativa, compared with annual winter wheat (Triticum aestivum). The effect of perennial crops on soil multifunctionality increased with infiltration rate, dissolved organic C, microbial biomass C, and extracellular enzymatic activities for both C and N acquisition. However, we observed that perennial crops had lower biomass yield than annual crop. Therefore, the transition of agricultural landscapes to perennials needs to take into account the balance between environmental protection and food security, as well as environmental heterogeneity, to promote sustainable agricultural development.

The need for cross-modal retrieval (CMR) among users is growing because of the swift advancements in computer vision and natural language processing. Promoting home operating systems is greatly aided by the openKylin home operating system. It is focused on enhancing the functionality of the operating system with safe and dependable operating technologies. Practical implications abound for integrating computer vision research into home operating systems. A multimodal retrieval approach based on openKylin is presented to improve the usability of text search graphs, audio, and video. The overview of pertinent domestic and international research is the main topic of this article. This technological advancement. It then offers details on the design, implementation procedure, and final implementation outcomes for demonstration. The works of natural operations show that this strategy has excellent accuracy and performance.

Static voltage stability has become one of the significant risks faced by large-scale renewable energy integration. However, traditional methods for static voltage stability analysis are often overly complex. This paper constructs an equivalent impedance model for renewable energy integrated distribution power systems, proposing a static voltage analysis method for renewable energy integrated distribution power systems based on impedance model index. This method has been verified to be applicable not only to renewable energy single-infeed system but also to multi-infeed system. Furthermore, an analysis is conducted on the influence of the integration capacity, location of renewable energy, and the topology of networks on impedance model index, indicating that a higher impedance model index corresponds to greater static voltage stability margins in the system. Hence, during the planning of renewable energy integration, the plan with the highest impedance model index should be selected. Finally, the accuracy of the analysis methods and conclusions in this paper was validated based on the IEEE 14-node system.

To understand the molecular mechanism underlying yellowing in pineapples during ripening, coupled with alterations in fruit quality, comprehensive metabolome and transcriptome investigations were carried out. These investigations were conducted using the pulp samples collected at three distinct stages of maturity: young fruit (YF), mature fruit (MF), and fully mature fruit (FMF). This study revealed a noteworthy increase in the levels of total phenols and flavones, coupled with a concurrent decline in lignin and total acid content, as the fruit transitioned from YF to FMF. Furthermore, the analysis yielded 167 differentially accumulated metabolites (DAMs) and 2194 differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes enrichment analysis based on DAMs and DEGs revealed that the biosynthesis of plant secondary metabolites, particularly the flavonol, flavonoid, and phenypropanoid pathways, plays a pivotal role in fruit yellowing. Additionally, a comprehensive regulatory network encompassing genes that contribute to metabolisms of flavones, flavonols, lignin, and organic acids was proposed. This network sheds light on the intricate processes that underlies fruit yellowing and quality alterations. These findings enhance our understanding of the regulatory pathways governing pineapple ripening and offer valuable scientific insight into the molecular breeding of pineapples.

After the end of colonial rule in 1997, the Hong Kong education system has been experiencing a policy reform on Senior Secondary Education (NSS) Curriculum commenced in September 2009 aiming to educate students as globalized Hong Kong citizens for the Western. Although previous scholars argued that it is hard to differentiate between domestic values and the Western values in account of curriculum development (Sewpaul, 2007), this study demonstrates an analysis using the dichotomy to investigate how local curriculum, especially in the post-colonial areas, embrace both the Western values and domestic values. Using content analysis on the NSS curriculum guides, this article evaluates the influence of the Western values and Chinese values in the NSS curriculum through investigating: (1) how the Western values and Chinese values was incorporated into the curriculum throughout its development (2) why some values are more significantly highlighted in the curriculum guide. Findings include that more Chinese values are involved in the curriculum documents. This may be because of the upholding of domestic values as a post-colonial city. The Western values which are academically related are greatly incorporated into the local curriculum.

Clarifying the distribution of temperature and pressure in the wellbore and cavern during hydrogen injection and extraction is crucial for quantitatively assessing cavern stability and wellbore integrity. This paper establishes an integrated flow and heat transfer model for the cavern and wellbore during hydrogen injection and production, analyzing the variations in temperature and pressure in both the wellbore and the cavern. The specific conclusions are as follows. (1) The temperature and pressure parameters of hydrogen and natural gas within the chamber and wellbore were compared. Under identical injection and production conditions, the temperature of hydrogen in the chamber was 10°C higher than that of natural gas, and 16°C higher in the wellbore. The pressure of hydrogen in the chamber was 2.9 MPa greater than that of natural gas, and 2.6 MPa higher in the wellbore. (2) A comparative analysis was conducted on the impact of surrounding rock’s horizontal and numerical distance on temperature during hydrogen and natural gas injection processes. As the distance from the cavity increases, from 5 to 15 meters, the temperature fluctuation in the surrounding rock diminishes progressively, with the temperature effect in the hydrogen storage chamber extending at least 10 meters. (3) The influence of rock thermal conductivity parameters on temperature during the processes of hydrogen injection and natural gas extraction is compared. The better the thermal conductivity, the deeper the thermal effects penetrate the rock layers, with the specific heat capacity having the most significant impact.

Snakes are a vital component of wildlife resources and are widely distributed across the globe. Bungarus multicinctus, a highly venomous snake, is found in central and southern China. B. multicinctus is a highly venomous snake and is distributed in central and southern China. Snakes are an ancient group of reptiles, and their genome resources can provide important clues for understanding the evolutionary history of reptiles. Meanwhile, genomic resources play a crucial role in comprehending the evolution of species. So far, the genomic resources of snakes are a rarity. In 2021, a snake sample was collected from Beiliu Longgukeng, Guangxi, which was identified as B. multicinctus through morphological identification. In this study, we present a highly contiguous genome of B. multicinctus with a size of 1.51 Gb. The genome contains a repeat content of 40.15%, with a total length exceeding 620 Mb. Additionally, we annotated a total of 24,869 functional genes. This research is of great significance for comprehending the evolution of B. multicinctus and provides a genomic basis for the genes involved in venom gland function.

Circular RNAs (circRNAs) served as covalently closed single-stranded RNAs have been proposed to influence plant development and stress resistance. Grapevine is the most economically valuable fruit crops cultivated worldwide and threaten by various abiotic stresses. Herein, we reported that a circRNA (Vv-circPTCD1) processed from the second exon of a pentatricopeptide repeat family gene PTCD1 was preferentially expressed in leaves and responded to salt and drought but not heat stress in grapevine. Additionally, the second exon sequence of PTCD1 was highly conserved but the biogenesis of Vv-circPTCD1 is species-dependent in plants. It was further found that the overexpressed Vv-circPTCD1 can slightly decreased abundance of the cognate host gene and the neighboring genes were barely affected in grapevine callus. Furthermore, we also successfully overexpressed the Vv-circPTCD1, and found that the Vv-circPTCD1 deteriorated the growth during heat, salt, and drought stresses in Arabidopsis. However, the biological effects on grapevine callus were not always consistent with that of Arabidopsis. Interestingly, we found that the transgenic plants of linear counterpart sequence also conferred the same phenotypes as that of circRNA during the three stress conditions, no matter what species. Those results imply that although the sequences are conserved, the biogenesis and functions of Vv-circPTCD1 are species-dependent. Our results indicate that the plant circRNA function investigation should be conducted in homologous species, which support valuable reference for further plant circRNA studies.

Cisplatin (CDDP), an important chemotherapeutic agent, could result in potential hepatotoxicity, but the precious molecular mechanisms remain unclear. In this study, the protective effect of ellagic acid (EA) on CDDP exposure-induced hepatotoxicity and underlying molecular mechanisms were investigated using a mouse model. Mice were randomly divided into control, CDDP model, EA100 (i.e., EA 100 mg/kg/day), and CDDP plus EA 25, 50, and 100 mg/kg/day. Mice in all CDDP-treated groups were intraperitoneally injected with CDDP 20 mg/kg/day for 2 days. In all EA co-treatments, mice were orally administrated with EA for 7 days. Our results found that, compared to the control group, CDDP treatment resulted in liver dysfunction, oxidative stress, and hepatocyte necrosis, which are effectively revised by EA supplementation in a dose-dependent manner. Meanwhile, EA supplementation inhibited CDDP-induced the elevation of caspases-9 and -3 activities in the liver tissues of mice. Furthermore, EA supplementation significantly downregulated CDDP exposure-induced the increases of NF-κB, IL-1β, TNF-α, and IL-6 proteins and mRNAs, while further upregulated the expression of Nrf2, and HO-1 proteins and mRNAs. Taken together, our results reveal that EA supplementation could ameliorate CCDP-induced liver injury in mice via the opposite regulation of Nrf2/HO-1 and NF-kB pathways.

Photoacoustic imaging (PAI) is a cutting-edge biomedical imaging modality, providing detailed anatomical and functional information about the area beneath the skin surface. Its light energy deposition is such that PAI typically provides clear images of the skin with high signal-to-noise ratios. Specifically, the rich optical contrast of PAI allows biological information related to lesion growth, malignancy, treatment response, and prognosis to be seen. Given its significant advantages and emerging role in imaging skin lesions, we summarize and comment on representative studies of skin PAI, such as the guidance of skin cancer biopsies and surgical excisions, and the accurate diagnosis of psoriasis. We conclude with our insights about the clinical significance of skin PAI, showing how its use to identify biological characteristics in lesion microenvironments allows early diagnosis and prognosis of disease.

This is a brief critique of the functions—particularly olfactory functions—specified for the “Chemosensory Protein” (CSPs) molecule family. On the basis of these proteins’ presence in the sensory antennal lymph of locusts, odor chemosensory ligand binding functions have been hypothesized. According to this hypothesis, the entire protein molecule superfamily is referred to as “CSPs”. However, new information and developments in the field of CSP molecular research, such as the expression of CSP genes in the gut, brain, fat body, wings, epidermis, and pheromone gland, as well as gene expression profiling from most early developmental stages—that is, CSP expression well in advance of the appearance of chemical sense nerve cells—strongly suggest that the protein molecule has other roles that are unrelated to chemosensing. Moreover, CSPs are found in bacterial microbial prokaryote organisms in addition to insects and all other arthropods. Thus, we examine the molecule’s name, definition, RNA editing, protein structure, lipid binding properties, DNA interaction, and evolutionary characteristics in brief before referring to this protein family as “Chemosensory Proteins”. As a means of renaming this protein family, this review article discusses the latest findings (“CSP” is attached to the tail of bigger intracellular proteins) and attempts to compel all the data. Because of its highly conserved molecular distinctive feature (four adjacent cysteines), we propose renaming “CSPs” as “4CSPs” (4 Cysteines Soluble Proteins) and use at least for abbreviations for distinctive animal proteins the common peptide 5-letter code, such as “Bommo-4CSPs”.

It is imperative to conduct experimental studies on the seepage behavior of gas-bearing coal under cyclic dynamic loading conditions. This paper focuses on the evolution of coal permeability under the combined effects of dynamic loading, static loading, and gas adsorption. The principal conclusions are as follows. (1) As the frequency and amplitude of dynamic loading increase, the development of pore and fissure structures within the coal body becomes increasingly pronounced during dynamic loading cycles, resulting in a gradual rise in permeability. Notably, as the coal approaches its yielding stage, the permeability can increase by up to 47%. (2) The permeability curve is divided into four regions: the compaction reduction zone, the oscillation zone, the gradual recovery zone, and the abrupt increase zone of failure. Ultimately, in the failure phase, the permeability surges dramatically, potentially reaching 4 to 5 times the initial permeability. (3) When the static load stage is constant, the rate of change in permeability of the coal under dynamic loading decreases with increasing adsorption amount. When the adsorption amount is constant, the rate of change in permeability of the coal under dynamic loading increases with the increase in static load stress stage, with the maximum increase reaching 75.2%. It can be concluded from the rate of change in permeability and the dynamic loading sensitivity coefficient that the permeability of the coal is highly sensitive to cyclic dynamic loading, with increased sensitivity associated with larger static load stages and decreased sensitivity with greater adsorption amounts.

In recent years, there has been significant growth in the ubiquity and popularity of three dimensional(3D) point clouds, with an increasing focus on the classification of 3D point clouds. To extract richer features from point clouds, many researchers have turned their attention to various point set regions and channels within irregular point clouds. However, this approach has limited capability in attending to crucial regions of interest in 3D point clouds and may overlook valuable information from neighboring features during feature aggregation. Therefore, this paper proposes a novel 3D point cloud classification method based on global attention and adaptive graph convolution. The method consists of two main branches: the first branch com-putes attention masks for each point, while the second branch employs adaptive graph convolu-tion to extract global features from the point set. It dynamically learns features based on point interactions, generating adaptive kernels to effectively and precisely capture diverse relationships among points from different semantic parts. Experimental results demonstrate that the proposed model achieves 93.8% in overall accuracy and 90.8% in average accuracy on the ModeNet40 dataset.

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

Animal personalities play a crucial role in invasion dynamics during alien species invasions. The behavioral strategies adopted by native species varied among personalities when facing an invasion by alien species, just as the invasive species exhibited variations in behavior strategies across different personalities during the invasion process. However, the effects of personality interactions between native species and invasive species on behavior and growth are rarely illustrated. We used the globally invasive freshwater turtle Trachemys scripta elegans and the native freshwater turtle Mauremys reevesii to investigate how the personality combinations of native and invasive turtles would impact the foraging strategy and growth of both species. We found that M. reevesii exhibited bolder and more exploratory personalities than T. scripta elegans. The foraging strategy of M. reevesii was mainly affected by the personality of T. scripta elegans, while the foraging strategy of T. scripta elegans was influenced by both their own personality and M. reevesii's personality. In addition, we did not found that the personality combination would affect the growth of either T. scripta elegans or M. reevesii. Difference in foraging strategy may be due to the competitive advantage of invasive species and variations in the exploration-exploitation foraging strategy among different personalities. Overall, our results reveal the mechanisms of personality interaction effects on the foraging behavior of both native and invasive species during alien species invasion and provide empirical evidence to help understand the effects of personality in invasion dynamics.

As the global population rapidly ages with longer life expectancy and declining birth rates, the need for healthcare services and caregivers for older adults is increasing. Current research envisions addressing this shortage by introducing domestic service robots to assist with daily activities. The successful integration of robots as domestic service providers in our lives requires them to possess efficient manipulation capabilities, provide effective physical assistance, and have adaptive control frameworks that enable them to develop social understanding during human-robot interaction. In this context, human factors, especially quantifiable ones, represent a necessary component. The objective of this paper is to conduct an unbiased review encompassing studies on human factors studied in research involving physical interactions and strong manipulation capabilities. We identified the prevalent human factors in physical human-robot interaction (pHRI), noted the factors typically addressed together and determined the frequently utilized assessment approaches. Additionally, we gathered and categorized proposed quantification approaches based on measurable data for each human factor. We also formed a map of common contexts and applications addressed in pHRI for a comprehensive understanding and easier navigation of the field. We found out that most of the studies in direct pHRI (when there is direct physical contact) focus on social behaviors with belief being the most commonly addressed human factor type. Task collaboration is moderately investigated, while physical assistance is rarely studied. In contrast, indirect pHRI (when the physical contact is mediated via a third item) studies often involve industrial settings, with physical ergonomics being the most frequently investigated human factor. More research is needed on human factors in direct and indirect physical assistance applications, including studies that combine physical social behaviors with physical assistance tasks. We also found that while the predominant approach in most studies involves the use of questionnaires as the main method of quantification, there is a recent trend that seeks to address quantification approaches based on measurable data.

In this paper, a new approach is proposed for designing ultra-low-power FFT (Fast Fourier Transform) system suitable for use in energy harvesting powered sensors. Bit-serial architecture is adopted to reduce the power consumption of butterfly operation. Simulation results show that, compared with state-of-the-art bit-serial and conventional parallel processors, the proposed technique is superior in terms of silicon area, power consumption, dynamic energy use due to variable precision arithmetic. A sample design of a 64-point FFT shows that the implementation can save about 40% area and 36% leakage power compared with a conventional parallel counterpart, accordingly achieving significant power benefits at a low sample rate and low voltage domain. The dynamic variation of the arithmetic precision can be achieved through a simple modification of the controller with hardware area overhead of 10% gate count.

In recent years, the High Dynamic Range (HDR) image has gained widespread popularity 1 across various domains such as security, multimedia, and biomedical fields, owing to its ability 2 to deliver an authentic visual experience. However, the extensive dynamic range and rich detail 3 in HDR images present challenges in assessing their quality. Therefore, current efforts involve 4 constructing subjective databases and proposing objective quality assessment metrics to achieve 5 efficient HDR Image Quality Assessment (IQA). Recognizing the absence of a systematic overview 6 of these approaches, this paper provides a comprehensive survey of existing HDR IQA methods. 7 Furthermore, this paper aims to serve as a valuable resource for researchers by discussing the 8 limitations of current methodologies and potential research directions in the future.

Smart air filters are beneficial to provide highly efficient particle removal, treat multiple contaminants simultaneously and conserve energy during air filtration processes. Herein, a type of self-supporting smart air filter (SSSAF) was fabricated by sandwiching the VOC-responsive PZT/PVDF electrospun membrane with two metal mesh electrodes. Besides the high filtration efficiency for sub-micron particles, the SSSAF showed good responses to pressure drop in the range of 0 to 500 Pa via the electroactivity of PZT/PVDF membrane. In addition, the SSSAF achieved VOC sensing function via the swelling properties of PZT/PVDF membrane in organic vapors, demonstrated by its signal to 50 to 200 ppm ethanol gases. The SSSAF based nanogenerator was employed to harvest wind energy, which was further applied to inhibit bacterial growth without the need of additional power input. The results provide new insight into development of all-in-one smart air filters.

Currently, efficient utilization of low-grade thermal energy is a great challenge. Thermoelectricity is an extremely promising method of generating electrical energy from temperature differences. As a promising energy conversion technology, thermo-electrochemical cells (TECs) have attracted much attention in recent years for their ability to convert thermal energy directly into electricity with high thermal power. Within TECs, anions and cations gain and lose electrons, respectively at the electrodes using the potential difference between the hot and cold terminals of the electrodes by redox couples. Additionally, the anions and cations therein are constantly circulating and mobile via concentration diffusion and thermal diffusion, providing an uninterrupted supply of power to the exterior. This review article focuses mainly on the operation of TECs, recent ad-vances in redox couples, electrolytes, and electrodes. The outlook for optimization strategies re-garding TECs is also presented in this paper.

The exploration and identification of targets and pathways for Atopic dermatitis (AD) treatment and diagnosis are critical for AD control. The conventional target exploration approach such as the literature review is not satisfying in terms of efficiency and accuracy. Recently, the bioinformatic approach is drawing attention for its unique advantage of high-volume data analysis for target and pathway exploration; Open Targets Platform is the targets source for this study to extract top 200 high-rank proteins from 3122 AD associated proteins. STRING, Cytoscape, CytoHubba, ClueGo, and CluePedia function had been applied for data analysis. The KEGG Mapper search & colour pathway was the pathway map resource for identified pathways; 23 key hub genes (VDR, KIT, BCL2L11, NFKBIA, KRAS, IL13, JAK2, STAT3, IL21, IL4R, REL, PDGFRB, FOXP3, RARA, RELB, EGFR, IL21R, MYC, CREBBP, NR3C1, IL2, JAK1, and KITLG). Additionally, 8 correlated pathways and the biological process had been identified; Through this study, a viable approach for target and pathway exploration had been presented. The identified AD targets and pathways will be tested for upcoming research for traditional Chinese medicinal herb interactions

Appetitive traits have been associated with eating behaviors and weight in youth. However, the relationships among adults have received less attention. In this study, we measured appetitive traits among 520 female college students from a University in eastern Chinese using the Chinese translated Adults Eating Behavior Questionnaire (C-AEBQ) and found that two food approach traits (food enjoyment and emotional over-eating) were positively while two food avoidance traits (slowness in eating and satiety responsiveness) were negatively associated with BMI. Individual trait was differentially associated with eating behaviors. Specifically, a positive correlation was found between food responsiveness and higher frequency of selecting delivery food, spicy food, and sugared beverage; conversely, satiety responsiveness was associated with higher frequency of skipping meals. Using latent profile analysis, participants were classified into four appetitive patterns: food approacher, food approacher with emotional under-eating, food avoider, and food avoider with emotional over-eating. Food avoiders had significant lower BMI and higher proportion of underweight than other three patterns. Compared to food approacher, food avoiders had higher frequency of skipping breakfast, and food avoiders with emotional over-eating had higher frequency of skipping both breakfast and lunch. No significant differences were observed in food choice and dieting behavior among four appetitive patterns. The findings suggested a correlation between an individual’s appetitive pattern and eating behaviors among female college students, those with food avoidance patterns are more likely to have irregular meals, which may contribute to their low BMI. The findings provide valuable insights for female college students to cultivate a healthy eating behavior and sustain a healthy body weight.

The data assimilation method to improve sea fog forecast over the Yellow Sea is usually three-dimensional variational assimilation (3DVAR), whereas ensemble Kalman filter (EnKF) has not yet been applied on this weather phenomenon. In this paper, two sea fog cases over the Yellow sea, one spread widely and the other spread narrowly along the coastal area, are studied in detail by a series of numerical experiments with 3DVAR and EnKF based on the Grid-point Statistical Interpolation (GSI) system and the Weather Research and Forecasting (WRF) model. The results show that the assimilation effect of EnKF outperforms that of 3DVAR: for the widespread-fog case, the probability of detection and equitable threat scores of the forecasted sea fog area get improved respectively by ~57.9% and ~55.5%; the sea fog of the other case completely mis-forecasted by 3DVAR is produced successfully by EnKF. These improvements of EnKF relative to 3DVAR are benefited from its flow-dependent background error, resulting in more realistic depiction of sea surface wind for the widespread-fog case and better moisture distribution for the other case in the initial conditions. More importantly, the correlation between temperature and humidity in the background error of EnKF plays a vital role in the response of moisture to the assimilation of temperature, which leads to a great improvement on the initial moisture conditions for sea fog forecast.

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

Wind power generation is one of the mainstream renewable energy resources. Voltage stability is as important as the frequency stability of a power system with a high penetration of wind power generation. The advantages of high-voltage direct current (HVDC) transmission systems become more significant with the increase of both installed capacity and transmission distance in offshore wind farms. Therefore, this study discusses about various voltage control methods for wind turbines and HVDC transmission systems. First, various voltage control methods of a wind farm were introduced, and they include QV control and voltage droop control. The reactive power of a wind turbine varies with active power, while the active power from each wind turbine may be different owing to wake effects. Thus, QV and voltage droop control with varying gain values were also discussed in this paper. Next, the voltage control methods for a HVDC transmission system, such as power factor control, voltage control, and Vac-Q control, are also summarized and tested in this study. When a three-phase short circuit fault occurs or a suddan reactive power load increases, the system voltage would drop immediately. Thus, various voltage control methods for wind turbines or HVDC can make the system's transient response more stable. Therefore, this study implemented the simulation scenarios, including a three-phase short circuit fault at the point of common coupling (PCC) or a sudden increase of reactive power load, and adopted various voltage control methods, which aims to verify whether additional voltage control methods are effective to improve the performance of transient voltage.

The merge areas of freeway work zones include relatively significant safety hazards that have continuously led to urgent safety issues to be solved by the management departments. In order to make up for the cumbersome process of independent identification of rear-end collision and lane change collision on complex road sections, an appropriate identification method of traffic conflicts in the merge area of freeway work zone was explored, this study collected vehicle running tracking data from the merge areas of multiple work zones, using an unmanned aerial vehicle video technique. Based on an inter-frame difference method and the principle of a spatio-temporal context visual tracking algorithm, the vehicles were detected and tracked, and the coordinate data of the vehicles in continuous motion were parsed using MATLAB extension tools. Based on the behavior characteristics of vehicle conflict avoidance, a new identification method for evading severe traffic conflicts is proposed according to the initial velocity, acceleration and accident rate of section traffic. Then, a statistical analysis was performed on the spatial distribution characteristics of the traffic conflicts in typical merge areas. The impacts of the road conditions in work zones, vehicle factors, and traffic flow factors on the traffic conflicts were analyzed. A binomial logistic model was established to identify the main influencing factors. The results show that in the merge area of the freeway work zone, there are serious traffic conflicts between vehicles in the following two situations: (Ⅰ) v∈[7,13.5] m/s and a∈[-3.96,-0.65]m/s2; and (Ⅱ) v∈[13.5,24.3] m/s, and a∈[-3.96,-1.57] m/s2. The probabilities of serious traffic conflicts in the first and last 25 m of the merge area are greater than those in the other sections. The smaller the space between the upstream work zone and the merge area, the greater the probability of serious traffic conflicts between vehicles. When the average vehicle speed is relatively high, the probability of serious conflicts is the highest, i.e., by a multiple of 5.95 from the baseline. Moreover, the probability of serious conflicts between vehicles is higher for larger vehicles, i.e., 4.765 times that for small vehicles. The research results can serve as a reference for freeway management departments to improve the safety levels of merge areas during road work. For example, the probability of serious conflicts can be effectively reduced by setting up reasonable speed limit signs in the work zone, increasing the spacing between work zone and merge area, and appropriately diverting large vehicles.

(1) Background: Heart failure (HF) is the final stage of multiple cardiac diseases, which has now become a severe public health problem worldwide. β-Adrenergic receptor (β-AR) overactivation is a major pathological factor associated with multiple cardiac diseases and mediates cardiac fibrosis and inflammation. Previous study has demonstrated that Bruton's tyrosine kinase (BTK) mediated cardiac fibrosis by TGF-β related signal pathways, indicating that BTK was a potential drug target for cardiac fibrosis. Zanubrutinib, a second-generation BTK inhibitor, has shown anti-fibrosis effects in previous research. However, it is unclear whether Zanubrutinib can alleviate cardiac fibrosis induced by β-AR overactivation;(2) Methods: In vivo: Male C57BL/6J mice were treated with or without the β-AR agonist isoproterenol (ISO) to establish cardiac fibrosis animal model. Here, results showed that BTK inhibitor Zanubrutinib (ZB) had a great effect on cardiac fibrosis and inflammation induced by β-AR. In vitro: Results showed that ZB alleviated β-AR-induced cardiac fibroblast activation and macrophage proinflammatory cytokine production. Further mechanism studies demonstrated that ZB inhibited β-AR-induced cardiac fibrosis and inflammation by BTK、STAT3、NF-κB and PI3K/Akt signal pathways both in vivo and in vitro; (4) Conclusions: our research provides evidence that ZB ameliorates β-AR-induced cardiac fibrosis and inflammation.

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

Bipedal locomotion remains one of the major open challenges of humanoid robotics. The common approaches are based on simple reduced model dynamics to generate walking trajectories, often neglecting the whole-body dynamics of the robots. As motions in nature are often considered as optimal with respect to certain criteria, in this work we present an optimal control based approach that allows us to generate optimized walking motions using a precise whole-body dynamic model of the robot, in contrast with the common approaches. The optimal control problem is formulated to minimize a set of desired objective functions with respect to physical constraints of the robot and contact constraints of the walking phases. We apply the method with combinations of different objective criteria to the model of a reduced version of the iCub humanoid robot of 15 internal DOF. The obtained trajectories are executed on the real robot and we carry out a discussion on the differences between the outcomes of this approach with the classic approaches.

In order to meet the military requirements of the fuze, such as precision strike, efficient mutilates ability and low collateral damages, the microminiaturization is an inevitable trend of secure system. Based on the silicon-based MEMS S&A device designed by our term, the design principles of each module and fabrication process are introduced. The average fracture strength and Young's modulus of the silicon are 726 MPa and 175 GPa from the tensile test, respectively. From Hopkinson impact experiment, we can get the threshold-value judging mechanism being safety under the impact overload of 20526 g, and this value is much more than the standard of the drop overload 12000g; the arming value under the centrifugal overload obtained from theory, simulation and experiment is at the range of 28200 g and 32000 g, it shows that the threshold-value judging mechanism can be arming compared with the value 35951g of design principle. Therefore, the threshold-value judging mechanism can meet the design requirements of overload. Furthermore, the relationship of fracture threshold-values obtained by different theories is found out through parametric design method, as shown in Figure 14, it provides the theory evidence to the follow parametric design.

Jujube (Ziziphus jujuba Mill.) stands as a pivotal fruit tree with significant economic, ecological, and social value. Recent years have witnessed remarkable strides in multi-omics-based biological re-search on jujube. This review began by summarizing advancements in jujube genomics. Subse-quently, we provided a comprehensive overview of the integrated application of genomics, tran-scriptomics, and metabolomics to explore pivotal genes governing jujube domestication traits, quality attributes (including sugar synthesis, terpenoids, and flavonoids), and responses to abiotic stress, and discussed the transcriptional regulatory mechanisms underlying these traits. Further-more, challenges in multi-omics research on jujube biological traits were outlined, and we pro-posed the integration of resources such as pan-genomics and sRNAome to unearth key molecules and regulatory networks influencing diverse biological traits. Incorporating these molecules into practical breeding strategies, including gene editing, transgenic approaches, and progressive breeding, holds the potential for achieving molecular-design breeding and efficient genetic en-hancement of jujube.

Mixed lineage leukemia 1 (MLL1) introduces 1-, 2- and 3-methylation into histone H3K4 through the evolutionarily conserved set domain. In this study, bovine embryonic stem cells (bESCs, named bESCs-F7) were established from the in vitro fertilized (IVF) embryos by Wnt signaling inhibition, while its contribution to endoderm in vivo is limited. To improve the quality of bESCs, MM-102, an inhibitor of MLL1, was applied to the culture. The results showed that MLL1 inhibition along with GSK3 and MAP2K inhibition (3i) at the embryonic stage did not affect bESCs establishment and pluripotency. MLL1 inhibition improves the pluripotency and differentiation potentials of bESCs via up-regulation of stem cell signaling pathways such as PI3K-Akt and WNT. MLL1 inhibition decreases H3K4me1 modification at promoters in bESCs and altered the distribution of DNA methylation in bESCs. In summary, MLL1 inhibition enables bESCs to acquire better pluripotency, and its application may provide high quality pluripotent stem cells for domestic animals.

Given the increased provision of international exchange programmes in higher education, this paper examines students’ perceptions of their learning process in one Erasmus+ programme in Food Innovation and Product Design. Using evaluation model of international exchange programme and triple helix model as the analytical framework, students’ testimonials from 2015–2021 were analysed using a critical discourse analysis. EU and non-EU students had similar perceptions of learning outcomes related to knowledge of the food innovation industry, but non-EU students had a stronger sense of awareness of both the international context and multicultural interaction.

In the field of Natural Language Processing (NLP), Large Language Models (LLMs) have shown great potential in document-level event extraction tasks, but existing methods face challenges in the design of prompts. To address this issue, we propose an optimization strategy called "Definition-driven Document-level Event Extraction (DDEE)." By adjusting the length of the prompt and enhancing the clarity of heuristics, we have significantly improved the event extraction performance of LLMs. We used data balancing techniques to solve the long-tail effect problem, enhancing the model's generalization ability for event types. At the same time, we refined the prompt to ensure it is both concise and comprehensive, adapting to the sensitivity of LLMs to the style of prompts. In addition, the introduction of structured heuristic methods and strict limiting conditions has improved the precision of event and argument role extraction. These strategies not only solve the prompt engineering problems of LLMs in document-level event extraction but also promote the development of event extraction technology, providing new research perspectives for other tasks in the NLP field.

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

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

Modern war is sudden and rapid, and once the battle starts, the demand for equipment maintenance and guarantee will show an outburst situation, which puts equipment maintenance and guarantee capability to a severe test. To accurately grasp the civil-military integration of aviation maintenance and guarantee capabilities, it is necessary to evaluate their capabilities. To this end, the evaluation indicator system is established by using the three-dimensional indicator system construction model of "maintenance task → task demand → capability demand", and the evaluation method based on intuitionistic fuzzy entropy and normal grey cloud model is proposed, using intuitionistic fuzzy entropy theory to determine the expert weights and indicator weights, and the grey cloud model theory to determine the capability evaluation level. Finally, the application process of the evaluation model is demonstrated through specific examples, and the evaluation results are analyzed to verify the effectiveness of the evaluation model.

Modern war is sudden and rapid, and once the battle starts, the demand for equipment maintenance and guarantee will show an outburst situation, which puts equipment maintenance and guarantee capability to a severe test. To accurately grasp the civil-military integration of aviation maintenance and guarantee capabilities, it is necessary to evaluate their capabilities. To this end, the evaluation indicator system is established by using the three-dimensional indicator system construction model of "maintenance task → task demand → capability demand", and the evaluation method based on intuitionistic fuzzy entropy and normal grey cloud model is proposed, using intuitionistic fuzzy entropy theory to determine the expert weights and indicator weights, and the grey cloud model theory to determine the capability evaluation level. Finally, the application process of the evaluation model is demonstrated through specific examples, and the evaluation results are analyzed to verify the effectiveness of the evaluation model.

MEMS (Micro-electromechanical Systems) becomes important increasingly due to the smarter and smaller fuze used in OICW (Objective Individual Combat Weapon). MEMS Safety and Arming (S&A) device is employed in different platforms and regions for small caliber projectile. Therefore, it is necessary to make a parametric study of the MEMS S&A device in different apply environments and explore the main sensitive factors of the MEMS S&A device to provide reference for designs. In this paper, based on the MEMS S&A device designed by our term, theory and finite element models are established, and the centrifugal insurance mechanism of the MEMS S&A device is parametric studied under the different speeds, temperature and thickness of the model by nonlinear dynamic method. By comparing the experimental and predicted results, the established FEM model is verified, and the conclusion is that the temperature and the centrifugal force are the main sensitive factors in the centrifugal insurance mechanism. In summary, we can suggest that the application environment, which the MEMS S&A device is suitable for, is the temperature equal to or slightly greater than normal temperature and the rotating speed higher than35000r/min of small caliber projectile.

Short video addiction refers to a psychological dependency on short video applications, characterized by an intense attachment and an inability to control usage, leading to typical addiction symptoms. While its definition bears similarities to substance addiction, significant differences also exist. According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), published in 2013, short video addiction has not yet been officially classified as an addiction disorder. To facilitate more in-depth and standardized research on short video addiction, it is essential to synthesize and organize existing studies on its theoretical foundations and mechanisms.

Territory space is an ecological resource carrier and place for human development. Human activities and ecological systems are the basis of ecological product supply. Promoting territory spatial protection and governance by improving the ecological products supply is very important. In this study, we established an ecological products supply capacity evaluation index system involving three types of ecological products, i.e., ecological environmental products, ecological material products, and ecological cultural products. For the case of the Beijing-Tianjin-Hebei region, we comprehensively used principal component analysis, equivalent factor method, and entropy method to evaluate the supply capacity of the ecological products from 2011 to 2021. Then, we analyzed the spatio-temporal pattern combining the natural breakpoint and quantile classification methods and analyzed the obstacle factors using the obstacle degree model of ecological supply. The results show that the supply capacity of different ecological product in each city are closely related to ecological resource endowment. The supply capacity of ecological products exhibited an upward trend, with the highest ecological environmental products supply, relatively smaller ecological material product supply, and the largest growth rate for ecological cultural product supply. The supply capacity of different ecological products varied across cities over time and displayed noticeable spatial differentiation. The main obstacle factors included eco-land, eco-tourism, eco-leisure, park green space, and fishery products, although there were variations among cities. Finally, based on the level, spatial-temporal pattern, and obstacle factors of ecological product supply, we proposed strategies for territory spatial protection and governance from the perspectives of integrated protection of elements, structural regulation, and systematic governance. The results reflected the ecological functional heterogeneity of territory space, which can provide spatial planning guidance for sustainable development.

Determining the general-name-derived semantic relationships between geographic names often requires consulting many geographic name documents for verification. In geographic name translation and geographic name knowledge graphs, this method cannot meet the needs of large-scale extraction of general-name-derived semantic relationships between geographic entities. To solve this problem, this paper proposes a general-name derivation relation recognition method based on Prompt learning and Semantic Spatiotemporal Distribution Attention Feature Fusion (SSD-AFF). This method adopts a pipe-based relationship recognition strategy. First, the Prompt learning method is adopted to form a general-name derivation pattern with the general-name-derived geographical name category and the original geographical name category as the prompt word, and then the derivation pattern is combined with the geographical name as the input of the model so that the recognition problem of the general-name derivation of the geographical name can be transformed into a classification problem using the bidirectional language model. Then, by analyzing the characteristics of the semantic association and geographical spatio-temporal distribution between the general-name-derived geographical name and the original geographical name, the semantic spatio-temporal distribution characteristics of the general-name-derived geographical name are constructed. Finally, the network model based on the semantic spatio-temporal distribution Attention Feature Fusion (SSD-AFF) is used to distinguish the general-name-derived semantic relationships. The experimental results show that the proposed method has good performance. It can effectively mine the general-name-derived semantic relations between the vector data of geographical entities and has important application value in geographical name translation and geographical name knowledge maps.

Thought runs through the mind like blood runs through our body to keep us alive. Like the mind, the body does not stay inert and is in constant motion. Not a single cell in our body is left inert unless cell is under stress or dying. These scenarios are reflected upon when a person is sick, the person lies in bed with less movement; however, is active when the person is healthy. The topic of mechanical stimulation has emerged due to the increasing understanding of the physical stimulations we face each day. Further understanding of the mechanically-regulated mechanism can help us explore the pathological events in a disease. Here, we reviewed the role of sensory proteins in pathological events that are observed in cardiomyopathy, cancer, respiratory, renal, obesity, genetics, physical injury and bacterial infection. Taken together, sensory proteins are mechanically-activated which assist reception of external physical stimulation and convert into biochemical to trigger intracellular signaling cascade.

pH is considered one of the paramount factors in bodily functions, because most of the cellular tasks exclusively rely on precise pH values. The regulation of pH is a necessary feature of the intracellular atmosphere and can be established as a strong indicator to judge a physiological abnormality in most of the cases. In this context, the current techniques for pH sensing provide us with the futuristic insight to further design therapeutic and diagnostic tools. Thus, pH-sensing (electrochemically and optically) is rapidly evolving toward exciting new applications and expanding researchers’ interests in many chemical contexts, especially in biomedical applications. The adaptation of cutting-edge technology is subsequently producing the modest form of these biosensors as wearable devices, which are providing us the opportunity to target the real-time collection of vital parameters, including pH for improved healthcare systems. The motif of this review is to provide an insight of trending tech-based systems employed in real time or in-vivo pH responsive monitoring. Herein, we briefly go through the pH regulation in the human body to help the beginners and scientific community with quick background knowledge, recent advances in the field, and pH detection in cancerous environments. In the end, we summarize our review by providing an outlook; challenges that need to be addressed and prospective integration of various pH in vivo platforms with modern electronics that can open new avenues of cutting-edge techniques for disease diagnostics and prevention.

Quadruped robots possess significant mobility in complex and uneven terrains due to their outstanding stability and flexibility, making them highly suitable in rescue missions, environmental monitoring, and smart agriculture. With the increasing use of quadruped robots in more demanding scenarios, ensuring accurate and stable state estimation in complex environments has become particularly important. Existing state estimation algorithms relying on multi-sensor fusion, such as those using IMU, LiDAR, and visual data, often face challenges on non-stationary terrains due to issues like foot-end slippage or unstable contact, leading to significant state drift. To tackle this problem, this paper introduces a state estimation algorithm that integrates an Invariant Extended Kalman Filter (InEKF) with a disturbance observer, aiming at estimating the motion state of quadruped robots on non-stationary terrains. Firstly, foot-end slippage is modeled as a deviation in body velocity and explicitly included in the state equations, allowing for a more precise representation of how slippage affects the state. Secondly, the state update process integrates both foot-end velocity and position observations to improve the overall accuracy and comprehensiveness of the estimation. Lastly, a foot-end contact probability model, coupled with an adaptive covariance adjustment strategy, is employed to dynamically modulate the influence of the observations. These enhancements significantly improve the filter's robustness and the accuracy of state estimation in non-stationary terrain scenarios. Experiments conducted with the Jueying Mini quadruped robot on various non-stationary terrains show that the enhanced InEKF method offers notable advantages over traditional filters in compensating for foot-end slippage and adapting to different terrains.

Edvard Munch, a founder of Expressionism was pre-occupied with depicting his subjective experience and the most prolific painter of self-portraits since Rembrandt. Based on evidence that faces and self-related images are more salient than other objects it is plausible that self-portraits, in which the subject and object are the same, reflect the artist’s state of mind. Although he suffered from a variety of physical and psychological illness Munch was not diagnosed with any specificity in his lifetime. Posthumous diagnoses include schizophrenia, anxiety, bipolar and other disorders. Recent research has revealed altered visual perception in such patients. The present study empirically analysed three stylistic elements of Munch’s painted self-portraits and portraits: contrast, colour and fractal dimension and his painted productivity, to determine if variations correlate with critical life events and if so whether they indicate states of mind. It found significant increases in contrast and colour brightness and persistent high complexity during critical periods supporting the conclusion that Munch is diagnostically best described as suffering from early onset schizophrenia and comorbid social anxiety disorder.

Many have speculated that events of personal and financial loss in Rembrandt’s life caused depression and that this is revealed by examination of his self-portraits particularly those painted in old age. Some report detecting various physiological diseases associated with aging, including vision impairment, which may have affected his mood and work. Aging and neurodegenerative disease which often accompanies it, are both associated with depression. Recent advances in imaging and computer technology make it possible to empirically examine changes in artistic style which can contribute to understanding artists’ physical and mental health. In the current study changes in contrast, colour and fractal dimension were measured in the entire corpus of Rembrandt’s painted self-portraits and portraits to determine whether changes in style indicate depression or disease. Productivity was also examined as an indirect indicator. Given the high salience attributed to self-images, it also examined whether differences in style could be detected between self-portraits and portraits of related and unrelated others. The results indicate that it is unlikely that Rembrandt suffered from unipolar or bipolar depression, age-related cognitive decline, or neurodegenerative disease. The data are consistent with someone experiencing episodes of low mood consistent with normal grieving and adversity followed by resilient recovery. There is evidence of a gradient in saliency and complexity between self-portraits and related and unrelated portraits, of a less formal style in portraits of related others and of a ‘late’ style identified by leading art historians consistent with macular degeneration. The results are also consistent with an association of aesthetic preference with mid-level fractal values tending towards the Golden Mean long associated with beauty in nature and in art.

Researches on the runoff and sediment reduction effects of soil and water conservation measures are being on the rise, which is of great significance for carrying out strategic on soil and water conservation in the Yellow River Basin. Through the analysis of various soil and water conserva-tion measures, runoff, sediment, and rainfall datas in the Sanchuan River Basin from 1960 to 2019, we use the lagrange multiplier method to determining the threshold year of soil and water con-servation measures on runoff and sediment processes. The preliminary conclusion is as follows: The trend of flood season rainfall and annual rainfall in the Sanchuan River Basin is consistent. The 10-year average rainfall in each periods indicates that before 2000, it gradually decreased and then significantly increased. The 10-year average runoff showed a gradual decrease before 2010, followed by a sudden increase, while the 10-year average sediment has shown a decreasing trend years by years, especially after the centralized treatment period. Terrace and dam measures show a trend of first decreasing, then increasing, and then approaching stability during different treat-ment periods, while the trend of forest and grass measures is slightly decreasing and then in-creasing rapidly. The runoff and sediment reduction effects of various soil and water conservation measures during different treatment periods indicate that the runoff reduction effect reached its peak in 2005, while the sediment reduction benefit reached its best in 2015. Based on the compre-hensive benefits of runoff and sediment regulation, 2015 are considered as the threshold year for various soil and water conservation measures, with each measure areas being 4.86 × 104, 17.91 × 104, 1.20 × 104, and 0.83 × 104hm2, respectively. The research results will have certain reference significance for the high-quality development of soil and water conservation in the Yellow River Basin.

The scope of this work was part of our previous research on Pulsed Power Plasma Stimulation Technique. Electromagnetic fields generated during a pulsed power plasma discharge were simulated using a finite element method in the COMSOL RF module. The field distributions were calculated during and after the pulse. The current paper takes advantage of prior work measuring and modeling the current distribution in the plasma arc. Agreement with laboratory experimental measurements provides support for extension of the model to reservoir scale. The validated model was used to quantify the signal attenuation level in different medium environment.

Wagyu beef is gaining worldwide popularity, primarily due to the fineness of its marbling. Cur-rently, the evaluation of this marbling is performed visually by graders. This method has several issues: varying evaluation standards among graders, reduced accuracy due to long working hours and external factors causing fatigue, and fluctuations in grading standards due to the grader's mood at the time. This paper proposes the use of fractal analysis for the grading evaluation of beef marbling to achieve automatic grading without the inconsistencies caused by human factors. In the experiments, cross-sectional images of the parts used for visual judgment were taken, and fractal analysis was performed on these images to evaluate them using fractal dimensions. The results confirmed a correlation between the marbling evaluation and the fractal dimensions, demonstrating that quantitative evaluation can be achieved, moving away from qualitative visual assessments.

Salvia hispanica (chia) is a highly nutritious food source and has gained popularity due to its high omega-3 fatty acid content. Red spider mites are a serious problem in the production of S. hispanica. However, no study has been conducted to analyse the defensive response to the infestation of red spider mites in S. hispanica. To elucidate the molecular mechanisms of the defensive response of S. hispanica to red spider mites, we performed a transcriptomic analysis of S. hispanica when infested by red spider mites. In the comparative assessment of leaf transcriptomes, a total of 1743 differentially expressed genes (DEGs) were identified between control and mite-infested S. hispanica. From these, 1208 (69%) transcripts were up-regulated and 535 (31%) were down-regulated. The DEGs included transcription factors, defense hormones, and secondary metabolites that were either suppressed or activated in response to spider mite herbivory. Gene Ontology (GO) enrichment analysis revealed that plant secondary metabolites such as glucosinolates, and signalling pathways, including the jasmonic acid signalling pathway, may play an important role in the defence against red spider mites. This study provides novel insights into the defence response of S. hispanica in response to insect herbivory and could be a resource for the improvement of pest resistance in the chia.

High-dimensional measurement error data are becoming more prevalent across various fields. Research on measurement error regression models has gained increasing attention due to the risk of drawing inaccurate conclusions if measurement errors are ignored. When the dimension p is larger than the sample size n, it is challenging to develop statistical inference methods for high-dimensional measurement error regression models due to the existence of bias, nonconvexity of objective function, high computational cost and many other difficulties. Over the past few years, some works have overcome the aforementioned difficulties and proposed several statistical inference methods. This paper mainly reviews the current development on estimation, hypothesis testing and variable screening methods for high-dimensional measurement error regression models and shows the theoretical results of these methods with some directions worthy of exploring for future research.

Version Control and Source Code Management Systems, such as GitHub, contain large amount ofunstructured historical information of software projects. Recent studies have introduced Natural Language Processing (NLP) to help software engineers retrieve information from very large collection of unstructured data. In this study, we have extended our previous study by increasing our datasets and ML and clustering techniques. Method: We have followed a complex methodology made up of various steps. Starting from the raw commit messages we have employed NLP techniques to build a structured database. We have extracted their main features and used as input of different clustering algorithms. Once labelled each entry, we have applied supervised machine learning techniques to build a prediction and classification model. Results: We have developed a machine learning-based model to automatically classify commit messages of a software project. Our model exploits a ground-truth dataset which includes commit messages obtained from various GitHub projects belonging to the HEP context. Conclusions: The contribution of this paper is two-fold: it proposes a ground-truth database; it provides a machine learning prediction model. They automatically identify the more change-proneness areas of code. Our model has obtained a very high average precision, recall and F1-score.