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

In this paper, we design two inertial-type subgradient extragradient algorithms with line-search process for solving the pseudomonotone variational inequality problems (VIPs) and common fixed-point problem (CFPP) of finite Bregman relatively nonexpansive mapping and a Bregman relatively demicontractive mapping in p-uniformly convex and uniformly smooth Banach spaces, which are more general than Hilbert spaces. Under mild conditions, we derive weak and strong convergence of the suggested algorithms to a common solution of the VIPs and CFPP, respectively. Additionally, an illustrated example is furnished to back up the feasibility and implementability of our proposed methods.

Endoscopic retrograde cholangiopancreatography (ERCP) is a routinely used therapeutic procedure for the biliary and pancreatic diseases. Population aging may increase the typical indications of ERCP and come with more complexity and difficulties, especially in cannulation. This study aimed to evaluate the incidence, causes, and management of difficult biliary cannulation during ERCP in super-aged patients and the role of difficult cannulation as a risk factor for adverse events. A total of 614 patients, underwent ERCP, were prospectively studied as a cohort and divided into two groups based on their age. There were 146 patients aged 80 years or older in group A and 468 patients aged less than 80 years in group B. The primary outcome measures were the difficulty grade of papilla cannulation, clinical outcomes, and ERCP-related complications in the two groups. The adverse events were analyzed using logistic regression for patient age, co-morbidities, indications, and cannulation difficulty grade variables. There was no difference in the incidence of difficult cannulation between the two groups (32.9% vs. 34.4%, p=0.765) though, as expected, super-aged Group A had a higher prevalence of periampullary diverticulum (29.5% vs. 16.7%, p=0.001). The technical cannulation success rate was (96.6% vs. 96.8%, p= 0.54). All used cannulation techniques in the elderly group were efficient and safe. Logistic regression showed that age ≥80 was not associated with increased adverse events; however, difficult cannulation (adjusted odds ratio [AOR]=3.478; 95% confidence interval [CI]=1.877, 6.442; p<0.001) and CCI ≥2 (AOR=1.824; 95% CI=0.993, 3.349; p=0.045) were more likely to have adverse events. Age ≤65 (AOR=3.460; 95% CI=1.511, 7.922; p=0.003), female gender (AOR=2.362; 95% CI=1.089, 5.124; p=0.030), difficult cannulation (AOR=4.527; 95% CI=2.078, 9.860; p<0.001), and patients with cholangitis (AOR=3.261; 95% CI=1.204, 8.832; p=0.020) were strongly associated with increasing Post-ERCP Pancreatitis (PEP). Advanced age has not proved to be a risk factor of difficult cannulation, and secondary cannulation techniques can be safely and efficaciously utilized for this group. CCI ≥2 and difficult cannulation are associated with increased overall adverse events rate while age ≥80 factor is not.

Cancer immunotherapy targeting immune checkpoints has exhibited promising clinical outcomes in many cancers, but it offers only limited benefits for pancreatic cancer (PC). Cancer stem cells (CSCs), a minor subpopulation of cancer cells, play important roles in tumor initiation, progression, and drug resistance. Accumulating evidence suggests that CSCs employ immunosuppressive effect to evade the immune recognition. However, clinical implications of the associations among CD8+ T cells infiltration, programmed death receptor ligand-1 (PD-L1) expression, and CSCs existence are poorly understood in PC. Immunostaining and quantitative analysis were performed to assess CD8+ T cells infiltration, PD-L1 expression, and their relationship with CD44+/CD133+ CSCs and disease progression in PC. CD8+ T cells infiltration was associated with better survival while PD-L1 expression was correlated with PC recurrence. Both the low CD8+ T cells infiltration/high PD-L1 expression group and the high CD8+ T cells infiltration/high PD-L1 expression group show high levels of CD44+/CD133+ CSCs, but patients with low CD8+ T cells infiltration/high PD-L1 expression had worse survival and higher recurrence risk than those with high CD8+ T cells infiltration/high PD-L1 expression. Moreover, CD8+ T cells infiltration could reduce unfavorable prognostic effect of high co-expression of PD-L1 and CD44/CD133. Our study highlights an interaction among CD8+ T cells infiltration, PD-L1 expression, and CD44+/CD133+ CSCs existence, which contributes to PC progression and immune evasion.

In a p-uniformly convex and uniformly smooth Banach space, let the pair of variational inequality and fixed point problems (VIFPPs) consist of two variational inequality problems (VIPs) involving two uniformly continuous and pseudomonotone mappings and two fixed point problems implicating two uniformly continuous and Bregman relatively asymptotically nonexpansive mappings. This article designs two parallel subgradient-like extragradient algorithms with inertial effect for solving this pair of VIFPPs, where each algorithm consists of two parts which are of symmetric structure mutually. Under mild registrations, we prove weak and strong convergence of the suggested algorithms to a common solution of this pair of VIFPPs, respectively. Lastly, an illustrative example is furnished to verify the applicability and implementability of our proposed approaches.

The twisted Wang transform distribution family, defined as the composition of parameter shifted inverse CDF function with an original CDF function, is found to be most suitable for matching low shape factor distributions, characterizing hard to fit or to simulate reinsurance portfolio losses for some perils from our previous study. Among them, the best form for matching a hard-to-fit empirical loss distribution for a specific peril, is the Exponential Fractional Extra Power 0 Distribution in (0,1) with CDF:.The simplest yet still a good form of this family is the Transformed Hyperbolic Tangent Distribution with CDF:,which has analytical formulas for the moments. The twisted Wang transform distribution family is compared and confirmed to be superior to all other well-known distribution families through extensive numerical optimization practice, distribution forms guesses, and computer-aided exploration experiments.

Natural image matting is an essential technique for image processing that enables various applications, such as image synthesis, video editing, and target tracking. However, the existing image matting methods may fail to produce satisfactory results when computing resources are limited. Sampling-based methods can reduce the dimensionality of the decision space and therefore reduce computational resources by employing different sampling strategies. While these approaches reduce computational consumption, they may miss an optimal pixel pair when the number of available high-quality pixel pairs is limited. To address this shortcoming, we propose a novel multi-criterion sampling strategy that avoids missing high-quality pixel pairs by incorporating multi-range pixel pair sampling and high-quality samples selection method. This strategy is employed to develop a multi-criterion matting algorithm via Gaussian process, which searches for the optimal pixel pair by using the Gaussian process fitting model instead of solving the original pixel pair objective function. Experimental results demonstrate that our proposed algorithm outperforms other methods even with 1% computing resources, and achieves alpha matte results comparable to those yielded by the state-of-the-art optimization algorithms.

The group delay response of chirped fiber Bragg gratings (CFBG) written in polarization-maintaining fiber can be measured using the beat spectrum of the reflections from the two polarization axis, with a resolution and reproducibility better than 50 fs. The method is theoretically described, and we analyze the effect of group delay ripples (GDR) on the performance of a stretcher-compressor pair used in chirped pulse amplification systems. Ripples with a spectral period of the order of the pulse bandwidth are the most deleterious. Those are readily captured with our method, despite the limit on resolution due to the fiber polarization beat length. As a rule of thumb, the GDR should not exceed half the pulse duration. The reconstructed phase of the CFBG is also used to predict the pulse compression performance for a given device. Measurement of GDR as low as 161 fs is experimentally demonstrated.

Neuroinflammation and brain oxidative stress are recognized as significant contributors to hypertension including salt sensitive hypertension. Extracellular vesicles (EVs) play an essential role in intercellular communication in various situations, including physiological and pathological ones. Based on this evidence, we hypothesized that EVs derived from the brains of hypertensive rats with salt sensitivity could trigger neuroinflammation and oxidative stress during hypertension development. To test this hypothesis, we compared the impact of EVs isolated from the brains of hypertensive Dahl Salt Sensitive rats (DSS) and normotensive Sprague Dawley (SD) rats on inflammatory factors and mitochondrial reactive oxygen species (mtROS) production in primary neuronal cultures and brain cardiovascular relevant regions, including the hypothalamic paraventricular nucleus (PVN) and lamina terminalis (LT). We found that brain-derived DSS-EVs significantly increased mRNA levels of proinflammatory cytokines (PICs) and chemokines, including TNFα, IL1β, CCL2, CCL5, and CCL12, as well as the transcriptional factor NF-κB in neuronal cultures. DSS-EVs also induced oxidative stress in neuronal cultures, as evidenced by elevated NADPH oxidase subunit CYBA coding gene mRNA levels and persistent mtROS elevation. When DSS-EVs were injected into the brains of normal SD rats, mRNA levels of PICs, chemokines, and the chronic neuronal activity marker FOSL1 were significantly increased in the PVN and LT. Furthermore, DSS-EVs caused mtROS elevation in brain PVN and LT, particularly in neurons. Our study reveals a novel role for brain-derived EVs from hypertensive rats in triggering neuroinflammation, upregulating chemokine expression, and inducing excessive ROS production. These findings provide insight into the complex interactions between EVs and hypertension-associated processes, offering potential therapeutic targets for hypertension-linked neurological complications.

Methylsilsesquioxane aerogels with uniform mesopores have been facilely prepared via a sol–gel process followed by microwave drying with methyltrimethoxysilane (MTMS) as precursor, hydrochloric acid (HCl) as catalyst, water and methanol as solvents, hexadecyltrimethylammonium chloride (CTAC) as surfactant and template and propylene oxide (PO) as gelation agent. The microstructure, chemical composition and pore structures of the resultant MSQ aerogels were investigated in detail to achieve controllable preparation of MSQ aerogels, and the thermal stability of MSQ aerogels was also analyzed. The gelation agent, catalyst, solvent and microwave power have important roles on pore structures of MSQ aerogels. Meanwhile, microwave drying method is found to not only have a remarkable effect on improving production efficiency, but also be conducive to avoid the collapse of pore structure especially micropores during drying. The resulting MSQ aerogel microwave-dried at 500 W possesses a specific surface area up to 821 m2/g and a mesopore size of 20 nm, and displays good thermal stability.

This study was to identify clinical cancer biomarkers for recurrent gastric cancer survivors using artificial intel-ligence. From a hospital-based cancer registry database in Taiwan, the datasets of the incidence of recurrence and clinical risk features were included in 2476 gastric cancer survivors. We benchmarked Random forest with MLP, C4.5, AdaBoost, and Bagging algorithms on metrics and leveraged synthetic minority oversampling technique (SMOTE) for imbalanced dataset issues, cost-sensitive learning for risk assessment, and SHapley Additive ex-Planations (SHAP) for feature importance analysis in this study. Our proposed Random forest outperformed the other models with an accuracy of 87.9%, a recall rate of 90.5%, an accuracy rate of 86% and F1 of 88.2% on re-current category by a 10-fold cross-validation in a balanced dataset. We identified clinical features of recurrent gastric cancer, which are the top five features, stage, number of regional lymph node involvement, Helicobacter pylori, BMI(body mass index), and gender, which significantly affect the prediction model's output, are worth paying attention to in the following causal effect analysis. Using an artificial intelligence model, the risk factors for recurrent gastric cancer could be identified and cost-effectively ranked according to their feature importance. In addition, they should be crucial clinical features to provide physicians with the knowledge to screen high-risk patients in gastric cancer survivors as well.

The Epithelial-Mesenchymal-Transition (EMT) phenotype, identified as a significant clinical indicator in cancer, manifests as a biological process where cells transition from epithelial to mesenchymal characteristics. Physiologically, EMT plays a crucial role in tissue remodeling, promoting healing, repair, and responding to various tissue damages. This study investigates the impact of BNE-RRC on oral cancer cells (KB) and reveals its significant effects on cancer cell growth, migration, invasion, and EMT. BNE-RRC induces the epithelial-like morphology in KB cells, effectively reversing EMT to Mesenchymal-Epithelial Transition (MET). Extraordinarily, sustained culture of cancer cells with BNE-RRC for 14 days maintains an epithelial status even after treatment withdrawal, suggesting BNE-RRC as a potential therapeutic agent for cancer. These findings highligh the promise of BNE-RRC as a comprehensive therapeutic agent in cancer treatment by inhibiting cancer cell growth, migration, and invasion, while also orchestrating a reversal of the EMT process. The study proposes that BNE-RRC could be effective agent for cancer treatment.

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

Tourism activities generally have a ∩-type lock on the level of tourism ecological security in an area, but when applied to the border areas of China, there are certain specificities in the spatial evolution of tourism ecological security (TES) compared to traditional findings. This paper measures tourism ecological security in China’s border areas from 2009 to 2020 by using the DPSIR model with the superefficient SBM-DEA and analyzes the spatial differences, evolutionary characteristics, and driving factors of tourism ecological security in border areas by using Pearson’s correlation coefficients, center of gravity models, and geographic probes: (1) The overall tourism ecological security index of China’s border provinces is relatively good. Tourism activities do not completely affect the traditional “∩ lock” of the border provinces. The tourism ecological security level of the border provinces presents three spatial-temporal changes (“∩” type, “U” type, “\” type) and four evolution trends (“high–high–high”, “middle–middle–medium”, “medium–low–low”, and “low–low–low”). (2) The overall tourism ecological security level in border areas is polarized between high and low levels, and the ecological security efficiency of the three large areas is spatially characterized as “Southwest Area &gt; Northeast Area &gt; Northwest Area”, and the center of gravity of ecological security is mostly concentrated in Xinjiang, Tibet, and Neimenggu, where the ecological security level is higher. (3) Social and environmental factors are the main factors that influence tourism ecological security in border areas, while economic factors account for a smaller proportion. Accordingly, this thesis also proposes the driving mechanism of the ecological security of tourism sites in border areas in China with a view to providing theoretical support for policy formulation.

Taiwan's bed and breakfast (B&B) development has been more than 25 years ago, from the first generation of retirement to the B&B industry, serving tourists from all over the world accom-modation, providing breakfast and accommodation mode to the present, after the change of employees from the second generation, more and more attention is paid to the cultivation and cultivation of business ability. With the advent of the era of AI technology networking, the ca-pabilities required for B&B operation are more focused on all aspects of service, and the good marketing ability of B&B can promote a green chimney-free tourism economy, which is also a favorite industry of various governments and the public. This study explores the basic vocational competency indicators required for running a B&B, with (1)EQ emotion management skills, (2)Financial management ability, (3)(SK) technical skills, and (4)Marketing and promotion management capabilities. Through the study method, the K-S Z test was determined by the con-sensus conclusion of expert reliability and validity p value

Meat serves as a vital component of the human diet, offering a rich source of protein and essential trace elements. China stands as both a significant producer and consumer of meat on a global scale, leading the world in terms of total meat production and consumption. As the standard of living within the country continues to rise, there is a growing emphasis on the nutritional value and safety of meat consumption. The tenderness of meat is a critical factor influencing its overall quality. Traditionally, tenderness has been assessed through shear force testing, a method that is inherently destructive, inefficient, and results in considerable sample wastage. In light of these drawbacks, non-destructive testing techniques have emerged as a preferred alternative, promising greater accuracy, efficiency, and convenience without compromising the integrity of the samples. This paper delves into the application of five advanced non-destructive testing technologies in the realm of meat tenderness assessment. These include near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, airflow optical fusion detection, and nuclear magnetic resonance detection. Each technology is scrutinized for its respective strengths and limitations, providing a comprehensive overview of their current utility and potential for future development. Moreover, the integration of these techniques with the latest advancements in artificial intelligence (AI) technology is explored. The fusion of AI with non-destructive testing offers a promising avenue for the development of more sophisticated, rapid, and intelligent systems for meat tenderness evaluation. This integration is anticipated to significantly enhance the efficiency and accuracy of quality assessment in the meat industry, ensuring a higher standard of safety and nutritional value for consumers. The paper concludes with a set of technical recommendations aimed at guiding the future direction of non-destructive, AI-enhanced meat tenderness detection, thereby contributing to the ongoing improvement of the meat industry in China and beyond.

Anode bonding is a widely used method for fabricating devices with suspended structures, and this approach is often combined with deep reactive ion etching (DRIE) for releasing the device. However, the DRIE process with a glass substrate can potentially cause two critical issues: heat accumulation on the suspended surface and charging effects resulting from the reflection of charged particles from the glass substrate. In particular, for torsional bars with narrow width, the heat accumulated on the suspended surface may not dissipate efficiently, leading to photoresist burning and subsequently resulting in the fracture of the torsional bars. Moreover, once etching is finished through the silicon diaphragm, the glass surface becomes charged, and incoming ions are reflected towards the back of the silicon, resulting in the etching of the back surface. To address these issues, we proposed a method of growing silicon oxide on the back of the device layer. By designing, simulating, and fabricating electrostatic torsional micromirrors with common cavity silicon-on-glass (SOG) structures, we successfully validated the feasibility of this approach. This approach ensures effective heat dissipation on the suspended surface, even when the structure is over-etched for an extended period, and enables the complete etching of torsional bars without adverse effects due to the overheating problem. Additionally, the oxide layer can block ions from reaching the glass surface, thus avoiding the charging effect commonly observed in SOG structures during DRIE.

Objectives: In order to solve the problem that most of the existing research focuses on the binary tactile attributes of objects,which ignores the tactile attribute strength and category recognition,an attribute strength and category recognition method based on convolutional neural network matrix-label is proposed. Methods:Firstly,in the data preparation stage,we preprocess the raw data and determine the matrix labels to build the haptic dataset.Secondly,in the feature extraction stage,we fuse the haptic data of two fingers and use the convolutional neural network to extract the attribute strength features.Finally,in the attribute strength and category recognition stage,all channel haptic data is fused to predict the attribute strength and category.Results:We compared with the multi-label convolutional neural network method in terms of elastic strength,hardness strength and category,and compared the attribute strength recognition capabilities of the two methods using novel objects outside the haptic dataset.The results show that the accuracy of the last 20 iterations of the matrix-label method has an average elastic strength of 96.73%,hardness strength of 97.34%,and category of 96.67%.The performance is better.When the Euclidean distance between the prediction of the novel object and the real label is less than 1,the accuracy of the elastic strength is best to reach 100%,and the hardness strength is best to reach 100%.The performance is better. Conclusions:The effectiveness of the method has been verified.Comparing with the convolutional neural network method,our method can effectively recognize the attribute strength and category of objects.

In GNSS/IMU integrated navigation systems, factors such as satellite occlusion and non-line-of-sight conditions can lead to degradation of satellite positioning results, Subsequently affecting the overall accuracy of the integrated navigation system. To address this issue and ef-fectively utilize historical pseudorange information from satellites, this paper proposes a graph optimization-based GNSS/IMU model with virtual constraints. These virtual constraints are con-structed using satellite ‘s position from previous time step, the rate of change of pseudoranges, and ephemeris data. This virtual constraint can serve as an alternative solution for individual satellites in case of signal anomalies, ensuring the integrity and continuity of the graph optimi-zation model. Additionally, this paper conducts an analysis of the graph optimization model constructed using these virtual constraints, comparing it with traditional integrated navigation graph optimization model, and analyzes and reconstructs the marginalization process based on these virtual constraints. The experimental results, compared with tightly coupled Kalman fil-tering and the original graph optimization method on a set of real-world data, demonstrate that the introduction of virtual pseudoranges maintains high positioning accuracy. The RMSE error between it and the original graph optimization remains within 5%, affirming the high feasibility of this approach.

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

We study a two-echelon supply chain made up of a supplier and a manufacturer, both of which can reduce their component/product carbon emissions. With the vertical technology spillovers, we explore the optimal decisions of centralized and decentralized supply chains with price dependent demand and propose coordination strategy for the decentralized supply chain. Considering the cost contraction effectiveness of the technology spillovers, the centralized and decentralized game theoretic models of a two-echelon supply chain are developed to investigate optimal decisions of pricing and carbon emissions reduction. Through a systematic comparison and numerical analysis, we show that the profits of both players and the entire supply chain improve with the effect of technology spillovers increasing. Carbon emissions reduction will be taken by various protective measures so that the supplier and the manufacturer who do not innovate can hardly share the results of innovating via the “free-riding” methods when the technology spillover is relatively small. We also propose a revenue-cost sharing contract through bargaining to enhance the performance of the decentralized supply chain.

With the increase of global human activities, a large number of technogenic magnetic particles (TMPs) generated by industrial activities such as coal combustion, traffic and so on enter sediments on continental shelves. However, there is currently a lack of understanding of the spatiotemporal distribution of TMPs on continental shelves, as well as the sedimentary effects they cause. This review work comprehensively analyzes the source, morphology, composition, and spatiotemporal distribution characteristics of TMPs. Then it elucidates their magnetic contribution to sedimentary environments in continental shelf seas, as well as the influence of heavy metals and active iron. At the same time, the existing problems and future development directions of TMPs on continental shelves are summarized.

The excessive vibration caused by crowds walking across footbridges has attracted great public concerns in the past few decades. This paper presents, from considering the dynamic characteristics of the bipedal crowd model, a new stability limit criterion based on the bipedal excitation model. The stability limit can be used to estimate the upper boundary of crowd size. In addition, the dynamic stable performances of a structure, under a certain walking crowd size, can be predicted by the stability criterion. This proposed mechanism provides an alternative comprehension how crowd excite the excessive sway motion with a large-span structure.

Hydrothermal carbonization of cellulose was examined at 240 ℃ for 1 h. Ammonium sulfate and thiourea were selected as the doping sources of inorganic nitrogen and organic nitrogen for the preparation of supercapacitor carbon. The effect of boric acid on the properties of the resulting hydrochar after KOH activation was examined. The results showed that the proportion of functional groups and the specific surface area of the activated hydrochar would be reduced after the addition of boric acid, and the pore-forming process of the micropores would be inhibited. The hydrochar obtained from the reaction of cellulose and organic nitrogen compounds had better pore size distribution and electrochemical properties after activation. The largest specific surface area (952.27 m2 g-1) was obtained when only thiourea was used as the only doping source. In the three-electrode system, the specific capacitance resulting activated hydrochar reached 236.25 F g-1 at a current density of 1 A g-1. After 20,000 cycles of charging and discharging at a current density of 10 A g-1, the capacitance retention rate reached 99.96%. Therefore, this study proves that the supercapacitor carbon with good electrochemical properties could be obtained by the direct reaction of cellulose with organic nitrogen compounds.

Aiming at the problem of low charging efficiency caused by the scattered sensor nodes in traditional wireless rechargeable sensor networks (WRSNs), a UAV-assisted WRSN Online Charging Strategy Based on Dynamic Queue and Improved K-means (UOCS) is proposed. The scheme assumes that the energy consumption of nodes is unpredictable, and only generates charging requests when the energy is lower than a threshold, and performs on-demand responses to nodes that issue charging requests. The scheme combines the characteristics of one-to-one charging of UAVs, the selection and allocation timing of waiting queues and the number of UAVs, and the improved K-means partitioning based on space-time coordination(SPKM), which simplifies the problem of coordinated charging of multiple UAVs and maximizes energy. Using the efficiency and charging success rate, the optimal charging trajectory can be found under the constraint that the node will not starve to death due to power shortage. Finally, a simulation comparison experiment is carried out with the existing UAV charging scheduling strategy. UOCS achieves the optimal node survival rate with low algorithm complexity.

When there are multiple key strata in the overburden of deep coal seam and the surface subsid-ence coefficient after mining is small, it indicates that the overlying key strata fail to break com-pletely after mining. On this occasion, the stress concentration on the working face occurs easily, which in turn leads to the occurrence of dynamic disasters such as rock burst. This study adopted a comprehensive analysis method of field monitoring and numerical simulation to explore the in-fluence of key stratum on the evolution law of mining-induced stress in the working face. Dis-tributed optical fiber sensor (DOFS) and surface subsidence GNSS monitoring system were re-spectively arranged inside and at the mouth of the ground observation borehole. According to the monitoring results of strain obtained from DOFS, the height of broken stratum inside the overlying strata was obtained; according to the monitoring results of surface subsidence, the sur-face subsidence coefficient was proved to be less than 0.1, indicating that the high key stratum does not break completely, but enters a state of bending subsidence instead. In order to reveal the influence of key stratum on the mining-induced stress of working face, two 3DEC numerical models with and without key stratum were established for comparative analysis. As the numeri-cal simulation results show, when there are multiple key strata in the overburden, the stress in-fluence range and stress concentration coefficient of coal seam after mining are relatively large. The study revealed the working mechanism of rock burst accidents after large-scale mining and predicted the potential area of rock burst risk after the mining of the working face, which has been verified by field investigation. The research results are of great guiding significance for the revelation of the working mechanism of rock burst in deep mining condition and its prevention and control.

Flood records of the Kunmalik River in Chinese Tien Shan mountains have showed that glacier- dammed lake outburst floods (GLOF) had occurred almost every year since 1956 from the glaci-er-dammed Lake Merzbacher. However, GLOF in cold season is seldomly studied. The defense and management of the flood need further observation and study. The maximum peak discharge of 825 m3/s occurred on 5th December 1996 with the maximum flood volume of 2.875×108 m3, which was 18 times larger than that of the mean daily discharge in winter over the past six decades. The drainage of the Merzbacher lake is not a mechanical breaking up of the glacier dam, but the release of pressurized water along a subglacial tunnel triggered by quickly surge of the Northern Glacier, the subglacial tunnels are enlarged by both ice melting and frictional heat in the flooding water and heat under the glaciated dam and the lake in winter. There is no correlation between the GLOF size and air temperature of cold season. The floods in cold season have become bigger since 1996 than that before, and the flood duration has been extended from winter to spring. Once the cold GLOF starts, its discharge can be forecasted day by day to extrapolate the monitoring hydrograph as a linear curve.

A spinning gyroscope precesses about the vertical due to a torque acting upon the wheel. The torque is generated by the shift of moment of force by gravity and it points to the vertical instead of the tangential direction of precession. This intuition offers an alternative and straightforward view of precession dynamics in comparison with the literature. It also presumes a dynamic balance of momentum between circular motions of the wheel spin and precession. Accordingly, the gyroscopic dynamics is then applied to the study of galactic motion of the solar system in space and the Galactic mass is calculated with the inclusion of gyroscopic effect of the solar planets. Results indicate that the gyroscopic effect of Mercury orbiting around the Sun can increase the calculated Galactic mass by 23% in comparison with the result obtained by the classic approach.

Ship detection in large-scene offshore synthetic aperture radar (SAR) images is crucial in civil and military fields, such as maritime management and wartime reconnaissance. However, the problems of low detection rates, high false alarm rates, and high missed detection rates of offshore ship targets in large-scene SAR images are due to the occlusion of objects or mutual occlusion among targets, especially for small ship targets. To solve this problem, this study proposes a target detection model (TAC_CSAC_Net) that incorporates a multi-attention mechanism for detecting marine vessels in large-scene SAR images. Experiments were conducted on two public datasets, the SAR-Ship-Dataset and high-resolution SAR image dataset (HRSID), with multi-scene and multi-size, and the results showed that the proposed TAC_CSAC_Net model achieves good performance for both small and occluded target detection. Experiments were conducted on a real large-scene dataset, LS-SSDD, to obtain the detection results of subgraphs of the same scene. Quantitative comparisons were made with classical and recently developed deep learning models, and the experiments demonstrated that the proposed model outperformed other models for large-scene SAR image target detection.

The compatibility of graphene or graphene oxide with its dispersion medium (polymer) plays a critical role in the formation nanocomposite materials with significant property improvements. Environmentally friendly miniemulsion polymerization, which allows a formation of nanoencapsulation in an aqueous phase and high molecular weight polymer/composite production is one promising method. In this study, we screened a series of amphiphilic modifiers and found that the quaternary ammonium (ar-vinyl benzyl) trimethyl ammonium chloride (VBTAC) pending carbon double bonds could effectively modify the graphene oxide (GO) to be compatible with the organophilic monomer. After that, free radical miniemulsion polymerization could successfully synthesize stable latex of exfoliated poly (methyl methacrylate) (PMMA)/ GO nanocomposite. The final latex had an extended storage life and a relatively uniform particle size distribution. X-ray powder diffraction (XRD), transmission electron microscopy (TEM), and scanning electron microscopy (SEM) analysis of this latex and its films indicated successful encapsulation of exfoliated nano-dimensional graphene oxide inside a polymer matrix.

Impervious surface mapping with high-resolution remote sensing imagery has attracted increasing interest as it can provide detailed information for urban structure and distribution. Previous studies have suggested that the combination of LiDAR data and high-resolution imagery for impervious surface mapping performs better than using only high-resolution imagery. However, due to the high cost of the acquisition of LiDAR data, it is difficult to obtain the multi-sensor remote sensing data acquired at the same acquisition time for impervious surface mapping. Consequently, real landscape changes between multi-sensor remote sensing data at different acquisition times would lead to the error of misclassification in impervious surface mapping. This issue has mostly been neglected in previous works. Furthermore, the observation differences generated from multi-sensor data, including the problems of misregistration, missing data in LiDAR data, and shadow in high-resolution images would also challenge the final mapping result in the fusion of LiDAR data and high-resolution images. In order to conquer these problems, we propose an improved impervious surface mapping method incorporating both LiDAR data and high-resolution imagery at different acquisition times in consideration of real landscape changes and observation differences. In the proposed method, a multi-sensor change detection by supervised multivariate alteration detection is employed to obtain changed areas and misregistration areas. The no-data areas in the LiDAR data and the shadow areas in the high-resolution imagery are extracted by independent classification yielded by its corresponding single sensor data. Finally, an object-based post-classification fusion is proposed to take advantage of independent classification results with single-sensor data and the joint classification result with stacked multi-sensor data. Experiments covering the study site in Buffalo, NY, USA demonstrate that our method can accurately detect landscape changes and obviously improve the performance of impervious surface mapping.

This paper explores the use of different deep learning models for predicting precipitation in 56 meteorological stations in Jilin Province, China. The models used include Stacked-LSTM, Transformer, and SVR, and Gaussian noise is added to the data to improve their robustness. Results show that the Stacked-LSTM model performs the best, achieving high prediction accuracy and stability. The study also conducts variable attribution analysis using LightGBM and finds that temperature, dew point, precipitation in previous days, and air pressure are the most important factors affecting precipitation prediction, which is consistent with traditional meteorological theory. The paper provides detailed information on the data processing, model training, and parameter settings, which can serve as a reference for future precipitation prediction tasks. The findings suggest that adding Gaussian noise to the dataset can improve the model's generalization ability, especially for predicting days with zero precipitation. Overall, this study provides useful insights into the application of deep learning models in precipitation prediction and can contribute to the development of meteorological forecasting and applications.

In this study, the decision-making process management of forest tending in the forestry business is decentralized, and forest tending decision-making activities at different points in time are integrated by decision makers at different geographical locations. The decision-making process was analyzed and optimized from a system perspective. Based on the optimized decision-making process, a forest tending business group decision support system (FTGDSS) was established. We first reviewed and discussed the characteristics and development of the forest tending business and forestry decision support system. Business Process Modeling Notation was used to draw a current state flow chart of the forest tending business, to identify and discover important decision points in the process of tending decision-making. We also analyzed the content and attributes of each decision point, and described the system structure, functional framework, knowledge base structure, and reasoning algorithm of FTGDSS in detail. Finally, FTGDSS was evaluated from the two dimensions of the technology adoption model. FTGDSS integrates different levels of time-space decision-making activities, historical tending data, business plans, decision-makers' management tendencies into the decision-making process and automatically extracts decision-making data from the forest business process management enterprise resource planning system (Smartforest) that improves the ease of use of the decision support system (DSS). It also improves the quality of forest tending decisions, and enables the DSS to better support multi-target management strategies.

Land use and cover change (LUCC) is an important method to investigate the causes of global environment change. We utilized the emergy ecological footprint (EEF) model to construct a land-use change model to be used as a systematic measuring tool for monitoring sustainable development trends. In particular, we estimated the eco-security of the Cing-jing region as a case study so that responsible agencies can use it to maintain a balance between ecological preservation and tourism development. The results indicated the following: First, the ecological environment of the Cing-jing region satisfied the safety standard in 2008–2014; however, the related indices increased considerably. Second, the grey model predicted a decrease in 2015–2024 ecological carrying capacities of Cing-jing and a large increase in capita EFs, resulting in a larger ecological deficit and higher EFI. The eco-security from 2015–2024 was higher compared to 7 years ago and is predicted to reach the Grade 2 intermediate level in 2022; thus the Cing-jing region is gradually becoming ecologically unsustainable. Strengths of our study included the use of EEF theory in a quantitative analysis of slope lands for the effective evaluation of ecological security. Finally, we expanded our research to include ecological security issues.

The MQTT IoT connection technology is widely used, becoming the primary means for IoT devices to communicate with servers amid the vigorous development of IoT technology. On the OneNET cloud platform, MQTT protocol connection and data communication, message sending, and subscription are established, one-to-many message transmission is solved, and the reverse control from server to device is realized in big data environment. This technology can provide fast and secure messaging services for remote devices with a small code capacity and limited bandwidth. Experiments indicated that the communication mode has low cost, small bandwidth, and slight delay, which meets the requirements of device data acquisition and control in a large area and has broad application prospects and reference significance in the field of mobile applications.

Autonomous target recognition (ATR) plays a crucial role in maintaining situational awareness during environmental monitoring. Unmanned aerial vehicles (UAVs) equipped with autonomous target recognition technology can gather and analyze real-time information about targets, including their locations, sizes, and types. However, UAV-captured images in complex real-world environments often display significant variations in perspective and scale due to changes in UAV altitude and distance. Existing methods for autonomous target recognition on UAVs struggle to capture targets from large field-of-view and multi-scale images, resulting in low recognition accuracy and high false-positive rates. This paper introduces two novel Slimmable neural network models, namely SE-YOLOv5s and ST-YOLOv5s, which are based on the YOLOv5s architecture. These models incorporate the Squeeze and Excitation and Swin-Transformer mechanisms to enhance the ability to extract features from large field-of-view and multi-scale images. To evaluate their performance, experiments were conducted on the Visdrone19 aerial dataset. Compared to the state-of-the-art YOLOv5s algorithm, the utilization of SE-YOLOv5s and ST-YOLOv5s for autonomous target recognition on low-altitude drones resulted in improvements in both accuracy and false-positive rates. These proposed methods combine Slimmable neural network design with feature enhancement mechanisms, addressing the challenges posed by complex real-world environments in UAV missions. The advancements in autonomous target recognition on low-altitude drones will significantly contribute to enhancing situational awareness in future environmental monitoring.

Background: Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory infection globally. There are vaccines in pipeline to prevent it but a systematic review on immunogenicity and safety of vaccine is lacking. Methods: This systematic review of RSV vaccine clinical trials was undertaken using 4 databases. Searches were conducted using both controlled vocabulary terms such as ‘Respiratory Syncytial Virus, Human’, ‘Respiratory Syncytial Virus Infections’, ‘Respiratory Syncytial Virus Vaccines’, ‘Immunization’, ‘Immunization Programs’ and ‘Vaccines’ and corresponding text word terms. The searches for published papers were limited to clinical trials published from January 2000 to August 6th, 2018. RSV infection case was defined as RSV associated medically attended acute respiratory illness (MAARI) or RSV infection by serologically-confirmed test (Western Blot) during the RSV surveillance period. We calculated the relative risk of each vaccine trial with RSV infection case. Results: Of 4395 publications, 24 were included and data were extracted covering 4 major types of RSV vaccine candidates, these being live-attenuated/chimeric (n=9), recombinant-vector (n=10), subunit (n=1) and nanoparticle vaccines (n=4). For RSV infection cases, 7 trials were involved and none of them showed a vaccine-related increased MAARI during RSV surveillance season. Conclusion: LID ∆M2-2, MEDI M2-2, and RSVcps2 (live-attenuated) were considered the most promising vaccine candidates in infant and children. In the elderly, a nanoparticle F vaccine candidate was considered as a potential effective vaccine. Although no promising vaccine was identified from pregnant-women test, RSV F-024 subunit vaccine candidate and an RSV F nanoparticle vaccine showed encouraging results in healthy non-pregnant women.

Raman spectroscopy is a type of inelastic scattering that provides rich information about a sub-stance based on the coupling of the energy levels of their vibrational and rotational modes with incident light. It has been applied extensively in many fields. As there is an increasing need for remote detection of chemicals in planetary exploration and anti-terrorism, it is urgent to develop a compact and easily transportable fully automated remote Raman detection system for trace detection and identification of information with high-level confidence about the target’s compo-sition and conformation in real-time and for real field scenarios. Here, we present an unmanned vehicle-based remote Raman system, which includes a 266 nm air-cooling passive Q-switched nanosecond pulsed laser of high-repetition frequency, a gated ICMOS, and an unmanned vehicle. This system obtains good spectral signals from remote distances ranging from 3 m to 10 m for simulating realistic scenarios, such as aluminum plate, woodblock, paperboard, black cloth, and leaves, and even for detected amounts as low as 0.1 mg. Furthermore, a CNN-based algorithm is implemented and packaged into the recognition software to achieve fast and more accurate de-tection and identification. This prototype provides a proof-of-concept for an unmanned vehicle with accurate remote substance detection in real-time, which can be helpful for remote detection and identification of hazardous gas, explosives, their precursors, and so forth.

This study explores the relationship between mental and physical therapeutic through three dimensions: man-environment relationships; a sense of place and symbolic landscapes. The study used a combination of qualitative and quantitative research methods. Local residents living in the coastal area of Xinglin Bay are the research objects. Quantitative data analysis revealed that the frequency of residents' visits was an important variable affecting their physical and treatment perceptions. In addition, the significance is higher for females than for males. The text analysis shows that the environment, especially the ecological restoration of water quality and migratory birds, is of great significance to the identity of local residents. Daily activities contribute to a sense of place and are what make the coast a place of therapeutic landscape function.

This research develops the Osteoporosis Knowledge, Attitude, and Behaviors Questionnaire (OKABQ) with the intent to evaluate levels of osteoporosis knowledge, attitude and behavior change. The aims of the study were to develop and validate the OKABQ; and to establish a mediation model of the research. A quantitative, descriptive, and instrumental study was conducted in two phases: Phase I—development of the scale through Delphi Method by osteoporosis experts; Phase II—evaluation of the validity and reliability of the scale and construction of a mediation model using SmartPLS. In Phase I, the content validity index (CVI) of the questionnaire was higher than 0.96 and the inter-rater reliability (IRR) kappa was 1.00. In Phase II, exploratory factor analysis showed that two predominating factors of attitude as a mediation were addressed by the 26-item OKABQ. The indirect effect results from the estimated model indicates that attitude mediates the relationship between knowledge and behaviors (β = 0.114, t = 2.627, p < 0.001), which is positive and statistically significant. We concluded that the OKABQ is a valid measure of osteoporosis knowledge, attitude and behaviors for women with osteoporosis. These assessment results could assist healthcare providers in mitigating insufficiency on health education.

In the current pandemic of COVID-19, students and faculty are subject to social distancing and online learning. How to test students in this unprecedented environment is a new educational challenge with immediate and global impacts. The main contribution of this paper is to establish the feasibility that by a clever design we can control the average gain (which is referred to as the g-factor) from cheating behaviors to a degree as small as pre-specified so that accurate and reliable online exams can be administered. It is underlined that even after the pandemic the methods and systems in the spirit of our proposal are still valuable for cost-effective exams to promote open courses and internet-based education.

Self-sustained learning (SSL) is considered a crucial factor in promoting students’ long-term learning and development in a sustainable society. To deepen the understanding of SSL, especially in the context of learning English as a second language, the current study examined the influence of intercultural communicative skills, language mindset, and positive L2 self on SSL in English learning among 1,238 college students in China. The results showed that students not only had a strong language mindset, positive L2 self, and intercultural communicative skills but also scored higher in long-term self-sustained English learning. Findings from the Structural Equation Modeling indicated that both language mindset and intercultural communicative skills positively predicted positive L2 self and self-sustained English learning. Furthermore, language mindset and intercultural communicative skills had an indirect impact on self-sustained English learning through positive L2 self. These findings suggest that to promote English learners’ SSL, instructors should help facilitate students’ intercultural communicative skills and foster a growth language mindset, as well as positive language learning beliefs.

Liposome vesicle is an ideal carrier for carbon nanotube (CNT) to serve as the water channel that allows the fast transport of water molecules, and thus enhancing the membrane permeability. However, low quantity of the inserted CNT in the liposome vesicle is an important factor that limited further improvement of the membrane flux. In present study, positively charged lipids (2,3-dioleoyloxy-propyl)-trimethylammonium-chloride (DOTAP) was introduced to the 1,2-dioleoyl-sn-glycero-3-phosphoethanolamineon (DOPE) liposome vesicles to tailor the vesicle charge, so as to evaluate the effect of positively charged DOTAP on the insertion of CNT into liposomes and separation performance of thin-film nanocomposite (TFN) membranes. The results showed that addition of DOTAP induced more quantity of CNT inserted into the liposome vesicles, since the shrinkage rate (k) and permeability (Pf) of liposome vesicles present obvious increase with increased content of DOTAP in the liposome vesicles. Besides, it contributed to 252.3% higher water flux for TFN membranes containing DOPE/DOTAP2:1-CNT liposomes (the mass ratio between DOPE and DOTAP was 2:1) than TFC membranes. More important, it presented 106.7% higher water flux for TFN membranes containing DOPE/DOTAP4:1-CNT liposomes (the mass ratio between DOPE and DOTAP was 4:1), which was originated from the more water channels that the CNT provided in the liposome vesicles. In all, positively charged DOTAP effectively tailored the vesicle charge, which provided a better carrier for the insertion of more quantity of CNT, and contributed to higher permeability of TFN membranes.

Intense climate change and rapid urbanization have increased the risk of urban flooding, seriously affecting urban economic and social stability. Enhancing the urban flood resilience (UFR) has required a new solution to cope with urban flood disasters. In this study, taking Yingtan city as an example, a system of indicators for evaluating UFR was constructed, with 17 representative indicators, comprising three subsystems: socio-economic, ecological and infrastructural. A hybrid (FAHP-EWM)-TOPSIS model was applied, to develop an index-based measurement to compare and evaluate UFR, and Gray Relational Analysis (GRA) was used to discover the main factors affecting UFR. In addition, the natural discontinuous method was innovatively used to divide the UFR grade interval into levels, and the grade change was evaluated based on the TOPSIS method. The results showed that (1) from 2010 to 2022, the UFR in Yingtan City increased by 80.69%, and the factors affecting UFR are highly correlated with urban infrastructure development. However, the ecological resilience in the subsystem showed a fluctuating downward trend, because of the influence of the surface area of lakes and rivers. (2) The grades of UFR for Yingtan City increased from Level III (2010 and 2016) to Level IV (2022), with local financial expenditures and the age structure of the population being the main factors currently limiting the development of UFR. The study provides a theoretical basis for the construction of an indicator system for assessing the UFR of Yingtan and proposes practical improvement directions for UFR.

Animal viruses are a significant threat to animal health and are easily spread across the globe with the rise of globalization. The limitations in diagnosing and treating animal virus infections have made the transmission of diseases and animal deaths unpredictable. Therefore, early diagnosis of animal virus infections is crucial to prevent the spread of diseases and reduce economic losses. To address the need for rapid diagnosis, electrochemical sensors have emerged as a promising tool. Electrochemical methods present numerous benefits, including heightened sensitivity and selectivity, affordability, ease of use, portability, and rapid analysis, making them suitable for real-time virus detection. This paper focuses on the construction of electrochemical biosensor, as well as promising biosensor models, and expounds its advantages in virus detection, which is a promising research direction.

Two 2,2':6',2''-terpyridine-based Schiff bases (TPySSB and TPySB) have been synthesized. The TPySSB shows remarkable selective ‘off-on’ fluorescence for Al³⁺ by photoinduced electron transfer (PET) mechanism of sensing. Chemosensor TPySSB binds Al³⁺ in a 1:2 ratio with an association constant 6.8×10⁵ (R²=0.98) and this 1:2 stoichiometric model is established on Job’s plot and ¹H NMR. Compared TPySSB and TPySB, it is of great importance of the existence of salicylidene unit due to its strong binding abilities of both phenol and C=N structure to the Al³⁺.

Klebsiella pneumonia (K. pneumoniae) is a Gram-negative bacterium that causes nosocomial infections in the lung, bloodstream, and urinary tract. Therefore, detecting K. pneumoniae in early time is important in preventing severe infections. However, clinical detection of K. pneumoniae requires a long time of agar plate culture. Nucleic acid detection like qPCR is precise but requires expensive equipment. Recent research reveals that collateral cleavage activity of CRISPR-LbCas12a has been applied in nucleic acid detection. In this study, PCR combined with CRISPR-LbCas12a targeting the K. pneumoniae system was established. This system showed excellent detection specificity and sensitivity in both bench work and clinical samples. Due to its advantages, its application can meet different detection requirements in health centers where qPCR is not accessible.

We fabricated high-quality MAPbBr3 single crystals (SC) by introducing moderate amount electron-rich poly(propylene glycol bis(2-aminopropyl ether) (PEA) additives with an inverse temperature crystallization (ITC) method. The intramolecular vibrations and defective states of prepared MAPbBr3 single crystals were systemically studied by the in situ variable-temperature Fourier Transform Infrared (FTIR) Spectroscopy, X-ray photoelectron spectroscopy (XPS), and the synchrotron-based X-ray absorption near edge structure (XANES), et al. We infer that the proper amount of PEA additives would prevent the formation of intermediate states and crystal boundaries, passivating the density of defective states. The X-ray detection properties of single-crystal MAPbBr3 crystals were investigated, using both high dose and low dose X-ray photons at 40keV in synchrotron beamlines. The photocurrent of optimized PEA-treated MAPbBr3 single crystals demonstrate better performance compared with the as-prepared single crystals. Meanwhile, the decay time of MAPbBr3 single crystal is decreased from 460 ns to 210 ns by Time-resolved photoluminescence (TRPL) decay measurement, owing to the defect passivation by 0.5wt% PEA additives. The PEA-treated single crystals possess much faster decay time than the commercialized Ce:YAG scintillator (>500ns). These results help elucidate the passivation of defective states and contribute paths to manufacture high-quality single crystal perovskites for next-generation optoelectronic devices.

In this paper, PEN3 electronic nose was used to detect and recognize fresh and moldy apples (inoculated with Penicillium expansum and Aspergillusniger) taken Golden Delicious apples as model subject. Firstly, the apples were divided into two groups: apples only inoculated with different molds (Group A) and mixed apples of inoculated apples with fresh apples (Group B). Then the characteristic gas sensors of the PEN3 electronic nose that were most closely correlated with the flavor information of the moldy apples were optimized and determined, which can simplify the analysis process and improve the accuracy of results. Four pattern recognition methods, including linear discriminant analysis (LDA), backpropagation neural network (BPNN), support vector machines (SVM) and radial basis function neural network (RBFNN), were then applied to analyze the data obtained from the characteristic sensors, respectively, aiming at establishing the prediction model of flavor information and fresh/moldy apples. The results showed that only the gas sensors of W1S, W2S, W5S, W1W and W2W in the PEN3 electronic nose exhibited strong signal response to the flavor information, indicating were most closely correlated with the characteristic flavor of apples and thus the data obtained from these characteristic sensors was used for modeling. The results of the four pattern recognition methods showed that BPNN presented the best prediction performance for the training and validation sets for both the Group A and Group B, with prediction accuracies of 96.29% and 90.00% (Group A), 77.70% and 72.00% (Group B), respectively. Therefore, it first demonstrated that PEN3 electronic nose can not only effectively detect and recognize the fresh and moldy apples, but also can distinguish apples inoculated with different molds.

Folk residence in the cold region of Northeast China is an important part of China's traditional folk residence, with significant geographical representation. In this paper, we take the residential compounds of villages and towns in the cold region of Northeast China as the research object, summarize four typical layout forms of residential compounds of villages and towns in the cold region of Northeast China, simulate the wind environment of compounds of different layout forms in winter by using the computer numerical simulation software Fluent, and then analyze and evaluate the wind environment of compounds by combining with the evaluation standard of wind speed ratio and considering the area of wind shadows, number of vortices and other factors.

This paper introduces a chip-level oven-controlled system for improving the temperature stability of MEMS resonators. Wherein the resonator and the micro-hotplate are manufactured by MEMS technology, then wire-bounded in a package shell at the chip level. The proposed resonator is transduced by the AlN film, and its temperature is monitored by temperature-sensing resistors on both sides. The designed micro-hotplate is placed at the bottom of the resonator chip as a heater and insulated by airgel. The PID pulse width modulation (PWM) circuit controls the heater according to the temperature detection result to provide a constant temperature for the resonator. The proposed oven-controlled MEMS resonator (OCMR) exhibits a frequency drift of 3.5ppm in the range of -50°C to 125°C, and the method also can be applied to other MEMS devices that require temperature control.

Visual question answering (VQA) is receiving increasing attention from researchers in both the computer vision and natural language processing fields. There are two key components in the VQA task: feature extraction and multi-modal fusion. For feature extraction, we introduce a novel co-attention scheme by combining Sentence-guide Word Attention (SWA) and Question-guide Image Attention (QIA) in a unified framework. To be specific, the textual attention SWA relies on the semantics of the whole question sentence to calculate contributions of different question words for text representation. For the multi-modal fusion, we propose a “Cross-modal Multistep Fusion (CMF)” network to generate multistep features and achieve multiple interactions for two modalities, rather than focusing on modeling complex interactions between two modals like most current feature fusion methods. To avoid the linear increase of the computational cost, we share the parameters for each step in the CMF. Extensive experiments demonstrate that the proposed method can achieve competitive or better performance than the state-of-the-art.

A new approach for the preparation of polymer brush was developed via the union of controlled/“living” radical polymerization and click chemistry. The application of the approach realized the more quickly and accurate design and synthesis of the polymer brushes. A novel functional polymer brush of poly(acrylonitrile-g-glycidyl methacrylate) with tremendous application potential in the field of biology has been successfully synthesized via the new approach. The reaction conditions of click chemistry were optimized with the reaction time and the reactant ratio and judged from UV-vis spectra. Under the optimum of click chemistry, the novel functional polymer brushes were prepared. The GPC, FTIR analyses, 1H NMR spectrum and TGA were employed to ensure the successful synthesis of poly(acrylonitrile-g-glycidyl methacrylate) polymer brushes.

Outliers seriously affect the accuracy in geometric model fitting. Previous works in coping with outliers involve threshold selection and scale estimation. However most scale estimators suppose the inlier distribution as a Gaussian model, which usually poorly meets the cases in geometric model fitting. Outliers, considered as the points with big residuals to all the true models, share common items with big values in quantized residual preferences, thus making the outliers gather away from the inliers in quantized residual preference space. In this paper we make use of this outlier consensus in quantized residual preference space by extending the usage of energy minimization to combine the model error and the spatial smoothness in quantized residual preference space for outlier detection. The energy minimization based outlier detection process follows an alternate sampling and labeling framework. After the outlier detection, an ordinary energy minimization method is employed to optimize the inlier labels, which also follows the framework of alternate sampling and labeling. The experimental results in this study show that the energy minimization based outlier detection method can detect most of the outliers in the data. Furthermore, the proposed energy minimization based inlier segmentation process segments the inliers into different models quite accurately. Overall, the performance of the proposed method is better than most of the state-of-the-art methods.

As an emerging model, self-service fitness centers are reshaping the consumer fitness experience globally. Given the crucial role of customer loyalty in the sustainable operation and management of fitness service enterprises, this study constructs a structural model incorporating service quality, service convenience, customer satisfaction, word-of-mouth intentions, and repatronage intentions. The model is designed to elucidate the factors and mechanisms impacting customer loyalty at self-service fitness centers and further investigates how these relationships are affected by service methods, either with staff or without staff. The study employs PLS-SEM to empirically analyze 552 customer questionnaires from four self-service fitness centers in first-tier cities in China. The results reveal positive correlations among the constructs in the structural model, emphasizing the important position of raising service quality standards and reducing the time and effort expended by customers in the management of customer loyalty. Concurrently, service convenience was found to play a significant driving role in customers' perceived service quality. Through the chain-mediating effect of service quality and customer satisfaction, service convenience exerts a considerable positive impact on word-of-mouth intentions and repatronage intentions. Moreover, the study reveals significant differences in these relationships when considering service methods, either with staff or without staff.

This study aims to identify factors associated with anxiety levels of adults living in Singapore before the pandemic and during the COVID-19 outbreak. Data were collected using a cross-sectional web-based survey conducted from July to November 2020 accruing 264 eligible participants. Ordered logistic regression was used to assess Generalized Anxiety Disorder-7 (GAD-7), ranked as minimal (0-4), mild (5-9), moderate (10-14), and severe (15-21) before the pandemic and during the pandemic. About 74% of participants were female, 50% were aged 25-34, and 50% were married. The GAD-7 level went up from pre-pandemic for both moderate (from 12.5% to 16%) and severe GAD (from 2% to 11%). Alcohol consumption (AOR 1.79, 95% CI 1.04-3.06), loneliness (AOR 1.28, 95% CI 1.05-1.54), and difficulty in switching off social media (AOR 2.21, 95% CI 1.29-3.79) predicted increased GAD-7 levels. The quality of life (AOR 0.84, 95% CI 0.79-0.90) was significantly associated with decreased GAD-7 levels. The results heighten the awareness that early initiation of mental health support is crucial for the population in addition to the various financial support measures provided by the government as they are adapting to live with the COVID-19 pandemic.

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

The phycobilisome (PBS) is the major light-harvesting apparatus in cyanobacteria and red algae, a large multi-subunit protein complex of several megadaltons that is found on the stromal side of thylakoid membranes in orderly arrays. Chromophore lyases catalyse the thioether bond between apoproteins and phycobilins of PBSs. Depending on the species, composition, spatial assembly and, especially, the functional tuning of different phycobiliproteins mediated by linker proteins, PBSs can absorb light between 450 and 650 nm, making them efficient and versatile light-harvesting systems. However, basic research and technological innovations are needed, not only to understand their role in photosynthesis but also to realise the potential applications of PBSs. Synthetic biology provides an innovative approach to expand our understanding of the distinctive properties that make the PBS such an efficient light-harvesting system and to explore its heterologous synthesis, photosynthetic functions and potential medical applications. Focusing on these topics, this review describes the essential components needed for PBS assembly, the functional basis of PBS photosynthesis and the applications of phycobiliproteins. Moreover, key technical challenges for heterologous biosynthesis of phycobiliproteins in chassis cells are discussed.

This study aims to test a model linking destination image, perceived value, tourist satisfaction, and tourist loyalty. Based on a sample of 300 tourists travelling by car from the World Natural Heritage Site of Tianchi, China, a new model of destination image was explored and data were analysed using partial least squares structural equation modelling (PLS-SEM). The results show that perceived value and satisfaction are direct antecedents of destination loyalty. Above all, perceived value and tourist satisfaction mediate the relationship between destination image and loyalty. Finally, this study discusses the theoretical and management implications of the findings in order to boost the tourism industry in the context of car trips.

Fructus Amomi (FA) is usually regarded as the dried ripe fruits of Amomum villosum Lour. (FAL) or Amomum villosum Lour. var. xanthioides T. L.Wu et Senjenis (FALX) However, FAL, which always has a much higher price because of its better quality, is confused with FALX in the market. As volatile oil is the main constituent of FA, a strategy of chromatography-mass spectrometry (GC-MS) and chemometric approches was applied to compare the chemical composition of FAL and FALX. The results showed that the oil yield of FAL was significantly higher than that of FALX. Total ion chromatograph (TIC) showed that cis-nerolidol existed only in FALX. Bornyl acetate and camphor, could be considered as the most important ones in FAL and FALX respectively. Moreover, hierarchical cluster analysis (HCA) and principal component analysis (PCA) successfully distinguished the chemical constitutes of the volatile oils in FAL and FALX. Additionally, bornyl acetate, α-cadinol, linalool, β-myrcene, camphor, d-limonene, terpinolene and endo-borneol were selected as the potential markers for discriminating FAL and FALX by partial least squares discrimination analysis (PLS-DA). In conclusion, this present study first developed a scientific approach to separate FAL and FALX based on volatile oils by GC-MS combined with chemometric techniques.

Objectives To determine the effects of omega-3 polyunsaturated fatty acids (ω-3 PUFA) from animal and plant sources on glucolipid metabolism and lipoprotein subfractions in type 2 diabetic patients with dyslipidemia. Methods Participants were recruited from the diabetes clinic at the Guanlin Hospital, Yixing City in Jiangsu province, China, from March 2017 through June 2017. Ninety participants were randomly assigned to take 3g/day fish oil (FO, containing EPA and DHA), 3g/day perilla oil (PO, containing ALA), or 3g/day blend oil containing fish oil and linseed oil (BO, containing EPA, DHA and ALA) for 3 months. The levels of serum glucose, glycated hemoglobin (HbA1c), C-peptide, triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), non-HDL, apolipoprotein A1 (Apo A1), apolipoprotein B (Apo B), lipoprotein a (Lp(a)), and free fatty acids were determined at baseline and after the 3 months. In addition, four fatty acids in serum and red blood cells membranes (RBCm) were analyzed using gas chromatography-mass spectrometry. The Lipoprint System was used to determine the lipoprotein subfractions. Results All 90 participants completed the final 3-month follow-up at the end of the study. After three months of intervention, blood glucose and HbA1c levels in the PO group were significantly lower than those at the baseline (p < 0.05). On the other hand, in the BO group, the HbA1c, non-HDL, Apo A1 and Lp(a) levels were significantly lower, while the C-peptide levels were significantly higher after intervention compared to the baseline (p < 0.05). In the FO group, the HbA1c and TG levels were significantly lower after the intervention compared to the baseline (p < 0.05). In addition, at the end of the study, there was significant increase in the levels of DPA and DHA in serum and RBCm of the FO group (p < 0.05), while in the BO group, there was significant increase in the levels of EPA, DPA and DHA in RBCm (p < 0.05). Finally, the FO group had the highest levels of large HDL subfractions compared to the BO and PO groups, but had the lowest levels of small HDL subfractions among the three groups. Conclusion For patients with diabetes, plant-derived ω-3 PUFAs are more effective at controlling blood glucose than animal-derived ω-3 PUFAs. However, animal-derived ω-3 PUFAs play a critical role in controlling blood lipids. Particularly, fish oil can effectively increase the beneficial large HDL subfractions and reduce the nonbeneficial small HDL subfractions. Both the animal- and plant-derived ω - 3 PUFAs have practical value in improving glucose and lipids metabolism in T2DM patients with dyslipidemia.

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

High mountain areas are an appropriate indicator of anthropogenic lead (Pb), which can reach the remote mountain ranges through long distance atmospheric transport. We compared the content of Pb in ecologically equivalent rodent species from Tian-Shan with European mountain ranges Tatra, Vitosha and Rila mountains. We used bone tissues from terminal tail vertebrae of small rodents for detection of Pb levels by using electrothermal atomic absorption spectroscopy (AAS). The tail bones of Tian-Shan rodents had significantly lower Pb levels than snow voles from Tatra mountains, but there was no significant difference in comparison with Vitosha and Rila mountains. We can conclude that Tian-Shan shows lower pollution by Pb than Tatra mountains, what may be a reason of longer lasting industrialization of north-western Europe and strongly prevailing west winds in Tatra mountains.

Understanding how industrial agglomeration affects agricultural green production efficiency is essential for green agricultural development. This study uses the super-efficient EBM-GML to measure and analyze the spatial and temporal evolution characteristics and core sources of dynamics of agricultural green production efficiency in China by using panel data from 30 Chinese provinces from 2006 to 2020. It also empirically investigates the relationships between industrial agglomeration, land transfer, and agricultural production efficiency. By using fixed, intermediary, and threshold effects models, the internal links between the industrial agglomeration, land transfer, and agricultural green production efficiency are examined. The findings indicate that the green production efficiency of Chinese agriculture exhibits the regional characteristics of being “high in the west and low in the east, high in the south and low in the north” in terms of space; in terms of time series, the overall trend is that of growing, with an average annual growth rate of 11.45%, and the growth primarily depends on the “single-track drive” of green technological progress. By promoting land transfer, industrial agglomeration can increase the agricultural green production efficiency and decomposition index. Land transfer has a double-threshold effect on the influence of industrial agglomeration on agricultural green production efficiency. As a result, this study suggests adhering to the idea of synergistic development, promoting agricultural green development, strengthening the development of industrial agglomerations, promoting the quality and efficiency of industry, improving land-transfer mechanisms, and placing a focus on resource efficiency improvements, as well as other policy recommendations.

Target pests of genetically engineered crops producing both defensive allelochemicals and Bacillus thuringiensis (Bt) toxins often sequentially or simultaneously uptake allelochemicals, Bt toxins, and/or insecticides. How the three types of toxins interact to kill pests remains underexplored. Here we investigated the interactions of Bt toxin Vip3A, plant allelochemical flavone, and insecticide emamectin benzoate in Spodoptera frugiperda. Simultaneous administration of flavone LC25 + Vip3A LC25, emamectin benzoate LC25 + Vip3A LC25, and flavone LC15 + emamectin benzoate LC15 + Vip3A LC15 but not flavone LC25 + emamectin LC25 yielded a mortality significantly higher than their expected additive mortality (EAM). One-day preexposure to one toxin at LC5 followed by 6-day exposure to the same toxin at LC5 plus another toxin at LC50 showed that the mortality of flavone LC5 + Vip3A LC50, emamectin benzoate LC5 + Vip3A LC50, and Vip3A LC5 + emamectin benzoate LC50, were significantly higher than their EAM, while that of flavone LC5 + emamectin benzoate LC50 was significantly lower than their EAM. No significant difference existed among the mortalities of Vip3A LC5 + flavone LC50, emamectin benzoate LC5 + flavone LC50, and their EAMs. The results suggest that the interactions of the three toxins are largely synergistic (inductive) or additive, depending on their combinations and doses.

Building facade design plays an essential role in enhancing energy efficiency and reducing environmental impact in high-performance building design. Balancing the conflicts among various building facade design parameters to satisfy different optimization objectives constitutes a highly complex optimization problem. The rapidly increasing number of studies demonstrates a significant interest in implementing multi-objective optimization methods to tackle building facade optimization problems. This study conducts a systematic review of optimization methods for building facade optimization (BFO). The optimization objectives and design variables are categorized based on their characteristics. The efficiency and effectiveness of optimization algorithms in addressing BFO problems are compared. Building optimization techniques and tools are showcased, along with their functions and limitations. Key findings highlight the robust feasibility and effectiveness of optimization algorithms, methods, and techniques in resolving a diverse range of BFO challenges. The limitations, challenges, and future potential of these methods are summarized and proposed.

Current artificial intelligence (AI) technology is still considered weak AI. However, the progression towards strong AI unavoidably involves grappling with concerns surrounding consciousness, the mind, and creativity. This paper focuses on analyzing consciousness, creativity, and the generation of emotions to explore the possibility of machine-based consciousness, creativity, and emotion. We believe that the emergence of consciousness relies on the complex interplay at different layers within a complex system, rather than wholly relying on the underlying substrates of the system. Thus, it is plausible to consider the existence of machine-based consciousness, creativity, and emotion. Furthermore, swarm intelligence should be recognized as a distinct form of intelligence. Human individuals serve as the foundational substrate enabling the realization of swarm intelligence, with individual intelligence reflecting the projection of swarm intelligence at the individual level. The advanced state of human civilization is primarily attributable to the effect of swarm intelligence. Building upon basic emotions to adapt to environmental conditions, advanced human emotions are a product of the evolutionary process by swarm intelligence. Emotions serve as a pivotal impetus for the formation and development of societies grounded in swarm intelligence. In pursuit of super-AI that surpasses human civilization in the future, nurturing swarm intelligence represents an inevitable trajectory.

Fasudil, a potent Rho kinase (ROCK) inhibitor, can ameliorate LPS-induced acute lung injury (ALI) in mice, but the mechanism remains obscure. In this study, a mice model of ALI was established by intra-tracheal instillation of LPS. Histological changes, cytokine levels, lung permeability, and endothelial apoptosis were determined to evaluate the effects of fasudil on lung injury. The cellular and molecular biological mechanisms were explored by culturing human pulmonary microvascular endothelial cells (PMECs). The results showed that fasudil reduced LPS-induced lung inflammation, pulmonary hyperpermeability, and endothelial apoptosis in mice. In cultured human PMECs, fasudil inhibited LPS-induced caspse-3 cleavage and cell apoptosis. It also decreased LPS-induced hyperpermeability of human PMECs monolayer by reversing the down-regulation of intercellular junctions. Moreover, fasudil inhibited LPS-induced overexpression of chemokines and intercellular adhesion molecule (ICAM)-1 in human PMECs, which in turn suppressed neutrophil chemotaxis and neutrophil-endothelial adhesion. Further molecular researches showed fasudil inhibited LPS-induced activation of ROCK, NF-κB, and p38 in human PMECs. Our findings demonstrated that fasudil alleviated LPS-induced ALI by protecting endothelial function via inhibiting endothelial apoptosis, maintaining endothelial barrier integrity, and reducing endothelial inflammation. These effects of fasudil could be attributed to the inhibition of ROCK and its downstream NF-κB and p38 signaling pathways.

From a scientific standpoint, both temporal and spatial variables must be examined when developing programs for training various soccer scoring techniques (SSTs), but a review of current literature reveals that existing scientific studies have overlooked this combinatory influence. Consequently, there is no reliable theory on temporal-spatial identification when evaluating scoring opportunities. Quantified by using biomechanical modeling, anthropometry, and SSTs found in FIFA Puskás Award (121 nominated goals between 2009 and 2020), it is found that players’ proprioceptive/effective shooting volume (i.e. players’ attack space) could be sevenfold the currently-practiced shooting volume. The ignorance of some SSTs’ training leads to the underuse of the potential shooting volume. These overlooked SSTs are airborne and/or acrobatic techniques, perceived as high-risk and low-reward. Relying on the talent of an athlete to improvise on the fly can hardly be considered as a viable coaching strategy. Therefore, for developing science-based SST training regimes, groundbreaking studies are needed to: 1) expand the perception of shooting volume, and 2) entrain one-touch-shot techniques (airborne/acrobatic) within this volume, in short, Focusing-on-Time-in-Space. Whence, the new temporal-spatial theory could guide future researches and develop novel training programs. An increase of airborne/acrobatic goals would ultimately further enhance the excitement of the game.

Periostracum cicadae, the cast-off shell of the cicada Cryptotympana pustulata Fabricius, is used in traditional Chinese medicine for its diaphoretic, anticonvulsive, sedative, antipyretic, and antiallergic effects. However, the exact pathogenesis of immunoglobulin A nephropathy (IgAN) remains unclear, thereby hindering investigations to identify novel therapeutic agents. A rat IgAN model was established by administration of bovine serum albumin, lipopolysaccharide, and carbon tetrachloride, which simultaneously established blood stasis and a heat syndrome model. The animals were sacrificed to detect changes in protein levels in urine and blood. Immunofluorescence was performed to assess IgA deposition in the glomeruli. Tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin 6 (IL-6) levels were measured in bronchoalveolar lavage fluid (BALF) by enzyme-linked immunosorbent assay. Hematology and eosin, periodic acid-Schiff, TUNEL, and immunohistochemical staining were performed to evaluate histopathological changes in kidney tissues. Additionally, target-related proteins were measured by western blotting. Periostracum cicadae resulted in a reduction in blood and urine protein levels. Serum TNF-α, IL-1β, and IL-6 levels significantly decreased in the periostracum cicadae-treated groups compared to the IgAN group. Furthermore, a reduction in MCP-1, TLR4, and IgA expression levels and a dose- dependent increase in caspace-3 expression were observed in response to periostracum cicadae treatment. TGF-β1 levels decreased, whereas that of Fas increased in the kidney tissues of the periostracum cicadae-treated groups. The findings of the present study indicate that periostracum cicadae induces apoptosis and improves kidney inflammation and fibrosis in IgA nephropathy rat models.

There is a current worldwide outbreak of a new type of coronavirus (2019-nCoV), which originated from China and has now spread to 17 other countries. Governments are under increase pressure to stop the outbreak spiraling into a global health emergency. At this stage, preparedness, transparency and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak sites, and from laboratories supporting the investigation. This paper aggregates and consolidates the virology, epidemiology, clinical management strategies from both English and Chinese literature, official news channels and other official government documents. In addition, by fitting the number of infections with a single-term exponential model, we report that the infection is spreading at an exponential rate, with a doubling period of 1.8 days.

Construction using earth materials demonstrates ecological sustainability using locally sourced natural materials and environmentally friendly demolition methods. In this study, the environmental impact of adding cement to soil materials for rammed-earth farmhouse construction in rural China was investigated and comparatively simulated using the One Click LCA database, focusing on the conflict between sustainability objectives and the practical aspects of cement addition. By analyzing how the addition of cement aligns with local construction practices and by addressing the debate surrounding the inclusion of cement in rammed earth construction, our objective is to provide insights into achieving a balance between the environmental impact and the pragmatic considerations of using cement in earthen building practices. Three local structure scenarios are evaluated via simulations: a cement-stabilized rammed earth wall, a fired brick wall, and a localized reinforced concrete frame structure. The quantitative environmental impacts are assessed, and the qualitative differences in adaptation, economic sustainability, and other factors are examined in the context of present-day development in rural China. The results show that the use of cement-stabilized rammed earth wall-supported structures is associated with higher embodied carbon emissions compared to structures supported by reinforced concrete frames and enclosed by brick walls; however, these emissions are lower than those for brick wall-supported structures, while effectively meeting the structural requirements. In addition, the use of cement-stabilized earth for perimeter walls simplifies material management and disposal throughout the building's life cycle, and the cost-effectiveness of cement has been found to be substantially greater than that of reinforced concrete frames and brick structures, improving economic viability and social acceptability, especially among low-income communities in rural areas.

Lodging poses a significant challenge to rice yield, prompting the need to identify elite alleles for lodging resistance traits to improve cultivated rice varieties. In this study, a natural population of 518 rice accessions was examined to identify elite alleles associated with plant height (PH), stem diameter (SD), stem anti-thrust (AT/S), and various internode lengths: (first (FirINL), second (SecINL), third (ThirINL), fourth (ForINL), and fifth (FifINL) internode lengths). 262 SSR markers linked to these traits were uncovered through association mapping in two environmental conditions. Phenotypic evaluations revealed striking differences among cultivars, and genetic diversity assessments showed polymorphisms across the accessions. Favorable alleles were identified for PH, SD, AT/S, and 1 to 5 internode lengths, with specific alleles displaying considerable effects. Noteworthy alleles include RM6811-160 bp on chromosome 6 (which reduces PH) and RM161-145 bp on chromosome 5 (which increases SD). The study identified a total of 42 novel QTLs. Specifically, seven QTLs were identified for PH, four for SD, five for AT/S, five for FirINL, six for SecINL, five for ThirINL, six for ForINL, and four for FifINL. QTLs qAT/S-2, qPH2.1, qForINL2.1, and qFifINL exhibited the most significant phenotypic variance (PVE) of 3.99% for the stem lodging trait. AT/S, PH, ForINL and FifINL had additive effects of 5.31 kPa, 5.42 cm, 4.27cm and 4.27cm, respectively, offering insights into eight distinct cross-combinations for enhancing each trait. This research suggests the potential for cross-breeding superior parents based on stacked alleles, promising improved rice cultivars with enhanced lodging resistance to meet market demands.

There are two contrary opinions regarding the risk if mainland China (MC) moves away from its zero-COVID policy. Some experts think the risk shall be much lower than influenza as per MC’s own COVID-19 case fatality rate (CFR), while some other experts think the risk shall be much higher than influenza as per the COVID-19 CFRs of other regions. We elucidate here that this and multiple other striking differences in the CFR between various scenarios all support and substantially resulted from the view that good IDM is highly powerful to mitigate COVID-19, where IDM (isolation-disinfection-maintenance) means isolation of COVID-19 cases from other people, disinfection of their living environments, and health maintenance (e.g., rest, nutrition, breathing). The high effect of good IDM is also supported by the theoretic functions of IDM in minimizing co-infections and maintaining body functions, and the fact that all the 505 COVID-19 deaths reported in MC in 2022 before May 5 died directly of severe underlying diseases with COVID-19. Although it is tough for people in poverty to obtain good IDM, good IDM can be feasible at home for the most mild cases and in hospitals for the most severe cases. Therefore, good IDM can be crucial to mitigating COVID-19 worldwide. It also suggests that the risk for China to end its zero-COVID policy depends on China’s control policies or measures. Based on the effect of IDM, the cautious co-existence policy was proposed for COVID-19 control. This policy could reduce the whole death toll in MC because good IDM is non-specific and can reduce deaths of various other diseases. The cautious co-existence policy (non-specific) and the vaccination policy (specific) aid each other to mitigate COVID-19, and they cannot replace each other. Those who are qualified in health for vaccination should be vaccinated against COVID-19 timely.

Density functional theory (DFT) and coupled cluster theory (CCSD(T)) calculations are performed to investigate the geometric, electronic structures and chemical bonding of a series of Cu-doped zinc oxide clusters, CunZn3O3 (n = 1-4). The structural evolution of CunZn3O3 (n = 1-4) clusters are elaborated in our work. The planar seven-membered ring of CuZn3O3 cluster plays an important role in the structural evolution, that is, the Cu atom, Cu dimer (Cu2) and Cu trimer (Cu3) anchor on the CuZn3O3 cluster. The aggregate behavior of Cu atoms on Zn3O3 may offer insight into the study of Cu/ZnO-based catalysts. Additionally, it is found that the CunZn3O3 clusters become more stable as the Cu content (n) increases. Bader charge analysis points out that as the Cu atoms doping, the reducibility of Cu aggregation (Cun-1) on the CuZn3O3 cluster increases. Combined with the d-band centers and the surface electrostatic potential (ESP), the reactivity and the possible reaction sites of CunZn3O3 (n = 1-4) clusters are also illustrated.

Quantitative determination of the critical size of inclined coal pillar in old goaf water affected area is of great significance for water damage prevention and safe mining. The critical size of inclined waterproof coal pillar is derived by using theoretical analysis, numerical calculation and field engineering practice for the stability of the waterproof coal pillar in old goaf water affected area of 1303 working face of Dananhu I mine in Xinjiang region. Firstly, a force model of inclined waterproof coal pillar was established to reveal the law that the critical size of the coal pillar increases with the increase of coal seam inclination under the action of asymmetric load. Then, numerical simulation was applied to reveal the dynamic evolution process of plastic deformation-destabilization-destruction of section coal pillar under the influence of mining and single-side water pressure, and the critical size of waterproof coal pillar in study area was determined to be 19.09m. Finally, measures such as pumping and pressure relief and slurry reinforcement were adopted to reduce the deformation rate of the roadway on side of waterproof coal pillar, which ensured the stability of the coal pillar and roadway and the safe recovery of the working face.

Heart regeneration after myocardial infarction remains challenging in reconstruction of blood resupply system. Here, we find that in zebrafish heart after resection of the ventricular apex, the local myocardial cells and the clotted blood cells undergo cell remodeling process via cytoplasmic exocytosis and nuclear reorganization within revascularization-based blastema. The regenerative processes are visualized by spatiotemporal expression of three blastema representative factors (alpha-SMA- which marks for fibrogenesis, Flk1for angiogenesis/hematopoiesis, and Pax3a for remusculogensis)，and two histone modifications (H3K9Ac and H3K9Me3 mark for chromatin remodeling). Using the cultured zebrafish embryonic fibroblasts we identify blastema fraction components and show that Krt5 peptide could link cytoskeleton network and BMP4 signaling pathway to regulate the transcription and chromatin accessibility at the blastema representative genes and bmp4 genes. Our study provides new mechanistic insights into the epithelial-dependent and revascularization-based blastema regeneration for potential myocardial infarction therapy.

Cordyceps sinensis is one rare medicinal fungus produced in the Qinghai-Tibetan Plateau. Its quality and price varies hugely with different habitat, and its numerous substitutes have sprung up in functional food markets. This paper aims to discriminate the geographic origin of wild C. sinensis and its substitutes via the element analyzer-isotope ratio mass spectrometry and gas chromatography-isotope ratio mass spectrometry. The δ¹³C values of major fatty acids in the lipids of Cordyceps sinensis are characterized unanimously by the variation relation C_18:0 ﹤ C_18:2 ≈ C_16:0 ﹤ C_18:1; while their fluctuation intervals are notably different between those of neutral and polar lipids. The comparative analysis of the δ¹³C ratios of major fatty acids in lipids of Cordyceps sinensis suggests that the δ¹³C patterns may be sensitive potential indicators to discriminate its geographical origin. The δ¹³C values of individual major fatty acids of lipids from the cultivated stromata of Cordyceps militaris (SCM), the fermented mycelia of Hirsurella sinensis (FMH) and Paecilomyces epiali (FMP) range from −31.2‰ to −29.7‰, −16.9‰ to −14.3‰, and −26.5‰ to −23.9‰, respectively. Their δ¹³C pattern of individual major fatty acids may be used as a potential indicator to discriminate the products of natural C. sinensis and its substitutes.

Obesity is a highly prevalent chronic disease characterized by excessive weight gain and fat accumulation. There is growing evidence that Lactiplantibacillus plantarum strains with bile salt hydrolase (BSH) activity are effective in preventing and alleviating obesity. However, few of them has confirmed the anti-obesity effect of BSH by gene deletion. In this study, 23 BSH-positive Lp. plantarum strains were screened by bile salt precipitation halo assay. Among these strains, Lp. plantarum Lp20 showed the highest BSH activity with a hydrolysis rate to glycodeoxycholic acid (GDCA) by 91.62%. Genomic sequencing and bioinformatics analysis indicated that gene bsh1 was associated with BSH activity of Lp. plantarum Lp20 and gene deletion of bsh1 confirmed the role of Bsh1 in GDCA hydrolysis. To investigate if the Bsh1 from Lp. plantarum Lp20 could alleviate obesity, the wild type and bsh1 deletion mutant strains were administered daily for 8 weeks to diet-induced obese mice, respectively. Compared with mutant strain, the wild type strain Lp20 significantly reduced body weight gain, inguinal white adipose tissue and mesenteric fat mass in obese mice. In addition, Lp20 also reduced serum total cholesterol levels and LDL-C by 20.8% and 33.3%, respectively. Furthermore, the recovered liver steatosis was only observed in Lp. plantarum Lp20 treated mice. Taken together, the bile salt hydrolase Bsh1 from Lp. plantarum Lp20 was a key functional factor on ameliorating HFD-induced obesity by reducing cholesterol levels and suppressing adipogenesis in mice.

To enhance the performance of visual SLAM in underwater environments, this paper presents an enhanced front-end method based on visual feature enhancement. The method comprises three modules aimed at optimizing and improving the matching capability of visual features from different perspectives. Firstly, to address issues related to insufficient underwater illumination and uneven distribution of artificial light sources, a brightness consistency recovery method is pro-posed. This method employs an adaptive histogram equalization algorithm to balance the brightness of images. Secondly, a method for denoising underwater suspended particulates is introduced to filter out noise from the images. After image-level processing, a combined underwater acousto-optic feature association method is proposed, which associates acoustic features from sonar with visual features, thereby providing distance information for the visual features. Finally, utilizing the AFRL dataset, the improved system incorporating the proposed enhancement methods is evaluated for performance against the OKVIS framework. The system achieves better trajectory estimation accuracy compared to OKVIS and demonstrates robustness in underwater environments.

Background and Objectives: Treatment for antineutrophil cytoplasmic antibody-associated vasculitis (AAV) must deal with immunosuppression as well as infections associated with compromised immune system, such as tuberculosis (TB). Our aim was to overcome the gap in the literature concerning the risk of incidental TB after diagnosis of AAV. Materials and Methods: This retrospective population-based cohort study was based on the data from the National Health Insurance Research Database in Taiwan. We used a novel algorithm to identify patients with newly diagnosed granulomatous polyangiitis (GPA) or microscopic polyangiitis (MPA) between January 1, 2000 and December 31, 2012. The primary outcome was risk of incidental TB. Cox proportional hazard models were used to evaluate the association between AAV and incidental TB. Results: A total of 2,257 patients with AAV and a propensity-score matched cohort of 9,028 patients were studied. Overall, patients with AAV were at a 1.48x higher risk of contracting incidental TB than were patients in the matched cohort (adjusted HR 1.48; 95% confidence interval [CI], 1.02-2.15). Note that the highest risk of contracting incidental TB was in the first two years following a diagnosis of AAV, with a nearly 1-fold increase in risk (adjusted HR, 1.91; 95% CI, 1.01-3.60). Female AAV patients were 3.24x more likely than females without AAV to develop TB (adjusted HR 3.24; 95%CI, 1.85-5.67). Conclusion: Patients with AAV face an elevated risk of contracting incidental TB, particularly within the first two years after AAV diagnosis. The risk of contracting TB is higher among female AAV patients than among females without AAV.

Papillary thyroid carcinoma (PTC) accounts for approximately 85%-90% of all thyroid cancers. BRAFV600E mutation is a highly specific target for papillary thyroid carcinoma (PTC) and may have a reciprocal causative relationship with iodide-metabolizing genes. Here, we performed a review of studies published in the past 10 years to determine the relationship between iodine intake and BRAFV600E mutation in patients with PTC. We searched the MEDLINE, PubMed, and EMBASE databases for studies published from 2009 to 2019; seven partially matched the selection criteria and were suitable for review, and five passed all selection criteria. We divided the patients into three groups by iodine intake: low (urinary iodine concentration [UIC] &lt;100 μg/L), adequate (UIC 100–200 μg/L), and high iodine intake groups (UIC ≥200 μg/L). Between-group analysis revealed no significant differences in the odds ratio of the prevalence of BRAFV600E mutation between the high and adequate/low iodine intake groups and between the adequate and low iodine intake groups. To further analyzed the results of studies, they exhibited U-shaped curves in the relation of deficient and excessive dietary iodine intake in BRAFV600E mutation. The results might suggest that iodine intake slightly influences the prevalence of BRAFV600E mutation in patients with PTC despite the heterogeneity of studies. Further research should explore potential mechanisms underlying the associations between iodine intake and BRAF mutation in PTC. The systematic review was registered in PROSPERO (CRD42021279462).

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

This is a survey study that dialysis patients were randomly sampled from a medical center in northern Taiwan, and those who gave their consent to participate were included in this study. The purpose of this study was to explore the correlation between depression, hope, and quality of life of dialysis patients. All subjects agreed to take "Beck’s Depression Inventory", " The Chinese version of Herth Hope Index" and " The Chinese version of Kidney Disease Quality of Life" (KDQOL-SFTM). Data were processed using SPSS for descriptive and inferential statistics. The results showed that patients were 12.45±SD 9.03, which was mild depression, the mean score of hope was 34.25, which was equivalent to 72.60%, and was at the middle level. In KDQOL-SFTM, the score in mental composite (M=42.65, SD=8.81) was higher than in physical composite (M=37.38, SD=9.28), and the score was at the intermediate quality of life, and hope and depression were significantly and negatively correlated. This study suggests that dialysis case managers provide nursing guidance to help dialysis patients learn comfortable care methods and support the resilience they need.

Subway construction is often in a complex natural and human-machine operating environment, and that complicated setting leads to subway construction more prone to safety accidents, which can cause substantial casualties and monetary losses. Thus, it is necessary to investigate the safety risks of subway construction. The existing literature on the identification and assessment of subway construction safety risks(SCSR) is susceptible to the influence of subjective factors. Moreover, although existing studies have explored the interrelationships between different risks, these studies usually analyze the interrelationships of single risks, lack the study of risk chain transfer relationships, and fail to find out the key path of risk transfer. Therefore, this paper innovatively combines text mining, association rules and complex networks to deep mine subway construction safety incident reports and explore risk transfer process. Firstly, it uses text mining technology to identify subway construction safety risk; Then, association rules are introduced to explore the causal relationships among safety risk; Finally, the key safety risk and important transfer paths of subway construction safety accidents (SCSA) are obtained based on the complex network model. Research results show that (a) improper safety management, unimplemented safety subject responsibilities, violation of operation rules, non-perfect safety responsibilities system and insufficient safety education and training are the key safety risk in SCSA; (b) two shorter key risk transfer paths in the subway construction safety network can be obtained: insufficient safety education and training→lower safety awareness→violation of operation rules→safety accidents; insufficient safety checks or hidden trouble investigations→violation of operation rules→safety accidents; (c) in the process of risk transfer, the risk can be controlled by controlling the key nodes or cutting off the transfer path. The results of the study provide new ideas and methods for SCSR identification and influence element mining, which help safety managers propose accurate subway construction safety risk control measures.

Biological parameters extracted from electrical signals from various body parts have been used for many years to analyze the human body and its behavior. In addition, electrical signals from cancer cell lines, normal cells, and viruses, among others, have been widely used for the detection of various diseases. Single-cell parameters such as cell and cytoplasmic conductivity, relaxation frequency, and membrane capacitance are important. There are many techniques available to characterize biomaterials, such as scanning tunneling microscopy (STM), nanotechnology, microstrip cavity resonance measurement, dielectric impedance measurement (DEPIM), etc. This article reviews the single cell isolation and sorting techniques, summarizes the common single cell operations such as impedance flow cytometry, cell electrical impedance, electrical impedance sensing, and summarizes the current single cell analysis techniques and their applications.

The rapid development of electrochemical CO2 reduction offers a promising route to convert in-termittent renewable energy into products of high value-added fuels or chemical feedstocks. However, low faradaic efficiency, low current density, and a narrow potential range still limited the large-scale application of CO2RR electrocatalyst. Herein, monolith 3D bi-continuous nano-porous Bismuth (np-Bi) electrodes are fabricated via a simple one-step electrochemical dealloying strategy from Pb-Bi binary alloy. The unique bi-continuous porous structure ensures highly effective charge transfer, meanwhile the controllable millimeter-size geometric porous structure enables easy catalyst adjustment to expose highly suitable surface curvatures with abundant reactive sites. This results in a high selectivity of 92.6% and superior potential window (400 mV, selectivity >88%) for electrochemical reduction of carbon dioxide to formate. Our scalable strategy provides a feasible pathway for mass-producing high-performance and versatile CO2 electrocatalysts.

The effects of environmental media on the corrosion fatigue fracture behavior of 25CrMo steel were investigated. The media include air, and a 3.5 wt.% and a 5.0 wt.% NaCl solutions. Experimental results indicate that the media induces the initiation of corrosion fatigue cracks at multiple sites. The multi-cracking sites cause the changes in the crack growth directions, the crack growth rate during the coupling action of the media and the stress amplitude. The coupling effects are important for engineering applications and research. The probability and predictions of the corrosion fatigue characteristic life can be estimated using the 3-parameter Weibull distribution function.

High density of buildings and the large traffic volume of cities give rise to narrow spaces and high passenger flows in most subway stations. When evacuation is required during an emergency, these problems may trigger issues in operational safety. Therefore, it is imperative to comprehensively assess subway station emergency evacuation times and capacities during the operating process to ensure the design is safe, science-based, and rational. To further enhance safe evacuation capacity, this paper proposes an overall evacuation time model that considers the multielement charac-teristics of subway stations in multiple segments. The evacuation route is decomposed into five stages according to the critical nodes in the evacuation process. An overall emergency evacuation time model is established based on the diversity of bottlenecks in the five stages, integrating elements such as the horizontal movement velocity of passengers, subway equipment parameters, and human density. Taking Xi’an Wulukou Subway Station as an example, this paper verifies the outcomes of the theoretical model against the Pathfinder software and conducts additional anal-yses of the evacuation conditions of stairs and exits. The results show that the error between the theoretical emergency evacuation time and simulation evacuation time was 5.4%, The emergency evacuation model established in this study boasts strong robustness and stability.

The characteristics of gap plasmon formed by nanoparticle-on-mirror (NPOM) structure composed of metal nanoparticles (MNP) and metal thin films have aroused the interest of various optoelectronic devices. The resonant spectrum obtained by the internal coupling effect of gap can be flexibly controlled by the polarization of incident light and the thickness of the dielectric layer between MNP and metal thin films. We have theoretically studied the resonance spectra of polarization-dependent gold ellipsoidal nanoparticles (GENP) and gold thin films in the gap region of NPOM structures. GENP and gold thin films are separated by a dielectric layer with a refractive index of 1.36. We observe that the intensity of the local electric field resonance peak in the gap region is inversely proportional to the polarization angle. Similarly, the intensity of the local electric field resonance peak in the gap region is inversely proportional to the thickness of the dielectric layer. We have obtained more than 2200 V/m local electric field intensity (dielectric layer thickness 0.3nm). Finally, the resonant peak wavelength of the electric field in the gap region of the NPOM structure is also controlled by the polarization angle of the incident light and the thickness of the dielectric layer.

The determination of a causal relationship between gut microbiota and a range of dyslipidemia remains uncertain. To clarify these associations, we employed a two-sample mendelian randomization (MR) analysis utilizing the inverse-variance weighted (IVW) method. This comprehensive analysis investigated the genetic variants that exhibited a significant association (p&lt;1e-5) with 129 distinct gut microbiota genera, and their potential link to diverse forms of dyslipidemia. The results indicated a potential causal relationship between 22 gut microbiota genera and dyslipidemia in humans. Furthermore, these findings suggested that the impact of gut microbiota on dyslipidemia regulation is dependent on the specific phylum, family, and genus. Bacillota phylum demonstrated the greatest diversity, with 15 distinct genera distributed among 8 families. Notably, gut microbiota derived from the Lachnospiraceae and Lactobacillaceae families exhibit statistically significant associations with lipid levels that contribute to overall health (p&lt;0.05). The sensitivity analysis indicated that our findings possess robustness (p&gt;0.05). The findings of our investigation provide compelling evidence that supports a causal relationship between the gut microbiota and dyslipidemia in the human body. It is noteworthy to highlight the significant influence of the Bacillota phylum as a pivotal regulator of lipid levels, and the families Lachnospiraceae and Lactobacillaceae should be acknowledged as probiotics that make substantial contributions to this metabolic process.

Heterosis plays a significant role in enhancing variety, boosting yield, and raising economic value, but the molecular mechanism is still unclear. We analyzed the transcriptomes and 3D genomes of hybrid (F1) and its parents (w30 and 082). Analysis of the expression revealed a total of 485 specially expressed genes (SEGs), 173 differentially expressed genes (DEGs) above parental expression level, more actively expressed genes and up-regulated DEGs in F1. Further study revealed that the DEGs detected in F1 and its parents were mainly involved in response to auxin, plant hormone signal transduction, DNA metabolic process, Purine metabolism, starch and sucrose metabolism, which suggested that these biological processes may play a crucial role in the heterosis of B. rapa. The analysis of 3D genome data revealed that hybrid F1 tend to contain more transcriptionally active A compartments after hybridization. Additionally, F1 had a smaller TAD (topologically associated domain) genome length, but the number was the highest, and the expression change of activated TAD was higher than repressed TAD. More specific TAD boundaries were detected between parents and F1. Subsequently, 140 DEGs with genomic structural variants were selected as potential candidate genes. Among them, we found two DEGs with consistent expression changes in A/B compartments and TADs. Our findings suggest that genomic structural variants, such as TADs and A/B compartments, may affect gene expression and contribute to heterosis in B. rapa. This study provides further insight into the molecular mechanism of heterosis in B. rapa.

An improved anti-noise morphology vision navigation algorithm is proposed for intelligent tractor tillage in a complex agricultural field environment. Firstly, the two key steps, Guided Filtering and improved anti-noise morphology navigation line extraction, were addressed in detail. Then the experiments were carried out in order to verify the effectiveness and advancement of the presented algorithm. Finally, the optimal template and its application condition were studied for improving the image processing speed. The comparison experiment results show that the YCbCr color space has minimum time consumption, 0.094 s, compared with HSV, HIS and 2R-G-B color spaces. The Guided Filtering method can enhance the new & old soil boundary effectively than any other methods such as Tarel, Multi-scale Retinex, Wavelet-based Retinex and Homomorphic Filtering, meanwhile, has the fastest processing speed of 0.113 s. The extracted soil boundary line of the improved anti-noise morphology algorithm has best precision and speed compared with other operators such as Sobel, Roberts, Prewitt and Log. After comparing different size of image template, the optimal template with the size of 140×260 pixels can meet high precision vision navigation while the course deviation angle is not more than 7.5°. The maximum tractor speed of the optimal template and global template are 51.41 km/h and 27.47 km/h respectively which can meet real-time vision navigation requirement of the smart tractor tillage operation in the field. The experimental vision navigation results demonstrated the feasibility of the autonomous vision navigation for tractor tillage operation in the field using the new & old soil boundary line extracted by the proposed improved anti-noise morphology algorithm which has broad application prospect.

Human monkeypox, caused by monkeypox virus, has spread unprecedentedly to more than 100 countries since May 2022. Here we summarized the epidemiology of monkeypox through a literature review and elucidated the risks and elimination strategies of this outbreak mainly based on the summarized epidemiology. We demonstrated that monkeypox virus became more contagious and less virulent in 2022, which could result from the fact that the virus entered a special transmission network favoring close contacts (i.e., sexual behaviors of men who have sex with men outside Africa) and the possibility that the virus accumulated a few adaptive mutations. We gave the reasons to investigate whether cattle, goats, sheep, and pigs are susceptible to monkeypox virus and whether infection with monkeypox virus could be latent in some primates. We listed six potential scenarios for the future of the outbreak (e.g., the outbreak could lead to endemicity outside Africa with increased transmissibility or virulence). We also listed multiple factors aiding or impeding the elimination of the outbreak. We showed that the control measures strengthened worldwide after the World Health Organization declared the outbreak a public health emergency of international concern (PHEIC) could eliminate the outbreak in 2022. We clarified eight strategies, i.e., publicity and education, case isolation, vaccine stockpiling, risk-based vaccination or ring vaccination, importation quarantine, international collaboration, and laboratory management, for the elimination of the outbreak.

Light pen 3D vision coordinate measurement systems are increasingly widely used due to their advantages, such as small size, convenient carrying and wide applicability. The posture of the light pen is an important factor affecting accuracy. The pose domain of the pen needs to be given so that the measurement system has a suitable measurement range to obtain more qualified parameters. The advantage of the self-calibration method is that the entire self-calibration process can be completed at the measurement site without any auxiliary equipment. After the system camera calibration is completed, we take several pictures of the same measurement point with different poses to obtain the conversion matrix of the picture, and then use spherical fitting, the generalized inverse method of least squares, and the principle of position invariance within the pose domain range. The combined stylus tip center self-calibration method calculates the actual position of the light pen probe. The experimental results show that the absolute error is stable below 0.0737 mm and that the relative error is stable below 0.0025 mm. The experimental results verify the effectiveness of the method; the measurement accuracy of the system can meet the basic industrial measurement requirements.

The reduction of biodiversity loss is one of the targets of the 2030 Agenda for Sustainable Development. The protection of endangered species is critical for conserving global biodiversity. Asian elephants，as one of the last few mega-herbivores on Earth, are currently threatened by climate changes and anthropogenic modifications. The modelling of their living habitats is of top priority to the conservation of Asian elephant. In this study, we used the maximum entropy model (MaxEnt) to identify the current and potential future habitats of Asian elephants in South and Southeast Asia. We performed analyses for future projections with 17 scenarios by using the present results as baseline. To optimise the modelling results, we delineated the core habitats by using the Core Mapper Tool and compared them with existing protected areas (PAs) through gap analysis. The results showed that the current total area of core habitats is 491,455 km2 in size and will be reduced to 332,544 km2 by 2090 under SSP585 (the shared socioeconomic pathway). The projection analysis under differential scenarios suggested that most of the core habitats in the current protected areas would remain stable and suitable for elephants in the future. However, the remaining 75.17% of the core habitats lay outside the current PAs, and finally we mapped approximately 219,545 km2 of suitable habitats as priority protected areas in the future. Although our model did not perform well in some regions, our analyses and findings still could provide useful references to the planning of protected areas and conservation of Asian elephant.

An improved anti-noise morphology vision navigation algorithm is proposed for intelligent tractor tillage in a complex agricultural field environment. At first the two key steps, Guided Filtering and improved anti-noise morphology navigation line extraction were addressed in detail. Then the experiments were carried out in order to verify the effectiveness and advancement of the presented algorithm. Finally, the optimal template and it’s application condition were studied for improving the image processing speed. The comparison experiment results show that the YCbCr color space has minimum time consumption of 0.094 s in comparison with HSV, HIS and 2R-G-B color spaces. The Guided Filtering method can effectively distinguish the boundary between the new and old soil than other competing vanilla methods such as Tarel, Multi-scale Retinex, Wavelet-based Retinex and Homomorphic Filtering inspite of having the fastest processing speed of 0.113 s. The extracted soil boundary line of the improved anti-noise morphology algorithm has best precision and speed compared with other operators such as Sobel, Roberts, Prewitt and Log. After comparing different size of image template, the optimal template with the size of 140×260 pixels can meet high precision vision navigation while the course deviation angle is not more than 7.5°. The maximum tractor speed of the optimal template and global template are 51.41 km/h and 27.47 km/h respectively which can meet real-time vision navigation requirement of the smart tractor tillage operation in the field. The experimental vision navigation results demonstrated the feasibility of the autonomous vision navigation for tractor tillage operation in the field using the new and old soil boundary line extracted by the proposed improved anti-noise morphology algorithm which has broad application prospect.

With the advancement of photoelectric technology and computer image processing technology, the visual measurement method based on point clouds is gradually applied to the 3D measurement of large workpieces. Point cloud registration is a key step in 3D measurement, and its registration accuracy directly affects the accuracy of 3D measurements. In this study, we designed a novel MPCR-Net for multiple partial point cloud registration networks. First, an ideal point cloud was extracted from the CAD model of the workpiece and was used as the global template. Next, a deep neural network was used to search for the corresponding point groups between each partial point cloud and the global template point cloud. Then, the rigid body transformation matrix was learned according to these correspondence point groups to realize the registration of each partial point cloud. Finally, the iterative closest point algorithm was used to optimize the registration results to obtain a final point cloud model of the workpiece. We conducted point cloud registration experiments on untrained models and actual workpieces, and by comparing them with existing point cloud registration methods, we verified that the MPCR-Net could improve the accuracy and robustness of the 3D point cloud registration.

Intelligent systems are increasingly present in various areas of society, gaining special relevance in healthcare environments. In this work, grounded on previous developments proposed by the authors, the evolution and improvement of a novel intelligent system focused on the diagnosis of obstructive sleep apnea (OSA) is addressed. To do this, starting from two packages of information of a heterogeneous nature, and deploying a set of Machine Learning classification algorithms, focused each of them on different levels of the apnea-hypopnea index (AHI), as well as a set of cascaded expert systems, it is possible to obtain a series of risk metric pairs (Statistical Risk, Symbolic Risk) for each AHI level, understood as a warning forecast associated with the early detection of the pathology. The risk indicators of each pair are subsequently aggregated by means of a symbolic inference system, whose knowledge base was determined using the automatic rule generation approach proposed by Wang and Mendel. At the output of each inference system, a risk indicator is obtained for each AHI level, the Apnea Risk, whose interpretation makes it possible to discriminate between patients who could suffer OSA and those who do not, as well as to generate the appropriate recommendations. For the initial tests of the system, the design and development of a specific software artifact was carried out using data from 4,400 patients from the Álvaro Cunqueiro Hospital in Vigo, obtaining when applied to the test set AUC values within the range 0.74–0.88, which invites optimism and points to the benefits expected from the architecture of the proposed intelligent system.

The recurrent coronavirus outbreaks in China (SARS-CoV and its relative, SARS-CoV-2) have raised speculations that perhaps Asians are somehow more susceptible to these coronaviruses. Here, we test this possibility based on an analysis of the lung-specific expression of ACE2, which encodes the known cell-entry receptor of both SARS-CoV and SARS-CoV-2. We show that ACE2 expression is not affected during tumorigenesis, supporting that the abundant transcriptomes in cancer genomic studies can be informatively used to study ACE2 expression among diverse individuals without cancer. We find that ACE2 expression in the lung increases with age, but is not associated with sex. Further, Asians do not differ from other populations for ACE2 expression and do not harbor unique genetic polymorphisms in the ACE2 locus. Thus, beyond illustrating an innovative method for assessing the potential impacts of demographic factors for non-cancer diseases from large-scale cancer sample datasets, our statistically robust findings emphasize that individuals of all races require the same level of personal protection against SARS-CoV-2.