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In order to explore the influence of the remaining coal pillar in the upper coal seam on the stress of the floor and the reasonable layout of the mining roadway in the lower coal seam, taking Tangshangou Coal Mine as the research object, the theoretical analysis and numerical simulation methods and a variety of influencing factors were used to construct the collaborative bearing structure model of the remaining coal pillar and the hinged rock block in the upper coal seam and the stress transfer calculation model of the floor, and the stress and influencing factors of the floor under the remaining coal pillar in the upper coal seam are studied. The research shows that the influence of the remaining coal pillars in the upper coal seam on the stress of the floor is mainly vertical stress, and the influence degree decreases with the increase of floor depth. The stress-increasing area of the floor under the remaining coal pillar is ellipsoidal. The influencing factors of the stress-increasing area of the floor are analyzed, and the quantitative relationship between the influence of different factors on the range of the stress-increasing area is obtained. The peak stress of the coal pillar plays a decisive role in the distribution of the stress-increasing area of the floor. According to the stress distribution of the floor and the results of theoretical calculation and numerical simulation, it is determined that the reasonable stagger distance between the 8 coal pillar and the 11−1 coal mining roadway in Tangshangou Coal Mine should be 20—25 m. This study reveals the stress transfer mechanism of the lower floor of the coal pillar left in the upper coal seam, clarifies the distribution and influencing factors of the floor stress increase area, and obtains the determination method of the reasonable stagger value of the roadway-coal pillar, which can provide a theoretical basis for the reasonable layout of the lower coal seam mining roadway.

Abstract Objective This study aimed to evaluate the performance of large language models (LLMs) in the task of abstract screening in systematic review and meta-analysis studies, exploring their effectiveness, efficiency, and potential integration into existing human expert-based workflows. Methods We developed automation scripts in Python to interact with the APIs of several LLM tools, including ChatGPT v4.0, ChatGPT v3.5, Google PaLM 2, and Meta Llama 2, and latest tools including ChatGPT v4.0 turbo, ChatGPT v3.5 turbo, Google Gemini 1.0 pro, Meta Llama 3, and Claude 3. This study focused on three databases of abstracts and used them as benchmarks to evaluate the performance of these LLM tools in terms of sensitivity, specificity, and overall accuracy. The results of the LLM tools were compared to human-curated inclusion decisions, gold standard for systematic review and meta-analysis studies. Results Different LLM tools had varying abilities in abstract screening. Chat GPT v4.0 demonstrated remarkable performance, with balanced sensitivity and specificity, and overall accuracy consistently reaching or exceeding 90%, indicating a high potential for LLMs in abstract screening tasks. The study found that LLMs could provide reliable results with minimal human effort and thus serve as a cost-effective and efficient alternative to traditional abstract screening methods. Conclusion While LLM tools are not yet ready to completely replace human experts in abstract screening, they show great promise in revolutionizing the process. They can serve as autonomous AI reviewers, contribute to collaborative workflows with human experts, and integrate with hybrid approaches to develop custom tools for increased efficiency. As technology continues to advance, LLMs are poised to play an increasingly important role in abstract screening, reshaping the workflow of systematic review and meta-analysis studies.

Abstract To investigate the significant deformation of the surrounding rock within the dynamic pressure zone of the gateroad, this study utilized the tailgate of the 1506 longwall face in Anyang Coal Mine as the engineering context. A combined approach of field measurement and numerical analysis was employed to explore the deformation and failure mechanisms of the surrounding rock under dynamic pressure. The findings indicate that before the exploitation of the 1506 longwall face, there was a notable reduction in stress across the floor and immediate roof, with minimal stress concentration observed in the coal pillar and the entity rib side. The plastic zone surrounding the tailgate was limited, suggesting a high degree of stability in the entry's surrounding rock. However, during the extraction of the 1506 longwall face, the tailgate, extending 60 m ahead of the working face, was subjected to dynamic pressure, leading to a marked increase in stress within the floor, coal pillar, and immediate roof. Stress concentration was more pronounced on the entity rib side than on the pillar rib side. This resulted in significant fissuring and severe deformation of the entry's surrounding rock. The primary failure mechanism involved damage to both the roof and floor corners, with the severity of damage escalating alongside the stress in the surrounding rock. This culminated in the failure of roof corner bolts and anchor cables, thereby compromising the stability of the entry within the dynamic pressure zone.

Highlights 3D printable functional inks incorporated with graphene and carbon nanotube nanoparticles were well-formulated by manipulating their rheological performance The frame with ultralight structure (0.076 g cm−3) and high-efficiency electromagnetic interference shielding (61.4 dB) was assembled 3D-printed c-SE module was in situ integrated onto the electronics, affording multiple functions of electromagnetic compatibility and thermal dissipation.

Safety signal detection is an integral component of Pharmacovigilance (PhV), which is defined by the World Health Organization as “science and activities relating to the detection, assessment, understanding, and prevention of adverse effects or any other possible drug related problems”. The purpose of safety signal detection is to identify new or known adverse events (AEs) resulting from the use of pharmacotherapeutic products. While post-marketing spontaneous reports from different sources are commonly utilized as a data source for detecting these signals, there are underlying challenges arising from data complexity. This paper investigates the implementation of the Apriori algorithm, a popular method in association rule mining, to identify frequently co-occurring drugs and AEs within safety data. We discuss previous applications of the Apriori algorithm for safety signal detection and conduct a detailed study of an improved method specifically tailored for this purpose. This enhanced approach refines the classical Apriori method to effectively reveal potential associations between drugs/vaccines and AEs from post-marketing safety monitoring datasets, especially when AEs are rare. Detailed comparative simulation studies across varied settings coupled with the application of the method to vaccine safety data from the Vaccine Adverse Event Reporting System (VAERS) demonstrate the efficacy of the improved approach. In conclusion, the improved Apriori algorithm is shown to be a useful screening tool for detecting rarely occurring potential safety signals from the use of drugs/vaccines using post-marketing safety data.

In recent years, due to the changing climate conditions and the continuous deepening of water resource conservation measures, the groundwater level in northern China has gradually risen, leading to the increasingly prominent issue of anti-floating in existing buildings and structures. The development and adoption of reliable anti-floating reinforcement techniques for existing structures are crucial for ensuring the quality of such reinforcements. Therefore, focusing on the limitations of the anchor method for anti-floating reinforcement, this paper proposes a new type of anti-floating prestressed compression anchor that features a full-length anti-compressive steel pipe with a bearing body at the end and uses non-bonding tendons throughout its length. Firstly, the structural form of this pressure-type anchor is introduced; subsequently, combined with the results of on-site pull-out tests of the anchor, an analysis is conducted on the working principle, lateral resistance distribution, and internal force transfer mechanism of the new anti-floating anchor, and its load-bearing characteristics are elucidated. Finally, relying on actual anti-floating reinforcement projects and through numerical calculations, the changes in internal forces under different anti-floating conditions of existing structures reinforced with the new anchor compared to conventional anchors are contrasted. Research findings and engineering practice indicate that this new anti-floating anchor improves the mechanical performance of the grout body of the anchor, solves the water seepage problem at the anchor location of the waterproof slab, effectively suppresses cracking of the foundation waterproof slab after reinforcement, and enhances the anti-floating and durability of existing structures.

Abstract Immunotherapy as a strategy to deal with cancer is increasingly being used clinically, especially in hepatocellular carcinoma (HCC). We aim to create an immunotherapy-related signature that can play a role in predicting HCC patients’ survival and therapeutic outcomes. Immunotherapy-related genes were discovered first. Clinical information and gene expression data were extracted from GSE140901. By a series of bioinformatics methods to analyze, overlapping genes were used to build an immunotherapy-related signature that could contribute to predict both the prognosis of people with hepatocellular carcinoma and responder to immune checkpoint blockade therapy of them in TCGA database. Differences of the two groups in immune cell subpopulations were then compared. Furthermore, A nomogram was constructed, based on the immunotherapy-related signature and clinicopathological features, and proved to be highly predictive. Finally, immunohistochemistry assays were performed in HCC tissue and normal tissue adjacent tumors to verify the differences of the four genes expression. As a result of this study, a prognostic protein profile associated with immunotherapy had been created, which could be applied to predict patients' response to immunotherapy and may provide a new perspective as clinicians focus on non-apoptotic treatment for patients with HCC.

To achieve the goals of carbon peaking and carbon neutrality in Shaanxi, the high energy consuming manufacturing industry (HMI), as an important contributor, is a key link and important channel for energy conservation. In this paper, the logarithmic mean Divisia index (LMDI) method is applied to determine the driving factors of carbon emissions from the aspects of economy, energy and society, and the contribution of these factors was analyzed. Meanwhile, the improved sparrow search algorithm is used to optimize Elman neural network (ENN) to construct a new hybrid prediction model. Finally, three different development scenarios are designed using scenario analysis method to explore the potential of HMI in Shaanxi Province to achieve carbon peak in the future. The results show that: (1) The biggest promoting factor is industrial structure, and the biggest inhibiting factor is energy intensity among the drivers of carbon emissions, which are analyzed effectively in HMI using the LMDI method. (2) Compared with other neural network models, the proposed hybrid prediction model has higher accuracy and better stability in predicting industrial carbon emissions, it is more suitable for simulating the carbon peaking process of HMI. (3) Only in the coordinated development scenario, the HMI in Shaanxi is likely to achieve the carbon peak in 2030, and the carbon emission curve of the other two scenarios has not reached the peak. Then, according to the results of scenario analysis, specific and evaluable suggestions on carbon emission reduction for HMI in Shaanxi are put forward, such as optimizing energy and industrial structure and making full use of innovative resources of Shaanxi characteristic units.

As the depth of coal seams increases and the demand for coal grows, the deformation and failure of roadways and coal pillars also intensify. To address the instability of roadways, it is crucial to study the appropriate dimensions for coal pillars. This paper focuses on the 1513 working face of the No. 5 coal seam at Anyang Coal Mine to address the issue of insufficient basis for determining coal pillar width. Through field observations and physical similarity simulations, this study examines the overlying strata failure patterns above coal pillars post-mining and the bearing structure formed by key layers. The relationship between these factors is analyzed using theoretical analysis and physical similarity simulations. A mechanical model of the coal pillar and the “hinged-hinged” overlying strata failure structure is established, analyzing the fracture characteristics of the overlying strata and the bearing structure of the coal pillar to determine the optimal coal pillar width under these conditions. The results indicate that when the coal pillar width is optimized from 25 m to 14 m, the overlying bearing layer is disrupted by the mining activities at the working face, with the lower key layer forming a “hinged” structure upon fracture. As mining progresses, the height of the overlying strata fractures gradually increases, causing the upper key layer to also fracture and form a “hinged-hinged” structure between the high and low bearing layers. According to the “three zones” development law, the height of overlying strata failure does not continue to increase indefinitely, and the coal pillar is affected by the “hinged-hinged” structure of the bearing strata. A mechanical model of the coal pillar bearing structure is established based on the fracture combination structure of the bearing strata. By calculating the load on the “hinged-hinged” structure of the overlying strata, the appropriate coal pillar width is determined to be 15 m. Theoretical calculations, physical similarity simulation experiments, and field applications show that without changing the support conditions, the deformation of the roadway is greater when the coal pillar is narrowed, compared to its original width. The maximum deformation, located 60 m ahead of the working face, increased by 41–42%, while deformation in other areas was relatively minor. This validates the reasonableness of the determined coal pillar width.

Typhoons bring great damages to transmission line systems located in coastal areas. Strong wind and extreme precipitation are the main sources of damaging effects. Transmission lines suffered from wind-driven rain exhibit more susceptibility to damage due to the coupled effect of wind and rainwater. This paper presents an integrated numerical simulation framework based on mesoscale WRF model, multiphase CFD model and FEM model to analyze the motions of a transmission line subjected to coupled wind and rain loads during typhoon events. A full-scale transmission line in Zhoushan Island is employed to demonstrate the effectiveness of the proposed framework by simulating typhoon evolution in terms of wind fields and rainfall, solving the coupled wind and rain fields around the conductor and predicting the dynamic responses of the transmission line during Super Typhoon Lekima in 2019. The results show that the horizontal displacements of the transmission line under the joint actions of wind and rain increase approximately 17–18% compared to those of wind loads only. It is important to consider the coupled effects of wind-driven rain on conductors in the design of transmission lines under typhoon conditions.

AbstractBackground The effects of serum uric acid (SUA) on clinical outcomes in patients with acute kidney injury (AKI) are unclear. The aim of this study was to investigate the association of SUA levels with clinical outcomes of AKI patients.Methods The data of AKI patients hospitalized in the Affiliated Hospital of Qingdao University were retrospectively reviewed. Multivariable logistic regression was utilized to assess the association between SUA levels and the clinical outcomes of AKI patients. Receiver operating characteristic (ROC) analysis was applied to assess the predictive ability of SUA levels for in-hospital mortality in patients with AKI.Results A total of 4,646 AKI patients were eligible for study inclusion. In multivariable analysis, after adjustment for various confounding factors in the fully adjusted model, a higher SUA level was found to be associated with increased in-hospital mortality of AKI patients with an odds ratio (OR) of 1.72 (95% CI, 1.21–2.33, p = 0.005) for the SUA level >5.1–6.9 mg/dl group and 2.75 (95% CI, 1.78–4.26, p 6.9 mg/dl group compared with the reference group (SUA ≤3.6 mg/dl). In the ROC analysis, the area under the curve (AUC) of SUA was 0.65 with a sensitivity of 51% and a specificity of 73%.Conclusions An elevated SUA level is associated with an increased risk of in-hospital mortality in patients with AKI, and it appears to be an independent prognostic marker for these patients.

The Corona Virus Disease 2019 (COVID-19) has influenced the daily life of urban residents worldwide. In the post COVID-19 period, the proportion of public transport commuting trips decreased, whereas that of car commuting trips increased. As a sustainable travel mode, customized bus services have been promoted to ensure the public health security during commuting in this period in many cities in China and other countries. This study focused on the promotion of sustainable travel behavior in the post COVID-19 period from the perspective of customized bus services. A total of 664 respondents from Shanghai, China participated in this study to provide revealed preference (RP) and stated preference (SP) data related to the customized bus services in the post COVID-19 period. The mode choice model was established based on the hypothetical scenarios to estimate the commuters’ intention to shift to the customized bus services, determine the mode preference of different groups, and suggest potential policies. The results showed that the preference for customized buses decreased with the increasing fare for one journey, the travel time, and the availability of a one-way ticket, and middle-class commuters had a higher preference for commuting by customized bus. The measures for the short and long term in the post COVID-19 period were proposed. The results of this study can help governments adopt policies to promote customized bus services not only in the post COVID-19 period but also during regular daily life.

As the core component of a ship’s engine room, the operation of a marine diesel engine (MDE) directly affects the economy and safety of the entire vessel. Predicting the future changes in the status parameters of a MDE helps to understand the operational status, enabling timely warnings to the engine crew, and to ensure the safe navigation of the vessel. Therefore, this paper combines the temporal pattern attention mechanism with the bidirectional long short-term memory (BiLSTM) network to propose a novel trend prediction method for short-term exhaust gas temperature (EGT) forecasting. First, the Pearson correlation analysis (PCA) is conducted to identify input feature variables that are strongly correlated with the EGT. Next, the BiLSTM network models input feature variables such as load, fuel oil pressure, and scavenging air pressure and capture the interrelationships between different vectors from the hidden layer matrix within the BiLSTM network. This allows the selection of valuable information across different time steps. Meanwhile, the temporal pattern attention (TPA) mechanism has the ability to explore complex nonlinear dependencies between different time steps and series. This assigns appropriate weights to the feature variables within different time steps of the BiLSTM hidden layer, thereby influencing the input effect. Finally, the improved slime mold algorithm (ISMA) is utilized to optimize the hyperparameters of the prediction model to achieve the best level of short-term EGT trend prediction performance based on the ISMA-BiLSTM-TPA model. The prediction results show that the mean square error, the mean absolute percentage error, the root mean square error and the coefficient of determination of the model are 0.4284, 0.1076, 0.6545 and 98.2%, respectively. These values are significantly better than those of other prediction methods, thus fully validating the stability and accuracy of the model proposed in this paper.

The 5-year recurrence rate of thermal ablation for hepatocellular carcinoma (HCC) is high, and whether this treatment strategy induces systemic immune response remains elusive. This study aimed to investigate the effects of thermal ablation on HCC patients’ cytokine profiles and to explore the correlation of cytokine profiles with tumor recurrence after ablation. A total of 22 HCC patients were included in this prospective study. The levels of 27 cytokines in the peripheral blood of HCC patients were measured before ablation (baseline), week 1, and week 4 after ablation using a Bio-Plex Pro Human Cytokine 27-plex Assay kit. Cytokines showed different dynamic changing trends after ablation treatment. It was found that the level of IL-6 was significantly elevated at week 1 and returned to the baseline level at week 4 after ablation. The level of IL-10 was slightly reduced at week 1 and significantly decreased at week 4. The levels of MCP-1, macrophage inflammatory protein-1β (MIP-1β), and TNF-α were similarly reduced at week 1 and increased at week 4. The levels of IL-17, platelet-derived growth factor-BB (PDGF-BB), and regulated upon activation, normal T cell expressed and secreted (RANTES) showed little to no change at week 1 while an observable increase at week 4. Patients with a high IL-10 level (2.99 pg/ml) at baseline and low levels of TNF-α (20.4 pg/ml), PDGF-BB (107.78 pg/ml), and RANTES (2303.94 pg/ml) at week 4 were at risk of tumor recurrence during 1-year follow-up. The results suggested that thermal ablation activated systemic immune responses by changing the levels of cytokines. The results also demonstrated that measurement of IL-10 at baseline, TNF-α, PDGF-BB, and RANTES at week 4 after ablation might predict the risk of tumor recurrence.

How to reasonably provide harmonized communication and sensing for different applications has become one of the important research directions of 5G network evolution and 6G technology.Based on the analysis of different scenarios and key performance indicators (KPIs), an architecture and brief realization including the implementation of each module of the harmonized communication and sensing simulation system was put forward.Furthermore, a correlation simulation case about communication spectrum efficiency and sensing range resolution was given to show how typical indicators work during the simulation under certain conditions.

Abstract Despite a variety of studies on the tropical cyclone (TC) response to climate change, few of them have examined the projected damages of future TCs. Here we quantify the impact of anthropogenic warming on TC-induced damages in the late twenty-first century along the coasts of Southeast China based on convection-permitting TC simulations and machine-learning-based damage models. We found that if the area’s 10 super typhoons between 2013 and 2019 were to occur at the end of the century under the high emissions RCP8.5 scenario, they would have on average a 12% ± 4% increase in landfall intensity, 25% ± 23% increase in precipitation, and 128% ± 70% increase in economic losses, compared to historical simulations. We also found a significant increase in the full risk profile. The estimated typhoon loss with a 50-year return period for Zhejiang, Fujian, Guangdong, and Hainan (four most typhoon-prone provinces among the seven provinces in the region) would increase by 71%, 170%, 20%, and 85%, respectively, towards the end of the century even under the lower emissions RCP4.5 pathway. Our findings imply the need to design effective local hazard mitigation measures to reduce future typhoon risks.

To reduce the hazard of sulfamethoxazole (SMX) to the water ecology, the removal mechanism of SMX in wastewater was revealed. This study evaluated the PVDF/DA modified membrane in the membrane bioreactor (MBR) toward the removal and degradation of SMX as a recalcitrant micropollutant. A strategy of dopamine for surface modification of polyvinylidene fluoride (PVDF) membrane was proposed, and PVDF/DA membrane was prepared. Subsequently, PVDF/DA was run in the MBR for 60 days, and the reactor could produce good removal ability for SMX after certain acclimation. When the SMX concentration increased from 0.5 to 2 mg/L, liquid chromatography was used for analysis, and the results showed that the average removal rate was above 85%. The removal effect of COD and NH4+-N and the degree of membrane fouling were also evaluated. By measuring the extracellular polymer (EPS) content, the results showed that after 30 days of operation, the protein and polysaccharide contents in the cake layer on the surface of the PVDF membrane were 1.35 times and 1.49 times that of PVDF/DA membrane, respectively, and the PVDF/DA membrane could alleviate membrane fouling, thereby improving the service life of the membrane and reducing its operating cost. Finally, degradation by-products are evaluated to achieve deeper insight into the degradation mechanisms in the MBR process.

Anhui Province locates in the Yangtze River Delta region. The spatial difference between the north and the south is significant, and the air quality is improved over time. Studying the spatial and temporal changes of air pollution and its influencing factors for the coordinated control of air pollutants in the Yangtze River Delta region is significant. This study used the annual and monthly average data of six pollutants, PM2.5, PM10, O3, NO2, SO2, and CO, in Anhui Province and various cities from 2015 to 2021 and analyzed the spatiotemporal change characteristics using Excel and GIS software. Meanwhile, this paper used the SPSS correlation analysis method to analyze the correlation between pollutants and meteorological factors and analyzed the impact of economic development and environmental protection policies. The results are shown below. (1) The concentrations of SO2, NO2, and CO showed an overall downward trend at an interannual level. Meanwhile, the concentrations of PM10 and PM2.5 first increased slowly before 2017 and then declined, while the concentrations of O3 increased significantly before 2018 and then declined slowly. On a monthly scale, O3 presented an M-shaped change, while the other five pollutants basically presented a U-shaped change mode. The top monthly pollutants in each city followed the order of PM2.5, O3, PM10, and NO2. (2) PM2.5 and PM10 showed apparent characteristics of high concentrations in the north and low concentrations in the south in space. There were no significant differences in NO2, SO2, and CO pollution between the north and the south in space, and the differences in spatial pollution among cities were reduced significantly. (3) Five pollutants (SO2, NO2, PM10, PM2.5, and CO) except O3 were positively correlated, and the degree of correlation was correlated, strongly correlated, and above. However, five pollutants were negatively correlated with O3. The temperature had the most significant impact of negative correlation on five pollutants except for O3. The sunshine duration had the most significant impact on O3. (4) Economic growth and environmental protection policies in Anhui Province have positively affected environmental governance.

Aiming at the deficiencies of the traction helical gear transmission system when the EMU is running at high speed, this paper proposes and designs a kind of arc toothed cylindrical gear adapted to the traction of higher speed EMU. A parametric arc toothed cylindrical gear model was constructed using CREO, and its dynamic contact characteristics and acoustic response characteristics were analyzed under sustained operating conditions using the finite element boundary element method. The design of a tooth profile combined with the radius of the arc toothed line of the comprehensive trimming program put forward a virtual trimming prototype method through MATLAB and CREO reconstruction gear, and trimming before and after the gear transmission simulation experiments occurred for comparison and analysis. This study shows that the traction arc toothed cylindrical gear comprehensive modification method proposed in this study achieves better dynamic performance optimization, effectively reduces the contact stress and radiation noise of the gear transmission, and provides a theoretical basis for the development of a new generation of high-speed EMU stock traction drive systems.

The effects of six control parameters, intake valve opening timing (IVO), exhaust valve opening timing (EVO), compression ratio (CR), engine speed, intake temperature, and intake pressure on engine output power, indicated specific fuel consumption (ISFC), and nitrogen oxides (NOx) emissions, are analyzed through engine simulation. The six parameters were categorized into two groups based on the degree of influence: high influence (EVO, speed and intake pressure) and low influence (CR, IVO and intake temperature). The relationship between these two groups of parameters and power, ISFC and NOx emissions was explored. Optimization was carried out for each of the two groups of parameters, and the optimization of the high impact parameters resulted in a higher diversity and wider distribution of the solution set. On the other hand, the optimization of the low-impact parameters resulted in a more concentrated distribution of the solution set, while better reflecting the trade-off between the optimization objectives. For the optimal solutions for both sets of parameters, the high-impact parameters provided significant optimization performance compared to the standard operating conditions. Although power and ISFC were optimized, the optimal solution for the low-impact parameter performed poorly with a significant increase in NOx emissions. Therefore, the parameters should be evaluated for optimization using high impact parameters to improve engine performance.

Abstract Increased intracellular toxicity due to an imbalance in copper homeostasis caused by copper ion accumulation could regulate the rate of cancer cell growth and proliferation. The goal of this study was to create a novel Cuproptosis-related lncRNA signature that may be utilized to predict survival and immunotherapy in HCC patients. Cuproptosis-associated lncRNAs and differentially expressed lncRNAs between HCC tumor tissue and normal tissue were discovered first. By LASSO-Cox analysis, the overlapping lncRNAs were then utilized to build a Cuproptosis-associated lncRNA signature, which might be used to predict patient prognosis and responsiveness to immune checkpoint blockade (ICB) therapy. Differences in the infiltration of immune cell subpopulations between high and low-risk score subgroups were also analyzed. Moreover, a nomogram based on the Cuproptosis-associated lncRNA signature and clinical features was developed and demonstrated to have good predictive potential. Finally, qRT-PCR was performed in HerpG2 and MHCC-97H cell lines to explore whether these lncRNAs were indeed involved in the process of Cuproptosis. In summary, we created a prognostic lncRNA profile linked to Cuproptosis to forecast response to immunotherapy, which may provide a new potential non-apoptotic therapeutic perspective for HCC patients.

Polyvinylidene fluoride (PVDF) membranes are favored for their excellent properties. However, the inherent strong hydrophobicity of PVDF membranes limits their development in the field of water treatment. The objective of this study was to improve the performance of PVDF membranes using the self-polymerization, strong adhesion properties, and biocompatible effects of dopamine (DA). The PVDF/DA membrane modification conditions were simulated and optimized using response surface methodology (RSM), and the experimental design was used to investigate three main parameters. The results showed that the DA solution concentration of 1.65 g/L, the coating time of 4.5 h, the post-treatment temperature of 25°C, the contact angle decreased from 69° to 33.9°, and the pure water flux on the PVDF/DA membrane was higher than that on the original membrane. The absolute value of the relative error between the actual and predicted values is only 3.36 %. In the MBR parallel comparison test, compared with the PVDF/DA membrane, the total amount of extracellular polymers (EPS) of the PVDF membrane increased by 1.46 times and the polysaccharide increased by 1.56 times, which further showed that the PVDF/DA modified membrane had the excellent anti-pollution ability. Through Alpha diversity analysis, the biodiversity detected on PVDF/DA membranes was higher than that of PVDF membranes, which further proved its good bio-adhesion ability. These findings could offer a reference for the hydrophilicity, antifouling, and stability of PVDF/DA membranes, which would establish the foundation for the comprehensive applications in MBR.

Article Highlights The finite element simulation reveals the details of stress field and displacement field around the underexcavation hole, which is difficult to capture in site observation or in model test; The soil failure takes the underexcavation hole as the defect center and develops in the shape of “X”, which is very different from the previous study but agrees with the laboratory tests. The multi-hole finite element simulation shows that the deformation caused by stress redistribution is negligible compared to the anticipated forced settlement, which indicates that the forced settlement is from the hole closure. This simulation provides a basis for derivation of key parameters of rectification design. According to the total vertical force balance between the bottom of the base and the horizontal plane at hole centre line, the formula for the preferred hole spacing is obtained; According to that the amount of base settlement is equal to the volume of soil excavation, the formula for the hole diameter is obtained. The two formulas can assist geotechnical engineers with the rapid design scheme for building rectification.

As the speed of the new generation of high-speed electric multiple units (EMU) increases, the requirements for vibration and noise reduction in traction gear trains are becoming higher and higher. Although most researchers have focused on the vibration mechanics analysis of gears, the actual noise has the most direct impact on passenger experience and safety. To address this problem, a new type of curved cylindrical gear is proposed to analyze the dynamic characteristics of the gear pair and predict its radiated noise based on the acoustic-vibration coupling theory using the finite element-boundary element method. Parametric modeling of the gear pair using CREO and assembly motion analysis were performed. ANSYS was used to analyze the stress distribution, inherent frequency, and inherent vibration pattern of the gear pair, and harmonic response analysis was performed using the modal superposition method to solve the displacement frequency response curve and vibration characteristics. ACTRAN was used to construct the free-field model, create acoustic excitation based on the acoustic-vibration coupling equation, set the field points, and predict radiated noise. The research results show that the noise is mainly concentrated in the tooth meshing area, and the root mean square RMS range of its sound pressure level value is 91–100 dB. Its dynamic characteristics and noise values are in line with the traction requirements of high-speed EMU, providing a new idea for improving the noise prediction of traction gears for new generation high-speed EMU, which in turn strongly support the noise control of high-speed EMU stock and thus improve the passenger experience and driving environment.

This study addresses the issue of large deformation in soft rock roadways, using the 50213 tailgate of Guantun Coal Mine as a case study. Field investigations were conducted to assess the condition of roadway bolts, anchor cables, and the internal damage characteristics of the surrounding rock. The upper bound method of limit analysis in plastic mechanics was utilized to construct a failure model for the surrounding rock and derive the upper limit solution of roof failure by integrating the principle of virtual work and variational extremum theorem. Physical similarity simulations were employed to investigate the fracture distribution and evolution law of the surrounding rock. Based on the deformation and instability mechanism of the roadway, optimized support parameters for soft rock roadways were proposed and verified through numerical simulation. The results indicate that the surrounding rock of the sharp corner of the roadway is initially destroyed and develops upward with increasing stress. The interconnected horizontal separation cracks at the anchorage end of the anchor cable and shear fracture zones at the two corners ultimately lead to the overall instability of the anchorage arch. Furthermore, the theoretical calculation boundary exhibited significant similarity with the failure evolution law and distribution pattern. Following the adoption of the optimized support scheme, roof subsidence decreased by 46.7% compared to the original scheme, and the amount of movement on both sides decreased by 36.2%. The control effect of the surrounding rock was favorable, and its internal stability was significantly improved, thereby effectively resolving the issue of large deformation in soft rock roadways.

High-speed rail has influenced the evolution of coopetition relationships among regional cities and promoted city-industry integration development within urban agglomerations. Still, the specific impact it brings needs further study. This paper aims to assess how opening high-speed railways affect the economic development and pattern of urban agglomerations along the route under the perspective of city-industry integration, and the mechanism of action of urban agglomerations’ coopetition relationships. The study is based on panel data from prefecture-level cities in Jiangxi Province, China, from 2014 to 2018. Through constructing an evaluation model of the degree of city-industry integration and an improved city economic linkage gravity model, we study the changes in the amount of economic linkage and affiliation of cities in Jiangxi Province after the opening of high-speed rail, which can analyze the changes in the structure and interconnectedness of each urban agglomeration. At the same time, an econometric model of the coopetition relationship of urban agglomerations is proposed to study the impact of high-speed rail on the economic cooperation of cities along the route in combination with the city-industry integration. The results show that 1) there are pronounced differences in the level of city-industry integration development of cities along the high-speed railway in Jiangxi Province, and the phenomenon is significantly improved by the improvement of inter-city economic links after the opening of the high-speed railway; 2) When cities enhance their fixed investment (FI) and labor force growth (LG), it has a significant promotion effect on their development, but will have a suppressing effect on other cities’ city-industry integration, while when enhancing industrial concentration and human capital mobility, it can make the city-industry integration development of each city achieve a win-win situation; 3) The opening of high-speed rail enhances the economic ties of cities along the route and the radiation capacity of the original central cities, which is conducive to the formation of new central cities while improving the weak economic ties between urban agglomerations due to their geographical locations. This study proposes some conclusions and suggestions to provide research support for theories related to city-industry integration and policies related to urban agglomeration competition and cooperation under the high-speed rail effect.

Summary: Nanocrystalline cellulose (NCC) preparation in an integrated fractionation manner is expected to solve the problems of low yield and environmental impact in the traditional process. An integrated fractionation strategy for NCC production from wood was developed through catalytic biomass fractionation, the partial dissolution of cellulose-rich materials (CRMs) in aqueous tetrabutylphosphonium hydroxide, and short-term ultrasonication. The presented process could tolerate a high CRM lignin content of 21.2 wt % and provide a high NCC yield of 76.6 wt % (34.3 wt % of the original biomass). The increase in the CRM lignin content decreased the NCC yield, facilitated the crystal transition of NCC from cellulose I to cellulose II, and showed no apparent effects on the NCC morphology. A partial/selective dissolution mechanism is proposed for the presented strategy. This study provided a promising efficient fractionation-based method toward comprehensive and high-value utilization of lignocellulosic biomass through effective delignification and high-yield NCC production.

BackgroundAblative therapy is a recommended treatment for hepatocellular carcinoma (HCC) not only for its effective eradication of tumors, but also for its induction of host immunity. However, the high 5-year recurrence rate after ablation underlines the poor understanding of the antitumor immunity response. Here, we investigated the effects of thermal ablation on antitumor immunity.MethodsWe analyzed the dynamics of tumor-associated antigen (TAA)-specific immune responses and changes in peripheral blood mononuclear cell phenotype in patients with HCC before and after tumor ablation. We used the IFN-γ ELISPOT assay and immunophenotyping by flow cytometry to evaluate the effects of ablation on host immunity. The correlation between the T cell response and disease outcome was explored to uncover the efficacy of the immune response in inhibiting HCC recurrence.ResultsDifferent TAA-specific T cell responses were identified among patients before and after ablation. One week after ablation, there was an improved immune state, with a switch from the dominance of an AFP-specific T cell response to that of a SMNMS-specific T cell response, which was correlated with better survival. Furthermore, an improvement in immune status was accompanied by a lower level of PD1+ and Tim3+ T cells in CD8+ T cells. Although this functional state was not durable, there was a higher degree of AFP-specific T cell responses at 4-weeks post-ablation. Furthermore, T cells presented a more exhausted phenotype at 4-weeks post-ablation than at the 1-week timepoint.ConclusionsAblation elicits a transient antitumor immune response in patients with HCC by changing the profile of the T cell response and the expression of immune checkpoint molecules, which correlated with longer recurrence-free survival of patients with HCC.

This paper proposes an abnormal behavior detection using visual monitoring in rehabilitation center. The proposed method solves the problems of inaccurate and delayed detection of abnormal behavior in traditional algorithms, and provides necessary technical support for medical staff to quickly deal with patient abnormal behaviors. Firstly, the deep neural network model is adopted to detect the patient feature nodes and skeleton in the images. Then, the vector representing the position and direction of the patient limb in each frame is extracted. Finally, the angle between the trunk, legs and the ground during the fall, the aspect ratio of the body frame and the irregular motion of the wrist and ankle joins are used as discriminant features to determine the occurrence of patient fall and twitch. The experimental results show that the detection accuracy of the proposed method is 96%, and the detection speed in the real medical rehabilitation center is 25 f/s. The proposed method can monitor the patient behavior characteristics in the elderly rehabilitation center in real time, and issue an alarm timely in the case of accidental falls and twitch. Meanwhile, this paper provides a more accurate and convenient computer-aided nursing method for medical staff to monitor patient abnormal behaviors.

Abstract Background Cancer-testis antigens (CTAs) and tumour-associated antigens (TAAs) are frequently expressed in hepatocellular carcinoma (HCC); however, the role of tumour-antigen-specific T cell immunity in HCC progression is poorly defined. We characterized CTA- and TAA-specific T cell responses in different HCC stages and investigated their alterations during HCC progression. Methods Fifty-eight HCC patients, 15 liver cirrhosis patients, 15 chronic hepatitis B patients and 10 heathy controls were enrolled in total. IFN-γ ELSPOT using CTAs, including MAGE-A1, MAGE-A3, NY-ESO-1, and SSX2, and two TAAs, SALL4 and AFP, was performed to characterize the T-cell immune response in the enrolled individuals. The functional phenotype of T cells and the responsive T cell populations were analyzed using short-term T-cell culture. Results T cell responses against CTAs and TAAs were specific to HCC. In early-stage HCC patients, the SALL4-specific response was the strongest, followed by MAGE-A3, NY-ESO-1, MAGE-A1 and SSX2. One-year recurrence-free survival after transcatheter arterial chemoembolization plus radiofrequency ablation treatment suggested the protective role of CTA-specific responses. The four CTA- and SALL4-specific T cell responses decreased with the progression of HCC, while the AFP-specific T cell response increased. A higher proportion of CD4+ T cells specific to CTA/SALL4 was observed than AFP-specific T cell responses. Conclusions The IFN-γ ELISPOT assay characterized distinct profiles of tumour-antigen-specific T cell responses in HCC patients. CTA- and SALL4-specific T cell responses may be important for controlling HCC in the early stage, whereas AFP-specific T cell responses might be a signature of malignant tumour status in the advanced stage. The application of immunotherapy at an early stage of HCC development should be considered.

This study aims to determine whether toll-like receptor 4 (TLR4)-mediated inflammation in rostral ventrolateral medulla (RVLM) causes sympathetic overactivity leading to preeclampsia (PE) and if TLR4 inhibition with hydrogen sulfide (H2S) would reduce PE severity. Thirty patients with PE and 30 pregnant controls were involved. PE in rats was induced through deoxycorticosterone acetate and normal saline. NaHS (donor of H2S), lipopolysaccharide (LPS) (TLR4 agonist), and TAK-242 (TLR4 inhibitor) were injected in lateral cerebral ventricle to investigate their effect on microglia-mediated inflammation in RVLM, sympathetic activation, and PE symptoms. In patients with PE, plasma levels of NE, TNF-α, and interleukin-1β were high compared with those of controls, whereas levels of H2S were low. Rats with PE showed an increased amount of renal sympathetic nerve activity and plasma levels of NE, with decreased H2S levels in RVLM. Microglia-mediated inflammation was observed in the RVLM of PE rats. Central infusion of LPS in pregnant rats induced microglia-mediated inflammation, sympathetic nervous tension, and PE-like symptoms, whereas TAK-242 reduced PE symptoms. NaHS treatment lessened microglia-mediated inflammation in the RVLM, sympathetic tension, and symptoms of PE both in PE rats and LPS-treating pregnant rats.These results suggest that inflammation in the RVLM caused by microglial activation might contribute to the progression of PE via an overactive sympathetic system. H2S could reduce PE via inhibiting inflammation in the RVLM. These results might provide a new target for the treatment of PE.

This paper discusses the optimization of emergency resource scheduling for major railway emergencies under multiple uncertainties while considering the uncertainties in demand, reserve, and transportation costs of resources. We introduce a novel approach that integrates stochastic mathematical programming, interval parameter programming, and fuzzy mathematical programming to study uncertain parameter interactions and coupling. A two-stage interval fuzzy credibility-constrained model is established and solved using an interval interactive algorithm. Finally, through a case study on China Railway Nanchang Group Co., Ltd., the novelty and effectiveness of the proposed method for optimizing emergency resource scheduling strategies under multiple uncertainties are demonstrated.

The National Railway Administration of the People’s Republic of China, the China State Railway Group Co., Ltd. and the front-line staff are the three main stakeholders in the railway safety supervision system, and their decision-making behaviors will directly affect the railway safety. In this paper, based on the organizational hierarchy of railway safety supervision system in China and accidental cause mechanism, considering the influence of collusion rewards and punishments between enterprise and staff, the tripartite evolutionary game model is built. According to the actual data of 2018, the complex phenomena and evolution forms in the game process are simulated, and the behavior evolution rules of the three parties in the game are revealed, as well as the controllable factors and methods for the evolution direction of the system are explored. Evolutionary simulation shows that the railway safety supervision system is at an ideal state, and the current policy and management system are in a scientific scope. Some parameters should be reasonably controlled, so as to guide the system evolution in the direction of Pareto optimality. The research can provide a theoretical reference for coordinating the relationship among the three parties, formulating regulatory policies and improving the ability to manage and control risks for railroads.

The NVH (Noise, Vibration, and Harshness) characteristics of new energy vehicles are the key indexes to measure interior comfort. The multi-stage gear reducer in the transmission system is the primary source of vibration and noise. The parameterized 3D model of the multi-stage gear transmission system of the new energy vehicle was established through Romax software, and the comprehensive gear modification method of the tooth direction combined with the tooth profile was built. Then a complete simulation analysis process is established to solve the maximum vibration acceleration of the multi-stage gear transmission system under constant speed condition, to obtain the simulation data of two-stage gear set under different modification parameters. The traditional BP (Back Propagation) neural network is optimized and improved through the optimal selection of network parameters combined with Bayesian regularization. Based on the optimized BP neural network, a modified parameter-vibration noise prediction model is constructed. Finally, the GA (Genetic Algorithm) optimization algorithm is used to solve the prediction model to obtain the optimal combination of modification parameters aiming at the minimum vibration acceleration, the effectiveness and reliability of the modified design are verified through actual simulation. It provides ideas and a basis for the research on vibration and noise reduction of multi-stage gears.

The dynamic characteristics of the traction gear transmission system have a great influence on the safety, comfort, and reliability of EMU (electric multiple units). Combining the methods of theoretical analysis, numerical simulation, and optimization design theory, establishing a parameterized gear modification model. Meanwhile, designing reasonable shape modification schemes and parameters. The dynamic characteristics, vibration response characteristics, and acoustic response characteristics of gear meshing of CRH380A high-speed EMU under continuous traction conditions are analyzed. The corresponding relationship between gear modification parameters and gear transmission radiation noise is approximated by finite element simulation data and RBF (radial basis function) neural network. Using a multi-island genetic algorithm to optimize gear modification parameters to minimize gear transmission noise, further seeking to meet the low-noise modification design of high-speed train traction helical gear transmission system under continuous operating conditions method.

Hepatocellular carcinoma (HCC) with cancer cells under endoplasmic reticulum (ER) stress has a poor prognosis. This study is aimed at discovering credible biomarkers for predicting the prognosis of HCC based on ER stress-related genes (ERSRGs). We constructed a novel four-ERSRG prognostic risk model, including PON1, AGR2, SSR2, and TMCC1, through a series of bioinformatic approaches, which can accurately predict survival outcomes in HCC patients. Higher risk scores were linked to later grade, recurrence, advanced TNM stage, later T stage, and HBV infection. In addition, 20 fresh frozen tumors and normal tissues from HCC patients were collected and used to validate the genes expressed in the signature by qRT-PCR and immunohistochemical (IHC) assays. Moreover, we found the ER stress-related signature could reflect the infiltration levels of different immune cells in the tumor microenvironment (TME) and forecast the efficacy of immune checkpoint inhibitor (ICI) treatment. Finally, we created a nomogram incorporating this ER stress-related signature. In conclusion, our constructed four-gene risk model associated with ER stress can accurately predict survival outcomes in HCC patients, and the model’s risk score is associated with the poor clinical classification.

The quasi-one-dimensional material PdTeI exhibits unusual electronic transport properties at ambient pressure. Here, we systematically investigate both the structural and electronic responses of PdTeI to external pressure, through a combination of electrical transport, synchrotron X-ray diffraction (XRD), and Raman spectroscopy measurements. The charge density wave (CDW) order in PdTeI is fragile and the transition temperature TCDW decreases rapidly with the application of external pressure. The resistivity hump is indiscernible when the pressure is increased to ~1 GPa. Upon further compression, the resistivity dropping is observed approximately ~15 GPa and zero resistance is established above ~20 GPa, suggesting the occurrence of superconductivity. Combined XRD and Raman data evidence that the emergence of superconductivity is accompanied by a pressure-induced amorphization of PdTeI.

A highly sensitive hollow-core photonic crystal fiber (HC-PCF) gas-sensing network based on intracavity absorption is designed and experimentally verified. The capacity of the multichannel sensing network is expanded by time division multiplexing and wavelength division multiplexing technology. The voltage gradient method is employed in the wavelength scanning process of Fabry–Perot (F-P) filter to enhance the detection efficiency up to six times. The proposed sensing network has 16 sensing points. Experimental results show that the minimum detection limit (MDL) of this sensing system is 25.91 ppm and 26.85 ppm at the acetylene gas absorption peaks of 1530.371 nm and 1531.588 nm, respectively. As far as we know, it is the first time to obtain an intracavity sensing network via the application of an optical switch and DWDM at the same time. The sensing network can be used for high-capacity, low-concentration dangerous gas detection. It has great potential in environmental monitoring, industrial manufacturing, safety inspection and similar occasions.

Previous studies have suggested that the sodium alginate (SA) is beneficial for the treatment of non-alcoholic fatty liver disease (NAFLD), while the potential mechanisms are largely unknown. The present study aimed to clarify the effects and potential mechanisms of SA in preventing NAFLD via the gut−liver axis. Thirty-two male Sprague−Dawley rats were randomly divided into four groups: normal control group (NC); high-fat diet group (HFD); HFD with 50 mg/kg/d sodium alginate group (LSA); HFD with 150 mg/kg/d sodium alginate group (HSA). After 16 weeks, the rats were scarified to collect blood and tissues. The results indicated that SA significantly reduced their body weight, hepatic steatosis, serum triglyceride (TG), alanine transaminase (ALT) and tumor necrosis factor α (TNF-α) levels and increased serum high-density lipoprotein-cholesterol (HDL-C) levels in comparison with HFD group (p < 0.05). The elevated mRNA and protein expression of genes related to the toll-like receptor 4 (TLR-4)/nuclear factor-kappa B (NF-κB)/nod-like receptor protein 3 (NLRP3) inflammatory signaling pathway in the liver of HFD-fed rats was notably suppressed by SA. In terms of the gut microbiota, the LSA group showed a significantly higher fecal abundance of Oscillospiraceae_UCG_005, Butyricicoccaceae_UCG_009 and Colidextribacter compared with the HFD group (p < 0.05). The rats in the HSA group had a higher abundance of unclassified_Lachnospiraceae, Colidextribacter and Oscillibacter compared with the HFD-associated gut community (p < 0.05). In addition, rats treated with SA showed a significant increase in fecal short chain fatty acids (SCFAs) levels and a decline in serum lipopolysaccharide (LPS) levels compared with the HFD group (p < 0.05). Moreover, the modulated bacteria and microbial metabolites were notably correlated with the amelioration of NAFLD-related indices and activation of the hepatic TLR4/NF-κB/NLRP3 pathway. In conclusion, SA prevented NAFLD and the potential mechanism was related to the modulation of the gut–liver axis.

Changes in precipitation patterns and eutrophication can cause changes in plant traits and abundance, potentially affecting plant community structure and functions. Here, we studied responses of traits and abundance of Potentilla anserina to precipitation change and nitrogen (N) and phosphorus (P) additions, and the effect of traits on its abundance in an alpine meadow of the Qinghai-Tibet Plateau. We found that precipitation change and N and P additions significantly affected the mean value of traits such as specific leaf area (SLA), leaf dry matter content (LDMC), single leaf area, plant height and individual size, while only P addition significantly affected intraspecific variation of SLA and individual size. Increased precipitation and N and P additions shifted plant traits to more resource acquisitive, and increased plant abundance. Responses of plant traits to P addition were larger than that of N addition. Plant abundance was mainly affected by precipitation, and was limited by N or P dependent on precipitation conditions. In conclusions, our research shows that P. anserina can respond to environmental changes by changing its traits to improve its adaptability, potentially affecting community structure and ecosystem functions.

BackgroundAberrant methylation of CpG sites served as an epigenetic marker for building diagnostic, prognostic, and recurrence models for hepatocellular carcinoma (HCC).MethodsUsing Illumina 450K and EPIC Beadchip, we identified 34 CpG sites in peripheral blood mononuclear cell (PBMC) DNA that were differentially methylated in early HCC versus HBV-related liver diseases (HBVLD). We employed multiplex bisulfite sequencing (MBS) based on next-generation sequencing (NGS) to measure methylation of 34 CpG sites in PBMC DNA from 654 patients that were divided into a training set (n = 442) and a test set (n = 212). Using the training set, we selected and built a six-CpG-scorer (namely, cg14171514, cg07721852, cg05166871, cg18087306, cg05213896, and cg18772205), applying least absolute shrinkage and selection operator (LASSO) regression. We performed multivariable analyses of four candidate risk predictors (namely, six-CpG-scorer, age, sex, and AFP level), using 20 times imputation of missing data, non-linearly transformed, and backwards feature selection with logistic regression. The final model’s regression coefficients were calculated according to “Rubin’s Rules”. The diagnostic accuracy of the model was internally validated with a 10,000 bootstrap validation dataset and then applied to the test set for validation.ResultsThe area under the receiver operating characteristic curve (AUROC) of the model was 0.81 (95% CI, 0.77–0.85) and it showed good calibration and decision curve analysis. Using enhanced bootstrap validation, adjusted C-statistics and adjusted Brier score were 0.809 and 0.199, respectively. The model also showed an AUROC value of 0.84 (95% CI 0.79–0.88) of diagnosis for early HCC in the test set.ConclusionsOur model based on the six-CpG-scorer was a reliable diagnosis tool for early HCC from HBVLD. The usage of the MBS method can realize large-scale detection of CpG sites in clinical diagnosis of early HCC and benefit the majority of patients.

RV6Sn6 (R = Sc, Y, or rare earth) is a new family of kagome metals that have a similar vanadium structural motif as AV3Sb5 (A = K, Rb, Cs) compounds. Unlike AV3Sb5, ScV6Sn6 is the only compound among the series of RV6Sn6 that displays a charge density wave (CDW) order at ambient pressure, yet it shows no superconductivity (SC) at low temperatures. Here, we perform a high-pressure transport study on the ScV6Sn6 single crystal to track the evolutions of the CDW transition and to explore possible SC. In contrast to AV3Sb5 compounds, the CDW order of ScV6Sn6 can be suppressed completely by a pressure of about 2.4 GPa, but no SC is detected down to 40 mK at 2.35 GPa and 1.5 K up to 11 GPa. Moreover, we observed that the resistivity anomaly around the CDW transition undergoes an obvious change at ~2.04 GPa before it vanishes completely. The present work highlights a distinct relationship between CDW and SC in ScV6Sn6 in comparison with the well-studied AV3Sb5.

The development of industrial robots in high-precision fields is currently constrained by the reliability of motion. Considering the influence of the joint clearance on the motion reliability of the industrial robot, the kinematic model of the industrial robot is established, the kinematic equation of the robot is deduced, and positive kinematic solutions are performed. The non-probability positioning accuracy reliability measure of a robot end-effector is proposed, based on the non-probability theory and method, combined with the prescribed permission interval and error interval, and different states of reliability can be judged according to the position relationship, the non-probability reliability properties are outlined, and the positioning accuracy reliability assessment model is established. Combined with the joint clearance modeling theory, the simulation of the robot end-effector under the influence of six joint clearances is carried out, and the displacement error interval of the end-effector under the preset motion path is analyzed for the industrial robot motion reliability problem. The motion path is split by time, and the end effector moves to different workspace areas in different time periods. The motion reliability of each segment is analyzed, and it is concluded that the reliability of the end-effector under the influence of uncertain joint clearance parameters changes in different working regions. Based on the above, the research direction of space division and partition parameter calibration is proposed, which lays a foundation for the study of partition non-probabilistic calibration of robot workspace.

Although widely used in various fields due to its powerful capability of signal processing, empirical mode decomposition has to decompose signals separately, which limits its application for multivariate data such as the structural monitoring data recorded by multiple sensors. In order to avoid this shortcoming, a multivariate extension of empirical mode decomposition is proposed to deal with the multidimensional signals synchronously by employing a real-valued projection on hyperspheres. This study presents a hybrid modal identification method combining the multivariate empirical mode decomposition with stochastic subspace identification and fast Bayesian FFT methods to more conveniently and accurately identify structural dynamic parameters from multi-sensor vibration measurements. Deployed as a preprocessing tool, the multivariate signals are decomposed into several aligned intrinsic mode functions, which contain only a dominant component in the frequency domain. Then, the modal parameters can be identified by advanced fast Bayesian FFT and stochastic subspace identification directly. The combined method is first validated by a numerical illustration of a frame structure and then is applied in a shaking table test and a full-scale measurement under nonstationary earthquake excitation. Compared with the finite element method, the peak–pick, the half-power bandwidth methods, and Hilbert–Huang transform method, the results show that this hybrid method is more robust and reliable in the modal parameters identification. The main contribution of this paper is to develop a more effective integrated approach for accurate modal identification with the output-only multi-dimensional nonstationary signal.

Background: Depression is a common mental illness. Previous studies suggested that health conditions and lifestyle factors were associated with depression. However, only few studies have explored the risk factors of depression in a large representative sample of the general population in the world.Methods: A population-based cross-sectional survey was conducted in the 2006 survey and 2009 survey in Qingdao, China. The participants with insufficient information were excluded: Zung score, body mass index (BMI), diabetes items, physical activity, smoking, or drinking. Finally, a total of 3,300 participants were included in this analysis. The category of depression was used in the Zung self-rating depression scale (ZSDS). The associations between different indicators of health conditions (diabetic status, BMI), lifestyle factors (physical activity, smoking, and alcohol consumption), and depression were assessed by the logistic regression model.Results: The mean Zung scores for all participants, male participants, and female participants were 29.73 ± 7.57, 28.89 ± 7.30, 30.30 ± 7.70, respectively. In all participants, those who were pre-diabetes status (OR: 1.53, 95% CI: 1.04–2.27), and irregular physical activity (OR: 0.39, 95% CI: 0.17–0.89) had an increased risk of depression. In man, the analysis showed an increased risk of depression those with pre-diabetes (OR: 2.49, 95% CI: 1.25–4.97), previously diagnosed diabetes (OR: 4.44, 95% CI: 1.58, 12.48), and in those irregular activities (OR: 0.07, 95% CI: 0.01–0.61). In women, those who were underweight (OR: 5.66, 95% CI: 1.04–30.71) had a greater risk of depression.Conclusions: These results suggested that health conditions and lifestyle factors were the potential risk factors for depression. Men with pre-diabetes, previously diagnosed diabetes, and irregular activity had an increased risk for depression; women with underweight status had a higher risk for depression.

The pools of plant community carbon (C) and nitrogen (N) are important sources of soil organic matter in terrestrial ecosystems and directly affect soil C and N cycling. A large amount of studies were manipulated with multiple N levels on soil C and N pools. However, how and whether the frequency of N addition can affect the plant C and N pools is still unclear. In order to comprehensively understand the N addition effects (including frequencies and levels) on C and N pools of the plant community, we executed a randomized complete block experiment with the addition of five levels of N, including 0, 2, 10, 20 and 50 g N m−2 yr−1 (designated as N-0, N-2, N-10, N-20 and N-50) and two N addition frequencies (twice a year vs. monthly, F2, F12) in August of 2008. After 5 years of treatment, the physical-chemical properties of the plants and soil were measured in 2013. The results indicated that with increasing N addition levels, the C and N pools of the plant community significantly increased, while N addition frequency had no significant effects. Moreover, significant interactions between N addition levels and the frequencies on the C and N pools of the plant community were also found in this typical grassland. Under different frequencies of N addition treatment, the plant community C and N pools showed different response patterns along with N addition levels in plants aboveground and belowground, respectively. Under different frequencies of N addition, the changes in the C and N pools of the plant community caused by N addition were regulated by different environmental factors. We highlight that long-term N deposition could affect the plant community C and N pools and would influence C and N cycling of terrestrial ecosystems based on global climate change in the future.

The demand prediction of emergency resources is helpful for rational allocation and optimization of emergency resources for railway rescue when emergency incident occurs. In this paper, a case base containing China railway traffic accident that has occurred since 1978 is established, and the case-based reasoning (CBR) method is applied in railway emergency resource demand predicting research. The core case attributes of railway emergencies are described. In view of the attribute types of railway emergency cases, five types of attributes, including enumeration, numerical, interval, character and fuzzy type, are considered, and the local similarity calculation models of different attributes are given. In order to avoid the problem of missing attribute in the traditional nearest neighbor algorithm, a global case similarity calculation method based on structural similarity and attribute similarity is designed. The empirical results show that case 3 is the most similar to the target case, and the calculating quantities of the proposed model are closer to the actual usage quantity and more accurate in the demand prediction of railway emergency resources, compared with the traditional empirical method. The relative errors of demand forecasts for the 9 resources have been, respectively, reduced by 15.9884%, 15.1471%, 6.4286%, 17.1429%, 66.6667%, 38.8889%, 27.5%, 0%, and 17.7778%. Therefore, the proposed model is both reasonable and applicable. The research results are of great significance to effectively deal with railway emergencies.

Deep excavation supported by vertical retaining walls together with strutting system is commonly used in Singapore for the construction of underground infrastructure. In this paper, a series of numerical scenarios simulated by PLAXIS software are carried out to study the influence of different design parameters such as pre-auger loosening effect, the embedded depth of retaining wall into the stiff soil layer, and the elastic modulus of the ground improvement layer on excavation design especially on strut force, retaining wall deflection, and bending moment. The results show that there is high risk if only a single set of parameters are used as input to predict the performance of the retaining system. Sensitivity analysis shall be carried out to evaluate the effects of these parameter variations within a reasonable range on strut force, retaining wall deflection, and bending moment.

BackgroundThe emergence and re-emergence of scrub typhus has been reported in the past decade in many global regions. In this study, we aim to identify potential scrub typhus infection risk zones with high spatial resolution in Qingdao city, in which scrub typhus is endemic, to guide local prevention and control strategies.Methodology/principal findingsScrub typhus cases in Qingdao city during 2006-2018 were retrieved from the Chinese National Infectious Diseases Reporting System. We divided Qingdao city into 1,101 gridded squares and classified them into two categories: areas with and without recorded scrub typhus cases. A boosted regression tree model was used to explore environmental and socioeconomic covariates associated with scrub typhus occurrence and predict the risk of scrub typhus infection across the whole area of Qingdao city. A total of 989 scrub typhus cases were reported in Qingdao from 2006-2018, with most cases located in rural and suburban areas. The predicted risk map generated by the boosted regression tree models indicated that the highest infection risk areas were mainly concentrated in the mid-east and northeast regions of Qingdao, with gross domestic product (20.9%±1.8% standard error) and annual cumulative precipitation (20.3%±1.1%) contributing the most to the variation in the models. By using a threshold environmental suitability value of 0.26, we identified 757 squares (68.7% of the total) with a favourable environment for scrub typhus infection; 66.2% (501/757) of the squares had not yet recorded cases. It is estimated that 6.32 million people (72.5% of the total population) reside in areas with a high risk of scrub typhus infection.Conclusions/significanceMany locations in Qingdao city with no recorded scrub typhus cases were identified as being at risk for scrub typhus occurrence. In these at-risk areas, awareness and capacity for case diagnosis and treatment should be enhanced in the local medical service institutes.