Positive Association of Pulse Pressure with Presence of Albuminuria in Chinese Adults with Prediabetes: A Community-Based Study.

Purpose: There has been limited evidence for the association between pulse pressure (PP) and proteinuria in prediabetes. The aim of our study was to explore the association between PP and albuminuria in community-dwelling Chinese adults with prediabetes. Materials and Methods: PP and urinary albumin-to-creatinine ratio (ACR) were measured in 2012 prediabetic patients and 3596 control subjects with normal glucose tolerance. Multivariate logistic regression models were used to evaluate the possible association of PP with the risk of presence of albuminuria. Results: PP was positively associated with the presence of albuminuria, and subjects in the higher PP quartiles had higher urinary ACR and presence of albuminuria as compared with those in the lowest quartile in both prediabetes and control groups (all P < 0.01). Multivariate logistic regression analysis demonstrated that the highest PP quartile was positively associated with increased risk of presence of albuminuria in all prediabetic subjects [odds ratio (OR): 2.289, 95% confidence interval (CI) 1.364-3.842, P < 0.01) and prediabetic subjects without anti-hypertensive drugs (OR: 1.932, 95% CI 1.116-3.343, P < 0.01), whereas higher PP quartile has nothing to do with the risk of presence of albuminuria in control subjects with and without anti-hypertensive drugs after adjustment for potential confounders (all P > 0.01). Consistently, stratified analysis showed that in the prediabetes group, the risks of presence of albuminuria progressively elevated with increasing PP quartiles in men, those aged 60 years or older, and with overweight/obesity, normal high-density lipoprotein cholesterol, and appropriate low-density lipoprotein cholesterol (all P for trend <0.05). Conclusion: Higher PP is independently related to increased risk of presence of albuminuria in community-dwelling Chinese adults with prediabetes.

Ameliorative effects of zinc and vitamin E against phthalates-induced reproductive toxicity in male rats.

OBJECTIVE: Phthalates (PEs) could cause reproductive harm to males. A mixture of three widely used PEs (MPEs) was used to investigate the ameliorative effects of zinc (Zn) and vitamin E (VE) against male reproductive toxicity. METHODS: Fifty male SD rats were randomly divided into five groups (n = 10). Rats in MPEs group were orally treated with 160 mg/kg/d MPEs, while rats in MPEs combined Zn and/or VE groups were treated with 160 mg/kg/d MPEs plus 25 mg/kg/d Zn and/or 25 mg/kg/d VE. After intervention for 70 days, it's was measured of male reproductive organs' weight, histopathological observation of sperms and testes, serum hormones, PIWI proteins and steroidogenic proteins. RESULTS: Compared with control, anogenital distance, testes weight, epididymides weight, and sex hormones were significantly decreased, while the sperm malformation rate was markedly increased in MPEs group (p < .05); the testicular tissues were injured in MPEs group with disordered and decreased spermatids, and arrested spermatogenesis. PIWIL1, PIWIL2, StAR, CYP11A1 and CYP19A1 were down-regulated in MPEs group (p < .05). However, the alterations of these parameters were restored in MPEs combined Zn and/or VE groups (p < .05). CONCLUSION: Zn and/or VE improved steroid hormone metabolism, and inhibited MPEs' male reproductive toxicity.

Alleviative effect of quercetin against reproductive toxicity induced by chronic exposure to the mixture of phthalates in male rats.

Phthalates (PEs) are widely used plasticizers in polymer products, and humans are increasingly exposed to them. This study was designed to investigate the alleviative effect of phytochemicals quercetin (Que) against male reproductive toxicity caused by the mixture of three commonly used PEs (MPEs), and further to explore the underlying mechanism. Forty-eight male SD rats were randomly and evenly divided into control group, Que group, MPEs group and MPEs+Que group (n = 12); The oral exposure doses of MPEs and Que were 450 mg/kg/d and 50 mg/kg/d, respectively. After 91 days of continuous intervention, compared with control group, the testes weight, epididymis weight, serum sex hormones, and anogenital distance were significantly decreased in MPEs group (P < 0.05); Testicular histopathological observation showed that all seminiferous tubules were atrophy, leydig cells were hyperplasia, spermatogenic cells growth were arrested in MPEs group. Ultrastructural observation of testicular germ cells showed that the edges of the nuclear membranes were indistinct, and the mitochondria were severely damaged with the cristae disrupted, decreased or even disappeared in MPEs group. Immunohistochemistry and Western blot analysis showed that testicular CYP11A1, CYP17A1 and 17ß-HSD were up-regulated, while StAR, PIWIL1 and PIWIL2 were down-regulated in MPEs group (P < 0.05); However, the alterations of these parameters were restored in MPEs+Que group. The results indicated MPEs disturbed steroid hormone metabolism, and caused male reproductive injuries; whereas, Que could inhibit MPEs' male reproductive toxicity, which might relate to the restored regulation of steroid hormone metabolism.

Long-term exposure to the mixture of phthalates induced male reproductive toxicity in rats and the alleviative effects of quercetin.

Phthalates (PEs), such as di(2-ethylhexyl) phthalate (DEHP), dibutyl phthalate (DBP) and butyl benzyl phthalate (BBP) could cause reproductive and developmental toxicities, while human beings are increasingly exposed to them at low-doses. Phytochemical quercetin (Que) is a flavonoid that has estrogenic effect, anti-inflammatory and anti-oxidant effects. This study was conducted to assess the alleviative effect of Que. on male reproductive toxicity induced by the mixture of three commonly used PEs (MPEs) at low-dose in rats, and explore the underlying mechanism. Male rats were treated with MPEs (16 mg/kg/day) and/or Que. (50 mg/kg/d) for 91 days. The results showed that MPEs exposure caused male reproductive injuries, such as decreased serum sex hormones levels, abnormal testicular pathological structure, increased abnormal sperm rate and changed expressions of PIWIL1 and PIWIL2. Furthermore, MPEs also changed the expression of steroidogenic proteins in steroid hormone metabolism, including StAR, CYP11A1, CYP17A1, 17ß-HSD, CYP19A1. However, the alterations of these parameters were reversed by Que. MPEs caused male reproductive injuries in rats; Que. inhibited MPEs' male reproductive toxicity, which might relate to the improvement of testosterone biosynthesis.

Truck model recognition for an automatic overload detection system based on the improved MMAL-Net.

Efficient and reliable transportation of goods through trucks is crucial for road logistics. However, the overloading of trucks poses serious challenges to road infrastructure and traffic safety. Detecting and preventing truck overloading is of utmost importance for maintaining road conditions and ensuring the safety of both road users and goods transported. This paper introduces a novel method for detecting truck overloading. The method utilizes the improved MMAL-Net for truck model recognition. Vehicle identification involves using frontal and side truck images, while APPM is applied for local segmentation of the side image to recognize individual parts. The proposed method analyzes the captured images to precisely identify the models of trucks passing through automatic weighing stations on the highway. The improved MMAL-Net achieved an accuracy of 95.03% on the competitive benchmark dataset, Stanford Cars, demonstrating its superiority over other established methods. Furthermore, our method also demonstrated outstanding performance on a small-scale dataset. In our experimental evaluation, our method achieved a recognition accuracy of 85% when the training set consisted of 20 sets of photos, and it reached 100% as the training set gradually increased to 50 sets of samples. Through the integration of this recognition system with weight data obtained from weighing stations and license plates information, the method enables real-time assessment of truck overloading. The implementation of the proposed method is of vital importance for multiple aspects related to road traffic safety.

Federated Transfer Learning Strategy: A Novel Cross-Device Fault Diagnosis Method Based on Repaired Data.

Federated learning has attracted much attention in fault diagnosis since it can effectively protect data privacy. However, efficient fault diagnosis performance relies on the uninterrupted training of model parameters with massive amounts of perfect data. To solve the problems of model training difficulty and parameter negative transfer caused by data corruption, a novel cross-device fault diagnosis method based on repaired data is proposed. Specifically, the local model training link in each source client performs random forest regression fitting on the fault samples with missing fragments, and then the repaired data is used for network training. To avoid inpainting fragments to produce the wrong characteristics of faulty samples, joint domain discrepancy loss is introduced to correct the phenomenon of parameter bias during local model training. Considering the randomness of the overall performance change brought about by the local model update, an adaptive update is proposed for each round of global model download and local model update. Finally, the experimental verification was carried out in various industrial scenarios established by three sets of bearing data sets, and the effectiveness of the proposed method in terms of fault diagnosis performance and data privacy protection was verified by comparison with various currently popular federated transfer learning methods.

Machine-Learning Algorithms for Process Condition Data-Based Inclusion Prediction in Continuous-Casting Process: A Case Study.

Quality-related prediction in the continuous-casting process is important for the quality and process control of casting slabs. As intelligent manufacturing technologies continue to evolve, numerous data-driven techniques have been available for industrial applications. This case study was aimed at developing a machine-learning algorithm, capable of predicting slag inclusion defects in continuous-casting slabs, based on process condition sensor data. A large dataset consisting of sensor data from nearly 7300 casting samples has been analyzed, with the empirical mode decomposition (EMD) algorithm utilized to process the multi-modal time series. The following machine-learning algorithms have been examined: K-Nearest neighbors, support vector classifier (linear and nonlinear kernels), decision trees, random forests, AdaBoost, and Artificial Neural Networks. Four over-sampling or under-sampling algorithms have been adopted to solve imbalanced data distribution. In the experiment, the optimized random forest outperformed other machine-learning algorithms in terms of recall and ROC AUC, which could provide valuable insights for quality control.

Structure-Crack Detection and Digital Twin Demonstration Based on Triboelectric Nanogenerator for Intelligent Maintenance.

The accomplishment of condition monitoring and intelligent maintenance for cantilever structure-based energy harvesting devices remains a challenge. Here, to tackle the problems, a novel cantilever-structure freestanding triboelectric nanogenerator (CSF-TENG) is proposed, which can capture ambient energy or transmit sensory information. First, with and without a crack in cantilevers, the simulations are carried out. According to simulation results, the maximum change ratios of natural frequency and amplitude are 1.1% and 2.2%, causing difficulties in identifying defects by these variations. Thus, based on Gramian angular field and convolutional neural network, a defect detection model is established to achieve the condition monitoring of the CSF-TENG, and the experimental result manifests that the accuracy of the model is 99.2%. Besides, the relation between the deflection of cantilevers and the output voltages of the CSF-TENG is first built, and then the defect identification digital twin system is successfully created. Consequently, the system is capable of duplicating the operation of the CSF-TENG in a real environment, and displaying defect recognition results, so the intelligent maintenance of the CSF-TENG can be realized.

An Approach to Integrated Scheduling of Flexible Job-Shop Considering Conflict-Free Routing Problems.

This study proposes an approach to minimize the maximum makespan of the integrated scheduling problem in flexible job-shop environments, taking into account conflict-free routing problems. A hybrid genetic algorithm is developed for production scheduling, and the optimal ranges of crossover and mutation probabilities are also discussed. The study applies the proposed algorithm to 82 test problems and demonstrates its superior performance over the Sliding Time Window (STW) heuristic proposed by Bilge and the Genetic Algorithm proposed by Ulusoy (UGA). For conflict-free routing problems of Automated Guided Vehicles (AGVs), the genetic algorithm based on AGV coding is used to study the AGV scheduling problem, and specific solutions are proposed to solve different conflicts. In addition, sensors on the AGVs provide real-time data to ensure that the AGVs can navigate through the environment safely and efficiently without causing any conflicts or collisions with other AGVs or objects in the environment. The Dijkstra algorithm based on a time window is used to calculate the shortest paths for all AGVs. Empirical evidence on the feasibility of the proposed approach is presented in a study of a real flexible job-shop. This approach can provide a highly efficient and accurate scheduling method for manufacturing enterprises.

Proposal and Validation of a New Nonradiological Method for Postoperative Three-Dimensional Implant Position Analysis Based on the Dynamic Navigation System: An In Vitro Study.

PURPOSE: To propose a novel, radiation-free method for postoperative three-dimensional (3D) position analysis of dental implants based on the dynamic navigation system (DNS) and evaluate its accuracy in vitro. METHODS: A total of 60 implants were digitally planned and then placed in the standardized plastic models with a single-tooth gap and a free-end gap under the guidance of the DNS. Postoperative 3D positions of the inserted implants were evaluated using specially designed navigation-based software, and its datasets were superimposed onto those of cone beam computed tomography (CBCT) for accuracy analyses. Deviations at the coronal, apical, and angular levels were measured and statistically analyzed. RESULTS: The mean 3D deviation was 0.88 ± 0.37 mm at the entry point and 1.02 ± 0.35 mm at the apex point. The mean angular deviation was 1.83 ± 0.79 degrees. No significant differences were noted in the deviations between implants placed in the single-tooth gap and the free-end situation (p > 0.05) or between different tooth positions at distal extensions (p > 0.05). CONCLUSIONS: This non-radiographic method provides facile, efficient, and reliable postoperative implant position evaluation and may be a potential substitute for CBCT, particularly for implants placed under the guidance of dynamic navigation.

Quercetin inhibits testicular toxicity induced by the mixture of three commonly used phthalates in rats.

BACKGROUND: Phthalates (PEs), such as butyl benzyl phthalate, dibutyl phthalate and di(2-ethylhexyl) phthalate, are one of the most widely used plasticizers, and humans are increasingly exposed to them. Phytochemical quercetin (Que) is a typical flavonoid with several biological effects, such as antioxidative and anti-inflammatory. The present study was designed to explore the effect of Que on testicular toxicity caused by the mixture of three commonly used PEs (MPEs), and the underlying mechanism. Forty male Sprague-Dawley rats were randomly and equally divided into five groups (n = 8). Rats in control the group were orally treated with the excipient. Rats in the MPEs group were orally administered with 900 mg kg-1 day-1 MPEs, whereas rats in the MPEs+L-Que, MPEs+M-Que and MPEs+H-Que groups were simultaneously treated with 900 mg kg-1 day-1 MPEs and, respectively, 10, 30 and 90 mg kg-1 day-1 Que for 30 days. RESULTS: Compared with the control group, the testes weight, epididymides weight, serum testosterone, luteinizing hormone, follicle-stimulating hormone and estradiol levels, and anogenital distance in the MPEs group were significantly decreased (P < 0.05). The testicular tissues were injured with atrophy of seminiferous tubules, hyperplasia of Leydig cells and arrest of spermatogenesis in the MPEs group. Testicular steroidogenic proteins (StAR, P450scc, CYP17A1 and 17ß-HSD, P450arom) were up-regulated, whereas P-element-induced wimpy testis proteins (PIWIL1 and PIWIL2) were down-regulated in the MPEs group (P < 0.05). However, the alterations of these parameters were inhibited in the MPEs+M-Que and MPEs+H-Que groups. CONCLUSION: MPEs disturbed steroid hormone metabolism and caused testicular injuries. Que could inhibit testicular toxicity of MPEs, which might relate to the improved regulation of steroid hormone metabolism. © 2022 Society of Chemical Industry.

Protective effect of quercetin against phthalates induced hepatotoxicity in rats.

Humans are increasingly exposed to ubiquitous phthalates (PEs), e.g. butyl benzyl phthalate (BBP), dibutyl phthalate (DBP), and di(2-ethylhexyl) phthalate (DEHP), which are widely used plasticizers in polymer products. This study was aimed to investigate the effect of phytochemical quercetin (Que) on hepatotoxicity caused by the mixture of the 3 commonly used PEs (MPEs), and further to explore the underlying mechanism. Forty male Sprague-Dawley rats were randomly divided into control group, MPEs group, and MPEs combined Que at Low-, Median-, and High-dose groups; rats in MPEs group were orally administered with 900 mg/kg/d MPEs, whereas rats in MPEs combined Que groups were simultaneously treated with 900 mg/kg/d MPEs and respectively 10, 30, and 90 mg/kg/d Que. The intervention last 30 days. Compared with control group, serum ALT, AST, LDH and AKP, and hepatic MDA, SOD, CAT and GPx were significantly increased, whereas, serum albumin and total protein were significantly decreased in MPEs group (P < 0.05); hepatic histopathological observation showed numerous inflammatory cells infiltration, hepatocyte ballooning degeneration, and numerous residual erythrocytes in the central vein in MPEs group. Western-blot analysis showed that hepatic Keap1 was downregulated, whereas Nrf2 and HO-1 were upregulated in MPEs group (P < 0.05). However, the alterations of these parameters were alleviated in MPEs combined Que at Median- and High-dose groups. The results indicated that MPEs-induced hepatic oxidative stress, and caused hepatic injuries; whereas, Que inhibited MPEs' hepatotoxicity, which might relate to Que's ability of quenching free radicals directly, and restored the regulation of Nrf2 signaling pathway.

Digital Twin-Driven Rear Axle Assembly Torque Prediction and Online Control.

During the assembly process of the rear axle, the assembly quality and assembly efficiency decrease due to the accumulation errors of rear axle assembly torque. To deal with the problem, we proposed a rear axle assembly torque online control method based on digital twin. First, the gray wolf-based optimization variational modal decomposition and long short-term memory network (GWO-VMD-LSTM) algorithm was raised to predict the assembly torque of the rear axle, which solves the shortcomings of unpredictable non-stationarity and nonlinear assembly torque, and the prediction accuracy reaches 99.49% according to the experimental results. Next, the evaluation indexes of support vector machine (SVM), recurrent neural network (RNN), LSTM, and SVM, RNN, and LSTM based on gray wolf optimized variational modal decomposition (GWO-VMD) were compared, and the performance of the GWO-VMD-LSTM is the best. For the purpose of solving the insufficient information interaction capability problem of the assembly line, we developed a digital twin system for the rear axle assembly line to realize the visualization and monitoring of the assembly process. Finally, the assembly torque prediction model is coupled with the digital twin system to realize real-time prediction and online control of assembly torque, and the experimental testing manifests that the response time of the system is about 1 s. Consequently, the digital twin-based rear axle assembly torque prediction and online control method can significantly improve the assembly quality and assembly efficiency, which is of great significance to promote the construction of intelligent production line.

An Improved Entropy-Weighted Topsis Method for Decision-Level Fusion Evaluation System of Multi-Source Data.

Due to the rapid development of industrial internet technology, the traditional manufacturing industry is in urgent need of digital transformation, and one of the key technologies to achieve this is multi-source data fusion. For this problem, this paper proposes an improved entropy-weighted topsis method for a multi-source data fusion evaluation system. It adds a fusion evaluation system based on the decision-level fusion algorithm and proposes a dynamic fusion strategy. The fusion evaluation system effectively solves the problem of data scale inconsistency among multi-source data, which leads to difficulties in fusing models and low fusion accuracy, and obtains optimal fusion results. The paper then verifies the effectiveness of the fusion evaluation system through experiments on the multilayer feature fusion of single-source data and the decision-level fusion of multi-source data, respectively. The results of this paper can be used in intelligent production and assembly plants in the discrete industry and provide the corresponding management and decision support with a certain practical value.

Characteristics of nitrogen deposition research within grassland ecosystems globally and its insight from grassland microbial community changes in China.

As global change continues to intensify, the mode and rate of nitrogen input from the atmosphere to grassland ecosystems had changed dramatically. Firstly, we conducted a systematic analysis of the literature on the topic of nitrogen deposition impacts over the past 30 years using a bibliometric analysis. A systematic review of the global research status, publication patterns, research hotspots and important literature. We found a large number of publications in the Chinese region, and mainly focuses on the field of microorganisms. Secondly, we used a meta-analysis to focus on microbial changes using the Chinese grassland ecosystem as an example. The results show that the research on nitrogen deposition in grassland ecosystems shows an exponential development trend, and the authors and research institutions of the publications are mainly concentrated in China, North America, and Western Europe. The keyword clustering results showed 11 important themes labeled climate change, elevated CO2, species richness and diversity, etc. in these studies. The burst keyword analysis indicated that temperature sensitivity, microbial communities, etc. are the key research directions. The results of the meta-analysis found that nitrogen addition decreased soil microbial diversity, and different ecosystems may respond differently. Treatment time, nitrogen addition rate, external environmental conditions, and pH had major effects on microbial alpha diversity and biomass. The loss of microbial diversity and the reduction of biomass with nitrogen fertilizer addition will alter ecosystem functioning, with dramatic impacts on global climate change. The results of the study will help researchers to further understand the subject and have a deep understanding of research hotspots, which are of great value to future scientific research.

Photosynthetic regulation in fluctuating light under combined stresses of high temperature and dehydration in three contrasting mosses.

Photosynthesis regulation is fundamental for the response to environmental dynamics, especially for bryophytes during their adaptation to terrestrial life. Alternative electron flow mediated by flavodiiron proteins (FLV) and cyclic electron flow (CEF) around photosystem I (PSI) play seminal roles in the response to abiotic stresses in mosses; nevertheless, their correlation and relative contribution to photoprotection of mosses exposed to combined stresses remain unclear. In the present study, the photosynthetic performance and recovery capacity of three moss species from different growth habitats were examined during heat and dehydration with fluctuating light. Our results showed that dehydration at 22 °C for 24 h caused little photodamage, and most of the parameters recovered to their original values after rehydration. In contrast, dehydration at 38 °C caused drastic injuries, especially to PSII, which was mainly caused by the inactivation of non-photochemical quenching (NPQ). Dehydration also induced a high accumulation of O2- and H2O2. A consistently higher CEF as well as a positive correlation between CEF and FLV was observed in resistant R. japonicum, implying CEF played a more important protective role for R. japonicum. In H. plumaeforme and P. cuspidatum, the positive relationship under mild stress switched to negative when stress became severe. Therefore, FLV pathway was sensitive to environmental fluctuations and maybe less efficient than CEF thus, readily to be lost during land colonization and evolution in angiosperms. Our work provides insights into the coordination of various pathways to fine-tune photosynthetic protection and can be used as a basis for species screening and development of breeding strategies for degraded ecosystem restoration with pioneering mosses.

Improved three-dimensional reconstruction algorithm from a multifocus microscopic image sequence based on a nonsubsampled wavelet transform.

In the multifocus microscopic image measurement method, the distortion of the three-dimensional (3D) reconstruction model has always been an important factor affecting the measurement result. In spatial domains, the focus measure algorithm is based on the gradient change of the pixel point to determine the degree of focus of the pixel. So it will be difficult to accurately extract the focus of the pixel in the areas where color difference is not obvious, resulting in 3D model distortion. According to the optical principle, the high-frequency coefficients of the clear image are larger than the high-frequency coefficients of the blurred image. Based on this characteristic, this paper proposes a new multifocus microscopic image 3D reconstruction algorithm using a nonsubsampled wavelet transform (NSWT). The NSWT does not consider the downsampling in wavelet decomposition and has translational invariance. Therefore, the wavelet transform value of each pixel can be calculated in the image, so the high-frequency coefficient of each pixel can be obtained; then the convolution calculation is performed on the high-frequency coefficients of the pixel points in the fixed window as the focus measure value of the pixel point. Compared with the traditional algorithm, the algorithm proposed in this paper can show better unimodal and antinoise performance on the focusing measure curve. In this paper, the reconstruction of the experimental object is Alicona standard block triangular and semicylindrical. The proposed algorithm and the traditional algorithm for comprehensive measure use the root mean square error, peak signal to noise ratio, and correlation coefficient as the measure index. The experimental results and comparative analysis prove the correctness of the proposed algorithm and enable more accurate reconstruction of 3D models based on multifocus microscopic images.