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Abstract Background The triglyceride glucose-body mass index (TyG-BMI) is considered to be a reliable surrogate marker of insulin resistance (IR). However, limited evidence exists regarding its association with the severity of coronary artery disease (CAD), particularly in hypertensive patients with different glucose metabolic states, including those with H-type hypertension. This study aimed to investigate the relationship between TyG-BMI and CAD severity across different glucose metabolism conditions. Methods This retrospective cohort study included 1537 hypertensive patients who underwent coronary angiography. The TyG-BMI was categorized into tertiles and analyzed using logistic regression models and restricted cubic spline (RCS) models to assess its association with multi-vessel CAD. Receiver operating characteristic (ROC) curves were used to evaluate the predictive value of TyG-BMI in detecting the severity of CAD in different glucose metabolism states, including normal glucose regulation (NGR), pre-diabetes mellitus (Pre-DM), and diabetes mellitus (DM). The above method has also been applied to populations of H-type hypertension patients. Results The TyG-BMI was significantly associated with the severity of multi-vessel CAD in hypertensive patients (Odds ratio [OR] 1.043, 95% CI 1.032–1.053). In the diabetic subgroup, after adjusting for risk factors, the risk of multi-vessel CAD in the T3 groups was 3.836-fold (95% CI 1.763–8.347; P = 0.001) higher than in the T1 group, with a non-linear dose–response relationship (P for non-linearity = 0.017). In H-type hypertension patients, the TyG-BMI was also significantly correlated with multi-vessel CAD (OR 5.248, 95% CI 1.821–15.126, P = 0.002) in the DM group. The ROC analysis revealed that TyG-BMI had the highest predictive value for multi-vessel CAD in diabetic patients, with an AUC of 0.720 (95% CI 0.661–0.780, P

Using Arca subcrenata as the research object, this study explored the differences in the utilization of simulated digestion products of Arca subcrenata myofibrillar protein by probiotics, namely Lactiplantibacillus plantarun, Bifidobacterium bifidobacterial, Lacticaseibacillus rhamnosus and Bifidobacterium animalis subsp. Lactis Probio-M8. The study first simulated the in vitro digestion of myofibrillar protein from Arca subcrenata and used it as a nitrogen source to co-culture with probiotics by nitrogen source replacement and nitrogen source addition, respectively. Subsequently, the utilization characteristics by the probiotics on the digestion products of myofibrillar protein from Arca subcrenata were evaluated by monitoring the growth curve, pH and colony number among others. The results showed that, compared to the de Man-Rogosa-Sharpe group, the nitrogen source replacement group could significantly inhibit the proliferation of the four probiotic species (P

Abstract Nowadays, the application of artificial intelligence (AI) algorithms and techniques is ubiquitous and transversal. Fields that take advantage of AI advances include sound and music processing. The advances in interdisciplinary research potentially yield new insights that may further advance the AI methods in this field. This special issue aims to report recent progress and spur new research lines in AI-driven sound and music processing, especially within interdisciplinary research scenarios.

Background:: Cerebellar intermittent theta burst stimulation (iTBS) modulates the excitability of the cerebral cortex and may enhance attentional performance. To date, few studies have conducted iTBS on healthy subjects for one week and used electroencephalography (EEG) to investigate the effect of multiple stimulation sessions on resting-state functional brain networks and the daily stimulation effect on attentional performance. Methods:: 16 healthy subjects participated in a one-week experiment, receiving bilateral cerebellar iTBS or sham stimulation and engaging in multi-task attentional training. The primary measures were the one-week attentional performance and pre- and post-experiment resting-state EEG activities. Amplitude Envelope Correlation (AEC) was used to construct the functional connectivity in the eye-open (EO) and eye-closed (EC) phases. Results:: At least three sessions of iTBS were required to enhance multi-task performance significantly, whereas only one or two sessions failed to elicit the improvement. Compared with the control group, iTBS induced significant changes in PSD, AEC functional connectivity, and AEC network properties during the EO phase, while it had little effect during the EC phase. During the EO phase, the network property changes of the iTBS subject were correlated with improved attentional performance. Conclusion:: The multi-task performance requires multiple stimulations to enhance. iTBS affects the resting-state alpha band brain activities during the EO rather than the EC phase. The AEC network properties may serve as a biomarker to assess the attentional potential of healthy subjects.

A 24-year-old male patient complained of mild knee pain after jogging. The subsequent knee MRI demonstrated bilateral lateral thickened tibiofemoral cartilages, evidenced by deformities of the bilateral subchondral bone beneath the lateral femoral condyle cartilage. The corresponding dislocations of almost all the left lateral meniscus and part of the right lateral meniscus to the center of the joint were detected. After excluding diagnoses of congenital ring-shaped meniscus, bucket handle tear of the C-shaped lateral meniscus, and central tear of the discoid meniscus, the displacement of all or part of the lateral meniscus into the intercondylar notch was considered a consequence of congenital thickening of the lateral superior and inferior cartilage. This case may report a new variant of knee joint pathology.

IntroductionMost foreign bodies (FBs) can spontaneously pass through the gastrointestinal tract. Sharp FBs are believed to be able to puncture any part of the gastrointestinal tract, causing perforation and potentially secondary damage to adjacent organs.Case descriptionA 44-year-old man complained of having persistent dull pain in the perianal region. He was diagnosed with a toothpick impacted into the wall of the lower rectum after accepting a digital rectal examination of the lower rectum and a pelvic computed tomography (CT). The surgeon extracted the FB using vascular forceps guided by the operator’s index finger. The patient was discharged after intravenous ceftriaxone was given for 6 days. A follow-up pelvic CT performed 2 weeks after surgery revealed that the perirectal fat and muscles had already normalized.ConclusionA systematic review of relevant literature from the past decade was performed to summarize the imaging features of an orally ingested toothpick perforating the gastrointestinal tract. The location of abdominal pain is an important clue for the diagnosis of toothpick perforation, and a CT examination is recommended as the first option for the detection of an ingested toothpick. Determining the location of the toothpick perforation and assessing the severity of local inflammation are important bases for the selection of treatment.

Aqueous zinc metal batteries (AZMBs) are considered a promising candidate for grid-scale energy storage systems owing to their high capacity, high safety and low cost. However, Zn anodes suffer from notorious dendrite growth and undesirable surface corrosion, severely hindering the commercialization of AZMBs. Herein, a strategy for engineering a dense ZnO coating layer on Zn anodes using the atomic layer deposition (ALD) technique is developed, aiming to improve its long-term cycling stability with fewer Zn dendrites. The surface-modified Zn anode (ZnO@Zn) exhibits an excellent long-cycling life (680 h) and stable coulombic efficiency when being used in a symmetric cell. Moreover, the ZnO@Zn electrode shows a high stability with almost no capacity decay after 1100 cycles at 2C in a full cell using MnO2 as the cathode. The ZnO coating is conducive to reducing corrosion and the generation of by-products, thus increasing the reversibility of Zn2+/Zn stripping/plating. Particularly, density functional theory (DFT) calculation results reveal that the ZnO coating layer could effectively lower the adsorption energy of the Zn(002) plane in ZnO@Zn, inducing the preferential deposition of Zn2+ towards the (002) crystal plane with fewer Zn dendrites. The surface ZnO coating protocol provides a promising approach to achieve a dendrite-free Zn anode for stable AZMBs.

Abstract String instruments, wind instruments and percussion instruments are three traditional categories of musical instruments, among which wind instruments play an important role. Usually, pitches of wind instruments are determined by the vibrating air column, and the musical pitches will be affected by multiple factors of the air flow. In this article, the mechanism of sound production by a pipe is analysed in terms of the coupling of the edge tone and the air column's vibration in the tube. Experiments and computational fluid dynamics numerical calculations are combined to study the influence of the jet velocity on the oscillation frequency of the edge tone and the musical sound produced by the tube, which help to gain deeper insight into the relation between physics and music.

The corrosion of rebars will change the mechanical properties of the reinforced concrete structure, leading to the decline in the structural strength, which seriously threatens the safety and stability of buildings and power equipment foundations. Hence, it is of great significance to detect the internal corrosion of reinforced concrete structures. In this paper, a nondestructive detection method for detecting the corrosion in reinforced concrete structures based on microwave was proposed, and the corrosion state of rebar can be evaluated by the change of microwave information. Compared with other detection methods, microwave nondestructive detection has the advantages of low energy consumption, strong penetration, no contact, and small equipment volume and weight. In order to verify the effectiveness of the method, a microwave nondestructive detection simulation test platform was built and reinforced concrete test models with different corrosion lengths and depths were made. The influences of concrete parameters, the microwave frequency, and the lifting distance of the waveguide were analyzed. The frequency sweeping and moving scanning detection methods of the waveguide were carried out for the test models with different corrosion defects, and the changes of microwave S-parameters under different corrosion defects were obtained. The results show that when the waveguide is placed horizontally by the frequency sweeping detection method, the corrosion length detection effect of rebar is better. When the waveguide is placed vertically by the frequency sweeping detection method, the corrosion depth can be identified and the amplitude of transmission coefficient increases with the increase in the corrosion depth. The corrosion length of rebars can be identified quantitatively by the moving scanning detection method of the waveguide.

Object detection is a focal point in remote sensing applications. Remote sensing images typically contain a large number of small objects and a wide range of orientations across objects. This results in great challenges to small object detection approaches based on remote sensing images. Methods directly employ channel relations with equal weights to construct information features leads to inadequate feature representation in complex image small object detection tasks. Multiscale detection methods improve the speed and accuracy of detection, while small objects themselves contain limited information, and the features are easily lost following down-sampling. During the detection, the feature images are independent across scales, resulting in a discontinuity at the detection scale. In this article, we propose the multiscale context and enhanced channel attention (MSCCA) model. MSCCA employs PeleeNet as the backbone network. In particular, the feature image channel attention is enhanced and the multiscale context information is fused with multiscale detection methods to improve the characterization ability of the convolutional neural network. The proposed MSCCA method is evaluated on two real datasets. Results show that for 512 × 512 input images, MSCCA was able to achieve 80.4% and 94.4% mAP on the DOTA and NWPU VHR-10, respectively. Meanwhile, the model size of MSCCA is 21% smaller than that of its predecessor. MSCCA can be considered as a practical lightweight oriented object detection model in remote sensing images.

Abstract Background Neonatal hyperbilirubinemia (NNH) is a common disease in newborns. This research study aimed to assess the associations between uridine diphospho-glucuronate-glucuronosyltransferase 1A1 (UGT1A1, c.-3279 T > G) polymorphisms and NNH risk. Methods We searched PubMed, the Cochrane Library, and the Embase electronic databases. All published eligible studies before July 1, 2019, were searched for this meta-analysis. Results We identified 7 independent studies including 1560 cases. The data showed that in the general population, compared with the GT + GG vs TT and GG vs TT, c.-3279 T > G (rs4124874) was significantly related to a higher NNH risk (GG vs TT: OR = 1.865, 95% CI: 1.031–3.373, P = 0.039; GT + GG vs TT: OR = 1.331, 95% CI: 1.055–1.679, P = 0.016). Although not statistically significant, the data showed that c.3279 T > G had a tendency to be associated with NNH under the allele model and GG vs GT + TT in the overall population (G vs T: OR = 1.288, 95% CI: 0.982–1.689, P = 0.067; GG vs TT + GT: OR = 1.583, 95% CI: 0.947–2.647, P = 0.080). Conclusion The UGT1A1 gene c.-3279 T > G (rs4124874) polymorphism increased susceptibility to NNH, especially for the comparison of GT + GG vs TT and GG vs TT. In the future, we can use homozygous state of the UGT1A1 gene c.-3279 T > G (rs4124874) polymorphism for the diagnosis and screening of molecular biomarkers in NNH patients.

Recently, the AC/DC hybrid distribution network has become a general trend in energy research. To accommodate the addition of renewable energy, this paper proposes a reliability assessment approach for AC/DC hybrid distribution network considering the new features introduced by the DC distribution technique. First, the probability models of renewable generations and loads are established. Second, the control modes of the voltage source converter (VSC) yielding to different fault scenarios are modeled based on its operating characteristics. Thereafter, an optimal load shedding model that considers the control modes of the VSC is developed, and it can be solved using a second-order cone algorithm. Finally, a reliability assessment method for the AC/DC hybrid distribution network is proposed that is based on the nonsequential Monte Carlo method. Case studies based on a modified AC/DC distribution network are applied to verify the effectiveness of the proposed method. The operational characteristics and reliability performance of the AC/DC distribution network with high integration of renewable energy are demonstrated by comparing it to a corresponding AC distribution network.

Energy storage system (ESS) has been advocated as one of the key elements for the future energy system by the fast power regulation and energy transfer capabilities. In particular, for distribution networks with high penetration of renewables, ESS plays an important role in bridging the gap between the supply and demand, maximizing the benefits of renewables and providing various types of ancillary services to cope the intermittences and fluctuations, consequently improving the resilience, reliability and flexibility. To solve the voltage fluctuations caused by the high permeability of renewables in distribution networks, an optimal capacity allocation strategy of ESS is proposed in this paper. Taking the life cycle cost, arbitrage income and the benefit of reducing network losses into consideration, a bilevel optimization model of ESS capacity allocation is established, the coordination between active/reactive power of associate power conversion system is considered, and the large scale nonlinear programming problem is solved using genetic algorithm, simulated annealing and mixed integer second-order cone programming method. The feasibility and effectiveness of the proposed algorithm have been verified.

In the face of the radical revolution of energy systems, there is a gradually held consensus regarding the adoption of distributed renewable energy resources, represented by Photovoltaic (PV) and wind generation. Consequently, the distributed Energy Storage Systems (ESSs) have become increasingly important in the distribution networks, as they provide the arbitrage and ancillary services. Determining the optimal installation site and the capacity of the distributed ESSs will defer the network reinforcements, reduce the investment of ESSs, and improve the reliability, flexibility, and efficiency of distribution grids. In order to investigate the optimal ESS configuration and to solve voltage fluctuations brought by the increased penetration of PV, in this study a two-stage heuristic planning strategy has been proposed, which considers both the economic operation and the lifetime of the distributed ESSs, to determine the optimal sitting and sizing of the ESSs, in the distribution grids. The first stage decides the optimal installation site and the economic scheduling of the ESSs, aiming to minimize the fabricating cost of the distributed ESSs and the network losses. Based on the output of the first stage, the second stage planning is further delivered to achieve the optimal ESS capacity, considering the Life-Cycle Cost (LCC) minimization. Finally, the feasibility and effectiveness of the proposed method is verified on a typical distribution case study network.

Abstract The protein corona formed on nanoparticles (NPs) has potential as a valuable diagnostic tool for improving plasma proteome coverage. Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules allows for the detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 µg/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depletes the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. Employing an optimized data-independent acquisition approach, the inclusion of phosphatidylcholine leads to the detection of 1436 proteins in a single plasma sample. Our molecular dynamics results reveal that phosphatidylcholine interacts with albumin via hydrophobic interactions, H-bonds, and water bridges. The addition of phosphatidylcholine also enables the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate the widespread adoption of this methodology for the identification and clinical translation of biomarkers.

The issue of coal spontaneous combustion greatly threatens the production safety of coal mining, storage, and transportation. It is significant to study oxygen adsorption understand the mechanism of coal spontaneous combustion. In this paper, based on the fractal dimension of coal and the self-similar fractal geometry, the internal pore structure of coal is modeled. Then, the lattice Boltzmann method is employed to conduct the numerical simulation of oxygen adsorption in coal. Compared with the existing experimental data and numerical simulation, the lattice Boltzmann method is verified to be correct. The numerical results indicate that in the process of oxygen adsorption in coal, the preferential flow occurs when the large pores connect to the channel. In the meantime, the large diffusion coefficient leads to an early time for adsorption equilibrium. The oxygen adsorption increases with an increased adsorption rate constant. Pore structure plays a significant role in the adsorption behavior of oxygen in coal. The results can provide theoretical support for reducing coal spontaneous combustion and ensuring coal mine safety in production. [ABSTRACT FROM AUTHOR]

Abstract The changes and influencing factors of soil inorganic carbon (SIC) and organic carbon (SOC) on precipitation gradients are crucial for predicting and evaluating carbon storage changes at the regional scale. However, people’s understanding of the distribution characteristics of SOC and SIC reserves on regional precipitation gradients is insufficient, and the main environmental variables that affect SOC and SIC changes are also not well understood. Therefore, this study focuses on the Alxa region and selects five regions covered by three typical desert vegetation types, Zygophyllum xanthoxylon (ZX), Nitraria tangutorum (NT), and Reaumuria songarica (RS), along the climate transect where precipitation gradually increases. The study analyzes and discusses the variation characteristics of SOC and SIC under different vegetation and precipitation conditions. The results indicate that both SOC and SIC increase with the increase of precipitation, and the increase in SOC is greater with the increase of precipitation. The average SOC content in the 0–300cm profile is NT (4.13 g kg−1) > RS (3.61 g kg−1) > ZX (3.57 g kg−1); The average value of SIC content is: RS (5.78 g kg−1) > NT (5.11 g kg−1) > ZX (5.02 g kg−1). Overall, the multi-annual average precipitation (MAP) in the Alxa region is the most important environmental factor affecting SIC and SOC.

Blood–brain barrier (BBB) prevents neurotoxins from entering central nervous system. We aimed to establish and characterize an in vitro triple co-culture BBB model consisting of brain endothelial cells hCMEC/D3, astrocytoma U251 cells, and neuroblastoma SH-SY5Y cells. Co-culture of SH-SY5Y and U251 cells markedly enhanced claudin-5 and VE-cadherin expression in hCMEC/D3 cells, accompanied by increased transendothelial electrical resistance and decreased permeability. Conditioned medium (CM) from SH-SY5Y cells (S-CM), U251 cells (U-CM), and co-culture of SH-SY5Y and U251 cells (US-CM) also promoted claudin-5 and VE-cadherin expression. Glial cell line-derived neurotrophic factor (GDNF) levels in S-CM and US-CM were significantly higher than CMs from hCMEC/D3 and U-CM. Both GDNF and US-CM upregulated claudin-5 and VE-cadherin expression, which were attenuated by anti-GDNF antibody and GDNF signaling inhibitors. GDNF increased claudin-5 expression via the PI3K/AKT/FOXO1 and MAPK/ERK pathways. Meanwhile, GDNF promoted VE-cadherin expression by activating PI3K/AKT/ETS1 and MAPK/ERK/ETS1 signaling. The roles of GDNF in BBB integrity were validated using brain-specific Gdnf silencing mice. The developed triple co-culture BBB model was successfully applied to predict BBB permeability. In conclusion, neurons enhance BBB integrity by upregulating claudin-5 and VE-cadherin expression through GDNF secretion and established triple co-culture BBB model may be used to predict drugs’ BBB permeability.

BackgroundBody constitution is the foundation of Traditional Chinese Medicine (TCM), and model workers consist of a special group of workers within China. This study aims to research the relationship between the physical body constitutions based on TCM and the mental health of model workers.MethodsWe recruited 314 model workers from Beijing Rehabilitation Hospital to conduct the questionnaires such as SCL-90 and CCMQ to investigate if there is an association between mental health status and TCM body constitutions. We performed a Partial Least Squares Path Modeling (PLS path modeling).ResultsOur path model results revealed associations between different TCM constitution types and SCL scores, which serve as indicators of psychological well-being. Our research findings demonstrate a strong correlation between the Balanced constitution and elevated levels of psychological well-being, with a path coefficient of -0.503. In contrast, the other eight constitutional types exhibit path coefficients exceeding 0.3, indicating a tendency toward lower levels of psychological well-being. We also investigated the intricate connections between various TCM constitutional types and both mild and severe psychological well-being.ConclusionIn conclusion, the Balanced constitution continues to be closely associated with higher levels of psychological well-being, while the remaining eight body constitution types are consistently linked to lower levels of psychological well-being.

Abstract The quality of the rebar thread head is crucial for the connection between the rebars, thereby affecting the public safety of the building. The edge extraction of the thread image is the most important step in obtaining the accurate size parameters, which helps to complete online inspection of quality. Here, an edge detection method based on improved Canny operator is proposed to solve the problems on sensitivity to noise, existence of false edges, and lack of self‐adaptability. Firstly, an improved adaptive median filtering algorithm is used to denoise the image. Then replace Sobel with Scharr to enhance the gap between pixel values, add 45° and 135° directional templates to prevent edge information loss as well. Besides, introduce a scale factor to improve the interpolation method for non‐maximum suppression and reduce false edges. Finally, use Ostu operator to achieve adaptive extraction of high and low thresholds to complete adaptive edge detection. The qualitative analysis and quantitative results show that the improved algorithm can not only have a good visual effect, have good robustness and feasibility, but also be faster than other algorithms, which provide a basic guarantee for real‐time online quality detection of the thread head.

As a vital conservation area for water sources in the Yellow River Basin, understanding the spatial-temporal dynamics of vegetation coverage is crucial, along with the factors that affect it, to ensure ecological preservation and sustainable development of the Yellow River Source Region (YRSR). In this paper, we utilized Landsat surface reflectance data from 2000 to 2020 using de-clouding and masking methods implementing the Google Earth Engine (GEE) cloud platform. We investigated spatial-temporal changes in vegetation coverage by combining the maximum value composite (MVC), the dimidiate pixel model (DPM), the Theil–Sen median slope, and the Mann–Kendall test. The influencing factors on vegetation coverage were quantitatively analyzed using a geographic detector, and future tendencies in vegetation coverage were predicted utilizing the Future Land Use Simulation (FLUS) model. The outcomes suggested the following: (1) On the temporal scale, vegetation coverage exhibited a general upward trend between 2000 and 2020, with the YRSR showing a yearly growth rate of 0.23% (p < 0.001). In comparison to 2000, the area designated as having extremely high vegetation coverage increased by 19.3% in 2020. (2) Spatially, the central and southeast regions have higher values of vegetation coverage, whereas the northwest has lower values. In the study area, 75.5% of the region demonstrated a significant improvement trend, primarily in Xinghai County, Zeku County, and Dari County in the south and the northern portion of the YRSR; conversely, a notable tendency of degradation was identified in 11.8% of the area, mostly in the southeastern areas of Qumalai County, Chenduo County, Shiqu County, and scattered areas in the southeastern region. (3) With an explanatory power of exceeding 45%, the three influencing factors that had the biggest effects on vegetation coverage were mean annual temperature, elevation, and mean annual precipitation. Mean annual precipitation has been shown to have a major impact on vegetation covering; the interconnections involving these factors have increased the explanatory power of vegetation coverage’s regional distribution. (4) Predictions for 2030 show that the vegetation coverage is trending upward in the YRSR, with a notable recovery trend in the northwestern region. This study supplies a theoretical foundation to formulate strategies to promote sustainable development and ecological environmental preservation in the YRSR.

Desertification poses a serious threat to ecosystem health, and with global changes, the variability and uncertainty of ecological functions in semi-arid alpine regions are increasing. A pressing issue is quantifying how desertification affects the soil system functions in these areas. However, empirical evidence is still lacking in exploring the interaction between desertification degradation gradients and soil functions under natural conditions by coupling soil physicochemical properties, soil microbiota, and vegetation. For this purpose, we conducted a survey sampling of soil and vegetation at five sites with no, light, moderate, severe and extremely severe desertification in Qinghai Area of Qilian Mountains National Park, China. We introduced a new concept soil health stability (SHS) to represent the actual health status of soil systems in semi-arid alpine regions and assessed the impact of desertification on this stability. We observed that the intensification of desertification has led to a significant decrease in soil organic matter, relative abundance of soil microorganisms, and plant factors. The contributions of plant factors and soil microbiota to SHS showed a negative correlation with the degradation gradient. SHS varied across different degradation gradients, rather than following a single linear relationship, with a relatively rapid decline in the transition from non-desertification to moderate desertification. Our work emphasizes that the coupled contributions of soil physicochemical properties, soil microbiota, and vegetation to SHS. It calls for intensified prevention and treatment of mild and moderate desertification, while providing new methods and deeper scientific understanding for accurately evaluating soil system functions in semi-arid alpine regions.

An online inspection method based on machine vision was proposed and validated to address the issues of high work intensity, low efficiency, low accuracy, and risk of missed inspection in traditional sampling methods for screw threads of rebar head. Firstly, an industrial camera was used to capture real-time images of the processed rebar thread heads, preprocess the images, and locate the target positions in the images to reduce the complexity and running time of subsequent algorithms. Then, the Canny operator was used to roughly extract the edge feature information of the rebar head, and the Shi–Tomasi algorithm was used for corner inspection to achieve precise optimization of sub-pixel level corners. Based on robust linear regression, the diagonal points were fitted with lines to detect the corresponding size parameters. Finally, an inspection system on screw threads of rebar head parameter was designed and developed, which consisted of an image-acquisition device, Siemens PLC controller, and inspection software. Test results show that this method can achieve online inspection without contact, with inspection accuracy reaching the micrometer level, and 8–10 rebar heads can be inspected per second.

Abstract Faults in rolling bearings are usually observed through pulses in the vibration signals. However, due to the influence of complex background noise and interference from other machine components present in measurement equipment, vibration signals are typically non‐stationary and often contaminated by noise. Therefore, in order to effectively extract the random variation and non‐linear dynamic variation characteristics of vibration signals, a new method of rolling bearing fault diagnosis based on generalized multiscale mean permutation entropy (GMMPE) and grey wolf optimized least squares support vector machine (GWO‐LSSVM) is put forward in this paper. Based on the multiscale permutation entropy (MPE), the multiscale equalization is firstly used to replace the coarse grained process, and the value of mean is extended to variance to avoid the dynamic mutation of the original signal. Finally, the parameters of LSSVM are optimized by the grey wolf optimization algorithm to achieve accurate identification of fault modes. The results of simulation and experiment show that applying the proposed GMMPE to rolling bearing fault feature extraction is feasible and superior, and the method based on GMMPE and GWO‐LSSVM has better noise robustness, which can effectively achieve rolling bearing fault diagnosis.

Aiming at problems such as inaccurate simulation of groundwater level in closed hydrogeological units, difficult quantitative prediction of soil salinization degree, and unclear water and salt migration, a three-dimensional simulation model of groundwater was established, and the development trend of groundwater level and soil salinization was predicted. The groundwater level simulation results are consistent with the changing trend of the observational data and the simulation model can be used to predict groundwater levels in closed hydrogeological units. When climate scenarios and human activity change are set as future scenarios, the average groundwater buried depth will continue to decrease in the next 10 years, the area with a groundwater buried depth of 0–5 m will exceed 50%, and even the groundwater will overflow to the surface. The change of soil salt content is predicted quantitatively and the salinization degree will develop from ‘saline–alkali soil’ and ‘mild saline–alkali soil’ to ‘medium saline–alkali soil’. The process of water and salt migration in three key hydrologic zones, namely ‘irrigation infiltration’, ‘solute migration’, and ‘water and salt accumulation’, is revealed in the closed hydrogeological unit. The research results can provide new ideas for the improvement of soil and water environment problems. HIGHLIGHTS Simulation and prediction of groundwater level in closed hydrogeological units of arid irrigation areas.; The spatial distribution of salinization in the study area is closely related to the buried depth of groundwater.; The movement of groundwater can be divided into three key hydrological zones: ‘irrigation infiltration’, ‘solute transport’, and ‘water collection and salt accumulation’.;

Eco-environmental vulnerability reflects the unfavorable degree of the ecological environment presented by external disruptions. The Shiyang River Basin, as a typical desert interior river basin in Northwest China, plays crucial ecological roles. Exploring eco-environmental vulnerability's spatial and temporal evolution is vital to maintaining ecosystem stability. We utilized the ecological sensitivity-resilience-press (SRP) model to create a complete evaluation index system of eco-environmental vulnerability using meteorological, remote sensing, and statistical data. The cloud theory improved analytic hierarchy process (CM-AHP) was used to calculate the subjective weights, the entropy weight method (EWM) was used to estimate the objective weights, and the comprehensive weights of the indicators were determined using the least square method, which combined the subjective and objective weights. From 2000 to 2020, the spatial-temporal features of eco-environmental vulnerability in the research area were analyzed. The results indicate that surface temperature, land use, and monthly precipitation are key factors impacting the state of eco-environmental vulnerability. The basin's potential-vulnerable and light-vulnerable areas are predominantly located in the south and southwest, whereas the northern and eastern areas are classified as severe-vulnerable and extreme-vulnerable. Extreme-vulnerable areas declined from 8.59% in 2000 to 4.3% in 2020, while potential-vulnerable areas climbed from 2.11% in 2000 to 8.08% in 2020. The eco-environmental vulnerability as a whole has evolved in a benign direction. The research results can serve as a theoretical groundwork for the restoration of the Shiyang River Basin's ecological environment and long-term development.

Plantations in dry and semi-arid areas significantly affect the soil’s ability to store carbon and maintain a stable water balance. It is yet unclear, though, how planted trees in these regions might impact the soil’s carbon and water levels. As a forest ages, it is unknown how soil water and soil carbon interact with one another. In order to conduct this study, four Saxaul plantations in the Alxa Plateau were chosen, with the neighboring mobile sandy (MS) ground serving as a control. The ages of the plantations ranged from 5 to 46 years. The major topics of the study included the relationship between soil water and soil carbon, changes in the 0-300 cm soil layer’s soil water content (SWC), soil organic carbon (SOC), and soil inorganic carbon (SIC) following afforestation. The findings demonstrated that, in comparison to MS, afforestation considerably increased SOC and SIC stocks. In comparison to MS, the SIC grew by 4.02 kg m-2, 4.12 kg m-2, 5.12 kg m-2, and 6.52 kg m-2 throughout periods of 5 years, 11 years, 22 years, and 46 years, respectively. SOC increased relative to MS by 2.55 kg m-2, 2.91 kg m-2, 3.53 kg m-2, and 4.05 kg m-2. Afforestation, however, also contributed to a considerable decline in deep SWC and an increase in the soil water deficit (SWD). In comparison to MS, the mean SWC values were lower at 5 years, 11 years, 22 years, and 46 years, respectively, by 0.48%, 1.37%, 1.56%, and 4.00%. The increase in soil carbon pool caused by sand afforestation actually came at the expense of a reduction in soil water due to a large negative association between deep SWC, SOC, and SIC. To limit SWC losses and encourage sustainable forest land development, we advocate suitable harvest management practices on forest land.

Climate change is considered to be a serious threat to crop production around the globe. In the northern Shanxi Province of China (SXN), foxtail millet (or millet) is the main crop and generally grows under rainfed conditions. Existing literature has confirmed the millet yield reductions due to climate change in the past. However, little is known about the impacts of future climate change on millet production in the SXN. The main objectives of this study were to investigate the future climate change impacts under two emission scenarios (SSP245 and SSP585) and the potentials of shifting sowing date combined with supplemental irrigation as an adaptation strategy to climate change for millet production in the SXN using the Decision Support System for Agrotechnology Transfer (DSSAT). Two supplemental irrigation strategies were tested: one presowing irrigation only (PSI), and two supplementary irrigations (PSGI) adopting one presowing irrigation and one irrigation during the growing season. We found that the air temperature, solar radiation and precipitation during the millet growing season in the future (2021–2060) are higher than those in the baseline (1981–2020). The rainfed millet yield will decrease by 8.6 % (SSP245) and 16.5 % (SSP585) in the future without an adaptation strategy, compared to the baseline yield (2.43 t ha−1) in 1981–2020 under the conventional sowing date. The reduction in rainfed millet yield caused by climate change cannot be reversed by shifting sowing date, but can be slightly mitigated by a suitable advancement of the sowing date. Adopting supplemental irrigation in the future can achieve higher millet yield than the baseline yield, especially PSGI. Compared to PSI, PSGI consumes more irrigation water but has higher irrigation water use efficiency (IWUE). There is a synergy between shifting sowing date and supplemental irrigation in coping with climate change, and a later sowing date than the conventional one (30 April) is recommended under supplemental irrigation in the future. In 2021–2060, the best adaptation strategy to climate change for maximizing grain yield, IWUE and economic benefit in the millet production of the SXN is that supplementary irrigation is applied before sowing and on 20 July–30 July combined with the sowing dates of 10 May–20 May.

The spatial and temporal evolution process of the water and soil resource carrying capacity in artificial oases in the arid zone of China was accurately revealed. This study constructs a water and soil resource analysis system based on system dynamics. It integrates cloud theory and hierarchical analysis to analyze the evolutional trend of the water and soil resource carrying capacity in irrigation areas. The spatial analysis technique was used to obtain a raster map of the spatial and temporal characteristics of the influencing factors, and analyze the evolutionary characteristics of the water and soil resources carrying capacity by integrating multi-source data. The results showed that: (1) the evaluation clouds of water and soil resources carrying capacity in 2002, 2010, and 2018 were (0.5034, 0.0236, 0.0071), (0.5586, 00218, 0.0062), and (0.5989, 0.0249, 0.0061), respectively. This showed that the carrying capacity of water and soil resources was transitioning from ‘critical bearing’ to ‘good bearing’, but the evolution rate was gradually decreasing; (2) from 2002 to 2018, the size of the ‘good bearing’ area increased by 8.38%, while the size of the ‘severe bearing’ area decreased by 6.4%; (3) the degree of dramatic evolution of the carrying capacity of water and soil resources is: continuous change > pre-change > post-change > continuous stable > repeated change; (4) the serious carrying capacity area shows a spatial pattern of decreasing in an arc from the town to the surrounding areas. The results showed that water and soil resource-carrying capacity of the irrigation area shows a healthy and continuous spatial and temporal evolution trend. HIGHLIGHTS Coupling SD, multilevel fuzzy theory and cloud model were used to assess the carrying capacity of water and soil resources.; Based on Arc GIS and ENVI we showed the spatial distribution characteristics of regional environmental conditions.; The carrying capacity of water and soil resources shows a healthy evolution trend, and the evolution rate slows down gradually.;

ObjectivesTo identify combined clinical, radiomic, and delta-radiomic features in metastatic gastroesophageal adenocarcinomas (GEAs) that may predict survival outcomes.MethodsA total of 166 patients with metastatic GEAs on palliative chemotherapy with baseline and treatment/follow-up (8–12 weeks) contrast-enhanced CT were retrospectively identified. Demographic and clinical data were collected. Three-dimensional whole-lesional radiomic analysis was performed on the treatment/follow-up scans. “Delta” radiomic features were calculated based on the change in radiomic parameters compared to the baseline. The univariable analysis (UVA) Cox proportional hazards model was used to select clinical variables predictive of overall survival (OS) and progression-free survival (PFS) (p-value

Abstract Background Acetaminophen is commonly recommended for the early analgesia of osteoarthritis. However, the molecular mechanism by which it acts remains unknown. The aim of this study is to investigate the effect of acetaminophen on inflammation and extracellular matrix degradation in human chondrocytes, and the possible molecular mechanisms involved in its effect. Methods The normal chondrocyte cell line C28/I2 was treated with interleukin-1β to mimic the inflammatory state. Acetaminophen and the methylation inhibitor (cycloleucine) were used to treat interleukin-1β-induced C28/I2 cells. The expression of RNA N6-methyladenosine -related proteins was detected by RT-qPCR and western blot. The total RNA N6-methyladenosine level was measured by dot blot analysis and enzyme linked immunosorbent assay. The levels of interleukin-6, interleukin-8 and anti-tumor necrosis factor-α were measured by enzyme linked immunosorbent assay. The extracellular matrix synthesis and degradation were examined by western blot. Results After interleukin-1β stimulated C28/I2 cells, the intracellular RNA N6-methyladenosine level increased, and the expression of regulatory proteins also changed, mainly including the increased expression of methyltransferase like 3 and the downregulated expression of AlkB family member 5. The use of cycloleucine inhibited interleukin-1β-induced inflammation and extracellular matrix degradation by inhibiting RNA N6-methyladenosine modification. In contrast, acetaminophen treatment counteracted interleukin-1β-induced changes in RNA N6-methyladenosine levels and regulatory protein expression. Furthermore, acetaminophen treatment of interleukin-1β-induced C28/I2 cells inhibited the secretion of interleukin-6, interleukin-8 and anti-tumor necrosis factor-α, down-regulated the expression of matrix metalloproteinase-13 and Collagen X, and up-regulated the expression of collagen II and aggrecan. In addition, AlkB family member 5 overexpression activated interleukin-1β-induced chondrocyte viability and suppressed inflammation and extracellular matrix degradation. Conclusion Acetaminophen affects inflammatory factors secretion and extracellular matrix synthesis of human chondrocytes by regulating RNA N6-methyladenosine level and N6-methyladenosine-related protein expression. Graphical abstract Stimulation of the normal chondrocyte cell line C28/I2 with the cytokine IL-1β (10 μM) mimics the inflammatory state in vitro. Acetaminophen (Ace, 50 μg/mL) changes the m6A related proteins expression and the total RNA m6A levels in IL-1β-treated chondrocyte cells. Furthermore, regulation of RNA m6A levels (by methylation inhibitor Cyc and/or Ace) affects IL-1β-induced inflammatory cytokines secretion and extracellular matrix synthesis in C28/I2 cells.

Afforestation is an important and effective way to curb wind-sand hazards in the Alxa Desert. However, over-afforestation makes soil drying occur frequently. The formation of a soil drying layer is seriously restricting the effectiveness of vegetation construction and regional ecological stability. To clarify the process of soil desiccation in Haloxylon ammodendron plantations and determine the suitable planting years, a typical H. ammodendron plantation in this area was selected as the research object, and the soil moisture variation characteristics of this sand-fixing vegetation region with vegetation age were analyzed. The analysis results on soil water supply, consumption, and balance showed that the soil water storage in 0–400 cm soil layer of H. ammodendron plantation varies significantly in different ages. The soil water storage in 0–11 years old was the largest, and the soil water supply was greater than the soil water consumption. The soil water storage in profile increased with the increase of precipitation, the soil water storage of H. ammodendron at 11–22 years old increased first and then decreased with precipitation, and the inflexion existed in 16.5 years old. The soil water consumption of H. ammodendron plantation at 22–46 years old was greater than that of soil water supplement, and the soil moisture appeared negative balance continuously. Therefore, to prevent further deterioration of soil moisture ecological environment in the H. ammodendron plantation and to promote the sustainable development of afforestation in desert areas, thinning measures are suggested when the growth period reaches 16.5 years. The research results could provide scientific basis for afforestation and soil dry layer regulation in the Alxa desert.

To explore the effects of different pressure pipeline layouts on pumping station pipeline vibration, this study establishes an ALGOR numerical model for pipeline flow considering fluid–structure interactions. A data acquisition and signal processing vibration test system is used to obtain vibration signals and verify simulation results including pipeline fluid velocity, fluid pressure, and transient stress. Based on the flow's vibration excitation characteristics, we consider structural vibration reduction technology and propose an optimized design scheme. As an example, we apply this approach to a pressure pipeline at the Ningxia Yanhuanding Pumping Station Project. Results show strong vibrations at the water inlet, the junction between the branch and main pipes, and the water outlet, with even stronger vibration at the inlet than at the outlet. In the optimized design scheme, adjusting the distance between the branch pipes only weakly reduces flow-generated pipeline vibration; increasing the pipe diameter and changing the main pipe's relative orientation show stronger effects. Vibration reduction is optimized for a main pipe dip angle of 2–5° relative to the branch pipes, simultaneously decreasing pumping station energy loss. These results provide a theoretical and practical basis for optimal design of pressure pipelines at high-lift pumping stations. HIGHLIGHT This paper established fluid-structure interaction-based water flow ALGOR numerical model of pressure pipeline in a pump station; meanwhile, DASP vibration test system is adopted to acquire the vibration signals to verify the simulation results, analyze the incentive characteristics of pressure pipeline flow formed on pipeline vibration and put forward an optimized design scheme.;

Afforestation as an effective measure for wind and sand control has achieved remarkable results in northern China, and has also greatly changed the land use and vegetation characteristics of the region. It is important to study the spatial and temporal dynamics of soil water content (SWC) in different afforestation years and its temporal stability to understand the dynamic characteristics of SWC during afforestation. In order to reveal the spatiotemporal dynamic characteristics of SWC in desert area Haloxylon ammodendron (HA)plantations, in this study, five restorative-aged HA plantations in desert areas were selected and their SWC was measured in stratified layers for the 0–400 cm soil profile; we also analyzed the spatiotemporal dynamics and temporal stability of the SWC. The results showed that the SWC of HA plantations decreased with the increase in planting age in the measurement period, and the SWC of deep layers increased by more than that of shallow layers with planting age. Spearman’s rank correlation coefficients for SWC of 0–400 cm in both 5- and 11-year-old HA plantations reached above 0.8 and were highly significantly correlated; the temporal stability of SWC tends to increase as the depth of the soil layer deepens. In contrast, the temporal stability of SWC in deeper layers (200–400 cm) of 22-, 34- and 46-year-old stands showed a decreasing trend with depth. Based on the relative difference analysis, representative sampling points can be selected to monitor the regional average SWC, but for older HA plantations, the uncertainty factor of stand age should be considered in the regional moisture simulation. This study verified that it is feasible to simulate large-scale SWC in fewer observations for HA plantations younger than 11 years old, while large errors exist for older stands, especially for deeper soils. This will help soil moisture management in HA plantations in arid desert areas.