Tao and Ming (name) or Tao and Yan (language or speech) is an inseparable pair of important concepts in traditional Chinese language philosophy. In LaoTze’s opinion, Tao could not be spoken out, and language or speech could not reach Tao’s essence. Yan and Tao are separated from each other, and they are paradoxical. All the confusion derives from Yan regardless of how delicate they are. Tao can be expressed in words, but it will never be expressed through common languages. In this article, Tao is regarded as a human being’s thoughts or intentions and is even considered to be the origin of the real world. Language can express people’s thought, although it has some limitations. There exist some contradictions between the real word and the world expressed in words. To enable people to better understand the existence of the real world from multiple perspectives at the language or linguistic level without being constrained by words, this article studies LaoTze’s linguistic philosophy reflected in his opinion on the relationship between Tao and Yan and makes a comparative analysis of modern Western language philosophers’ stand on language (or speech) and existence.

It has been empirically observed that the upper tail of the firm size distribution follows either the Pareto distribution or the Zipf distribution, with both patterns being explained by Gibrat’s law (Gabaix, 1999). This article analyzed firm revenue data from China, spanning from 2005 to 2013, to examine the whole range of the firm size distribution. Our empirical analysis revealed that firm revenue data over these years is well fitted by a three-parameter generalized Pareto distribution, with the fitted parameters indicating a dichotomy: The size distribution of large-sized firms, namely the upper tail, is asymptotically characterized by a Pareto distribution or a Zipf distribution, whereas the size distribution of smaller and medium-sized firms is approximated by an exponential distribution. This finding suggests that Gibrat’s law should be extended to account for the emergence of a generalized Pareto distribution.

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

Background Cancer is one of the most concerning public health issues in the world. One of cancer hallmarks wildly accepted is sustaining proliferative signaling, which involved most of the cell cycle biological activities. Centromeric histone, Centromere Protein A (CENPA), a variant of canonical histone H3, plays an essential role in selective chromosome segregation in the cell cycle. However, so far, a systematic pan-cancer bioinformatic analysis has not been done yet. Methods We accessed genome, transcriptome, and clinical information from open databases. The genetic alteration, mRNA expression, functional enrichment, stemness, mutation association, expression in cell populations and cellular locations, cell cycle association, survival association of CENPA, and immune association were analyzed. A prognostic model for glioma patients was constructed as an example application of CENPA as a biomarker. Drugs targeting CENPA in cancer cells were also screened and predicted by the CENPA correlation of drug sensitivity and protein-ligand docking. Results CENPA had low gene mutation in cancers. CENPA was overexpressed in almost all cancer types in TCGA compared to their normal control. CENPA was highly expressed in the nucleus of malignant cells. CENPA was associated with the cell cycle of cancer cells. CENPA is a biomarker for the cell cycle G2 phase in cancer cells. CENPA was a diagnostic and prognostic biomarker across multiple cancer types. The prognosis of glioma with CENPA was reliable and can be applied with other prognostic factors. CENPA was associated with the immune microenvironment. Drugs CD-437, 3-Cl-AHPC, Trametinib, BI-2536, and GSK461364 were predicted to target CENPA in cancer cells. Conclusion CENPA was a cell cycle biomarker in cancers with diagnostic and prognostic value.

Thermally-assisted-occupation density functional theory (TAO-DFT) has been an efficient electronic structure method for studying the ground-state properties of large electronic systems with multi-reference character over the past few years. To explore the time-dependent (TD) properties of electronic systems (e.g., subject to an intense laser pulse), in this work, we propose a real-time (RT) extension of TAO-DFT, denoted as RT-TAO-DFT. Besides, we employ RT-TAO-DFT to study the high-order harmonic generation (HHG) spectra and related TD properties of molecular hydrogen H2 at the equilibrium and stretched geometries, aligned along the polarization of an intense linearly polarized laser pulse. The TD properties obtained with RT-TAO-DFT are compared with those obtained with the widely used time-dependent Kohn-Sham (TDKS) method. In addition, issues related to the possible spin-symmetry breaking effects in the TD properties are discussed.

For the ground-state properties of gas-phase nanomolecules with multi-reference character, thermally-assisted-occupation density functional theory (TAO-DFT) has been recently found to outperform the widely used Kohn-Sham density functional theory, when the conventional exchange-correlation energy functionals are employed. Aiming to explore solvation effects on the ground-state properties of nanomolecules with multi-reference character at a minimal computational cost, we combine TAO-DFT with the polarizable continuum model (PCM). To show its usefulness, TAO-DFT-based PCM (TAO-PCM) is employed to study the electronic properties of linear acenes in three different solvents (toluene, chlorobenzene, and water). According to TAO-PCM, in the presence of these solvents, the smaller acenes should have nonradical nature, and the larger acenes should have increasing polyradical nature, showing remarkable similarities to the past findings in the gas phase.

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.

Policy induced decline of human mobility has been recognised to be effective in controlling the COVID-19 spread especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling data of confirmed COVID-19 cases with Google mobility data in Australia, we present a state-level empirical study to: 1) inspect the temporal variation of COVID-19 spread and the change of mobility adherent to social restriction policies; 2) examine the extent that different types of mobility are associated with the COVID-19 spread in eight Australian states/territories; and 3) analyse the time-lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively; the restriction of human mobility has a time-lag effect on growth rates, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between mobility and COVID-19 spread varies across space and time, and subjects to the types of mobility. Thus, it is important for governments to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.

Using co-precipitation to synthesize (CeO2)0.95(Y2O3)0.05 (YDC) and solid reaction method to synthesize (CeO2)0.75(ZrO2)0.25 (ZDC), and the characterization for both crystal structure and micro-structure of the two materials was conducted with X-ray diffraction (XRD) and scanning electron microscope (SEM) methods. Prepare the YDC and ZDC based limited current O2 sensor by employing platinum pasting bonding method. Sensing characteristics of the sensor were obtained at different conditions and study on the impact of temperature, O2 concentration as well as water vapor pressure on the sensing characteristics had been conducted. XRD results show that the phase structure of both YDC and ZDC is cubic phase. SEM results show that both YDC and ZDC layers are dense layers, which are then qualified to be the composition materials of the sensor. This limited current O2 sensor shows good sensing performance and conforms to the Knudsen model. Log(IL•T) depends linearly on 1000/T with R2 of 0.9904, IL depends linearly on x(O2) with R2 of 0.9726 and sensing characteristics are not affected by p(H2O).

The demand for precise indoor localization services is steadily increasing. Among various methods, fingerprint-based indoor localization has become a popular choice due to its exceptional accuracy, cost-effectiveness, and ease of implementation. However, its performance degrades significantly as a result of multipath signal attenuation and environmental changes. In this paper, we propose an indoor localization method based on fingerprints using self-attention and long short-term memory (LSTM). By integrating a self-attention mechanism and LSTM network, the proposed method exhibits outstanding positioning accuracy and robustness in diverse experimental environments. The performance of the proposed method is evaluated under two different experimental scenarios, which involve 2D and 3D moving trajectories, respectively. The experimental results demonstrate that our approach achieves an average localization error of 1.76 m and 2.83 m in the respective scenarios, outperforming the existing state-of-the-art methods by 42.67% and 31.64%.

How to achieve sustainable development and protection of historical district is a worthwhile research topic. As a vital way to update urban space, tourism development in historical district is an effective solution to redistribute urban functions and increase urban vitality. This paper takes the Insadong in South Korea as a case to carry out the evaluation of tourist satisfaction in historical districts. The research finds that: 1) The tourist satisfaction evaluation of Insadong includes 6 dimensions in total, namely “Embodiment of historical elements”, “The blend of tradition and modernity”, Industry distribution and type", "Consumer demand", "Street layout and function", "Landscaping". The most satisfying for tourists is "Landscaping", and the most dissatisfying is "Street layout and function". 2) “The blend of tradition and modernity” has the highest weight while “Industry distribution and type” has the lowest one in the analysis of influencing factors on overall satisfaction. 3) The analysis of the common factor weight and the common factor satisfaction shows that “The blend of tradition and modernity” and “Street layout and function” are the parts that need to be improved. “Consumer demand” also has a lot of room for promotion. The research results will benefit to enhance the tourist experiences of historical district and provide theoretical basis and practical experience reference for effective protection and sustainable development of historical district.

Electrospun fiber scaffolds are widely used in small diameter vascular tissue engineering because they mimick organizational structure and biological function of natural extracellular matrix. However, there is still one problem of low patency rate in the long term. The main reasons are the mismatch of compliance and the easy formation of thrombus. Therefore, it is very important to promote the rapid endothelialization of small diameter tissue engineering blood vessels by regulating the topological structure and biological properties of electrospun fiber scaffolds. Firstly, crimped polylactic acid (PLA) fibers were prepared by heat treatment to mimick the crimped structure and nonlinear mechanical properties of the elastic membrane of blood vessel wall. It improved effectively the aspect ratio of human umbilical vein endothelial cells (HUVECs) and promoted lateral alignment and growth. Then, crimped PLA fibers with three levels of pore structure were prepared by thermal induced phase separation, vapor induced phase separation and laser ablation to enhance the degree of HUVECs infiltrarion and realize patterned cell growth. Crimped PLA fibers with three levels of pore structure promote rapid endothelialization of blood vessels, which is of great significance to achieve long term patency rate of small diameter tissue engineering blood vessels.

Solid porous materials, like zeolites, have been widely used in a variety of fields such as size and shape-selective absorption/separation and catalysis because of their porosity. But there are few liquid materials exhibit permanent porosity. Porous liquids are a novel material that combine the properties of fluidity and permanent porosity. It has potential applications in many fields such as gas separation, storage and transport. Herein, we report a novel Type 1 porous liquid prepared based on Silicalite-1. The pore size of this porous liquid was determined by positron annihilation lifetime spectroscopy (PALS), and the CO2 capacities was determined by the intelligent gravimetric analyser (IGA). The unique properties of this porous liquid can promote its application in many fields such as gas storage and transport.

Aiming at the defects of low precision and time cumulative error, an external wireless signal weighted centroid localization algorithm aided inertial positioning method is designed in this paper. According to the signal strength of each anchor node received at the test point, the distance between the anchor node and the anchor node is obtained by using the attenuation model of the wireless signal. Three anchor nodes are used to measure the distance between the anchor node and the measured point. We can obtain the area to be measured according to the actual situation, the position of the measured point is obtained by the weighted centroid localization algorithm and a combined model of wireless signal aided inertial navigation system is established. The simulation results show that the method can greatly improve the positioning accuracy and restrain the divergence of the longitude error and latitude error.

Pt modified BaZr_0.76Y_0.2Ni_0.04O₃ (BZYN) is fabricated and characterized as a stable electrolyte for proton-conducting solid oxide fuel cell (H-SOFC). The utilization of X-ray diffraction method (XRD) and transmission electron microscopy (TEM) enables the identification of the presence of platinum (Pt) in both the crystal lattice sites and the grain interface. This occurrence contributes to a reduction in grain boundary resistance. Consequently, this phenomenon improves the conductivity of the electrolyte. The electrochemical performance of the single cell with Pt modified BZY electrolyte is improved by the reduction of ohmic resistance and enhancement of ion migration. This signifies a noteworthy advancement in the creation of more efficient and durable proton-conducting SOFCs.

Proper Post-Activation Performance Enhancement helps to improve athletic performance. This study aimed to investigate the effects of two different velocity loss (VL), 10%VL and 20%VL, on post-activation performance enhancement (PAPE) in 20m sprint performance among sprint athletes. Twenty-four male sprint athletes (100m sprint time: 10.96±0.15 s) were recruited. A randomized crossover experimental design was used for traditional group (TG), 10%VL, and 20%VL interventions. Sprint tests were conducted at the 4th, 8th, 12th, and 16th minutes after the intervention. Two-way repeated measures ANOVA revealed an interaction effect between group and time on 20m sprint performance (F=2.817, p=0.037, partial η²=0.585). Simple effect analyses showed significant differences compared to baseline at the 4th minute for the 20%VL group (P<0.05). Cohen's d values indicated improvement in 10m sprint times at the 8th minute of the rest interval for all three intervention groups (TG: ES=-0.270, 10%VL: ES=-0.038, 20%VL: ES=-0.279). Improvement in 20m sprint times was observed at the 4th minute for the 20%VL group (ES=-0.296) and at the 16th minute for the 10%VL group (ES=-0.276). Compared to traditional PAPE schemes based on 1RM, PAPE schemes based on velocity loss (20%VL) can better induce PAPE effects in sprint athletes.

In this computational study, we investigate the electronic properties of zigzag graphene nano-parallelograms (GNPs), which are parallelogram-shaped graphene nanoribbons of various widths and lengths, using thermally-assisted-occupation density functional theory (TAO-DFT). Our calculations reveal a monotonic decrease in the singlet-triplet energy gap as the GNP length increases. The GNPs possess singlet ground states for all the cases examined. With the increase of GNP length, the vertical ionization potential and fundamental gap decrease monotonically, while the vertical electron affinity increases monotonically. Besides, as the GNP length increases, the symmetrized von Neumann entropy increases monotonically, denoting an increase in the degree of multi-reference character associated with ground-state GNPs. The occupation numbers and real-space representation of active orbitals indicate that there is a transition from the nonradical nature of the shorter GNPs to the increasing polyradical nature of the longer GNPs. In addition, the edge/corner localization of active orbitals is found for the wider and longer GNPs.

With the targets of petroleum exploration transferred to the deep and ancient strata, abundant oil and gas resources have been found in the Lower Paleozoic and older strata in central and western China. Due to complex evolutionary processes including multiple episodes of hydrocarbon accumulation and ubiquitously accompanied by secondary alterations, significant uncertainties were remained for the generation time and accumulation processes of these revealed petroleum. In this paper, relative pure Re and Os elements existing in the asphaltene fractions of Lower Cambrian solid bitumen collected from the Guangyuan area, western Sichuan Basin, SW China and another Middle–Lower Ordovician heavy oils in the Aiding area of the Tahe oilfield in the Tarim Basin, NW China were successfully obtained by the sample pre-treatments, and Re–Os isotopic analysis was subsequently carried out for the dating of these two petroleum. The Re–Os isotopic composition indicates a generation time of Guangyuan bitumen to locate between 572 Ma and 559 Ma, corresponding to the late Sinian period of Neoproterozoic era. By the means of Re–Os isochron ages, initial 187Os/188Os ratios, and carbon isotopic compositions, the Lower Cambrian bitumen is supposed to be originated from source rocks of the Doushantuo Formation in the Sinian strata and subsequently migrated into the reservoirs of Dengying Formation. These previously reserved petroleum had been transformed to present bitumen by the destruction of reservoirs caused by tectonic uplift. The Re–Os dating results of Middle–Lower Ordovician heavy oil of Tarim Basin supposed that it was formed between 450 Ma to 436 Ma, corresponding to the Late Ordovician–Early Silurian system, and the generated petroleum is likely to migrate into the Middle–Lower Ordovician karst reservoirs to form early oil reservoirs. With tectonic uplift, these oil reservoirs were degraded and reformed to be present heavy oil reservoirs.

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 electrochemical oscillation was first observed in the charging process of anolyte in VRFBs. The chronopotentiometry with current ramp results could be used to judge the appearance of electrochemical oscillation. The electrochemical oscillation could be explained in terms of the competition between the growth and the chemical dissolution of V2O5 film in the H2SO4 solution. It was possible to regular the extra power consumption resulted by the electrochemical oscillation. This work might provide new focus on the charging process of the VRFBs and guide for new methods on energy saving.

The decline in assisted reproductive technology (ART) success among older women, attributed to decreased oocyte quantity and quality, poses a significant challenge. Currently, no consensus ex-ists on the optimal ovarian stimulation protocol for older women undergoing IVF. This retrospec-tive registered cohort study aimed to compare cumulative live birth rates (CLBR), time to live birth (TTLB), and cost-effectiveness in women over 35 years using gonadotropin-releasing hor-mone agonist (GnRHa) or clomiphene-primed ovarian stimulation (CPOS). We performed pro-pensity score matching (PSM) on 2,871 IVF cycles in women over 35 who received either GnRHa or CPOS protocols, resulting in 375 cycles in each group to compare treatment outcomes. Addition-ally, a decision tree model was utilized to assess the cost-effectiveness of the two protocols. Fol-lowing PSM, both groups showed similar baseline characteristics. The CPOS protocol exhibited a higher cycle cancellation rate (13.07% vs 8.00%, p=0.032), yet maintained comparable fertilization and embryo quality. While CLBRs per initial cycle (41.07% vs. 45.33%, p=0.269) and delivery out-comes were similar between the groups after a 24-month follow-up, TTLB was longer in the CPOS group. Notably, the average cost per live birth in the CPOS group was 21.27% less than that in the GnRHa group (￥32,301.42 vs ￥39,174.22). In conclusion, for women over 35 undergoing IVF, the CPOS protocol demonstrated similar CLBR to GnRHa but with lower costs, suggesting its potential as a viable and cost-efficient ovarian stimulation option.

Motivated by empirical observations, we propose a possible extension of Gibrat's law. By applying it into the random growth theory of income distribution (Gabaix, 2009), we find that the income distribution is described by a generalized Pareto-type distribution (GPD) with three parameters. We observe that there is a parameter /elta in the GPD that plays a key role in determining the shape of income distribution. By using the Kolmogorov-Smirnov test, we empirically show that, for typical market-economy countries, /elta is close to 0 significantly, such that the income distribution is characterized by a two-class pattern in which the bottom 90% of the population is approximated by an exponential distribution and the richest 1%~3% is approximated by an asymptotic power law. However, we empirically find that, for China both in planned economy period and in early stages of market reformation (from 1978 to 1990), /elta is significantly deviated from 0, such that the bottom of the population no longer conforms to an exponential distribution.

Carbon fiber reinforced polymer (CFRP) has been used widely in strengthening of steel structures. Steel/CFRP systems subjected to elevated temperatures is realistic in a summer climate event in many countries where the temperature in steel may approach 50 °C or even higher, which will lead to the degradation of the bond performance between CFRP and steel. Therefore, predicting the bond behavior of the CFRP/steel system under elevated temperature is critical. This paper investigated the mechanical performance of CFRP/steel adhesively-bonded double strap joints at elevated temperatures. Thirty CFRP-steel double strap joints were tested to failure under temperatures between 10 °C and 90 °C. It was found that the joint failure mode changed from adherend failure to debonding failure as the temperature approached T_g. In addition, the ultimate load and joint stiffness decreased significantly at temperatures near to and greater than T_g. Based on the experimental results, a model is proposed to predict the bond stress of the CFRP/steel at different temperatures.

Accompanied by increasing population growth and urban sprawl, most coastal cities are unprecedentedly vulnerable to climate change and its impacts, such as sea level rise, increasing extreme storm events, and coastal flooding. Coastal resilience and sustainable development are antidotes to vulnerability; they aim to enhance the adaptive capability of absorbing disturbances and resisting uncertainty. This study explores building a quantitative assessment framework to measure resilience and provide an objective and comparable method to understand the strengths and weaknesses in a given region. The proposed 25 resilience indicators incorporate the aspects of essential livelihood protection, infrastructure and natural resource maintenance, emergency facilities and institutions, floodplain management regulations, and adaptive planning process. Each indicator is assigned the resilience quality that includes robustness, resourcefulness, redundancy, and rapidity. The aggregated resilience quality scoring reflects the systematic performance of the city to cope with the coastal hazards. The innovative part of this framework is combining hazard mitigation measures, climate adaptation strategies, and sustainable development goals together to achieve a comprehensive assessment method. In the case of New Haven, the resilience assessment is taken as a practical monitoring tool and decision-making support.

The CuCrSn alloy is promising as high-strength and high-conductivity Cu alloy due to its relative low smelting requirement, while thus far reports on the CuCrSn alloy is still quite lacked. In this study, the microstructure and properties of Cu-0.20Cr-0.25Sn (wt%) specimens prepared under different rolling and aging combinations were comprehensively characterized, in order to reveal the effects of cold rolling and aging on the CuCrSn alloy. The results show that increasing the aging temperature from 400 ºC to 450 ºC can obviously accelerates the precipitation, and the cold rolling before aging significantly increases the initial microhardness and promotes the precipitation. Whereas, the deformation hardening will be eliminated during the aging process, making the microhardness even decrease monotonically when the aging temperature and the rolling ratio before aging are high. Performing the cold rolling after the aging can maximize the effects of precipitation strengthening and deformation strengthening, and its adverse impact on the conductivity is not serious. A tensile strength of 506.5 MPa and a conductivity of 70.33% IACS were obtained with such a treatment, only the elongation decreases. Different strength-conductivity combinations of the CuCrSn alloy can be achieved through appropriate combinations of the aging and post aging cold rolling conditions.

F-box protein is a key protein of the SCF E3 ubiquitin ligase complex, responsible for substrate recognition and degradation through specific interactions. Previous studies have shown that F-box proteins play crucial roles in Cryptococcus sexual reproduction. However, the molecular mechanism by which F-box proteins regulate sexual reproduction in C. neoformans is unclear. In the study, we discovered the AICAR transformylase/IMP cyclohydrolase Ade16 as a substrate of Fbp1. Through protein interaction, protein stability, and in vivo ubiquitination experiments, we demonstrated that Ade16 is a substrate for Fbp1. To examine the role of ADE16 in C. neoformans, we constructed the iADE16 strains and ADE16OE strains to analyze the function of Ade16. Our results revealed that the iADE16 strains had a smaller capsule and showed growth defects under NaCl, while the ADE16OE strains were sensitive to SDS but not to Congo red, which is consistent with the stress phenotype of the fbp1Δ strains, indicating that the intracellular protein expression level after ADE16 overexpression was similar to that after FBP1 deletion. Interestingly, although iADE16 strains can produce basidiospores normally, ADE16OE strains can produce mating mycelia but not basidiospores after mating, which is consistent with the fbp1Δmutant strains, suggesting that Fbp1 is likely to regulate the sexual reproduction of C. neoformans through the modulation of Ade16. Fungal nuclei development assay showed that the nuclei of the ADE16OE strains failed to fuse in the bilateral mating, indicating that Ade16 plays a crucial role in the regulation of meiosis during mating. In summary, our findings have revealed a new determinant factor involved in fungal development related to the post-translational regulation of AICAR transformylase/IMP cyclohydrolase.

The process of full-thickness skin regeneration is complex and has many parameters involved, which makes it difficult to use a single dressing to meet the various requirements of the complete regeneration at the same time. Therefore, developing hydrogel dressings with multifunction, including tunable rheological properties and aperture, hemostatic, antibacterial and super cytocompatibility, is a desirable candidate in wound healing. In this study, a series of complex hydrogels were developed via the hydrogen bond and covalent bond between chitosan (CS) and alginate (SA). These hydrogels exhibited suitable pore size and tunable rheological properties for cell adhesion. Chitosan endowed hemostatic, antibacterial properties and great cytocompatibility and thus solved two primary problems in the early stage of the wound healing process. Moreover, the sustained cytocompatibility of the hydrogels was further investigated after adding FGF and VE-cadherin via the co-culture of L929 and EC for 12 days. The confocal 3D fluorescent images showed that the cells were spherical and tended to form multicellular spheroids, which distributed in about 40-60μm thick hydrogels. Furthermore, the hydrogel dressings significantly accelerate defected skin turn to normal skin with proper epithelial thickness and new blood vessels and hair follicles through the histological analysis of in vivo wound healing. The findings mentioned above demonstrated that the CS/SA hydrogels with growth factors have tremendous potential as multifunctional hydrogel dressings for full-thickness skin regeneration incorporated with hemostatic, antibacterial, sustained cytocompatibility for 3D cell culture and normal skin repairing.

The modification of proteins by small ubiquitin-related modifier (SUMO) molecules, SUMOylation, is a key post-translational modification involved in a variety of biological processes such as chromosomes organization, DNA replication and repair, transcription, nuclear transport, and cell signaling transduction. In recent years, emerging evidence has shown that SUMOylation regulates the development and homeostasis of the skeletal system, with its dysregulation causing skeletal diseases, suggesting that SUMOylation pathways may serve as a promising therapeutic target. In this review, we summarize the current understanding of the molecular mechanisms by which SUMOylation pathways regulate skeletal cells in the physiological and disease contexts.

A simple and effective surface modification of polyester fabrics with sulfuric acid to improve the interfacial deposition of polypyrrole was presented in our work. A range of sulfuric acid concentrations were analyzed by studying water contact angle. Effect of sulfuric acid modification on the deposition of polypyrrole was investigated by sheet resistance and color depth of fabric samples. Polyester fabrics coated with polypyrrole layer were confirmed by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), X-Ray diffraction spectra (XRD), Fourier transform infrared spectroscopy (FTIR). XPS showed that sulphur containing functional groups were obviously appeared on the polyester fiber surface after modification, which were advantageous to promote the deposition of polypyrrole onto polyester fabrics. The improved deposition increased electrical conductivity of fabric samples.

To get a better knowledge of the effects of residual chlorothalonil on soil characteristics and soil microbial communities, we evaluated the dissipation of chlorothalonil and the effects of different chlorothalonil concentrations on soil respiration, enzyme activities, and microbial community structure in yellow-brown loam soils. Bacterial and fungal soil communities were examined using traditional plate counting and polymerase chain reaction-denaturing gradient gel electrophoresis (PCR–DGGE) methods. Soil properties and the results of DGGE band analysis were both used to estimate the status of the soil microbial ecosystem. The results show that residual chlorothalonil has considerable effects on soil respiration, enzymatic activities, and microbial community structure. In particular, soil respiration and phosphatase activities were increased, while saccharase activity, microbial biomass, and microbial community diversity were decreased by increasing levels of chlorothalonil treatment. Correlation analyses revealed that the application of chlorothalonil was significantly correlated with the change of the soil respiration, urease activity, sucrase activity, soil culturable bacteria and culturable fungi biomass. We conclude that residual chlorothalonil is directly related to soil respiration, enzyme activities, and microbial community structure.

Wild Chinese prickly ash with elevated antioxidants is a valuable genetic resource for Zanthoxylum bungeanum Maxim improvement. There are rich wild germplasm resources in the Qinling Mountains. In a study with wild germplasm resources from different altitudes and six cultivated varieties, the phenolic and flavonoid compounds were analyzed by high performance liquid chromatography (HPLC). The chromatograms of them were basically the same, although their chemical composition content was greatly different. The thirty samples were divided into three categories through the hierarchical clustering analysis. And catechin, hyperoside and quercitrin were considered to be key compound for the quality evaluation, by contrast, the wild samples with an altitude of 2300±50 m (Ⅳ group) had the highest content of key compounds, and showed stronger antioxidant activity and antibacterial ability, indicating that these wild samples could be used as an excellent breeding resource. This is the first time to evaluate the quality of wild Chinese prickly ash in different altitude areas of Qinling Mountains. These excellent wild germplasm resources provided substantial potential accessions for use directly in Chinese prickly ash breeding programs.

The upper ocean heat content in the equatorial Pacific usually serves as a primary precursor for an upcoming El Niño, while the strong atmospheric perturbations such as westerly wind burst and easterly wind surge sometimes play a decisive role in determining the final intensity of the event. The tropical Pacific Ocean has just experienced a rare 3-year La Niña, which accumulated a huge amount of warm water in the western basin by the winter of 2022. Using a state-of-the-art climate prediction system, here we show that the restored warm water is sufficient to boost a strong El Niño toward the end of 2023, and that an extreme event could take place if a few sizable westerly wind bursts would occur in spring and early summer. This prediction is not sensitive to initial errors within the tropical Pacific, but may be subject to some uncertainties brought about by influences from elsewhere.

In this work, we focus on investigating electrothermal flow in a rotating electric field (ROT-ETF), with primary attention paid to the horizontal traveling-wave electrothermal (TWET) vortex induced at the center of the electric field. The frequency-dependent flow profiles in the microdevice are analyzed using different heat transfer models. Accordingly, we address in particular the importance of electrode cooling in ROT-ETF as metal electrodes of high thermal conductivity while substrate material of low heat dissipation capability are employed to develop such microfluidic chips. Under this circumstance, cooling of electrode array due to external natural convection on millimeter-scale electrode pads for external wire connection occurs and makes the internal temperature maxima shift from the electrode plane to a bit of distance right above the cross-shaped interelectrode gaps, giving rise to reversal of flow rotation from a typical repulsion-type to attraction-type induction vortex, which is in good accordance with our experimental observations of co-field TWET streaming at frequencies on the order of reciprocal charge relaxation time of the bulk fluid. These results point out a way to make a correct interpretation of out-of-phase electrothermal streaming behavior, which holds great potential for handing high-conductivity analytes in modern microfluidic systems.

In order to improve the wear resistance of copper contacts in high-voltage switches and improve the abnormal discharge phenomenon caused by wear gaps, laser remelting technology was used to strengthen the surface of copper contacts. The surface morphology, microhardness, and wear resistance of the remelted samples were tested and characterized using scanning electron microscopy (SEM), microhardness tester, and friction and wear tester. The test results indicate that laser frequency, pulse width, and current parameters can directly affect the surface morphology and wear resistance of the sample, but their influencing processes vary. The laser frequency is achieved by the variation of the superposition relationship between the impact points, while the pulse width and current are achieved by the variation of the laser intensity at the impact points. When the pulse frequency is 10Hz, the pulse width is 10ms, and the current is 100A, the sample exhibits a more balanced surface morphology, microhardness, and wear resistance.

During Sep. 2011, forty-four Leymus chinensis culms with stroma development were collected from Inner Mongolia. Stromata surrounded the flag leaf sheathes, white, at the final stage of development. Perithecium but not asci were observed under microscope. Nine epichloid endophyte strains were obtained from Tongliao subdivision, and sixteen from Horqin. Morphological and phylogenetic properties of these strains were investigated. Morphological properties of these strains were similar among these 27 strains. Colonies could grow to 28.5~41.1 mm/21d at 25℃; phialides 24.1~26.4 μm long, 2.1~2.5 μm at base, tapering to less than 1.0 μm at tip; conidia reniform to elliptical, 4.7~5.5×2.8~3.5 μm, indicating typical properties of Epichloë endophytes. Based on the sequences of tefA and tubB gene fragments, strains isolated from Inner Mongolia formed a distinct subclade in E. bromolica/ E. yangzii clade, with a bootstrap value of 66% and 64% respectively. Considering morphological and phylogenetic properties, we tend to determine strains isolated from Leymus chinensis as a new taxon. The detailed taxonomic position of this taxon needs further investigations on hybridization or genomic sequence.

The central coast is one of the importantly livable regions in China, and green land plays a meaningful role in improving human settlements through regulating ecosystem services. However, the research on spatiotemporal heterogeneity of green land in different urbanized areas are still lacking in this region, which limits the timeliness of reporting on the land-surface thermal properties of residential environment from green land perspective. To address this issue, the synergistic methodology of “artificial numerical technology -- urban interior mixed pixel classification -- surface radiation energy balance model” was applied to investigate the green land change and its impact on human settlements in Rizhao region, which is known for its coastal ecology and greenery in China and obtained the United Nations habitat award. Main conclusions of this study are below: (1) Although total green land decreased by 474.05 km2, resulting in a decrease of 9.17% in its share of the entire study area from 2000-2022 during the urbanization process, but the greening levels improved within the built-up area, with the greening proportion of 25.34% in 2000 and 42.98 km2 in 2022. (2) Differences in green land at different urbanized regions were first observed, namely, urban greening rate was 37.78% in the old urban areas of 2022, while it was up to 46.43% in new urban areas. More attention was paid to the construction of urban green space during urban expansion, which will inevitably bring better visual and comfort experience to residents. (3) Thermal comfort indicators for urban residents were evaluated in latent heat flux (0-457.83 W/m2), sensible heat flux (0-645.09 W/m2), total available energy (254.07-659.42 W/m2) and others. (4) The lowered cooling temperature effect in the middle, high green land density region was 1.05 ℃ and 2.12 ℃ compared to the low-density region, and the average air temperature was 25.86 ℃. Also, spatial patterns of hot and cold uncomfortable areas were displayed in this study. Overall, this study provides the meaningfully practical reference for exploring the spatiotemporal heterogeneity of green land and its impact on residents' environments from the perspective of land-surface thermal properties in coastal areas of China and around the world.

Patients under immunosuppressive therapy for kidney diseases or on maintenance hemodialysis are more susceptible to infection than the general population since loss of renal function per se was an immunocompromised condition. Of relevance, CT imaging plays a crucial role in the detection and management of pulmonary infectious diseases. We hence presented diverse CT findings of pulmonary infections in the above said patients collected during our arduous work against a wide range of pathogens including klebsiella pneumoniae, staphylococcus aureus, candida parapsilosis, aspergillus, cryptococcus, mucor, pneumocystis carinii, cytomegalovirus, mycobacterium and nocardia. Notably, the pulmonary pathological changes were either primary pneumonia or secondary to the catheter-associated bloodstream infection. For a descriptive purpose, pulmonary manifestations of Wegener’s granuloma, lung cancer and diffuse alveolar hemorrhage/infection in vasculitis were also examined. As such, we retrospectively elaborated most likely CT features of each individual pathogen and briefly covered the differential diagnosis as well. Arguably, combination of pattern recognition with knowledge of the clinical setting could make a presumptive diagnosis and early treatment even more convenient. From the experience of first-line nephrologists, our work could make a substantial contribution to the expeditious and efficacious management of pulmonary infections in the pertinent patient population.

As the general acceptance of fiber-reinforced polymer (FRP) in the concrete construction industry continues to rise, it is increasingly imperative that the crack width of FRP reinforced concrete members of pavement and girder be predicted with good accuracy due to strengthening of RC pavement, slabs or beams structures using FRP is known to control crack width. However, no specific provisions are provided by most international design codes for predicting crack width in FRP reinforced concrete flexure members. In this paper, five formulas for predicting the crack width for FRP reinforced structures are derived from three common computational theories which including statistical method, comprehensive theory, and bond-slip theory. The formula of statistical method is simplest, but the parameters depend on much sample data. The comprehensive and slippage theory based on semi-empirical statistical crack spacing are obtained through the calculation of non-uniformity coefficient of strain. The comprehensive and slippage theory based on semi-empirical axial force balance are obtained through the calculation of tensile reinforcement factor. The comparative analysis of performance of five formulas is carried out. The results indicate that the formula from comprehensive theory based on semi-empirical statistical crack spacing is recommended for predicting the crack width of FRP reinforced concrete flexural structure.

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

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

Abstract In order to solve the problem that it is difficult to obtain the accurate trigger signal moment when using the time difference of UAV flight acoustic signals collected by acoustic sensors arranged in advance to locate the position of UAVs when they cannot be tracked by radar and are difficult to be observed by the human eye, an acoustic source localisation method with improved empirical modal decomposition (REMD) under an adaptive frequency window is proposed. Firstly, the collected UAV flight signals are smoothed and filtered, then the robust empirical modal decomposition (REMD) is used for IMF modal decomposition and spectral analysis of the collected signals, and a panning frequency window with variable bandwidth is introduced for corresponding frequency locking and extracting the IMFs; the GWO optimisation is used and the sliding metrics are set to determine the position of the panning frequency window automatically; finally, the extracted Finally, the extracted IMF components are reconstructed according to the criterion, and the trigger signal moments in the reconstructed IMF components are resolved and recorded, and the algorithm is used to calculate the difference between the reception moments of different sensors; for the traditional sound source localisation algorithms with a small detection range, which are prone to fall into the no-solution or false-solution, i.e., unable to achieve the localisation, a weighted least-squares-based Chan-Taylor algorithm is proposed for the localisation computation, and a weighted least-squares algorithm is proposed for the localisation computation, through the Inputting the sensor delay parameter and solving the linear equation system to get the target position information; finally, this paper verifies the robustness and performance of the design method with simulated and actual signals. The results show that the maximum positioning error is no more than 5% in an area with a side length of 15m in the measurement area. With the improved accuracy of time delay estimation, the positioning simulation results meet the positioning requirements even though the positioning error is further expanded when the measurement area is further expanded.

Abstract: To explore the interrelationship between groundwater microbial communities and hydrochemical characteristics in Mancheng district, Baoding city, samples from karst groundwater and porous groundwater were collected respectively. The hydrochemical analysis and 16s RNA gene V4-V5 region sequencing method were used to detail the water environmental characteristics and microbial community distribution pattern in the study area. The hydrochemical results reveal significant differences in major ion contents and other hydrochemical indices between karst water and porous water. Microbial community analysis demonstrates that Proteobacteria, Actinobacteria, and Firmicutes are the dominant taxa in both types of water bodies, but their proportions vary significantly in different water bodies. The difference in microbial communities between karst water and porous water reflects the influence of environmental factors such as ion concentration and pH on microbial distribution. Redundancy analysis (RDA) indicates significant associations between microbial community composition and environmental factors in both types of groundwater environments. Studying the distribution pattern of microbial communities and the connection with environmental factors in two types of groundwater provides important basis for interpreting the functional roles of microbes in groundwater ecosystems.

In order to realize rapid and nondestructive monitoring of wheat biomass in field, field experiments based on different densities, nitrogen fertilizer and variety treatments were studied. RGB images of wheat in the main growth stage were obtained by UAV, and wheat color and texture feature indices were obtained by image processing, and wheat biomass was obtained by field sampling in the same period. Then the relationship between different color and texture feature indices and wheat biomass was analyzed to select the color and texture feature index suitable for wheat biomass estimation. The results showed that there was a high correlation between image color index and wheat biomass in different stages, and most of them reached a very significant correlation level. However, the correlation between image texture feature index and wheat biomass was poor, only a few indexes reached significant or extremely significant correlation level. Based on the above results, the color indices with the highest correlation to wheat biomass or the combining indices of color and texture feature in different growth stage were used to construct estimation model of wheat biomass. The models were validated using independently measured biomass data, and the correlation between simulated and measured values reached the significant level, RMSE were smaller. This indicated that the estimated results by the models were reliable and accurate. It also showed that the estimation models of wheat biomass combined with color and texture feature indices of UAV image were better than the single color index models. The results would provide a new method for real-time monitoring of wheat field growth and biomass estimation.

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

After cut by basecutter, sugarcane stalks are carried to a chopper by the basecutter and the feeding/conveying rollers train of harvester. However, the conventional feeding/conveying channels of sugarcane chopper harvesters, when harvesting seriously lodged sugarcane, have numerous drawbacks, including easy clogging, and poor adaptability. In order to resolve these problems, a novel design and layout method of feeding/conveying and chopping channel are proposed in the paper. And a chopper centrally-mounted channel is designed for a sugarcane chopper harvester as well, which has been implemented in the HN4GDL-91 harvester. The proposed channel consists of a feeding/conveying rollers train, a chopper, and a billet conveying device. By mounting the chopper between the feeding/conveying rollers train and the billets conveying device, the harvester can avoid the chopper chopping back the billets, thus improving the harvest quality. The feeding/conveying rollers train is designed with only a pair of feeding rollers and a pair of conveying rollers, achieving a short channel path. Moreover, the structure of the basecutter and the mechanism carrying stalks to feeding rollers are studied via theoretical analysis and tests. The relationship between the basecutter and the chopper centrally-mounted channel is also conducted in systematic analysis. The results of the theoretical analysis show that the inclination angle of the disc of basecutter should be 2° greater than the angle of the feeding conveying channel (both angles are from the horizontal plane). The inclination angle of the disc of basecutter should go from 10° to 15°. A field experiment with four factors and three levels indicates that the field loss rate is 2.45%, the feed quantity is 16.66 kg/s, and the qualified rate of the billets is 98.02%, while the number of sugarcane stalks in a clump, the ground speed of harvester the rotational speed of the chopper, and the rotational speed of feeding/conveying roller are 10, 1.09 m/s, 390 r/min, and 230 r/min, respectively. It is concluded that the proposed chopper centrally-mounted channel could improve the conveying and harvesting performance significantly.

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.

Two algorithms of data processing are proposed to shorten the unmeasurable dead-zone close to the zero-position of measurement, i.e., the minimum working distance of a dispersive interferometer using optical frequency comb, which is a critical issue in millimeter-order short-range absolute distance measurement. After demonstrating the limitation of the conventional data processing algorithm, the principles of the proposed algorithms, namely the spectral fringe algorithm, and the combined algorithm that combines the spectral fringe algorithm with the excess fraction method, are presented, together with simulation results for demonstrating the possibility of the proposed algorithms for shortening the dead-zone with a high accuracy. An experimental setup of dispersive interferometer is also constructed for implementing the proposed data processing algorithms over spectral interference signals. Experimental results demonstrate that the dead-zone by the proposed algorithms can be as small as half of that by the conventional algorithm while the measurement accuracy can be further improved with the combined algorithm.

Water splitting technology is an efficient approach to generate hydrogen (H2) energy, which can well address the problems of environmental deterioration and energy shortage, as well as establishment of a clean and sustainable hydrogen economy powered by renewable energy sources due to the green reaction of H2 with O2. While the efficiency of H2 production by water splitting technology is intimately related with the reactions on electrode. Nowadays, the efficient electrocatalysts in water splitting reactions are the precious metal-based materials, i.e., Pt/C, RuO2 and IrO2. Ni (Co, Fe)-based layered double hydroxides (LDH) 2D materials are the typical non-precious metal-based materials in water splitting with advantages of low cost, excellent electrocatalytic performance and simple preparation methods, which exhibits a great potential for the substitution for precious metal-based materials. This review summarizes the recent progress of Ni (Co, Fe)-based LDH 2D materials for water splitting, which mainly focuses on discussing and analyzing the different strategies to modify LDH materials towards high electrocatalytic performance. We also discuss the recent achievements including their electronic structure, electrocatalytic performance, catalytic center, preparation process and catalytic mechanism. Furthermore, the characterization progress in revealing electronic structure and catalytic mechanism of LDH is highlighted in this review. Finally, we put forward some future perspectives related to design and explore advanced LDH catalysts in water splitting.

This paper provides attempts to formalize Hayek’s theory of knowledge. It has been theoretically shown that exponential income distribution is a spontaneous order of the well-functioning market economy. We show that this theoretical result is supported by the empirical evidence from the United Kingdom and China. In particular, we empirically show how the income structure of China evolved towards an exponential distribution after the market-oriented economic reformation. Furthermore, we strictly prove that, if the income structure of an economy obeys an exponential distribution, the income summation over all households leads to an aggregate production function with Hicks-neutral-like technical progress, in which the technology factor is exactly equal to society’s information stock that is a result of combining all of decentralized decisions.

In view of the floating rectangular aerostatic guideway problem of low load capacity and stiffness, this paper puts forward a kind of closed rectangular aerostatic guideway and its optimized design. Firstly, the analytic calculation formula of a closed rectangular aerostatic guideway was deduced. The use of MATLAB software for the numerical simulation and the parameter influence analyses was carried out in terms of the gas supply pressure on load capacity and stiffness. A simulation model of the rectangular air bearing was also built using the Fluent software, and the model was used for simulation calculations. Secondly, the static performance of the rectangular air bearing was analyzed by analyzing the distribution position and number of orifices on its load capacity and stiffness. On this basis, the response surface optimization design method is used to analyze the variation law of the load capacity and stiffness of the air bearing under different restrictor structural parameters. Finally, the optimal design parameters for the rectangular air bearing are obtained. The simulation results show that the optimized rectangular air bearing designed in this paper has a good load capacity and stiffness of 644.58N and 63.405N N∙μm^(-1).

Porcine sapovirus (PoSaV) is a significant pathogen causing diarrhea with high morbidity and mortality rates. Given its zoonotic characteristics, this study conducts a comprehensive genetic evolutionary analysis of PoSaV. Results confirmed PoSaV as the primary RNA virus in piglet feces (27.54%). Phylogenetic analysis identifies the prevalent PoSaV strain SHCM/Mega2023 in the GIII genogroup, involving a recombinant event with MK962338 and KT922089. The time tree revealed that the GIII genogroup exhibits the widest divergence time span, indicating a high likelihood of viral recombination. Further selective pressure calculations demonstrate that PoSaV was under purifying selection (dN/dS < 1), with seven positively selected sites in VP1 protein which might be related to the antigencity. In conclusion, this study presents a novel genomic evolution of PoSaV, offering valuable insights into antigenicity and vaccine research.

In order to reveal the mechanism and influencing factors of high pressure jet cavitation of nozzle in submerged environment, this study focused on the evolutionary process of cavitation bubbles and combined finite volume method and mixed multi-phase flow model to analyze the cavitation, velocity distribution and experimental cavitation intensity of fishing net cleaning equipment. Results show that the cavitation inception, growth and collapse mainly occurred in the peripheral region of the flow field. Ring-shaped cavitation erosion zone appeared on the test sample target. A lot of small dense erosion pits were densely distributed in the ring-shaped erosion zone, erosion marks were observed in the center. The cavitation erosion intensity was greatly affected by the nozzle structure. As the diameter of nozzle increased from 0.6 mm to 1 mm, the maximum gas volume fraction increased by 8.53%. The nozzle outlet enlargement angle greatly increased the cavitation intensity. The nozzle with an outlet angle of 30° exhibited the optimal cavitation erosion performance . The cavitation volume fraction of the nozzle with short necking structure was slightly larger than that of the nozzle with long necking structure at the same level in the necking length rang of 3mm to 7mm. In terms of the influence of nozzle structure on the cavitation erosion effect, the nozzle diameter D ranked the first, followed by the outlet angle α, and the necking length L was at the last.

To investigate the impact of electrode structure on Electrical Stimulation Therapy (EST) for chronic wound healing, this study designed three variants of flexible microelectrodes (FMs) with Ag-Cu coverings (ACCs), each exhibiting distinct geometrical configurations: hexagonal, cross-shaped, and serpentine. These were integrated with PPY@PDA/PANI (3/6) hydrogel dressings. Comprehensive animal studies, coupled with detailed electrical and mechanical modeling and simulations, were conducted to assess their performance. Results indicated that the serpentine-shaped FM outperformed its counterparts in terms of flexibility and safety, exhibiting minimal thermal effects and a reduced risk of burns. Notably, FMs with metal coverings under 3% demonstrated promising potential for optoelectronic self-powering capabilities. Additionally, simulation data highlighted the significant influence of hydrogel non-uniformity on the distribution of electrical properties across the skin surface, providing critical insights for optimizing EST protocols when employing hydrogel dressings.

Deep learning is improving by leaps and bounds in remote sensing images (RSIs) analysis, pre-trained convolutional neural networks (CNNs) have shown remarkable performance in remote sensing image scene classification (RSISC). Nonetheless, pre-trained CNNs require massive annotated data as samples for data training. When labeled samples are not sufficient, the most common solution is to the pre-trained CNNs using a great deal of natural image dataset (e.g. ImageNet). However, these pre-trained CNNs require a large quantity of labelled data for training, which is often not feasible in RSISC, especially when the target RSIs have different imaging mechanisms from RGB natural images. In this paper, we proposed an improved hybrid classical-quantum transfer learning CNNs composed of classical and quantum elements to classify open-source RSI dataset. The classical part of the model is made up of a ResNet network which extracts useful features from RSI datasets. To further refine the network performance, a tensor quantum circuit is subsequently employed by tuning parameters on near-term quantum processors. We tested our models on open-source RSI dataset. In our comparative study, we have concluded that the hybrid classical-quantum transferring CNN has achieved better performance than other pre-trained CNNs based RSISC methods with small training samples. Moreover, it has been proved that the proposed algorithm improves the classification accuracy while greatly decreasing sum of model parameters and sum of training data.

A series of Si-bearing MgAl₂O₄-spinels were synthesized at 1500-1650 °C and 3–6 GPa. These spinels had SiO₂ contents up to ~1.03 wt%, and showed a substitution mechanism of Si⁴⁺ + Mg²⁺ = 2Al³⁺. Unpolarized Raman spectra were collected from polished single grains, and displayed a set of well-defined Raman peaks at ~610, 823, 856 and 968 cm^-1 which had not been observed before. Aided with the Raman features of natural Si-free MgAl₂O₄-spinel, synthetic Si-free MgAl₂O₄-spinel, natural low quartz, synthetic coesite, synthetic stishovite and synthetic forsterite, we infer that these Raman peaks should belong to the SiO₄ groups. The relations between the Raman intensities and SiO₂ contents of the Si-bearing MgAl₂O₄-spinels suggest that at some P-T conditions some Si must adopt the M-site. Unlike the SiO₄ groups with very intense Raman signals, the SiO₆ groups are largely Raman-inactive. We have further found that the Si cations primarily appear on the T-site at P-T conditions ≤ ~3–4 GPa and 1500 °C, but attain a random distribution between the T-site and M-site at P-T conditions ≥ ~5–6 GPa and 1630–1650 °C. This Si-disordering process observed for the Si-bearing MgAl₂O₄-spinels hints that similar Si-disordering might happen to the (Mg,Fe)₂SiO₄-spinels (ringwoodite), the major phase in the lower part of the mantle transition zone of the Earth and the index mineral for the very strong shock stage experienced by extraterrestrial materials. The likely consequences have been explored.

The Paeonia suffruticosa, called as 'Feng Dan', has been used for thousands of years in traditional Chinese medicine. In our chemical investigation on the root bark of the plant, five new phenolic dimers, namely paeobenzofuranone A‒E (1‒5), have been characterized. Their structures were determined by spectroscopic analysis including 1D and 2D NMR, HRESIMS, UV, and IR, as well as ECD calculations. Compounds 2, 4, and 5 showed cytotoxicity against three human cancer cell lines with IC50 values ranging from 6.7 to 25.1 μM. Compounds 1 and 2 showed certain inhibitory activity on NO production. To the best of our knowledge, the benzofuranone dimers and their cytotoxicity of P. suffruticosa are reported for the first time.

In this study, we investigate the behavior of randomly moving particles with a defined average energy, focusing on their biased motion around a specific point. These particles' velocity magnitudes follow a Maxwell distribution with a specific scale parameter. Our analysis derives the stochastic rotation rules for these particles and introduces the Ito equation conditions for biased stochastic rotation at a given curl value. We also consider the special relativistic-like effects in this context. The findings are validated through a representative example.

We show that an exponential income distribution will emerge spontaneously in a peer-to-peer economic network that shares the publicly available technology. Based on this finding, we identify the exponential income distribution as the benchmark structure of the well-functioning market economy. However, a real market economy may deviate from the well-functioning market economy. We show that the deviation is partly reflected as the invalidity of exponential distribution in describing the super-low income class that involves unemployment. In this regard, we find, theoretically, that the lower-bound u of exponential income distribution has a linear relationship with (per capita) unemployment compensation. In this paper, we test this relationship for the United Kingdom from 2001 to 2015. Our empirical investigation confirms that the income structure of low and middle classes (about 90% of populations) in the United Kingdom exactly obeys exponential distribution, in which the lower-bound u is exactly in line with the evolution of unemployment compensation.

In a particle swarm with a fixed kinetic energy, the constituent particles move randomly and their velocity magnitudes follow a Maxwell distribution characterized by specific parameters. Within a certain time frame, particles in a sub-swarm may exhibit a bias in their movement direction. Thus, the particles may exhibit a special characteristic (biased random motion), where the group velocity in a particular direction remains constant u. For this biased particle swarm, composed of randomly moving particles with a fixed average speed c, particles have a higher probability of moving in a specific direction. Conversely, their likelihood of moving in all other directions is equally reduced. This study starts from the perspective of biased random walks and using Mathematica software proves that the diffusion rate of particles (in the reference frame R_u observed from R₀) in all directions is slower than that of an unbiased particle swarm with the same average speed c. Specifically, the degree of reduction is determined by the Lorentz-like factor. Lastly, we present the Ito equation for this biased random motion and provide associated verification examples. This study aims to serve as a reference for comprehending the underlying principles of the special relativity effect.

Heat dissipation from Li-ion batteries is a potential safety issue for large-scale energy storage applications. Maintaining low and uniform temperature distribution, and low energy consumption of the battery storage is very important. We studied the fluid dynamics and heat transfer phenomena of a single cell, 16-cell modules, battery packs, and cabinet through computer simulations and experimental measurements. The results show that the temperature distribution of single cell is relatively uniform when the cell is facing the air flow. In a module, very high air flow rate and large gap between the cells can reduce the cell temperature. A pack with a good thermally conductive case is very important to ensure good heat dissipation of the battery module. Due to limited space in the cabinet, additional air inlets and outlets can be opened outside of the cabinet to slightly lower the pack temperature. Installing fins outside the cabinet can also slightly reduce the temperature inside the cabinet. Liquid cooling medium, such as water, is much better than the air-cooling medium.

Polysaccharide from Ficus carica L. (FCP) exert multiple biological activities, as a biological macromolecule, the available knowledge about the specific structures and mechanisms of biological activity of purified 'Brunswick' fig polysaccharide is currently limited. In the present study, by chemical purification and characteristics identified via specific instruments, and then the impact of FCP on the immunomodulation activity in vitro and in vivo was examined. Structural char-acteristics showed that the molecular weight of the FCP was determined to be 127.5 kDa, the primary monosaccharides present in the FCP were galacturonic acid (GalA), arabinose (Ara), galactose (Gal), rhamnose (Rha), glucose (Glc), and xylose (Xyl) at a ratio of 0.321:0.287:0.269:0.091:0.013:0.011. Based on the investigation of in vitro immunomodulatory ac-tivity, FCP was found to stimulate the production of NO, TNF-α, and IL-6 and increased the pi-nocytic activity of macrophages. Further analysis revealed that FCP activated macrophages by interacting with toll-like receptor 4 (TLR4). Moreover, the in vivo test results indicate that FCP showed significant increase serum pro-inflammatory factors in immunosuppressed mice. Overall, this study suggests that FCP has the potential to be utilized as a novel immunomodulator in the pharmaceutical and functional food industries.

Retinal vein cannulation involves puncturing an occluded vessel on the micron scale. Even single millinewton force can cause permanent damage. An ophthalmic robot with a piezo-driven injector is precious enough to perform this delicate procedure, but the uncertain viscoelastic characteristics of the vessel makes it difficult to achieve the desired contact force without harming the retina. The paper utilizes a viscoelastic contact model to explain the mechanical characteristics of retinal blood vessels in order to tackle this issue. The uncertainty in the viscoelastic properties is considered an internal disturbance of the contact model, and an active disturbance rejection controller is then proposed to precisely control the contact force. The experimental results show that this method can precisely adjust the contact force at the millinewton level even when the viscoelastic parameters vary significantly (up to 403.8%). The root mean square (RMS) and maximum value of steady-state error are 0.32 mN and 0.41 mN. The response time below 2.51 s with no obvious overshoot.

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

This paper systematically examines Chinese academic discourse that concurrently addresses Indonesia and Timor-Leste, analysing 137 articles from the China National Knowledge Infrastructure (CNKI) and indexed by the Chinese Social Sciences Citation Index (CSSCI). The analysis reveals significant publication trends, particularly during periods of heightened geopolitical and economic engagement, such as the global expansion of the Belt and Road Initiative (BRI). It identifies predominant themes such as economic cooperation, security concerns, and historical-cultural dynamics. The findings highlight China’s strategic interests and leadership aspirations in Southeast Asia， providing insights into how Chinese scholars perceive and articulate China’s strategic interests and diplomatic efforts in the region involving Indonesia and Timor-Leste.

The integration of deep learning methods, especially Convolutional Neural Networks (CNN), and Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has been widely deployed in the field of radar signal processing. Nevertheless, these methods are frequently regarded as black-box models due to the limited visual interpretation of their internal feature representation and parameter organization. In this paper, we propose an innovative approach named C-RISE, which builds upon the RISE algorithm to provide a post-hoc interpretation technique for black-box models used in SAR Images Target Recognition. C-RISE generates saliency maps that effectively visualize the significance of each pixel. Our algorithm outperforms RISE by clustering masks that capture similar fusion features into distinct groups, enabling more appropriate weight distribution and increased focus on the target area. Furthermore, we employ Gaussian blur to process the masked area, preserving the original image structure with optimal consistency and integrity. C-RISE has been extensively evaluated through experiments, and the results demonstrate superior performance over other interpretation methods based on perturbation when applied to neural networks for SAR image target recognition. Furthermore, our approach is highly robust and transferable compared to other interpretable algorithms, including white-box methods.

Two-dimensional (2D) materials have been a research hot topic in the passed decades due to their unique and fascinating properties. Among them, mechanical properties plays an important role for their application. However, there lacks an effective tool for high-throughput calculating, analysing and visualizing the mechanical properties of 2D materials. In this work, we present, mech2d package, a highly automated toolkit for calculating and analysing second-order elastic constants (SOECs) tensor and relevant properties of 2D materials with considering their symmetry. In the mech2d, the SOECs can be fitted by both strain-energy and stress-strain approach, where the energy or strain can be calculated by first-principles engine, such as VASP. As a key feature, the mech2d package can automatically submit and collect the tasks from local or remote machine with robust fault-tolerant ability, make it suitable for high-throughput calculation. The present code has been validated by several common 2D materials, including graphene, black phosphorene, GeSe2 and so on.

The shortwave infrared Ge-Si photodetector will become the core device of the LiDAR optical receiver. In order to meet the urgent demand for photodetectors in the LiDAR field, we have designed and produced a 32×32 pixel Ge-Si photodetector array proposed and developed to meet the performance requirements of the detector array. A dark current detection system for fast scanning and detecting large-scale Ge-Si detector arrays is proposed and developed to achieve rapid detection of dark current in each pixel of the detector. The system was used to validate the main performance indicators of the detector array we designed, achieving rapid discrimination of array performance and rapid localization of damaged pixels. The scanning test results show that the average dark current of the detector array chip we designed is at the nano ampere level, and the proportion of bad points is less than 1%. The consistency of the array chip is high, which can meet the requirements of light detection at the receiving end of the LiDAR. This work laid the foundation for our subsequent development of a LiDAR prototype system.

Bacterial indole-3-acetic acid (IAA), an effector molecule in microbial physiology, plays an important role in plant growth-promotion. Here, we comprehensively analyzed about 7282 prokaryotic genomes representing diverse bacterial phyla, combined with root-associated metagenomic data to unravel the distribution of tryptophan-dependent IAA synthesis pathways and to quantify the IAA synthesis-related genes in the plant root environments. We found that 82.2% of the analyzed bacterial genomes were potentially capable of synthesizing IAA from tryptophan (Trp) or intermediates. Interestingly, several phylogenetically diverse bacteria showed a preferential tendency to utilize different pathways and tryptamine and indole-3-pyruvate pathways are most prevalent in bacteria. About 45.3% of the studied genomes displayed multiple coexisting pathways, constituting complex IAA synthesis systems. Furthermore, root-associated metagenomic analyses revealed that rhizobacteria mainly synthesize IAA via IAM and tryptamine (TMP) pathways and might possess stronger IAA synthesis abilities than bacteria colonizing other environments. The obtained results refurbished our understanding of bacterial IAA synthesis pathways and provided a faster and less labor-intensive alternative to physiological screening based on genome collections. The better understanding of IAA synthesis among bacterial communities could maximize the utilization of bacterial IAA to augment the crop growth and physiological function.

Meiosis is a specialized cell division that produces haploid gametes from diploid germ cells, and the phosphorylation activity of cyclin-CDK complexes and Polo-like kinase is required for synaptonemal complex (SC) disassembly and metaphase I exit. Here, we identified a novel protein MSCDK (meiotic substrate of cyclin dependent kinase) that functions as a substrate of CDK1 in initiating SC disassembly and metaphase I transition during meiosis prophase I in mice. Deletion of MSCDK caused germ cell death and infertility in males but not females. Mechanistically, we show that MSCDK is sparsely localized as discrete foci along synaptic homologous chromosomes from the early zygotene to the early diplotene, and we confirm that MSCDK can be phosphorylated by CDK1 and dephosphorylated by the cell cycle exit regulator phosphatase PP1α. We also provide evidence that MSCDK is essential for SC disassembly based on its dephosphorylation-related function, which apparently promotes HSPA2 nuclear recruitment.

Time and space are fundamental concepts for characterizing and understanding our world. Despite of continuous curiosity and extensive studies, the nature of time and space remains elusive, and the underlying quantum structure is unclear. Here we propose a molecular model based on energy space decomposition to incorporate time and space synthetically in a unified framework. In the proposed model, the multipole expansion of action mapped to energy modules in scalar, vector, and matrix forms, results in the generators of time, space, and a material framework, cloud. And the invariance of time, space and cloud transformation corresponds to the conservation of energy, momentum, and mass, respectively. The classification of energy modules reveals a periodicity of energy elements, which constructs a hierarchical world in a molecular framework with dynamics represented by energy transformations. Here the role of time and space could switch from each other, and motion is attributed to the coupling of particle with intermediate bosons, corresponding to energy transformations among different energy modules. The application on Bohr model demonstrates that this picture provides a consistent classical interpretation to the foundation of quantum mechanics, and suggests an atomic model for gravitation.

Defect detection plays a pivotal role in quality control for fabrics. In order to enhance the accuracy and efficiency of fabric defect detection, we have proposed the PRC-Light YOLO model for fabric defect detection and have established a detection system. Firstly, we add new convolution operators in Backbone for the YOLOv7 and integrate them with Extended-Efficient Layer Aggregation Network. This combination constructs a new feature extraction module that not only reduces the computational effort of the network model, but also extracts spatial features effectively. Secondly, we employ multi-branch dilated convolutions feature pyramid, and introduce lightweight upsampling operators to improve performance of the feature fusion network. This module achieves an expanded receptive field by generating real-time adaptive convolution kernels, allowing for the collection of crucial information from regions with a richer contextual context. To further minimize the computation during network model training, we adopt the HardSwish activation function. Finally, we apply the Wise-IOU v3 bounding box loss function as a dynamic non-monotonic focusing mechanism, which decreases adverse gradients from low-quality instances. We conduct data augmentation on real fabric dataset to raise the generalization capability of the PRC-Light YOLO model. Compared with the YOLOv7 model, numerous simulation experiments show that our proposed methods reduce the model’s parameters and computation by 18.03% and 20.53%, respectively. Simultaneously, there has been a 7.6% improvement in mAP.

This paper aims to investigate the coal thickness change area of the combined rock strata energy accumulation law. The method of connecting a uniaxial compression experiment with a theoret-ical analysis is used in this work. We employ a combination of coal and rock to carry out our studies. We investigate how different lithologies and ratios of coal-rock height affect the me-chanical properties of the mixture and the law governing energy accumulation. We have deter-mined the following facts: (1) The combination's peak strength and elastic modulus exceed that of coal and are inferior to that of rock but are nearer to that of coal. (2) When the coal-rock height ratios are dissimilar, the peak strength and modulus of elasticity of the combination show a negative correlation with the coal-thickness share, and the pre-peak energy accumulation and impact energy index of the combination shows a positive correlation with the coal-thickness share. (3) For the combination with the same coal-rock height ratio, the peak strength, elastic modulus, pre-peak energy accumulation, and impact energy index all increase with greater rock strength and elastic modulus. The presence of a hard rock layer affects the accumulation of pre-peak energy. ( 4 ) The stress in the surrounding rock gradually decreases as the coal thick-ness increases. In the area where coal thickness declines, the stress in surrounding rock is higher than that in the region where it thickens. The energy stored in the surrounding rock is directly proportional to the coal in the zone. Conversely, areas with thinner coal deposits exhibit a lower energy storage capacity in the surrounding rock than those with thicker coal deposits. The stress distribution of surrounding rock in coal thickness change is abnormal; substantial energy accu-mulation can swiftly initiate dynamic disasters, such as rock bursts. This study has important reference significance for preventing and controlling rock burst in coal thickness change areas.

Underwater target detection is widely used in various applications such as underwater search and rescue, underwater environment monitoring, and Marine resources survey. However, the visibility of the underwater environment and the accuracy of target detection can be affected by complex underwater light changes and unpredictable background noise. To address these issues, we propose an improved underwater target detection algorithm based on YOLOv8n. Our algorithm focuses on three aspects. Firstly, we replace the original C2f module with Deformable Convnets v2 to enhance the adaptive ability of the target region in the convolution check feature map and extract the target region's features more accurately. Secondly, we introduce SimAm, a non-parametric attention mechanism, which can deduce and assign three-dimensional attention weights without adding network parameters. Lastly, we optimize the loss function by replacing the CIOU loss function with the Wise-IOU loss function. To conduct our experiments, we create our own dataset of underwater target detection for experimentation. Meanwhile, we also utilized the Pascal VOC dataset to evaluate our approach. The [email protected] and [email protected]:0.95 of the original YOLOv8n algorithm on the underwater target detection were 88.6% and 51.8%, respectively, and the improved algorithm [email protected] and [email protected]:0.95 can reach 91.8% and 55.9%. The original YOLOV8n algorithm was 62.2% and 45.9% [email protected] and [email protected]:0.95 on the Pascal VOC dataset, respectively. The improved YOLOV8n algorithm [email protected] and [email protected]:0.95 were 65.7% and 48.3%, respectively. The floating-point computation volume of the model is reduced by about 6%. The above experimental results prove the effectiveness of our method.

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.

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

Objective: To investigate the efficacy of a magnetic resonance imaging (MRI) radiomics model in predicting colorectal cancer liver metastasis (CRLM). Methods: A total of 120 patients who underwent baseline MRI examination at the Affiliated Hospital of North Sichuan Medical College from June 2016 to August 2022 and were pathologically confirmed to have colorectal cancer (CRC) were randomly divided into a training group and a validation group. The clinical risk factors and MRI data of all patients were collected. Univariate and multivariate analysis were used to screen the clinically independent risk factors for CRLM. The radiomic features of each sequence were extracted from oblique axial or axial fat-free T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the optimal radiomic features of each sequence. Logistic regression was used to establish a prediction model of each sequence (T2WI and DWI models), a combined radiomics model (M) integrating the features of T2WI and DWI sequences, and a combined imaging-clinical model (U) combining the radiomic features of each sequence with clinically independent risk factors. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the predictive performance of each model. Results: Among the 120 CRC patients enrolled, 57 had liver metastasis, and 63 did not. The tumor markers carcinoembryonic antigen and carbohydrate antigen 19-9 were clinically independent risk factors for CRLM. Three optimal radiomic features were screened from T2WI and DWI sequences through LASSO regression analysis, respectively. The AUC values of the T2WI, DWI, M, and U models were 0.811, 0.803, 0.824, and 0.899 in the training group and 0.795, 0.798, 0.813, and 0.889 in the validation group, respectively. The predictive performance of the combined models was better than that of the single-sequence models. The U model performed best at predicting CRLM. Conclusion: An MRI radiomics model based on CRC primary lesions can predict CRLM well. Our combined model integrating the radiomic features of each sequence and clinically independent risk factors had the best predictive performance.

The current pneumonia epidemic could evolve into a pandemic on a global scale if not effectively contained. The COVID-19 virus possesses a 61-amino acid open reading frame resembling SARS-CoV virulence factor - ORF6 peptide. The isoleucine content is 15.9% in ORF6 of SARS-CoV versus 16.4% of that in SARS-CoV-2. Given the proton affinity in the carbonyl oxygen in isoleucine, augmented proton traffic can enhance proton-ion antiport and prompt cell swelling. Calorie restriction has been confirmed in animal studies to extend lifespan, and its underlying mechanism is not fully known. As the content of essential amino acids in the open reading frame of SARS-CoV-2 reaches 57.4%, a starch/vitamin diet served for short period of time does not give rise to essential amino acids and halts virion production, which could be adopted as prophylactic approach of many viral infections. Plant-based diet or fasting/boiled rice water can also minimize the intake of essential amino acids or all amino acids respectively. Furthermore, several proteins of SARS-CoV-2 possess high valine plus glycine content which is implicated in heart disease, justifying the aforementioned approaches.

The development of computational acoustics allows simulation of sound generation and propagation in complex environment. In particular, meshfree methods are widely used to solve acoustics problems through arbitrarily distributed field points and approximation smoothness flexibility. As a Lagrangian meshfree method, smoothed particle hydrodynamics (SPH) method reduce the difficulty in solving problems with deformable boundaries, complex topologies, or multiphase medium. The traditional SPH method has been applied in acoustic simulation. This study presents the corrective smoothed particle method (CSPM), which is a combination of SPH kernel estimate and Taylor series expansion. The CSPM is introduced as a Lagrangian approach to improve accuracy in solving acoustic wave equations in the time domain. Moreover, a boundary treatment technique based on the hybrid meshfree and finite difference time domain (FDTD) method is proposed to represent different acoustic boundaries with particles. To model sound propagation in pipes with different boundaries, soft, rigid, and absorbing boundary conditions are built with this technique. Numerical results show that the CSPM algorithm is consistent and demonstrates convergence with exact solutions. Main computational parameters are discussed, and different boundary conditions are validated to be effective for benchmark problems in computational acoustics.

It has been well known that the exponential distribution is the only continuous distribution that has the memoryless property. Here, we observe that, if the exponential distribution dominates an economy as a probability distribution of income acquisition, then the memoryless property imposes equal opportunities on agents in this economy to acquire earnings. Based on this observation, we propose to identify the emergence of an exponential income distribution as a potential necessary condition for guaranteeing the equality of opportunity. Together with other conditions (such as social and economic mobility), it would promote equal opportunities for income acquisition among citizens. Empirically, we employ the latest data available from four representative market-economy countries (the United Kingdom, the United States, Canada, and China) to demonstrate that the exponential distribution is a stylized feature of the income structure of the low- and middle-income class, which occupies the great majority of populations. By contrast, the top income classes in these countries obey the Pareto distribution. To validate the relationship between exponential distribution and equal opportunity, we empirically show how the income structure of the low- and middle-income class in China (from 1978 to 2015) evolved towards an exponential distribution after the market-oriented economic reformation.

Prior studies have focused on the overall behavior of randomly moving particle swarms. However, the characteristics of the stochastic-constrained particles that form ubiquitously within these swarms remain oblivious. This study demonstrates a generalized diffusion equation for stochastic-constrained particles that considers the velocity and location aggregation effects observed from their parent particle swarm (i.e., a completely random particle swarm). This equation can be approximated as the form of Schr\"odinger equation in the microcosmic case (low relative density) and describe the dynamics of the total mass distribution in the macrocosmic case (high relative density). The predicted density distribution of the particle swarm in the stable aggregation state is consistent with the total mass distribution of massive, relaxed galaxy clusters (at least in the range of r < r_s), preventing cuspy problems in the empirical Navarro-Frenk-White (NFW) profile. This study opens a window to observe the dynamics of stochastic-constrained particles from a third perspective, from which the aggregation effect of particles without gravitation can be saw.

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.

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

In this paper, four lithological parameters, i.e. thermal conductivity, particle size, porosity and saturation, are investigated by combining experimental observations with numerical simulations to study the influence laws and mechanisms of action on the combustion process of methane hydrate sediments. The variation of combustion characteristics parameters such as flame height, effective combustion ratio and dimensionless discharge water mass with the lithological parameters are studied. In addition, the combustion mechanism of lithologic parameters on methane hydrate deposits is revealed. Combining the experimental results and simulation calculations, to optimize the combustion of methane hydrate sediments, it is recommended to use methane hydrate sediment samples with high saturation and low thermal conductivity, while the oxidant concentration and porosity of methane hydrate sediment samples should be increased.

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.

As the oil industry increasingly turns to unconventional low-permeability and low-porosity reservoirs, precise post-fracture production prediction is a pivotal instrument in investment de-cision-making, formulation of energy policies, and promotion of environmental assessments. Nevertheless, despite extensive research spanning decades, the precise post-fracture production prediction based on logging parameters remains an intricate task. In this study, we gathered ex-tensive logging data and segmented the post-frac gas production during well testing on the first day to enrich the dataset. Nine pipelines were then architected using various techniques of data preprocessing, feature extraction, and advanced machine learning models. Hyperparameter op-timization was executed via the GridsearchCV. To assess the efficacy of diverse models, metrics including the coefficient of determination (R2), standard deviation (SD), and root mean square error (RMSE) were invoked. Among the several pipelines explored, the PS-NN exhibited excellent predictive capability in specific reservoir contexts (an R2 value of 0.94 and an RMSE of 48.15). In essence, integrating machine learning with logging parameters effectively assesses reservoir productivity at multi-meter formation scales. This strategy not only mitigates uncertainties en-demic to reservoir exploration but also equips petroleum engineers with monitoring on reservoir dynamics, thereby facilitating reservoir development. Additionally, this approach provides res-ervoir engineers with an efficient way of reservoir performance oversight.

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.

Hyperactivation of Janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3) signaling is an attractive therapeutic target for tumor therapy. Herein, forty-eight novel meridianin derivatives were designed and synthesized, and their anti-tumor activity were evaluated in vitro both for activity optimization and structure-activity relationship (SAR) study. The results indicated that most derivatives exhibited significantly improved anti-tumor activity, especially for compound 6e. The compound 6e contains an isothiouronium linked by an alkyl chain consisting of 6 carbon atoms with IC50 ranging from 1.11 to 2.80 μM on various cancer cell lines. Consistently, 6e dose dependently induced the apoptosis of A549 and DU145 cells, in which STAT3 are constitutively active. Western blotting assays indicated that the phosphorylation levels of JAK1, JAK2 and STAT3 were inhibited by 6e at 5 μM without significant change in total STAT3 level. Moreover, 6e also suppressed the expressions of STAT3 downstream genes, including c-Myc, Cyclin D1 and Bcl-XL at 10 μM. An additional in vivo study revealed that 6e at the dose of 10 mg/kg could potently inhibit the DU145 xenograft tumor without obvious body-weight loss. These results clearly indicate that 6e could be a potential anti-tumor agent by targeting JAK/STAT3 signaling pathway.

Background: Diabetic retinopathy (DR) is one of the most prominent pathological microvascular complications in diabetes. A series of studies reported that vitamin D deficiency was associated with increased prevalence of retinopathy in diabetic patients but the results were inconsistent. In this study we focused on evaluating the relationship between vitamin D deficiency and DR by conducting a meta-analysis of observational studies. Methods: Systematic computerized searches were performed in PubMed, MEDLINE, and the Cochrane Library for relevant original articles till November 20, 2016. The pooled odds ratios (ORs) with corresponding confidence intervals (CIs) were calculated to assess the associated value of vitamin D deficiency to the risk of DR. 9 studies including 6332 participants were subjected to final analysis. Results: The results indicated that vitamin D deficiency increases the risk of DR (OR = 1.57, 95% CI 1.32-1.87) with a little heterogeneity (I2 = 23%). In addition, the subgroup analysis demonstrated that there were obvious heterogeneities in T2DM (I2 = 47.8%). Sensitivity analysis showed that the results were relatively stable and reliable. Conclusion: our meta-analysis demonstrated that vitamin D deficiency could increase the risk of DR.

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.

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.

Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA), including expert system (EPS), artificial neural network (ANN), fuzzy theory, rough sets theory (RST), grey system theory (GST), swarm intelligence (SI) algorithms, data mining technology, machine learning (ML), and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as well as references and guidance for researchers to choose optimal approach to achieve DGA-based fault diagnosis and decision of the large oil-immersed power transformers in preventive electrical tests.

Large-scale volumetric fracturing is generally used during shale gas development. The return rate of fracturing fluid is low, and a large amount of slickwater will be retained in the reservoir. The adsorption and desorption of partially hydrolyzed polyacrylamide (HPAM), an additive commonly used in slickwater, on the surface of shale was studied using Longmaxi Shale from the Sichuan Basin. The experimental results showed that the mass ratio of the HPAM solution to shale reached saturation adsorption at 20:1 when the concentration of HPAM solution was 1000 mg/L and 25:1 when the concentration of HPAM solution was 500 mg/L. The mass ratio of the HPAM solution to shale was fixed at 25:1, and the adsorption equilibrium was reached at a HPAM concentration of 1000 mg/L when the aqueous solution temperature was 30°C and 800 mg/L when the aqueous solution temperature was 60°C. The Langmuir adsorption model yielded a better fit than the Freundlich adsorption model. The adsorption equilibrium time at 30°C was at 60 min for a HPAM concentration of 500 mg/L, while for a concentration of 1000 mg/L, it was at 90 min. The adsorption equilibrium time at 60°C was 40 min for a HPAM concentration of 500 mg/L, whereas it was 60 min for a HPAM concentration at 1000 mg/L. The pseudo-second order kinetics model yielded better fits than the pseudo-first order kinetics model. The adsorption of HPAM on shale was strong, and the adsorbed HPAM resembled cobwebs adhering to the shale surface. HPAM on the surface of shale after adsorption could resist the desorption capacity of water. However, when the amount of adsorbed HPAM on shale increased significantly, the amount of residual HPAM on the surface of the shale decreased rapidly during desorption in deionized water. The desorption of HPAM on the shale surface followed a modified desorption model. The higher the concentration of HPAM adsorbed on the shale surface was, the easier it was to desorb, the easier it was to be removed from the shale.

In this nano era, nanomaterials and nanostructures are popular in developing novel functional materials. However, the combinations of nanoproducts with materials at micro and macro scale can open new routes for conceiving novel materials with an improved or even new functional performances. In this study, a brand-new hybrid, containing both nanofibers and particles having a microsize, was fabricated using a sequential electrohydrodynamic atomization (EHDA) process. Firstly, the microparticles loaded with drug (berberine hydrochloride, BH) molecules in the cellulose acetate (CA) were fabricated using a solution electrospraying process. Later, these microparticles were suspended into a co-dissolved solution containned BH and a hydrophilic polymer (polypyrrolidone, PVP), and were co-electrospun into the nanofiber/microparticle hybrids. The EHDA processes were clearly recorded, and the resultant products showed a typical hybrid topography, with microparticles distributed all over the nanofibers, which was demonstrated by SEM assessments. FTIR and XRD demonstrated that the components within the hybrids were presented in an amorphous state and have fine compatibility with each other. In vitro dissolution tests verified that the hybrids were able to provide the designed dula-step drug release profiles, a combination of the fast release step of BH from the hydrophilic PVP nanofibers through an erosion mechanism and the sustained release step of BH from the insoluble CA microparticles via a typical Fickian diffusion mechanism. The present protocols pave a new way for developing trans-scale functional materials.

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.

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.

InGaN-based red micro light-emitting diodes (µLEDs) of different sizes prepared in this work. The red GaN epilayers were grown on a 4-inch sapphire substrate through metal organic chemical vapor deposition (MOCVD). Etching, sidewall treatment, and p- and n- contact deposition was involved in the fabrication process. Initially, the etching process would cause undesirable damages to the GaN sidewalls, which leads to an increase in leakage current. Hence, we employed KOH wet treatment to rectify the defects on the sidewalls and conducted a comparative and systematic analysis on electrical as well as optical properties. We observed that the µLEDs with a size of 5µm exhibited substantial leakage current, which was effectively mitigated by the application of KOH wet treatment. In terms of optical performance, the arrays with KOH demonstrated improved Light Output Power (LOP). Additionally, while photoelectric performance exhibited a decline with increasing current density, the devices treated with KOH consistently outperformed their counterparts in terms of optoelectronic efficiency. It is noteworthy that the optimized devices displayed enhanced photoelectric characteristics without significantly altering their original peak wavelength and FWHM. Our findings point to the elimination of surface non-radiative recombination by KOH wet treatment, thereby enhancing the performance of small-sized red µLEDs which has significant potential in realizing full-color micro-displays in near-eye projection applications.

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

Simple summary: The noninvasive differentiation of hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC) remains challenging. In recent years, the number of studies on the application of radiomics in liver cancer has grown dramatically. However, there have been very few studies on the differentiation of HCC from ICC based on multisequence magnetic resonance imaging (MRI) radiomics. This study aimed to investigate the efficacy of a radiomic model based on preoperative fat suppression T2-weighted imaging (FS-T2WI) and dynamic contrast-enhanced MRI features in the arterial phase (A) and portal venous phase (P) for the differentiation of HCC from ICC. Abstract: The purpose of this study was to investigate the efficacy of magnetic resonance imaging (MRI) radiomics in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). The clinical and MRI data of 129 pathologically confirmed HCC cases and 48 ICC cases from April 2016 to December 2021 at the Affiliated Hospital of North Sichuan Medical College were retrospectively analyzed. Included cases were randomly divided at a ratio of 7:3 into a training group of 124 cases (90 HCC cases and 34 ICC cases) and a validation group of 53 cases (39 HCC cases and 14 ICC cases). Radiomic features were extracted from axial fat-suppression T2-weighted imaging (FS-T2WI) and axial arterial-phase (A) and portal-venous-phase (P) dynamic contrast-enhanced MRI sequences, and the corresponding datasets were generated. The least absolute shrinkage and selection operator (LASSO) method was used to select the best radiomic features. Logistic regression was used to establish a radiomic model for each sequence (FS-T2WI, A, and P models) and a joint model (M model) integrating the radiomic features of all the sequences. The performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC). The AUC of the FS-T2WI, A, P, and M models for distinguishing HCC from ICC was 0.693, 0.863, 0.818, and 0.914 in the training group and 0.690, 0.784, 0.727, and 0.802 in the validation group, respectively. The results of this study suggest that MRI-based radiomics may help noninvasively differentiate HCC from ICC. The model integrating the radiomic features of multiple sequences showed further improvement in performance.

Laminitis is considered as an important underlying cause of lameness diseases, yet its specific pathogenesis remains unclear. Autophagy is an intracellular degradation mechanism that controls recycling of membrane-associated integrin and may aid in the progression of metabolic diseases. But the significance of autophagy for initiation and development of laminitis is unknown. The present study aimed to explore autophagy activity in the laminar tissue of dairy cows with oligofructose-induced laminitis. Twelve healthy non-pregnant Holstein cows were randomly divided to 2 groups of 6 cows each, entitled the control group and the oligofructose overload group (OF group), respectively. At 0 h, cows in OF group were gavaged with oligofructose (17 g/kg BW) dissolved in warm deionized water (20 mL/kg BW) through oral rumen tube, and dairy cows in control group were gavaged with the same volume of deionized water by the same method. At -72 h before perfusion as well as 0 h, 6 h, 12 h, 18 h, 24 h, 36 h, 48 h, 60 h, and 72 h after perfusion, clinical evaluations in both groups were monitored. After 72 h, laminar tissues of dairy cows in both groups were collected to examine genes and proteins. We found the significantly higher (P<0.05) levels of mRNA ATG5, ATG12, and Becilin1, but P62 and mTOR were extensively lower (P<0.01) in the laminar tissue of the OF group than the control group. Protein expression level of Becilin-1 was higher significantly (P<0.05), and the protein expression level of LC3II was lower significantly (P<0.05) in OF group than control group. However, the expression of P62 reduced (P>0.05) non-significantly in OF group than control group. The distribution of Beclin1 protein in laminar tissue increased (P<0.01) significantly, and distribution of P62 protein decreased (P<0.05) significantly in OF group than control group. In conclusion, laminar tissue damage occurred during the onset of laminitis, which promoted the occurrence of autophagy, and confirmed that autophagy was involved in the regulation and pathogenesis of laminitis in dairy cows.