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【Objective】The study was carried out to evaluate the feasibility and efficacy of feeds produced by fermented kitchen waste to spotted-brown chickens as a partial replacement of basal diets, with a view to providing basic data for the resource utilization and promotion of kitchen waste feed.【Method】One-day-old spotted-brown chickens were selected, and 0% (CK), 10% and 20% fermented kitchen waste feeds (FKWF) were added to the basal diet, and the amount of basal diet was reduced accordingly. At the 63rd day of the test period, the growth performance, slaughter performance and nutritional performance indexes such as crude protein, crude fat, calcium, phosphorus, zinc, selenium, inosinic acid and amino acids in chicken meat were measured.【Result】The results of broiler growth performance showed that the differences in feed-to-weight ratios between broilers in the 10% and 20% FKWF groups and CK were not significant, however, broilers in the 10% FKWF group had the highest weight. The results of slaughter performance showed that there were no abnormality in the skin color, muscle tissue elasticity, pH and odor of broilers of 10% and 20% FKWF groups, and the differences in organ coefficients were not significant compared with that of CK; the results of muscle nutritional performance showed that the crude protein contents of chicken meat in 10% and 20% FKWF groups increased by 7.50% and 3.42%, phosphorus contents increased significantly by 11.44% and 4.37%, and inosinic acid contents increased significantly by 7.10% and 6.00%; the fresh-flavored amino acid (FAA), sweet amino acid (SAA), essential amino acid (EAA), and total amino acid (TAA) were significantly higher in 10% and 20% FKWF groups than those in CK; aspartic acid, glycine, alanine, valine, isoleucine, leucine, tyrosine, phenylalanine, histidine and cysteine were significantly increased by 4.49%to 12.79% compared with CK; aspartic acid, valine, isoleucine, and leucine in the 20% FKWF group were significantly increased by 3.37% and 5.74%, compared with CK.【Conclusion】It is feasible and effective to replace the basal diet by a certain proportion of biofeed produced by fermented kitchen waste to feed broilers, which can save feed costs and improve economic benefits.

The main challenges in the field of fault diagnosis of robot arms lie in the difficulties of acquiring fault data and ensuring model applicability. For a fault robot arm, the trained models typically only perform well on test data and cannot be effectively applied in practical scenarios. As a result, the time cost is very much to construct adequate fault datasets. The paper proposes a dynamic simulation method for obtaining fault data to address these issues. The motion feature of the arm with joint faults is replicated by the simulation software, thereby obtaining vibration signals in the fault mode as samples. Additionally, under the main framework of Deep Learning (DL) with an end-to-end feature extraction capability, a Stacked Continuous Wavelet Transform (SCWT) method is designed to visualize timing signals graphically based on the traditional wavelet transform. Furthermore, to enhance traditional DL performance, a dual-channel architecture for data fusion within DL is designed to enrich the feature space and improve fault-distinguishing ability. Lastly, a Domain Discriminator $G_{d}$ is designed to identify the upper bounds for differences between spatial distributions of simulated and actual fault data. By the domain discriminator, the feature distribution of target and source data is aligned, facilitating the transfer application of the simulation-trained diagnostic model on the actual fault. The proposed method is tested and evaluated using a self-constructed experimental data set. The results substantiate its effectiveness and superiority.

The speed regulation technology for energy conservation of pump and fan systems occupies an important position in industrial field. The paper focuses on the rapid development and research significance of speed regulation technology for energy conservation based on different permanent magnet adjustable speed drives (PMASDs). The development history and speed regulation scheme for energy conservation are introduced step by step. The features of theoretical model based on magnetic vector potential and equivalent magnetic circuit methods are presented and studied in the paper, which is benefit to select a suitable method for a specific drive. Several optimization methods of design parameters of PMASDs are given in the paper. The structure and operating principle of some new speed regulation scheme are described, and their advantages, disadvantages and feasibility of engineering application are analyzed. Finally, the proposed speed regulation technologies for energy conservation are summarized and classified from the aspects of magnetic circuit structure, permanent magnet rotor structure, conductor rotor structure, and the slip power conversion scheme. In a conclusion, the power-fed PMASD will be the future of energy conservation technology for the high-efficiency and low-cost large pump and fan systems.

Motor unit (MU) discharge information obtained via electromyogram (EMG) decomposition can be used to decode dexterous multi-finger movement intention for neural-machine interfaces (NMI). However, the variation of the motor unit action potential (MUAP) shape resulted from forearm rotation leads to the decreased performance of EMG decomposition, especially under the real-time condition and then the degradation of motion decoding accuracy. The object of this study was to develop a method to realize the accurate extraction of MU discharge information across forearm pronated/supinated positions in the real-time condition for dexterous multi-finger force prediction. The FastICA-based EMG decomposition technique was used and the proposed method obtained multiple separation vectors for each MU at different forearm positions in the initialization phase. Under the real-time condition, the MU discharge information was extracted adaptively using the separation vector extracted at the nearest forearm position. As comparison, the previous method that utilized a single constant separation vector to extract MU discharges across forearm positions and the conventional method that utilized the EMG amplitude information were also performed. The results showed that the proposed method obtained a significantly better performance compared with the other two methods, manifested in a larger coefficient of determination ( ${R}^{{2}}\text {)}$ and a smaller root mean squared error (RMSE) between the predicted and recorded force. Our results demonstrated the feasibility and the effectiveness of the proposed method to extract MU discharge information during forearm rotation for dexterous force prediction under the real-time conditions. Further development of the proposed method could potentially promote the application of the EMG decomposition technique for continuous dexterous motion decoding in a realistic NMI application scenario.

Decoding continuous human motion from surface electromyography (sEMG) in advance is crucial for improving the intelligence of exoskeleton robots. However, incomplete sEMG signals are prevalent on account of unstable data transmission, sensor malfunction, and electrode sheet detachment. These non-ideal factors severely compromise the accuracy of continuous motion recognition and the reliability of clinical applications. To tackle this challenge, this paper develops a multi-task parallel learning framework for continuous motion estimation with incomplete sEMG signals. Concretely, a residual network is incorporated into a recurrent neural network to integrate the information flow of hidden states and reconstruct random and consecutive missing sEMG signals. The attention mechanism is applied for redistributing the distribution of weights. A jointly optimized loss function is devised to enable training the model for simultaneously dealing with signal anomalies/absences and multi-joint continuous motion estimation. The proposed model is implemented for estimating hip, knee, and ankle joint angles of physically competent individuals and patients during diverse exercises. Experimental results indicate that the estimation root-mean-square errors with 60% missing sEMG signals steadily converges to below 5 degrees. Even with multi-channel electrode sheet shedding, our model still demonstrates cutting-edge estimation performance, errors only marginally increase 1 degree.

Highlights The LiNO3-implanted electroactive β phase polyvinylidene fluoride-co-hexafluoropropylene was built as an artificial solid electrolyte interphase layer for dendrite suppression. The electronegatively charged polymer layer can capture Li ion on its surface to form Li-ion charged channels and recompense the ionic flux of electrolytes via continuous supply of Li ion. The modified Li anode achieved a long cycle life over 2000 h under ultrahigh Li utilization of 50% in symmetric cell and worked in full cell for 100 cycles at harsh condition of extremely low N/P of 0.83.

In recent years, convolutional neural network (CNN) has achieved great success in the field of network security protection. With the popularization of smart terminals and the gradual increase of power grid informatization and digitization, the protection of power monitoring systems from various cybersecurity threads is a current scientific problem that needs to be solved urgently. To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. The examples under the public dataset containing 8 kinds of malware show that the proposed method is better than the traditional algorithmic model, and can accurately and efficiently achieve malware detection with strong generalization ability.

Abstract Background Although multiple measures of blood pressure variability (BPV) have been proposed, whether they are better than mean blood pressure in predicting target organs is unclear. We aimed to determine the relationship between short term BPV and target organ injury. Methods This study was a retrospective study, and 635 inpatients in the Department of Cardiology from 2015 to 2020 were selected. We divided participants into four groups on the basis of the quartiles of BPV. One‐way analysis of variance was used to compare the differences between the groups, and linear regression was used to analyze the relationship between BPV and target organ damage. Results The average age of 635 patients was 74.36 ± 6.50 years old. Among them, 354 of 627 patients had diminished renal function (56.5%), 221of 604 patients had associated left ventricular hypertrophy (36.6%), and 227 of 231 patients had carotid plaque formation (98.3%). The baseline data indicated significant differences in fasting glucose, total cholesterol, low‐density lipoprotein, creatinine, glomerular filtration rate, sex, calcium channel blocker use, and the rate of diminished renal function. Multiple linear regression analysis showed that BPV was negatively correlated with renal injury (creatinine: r = 0.306, p

Abstract In bioethanol production, the main by-product, 5-hydroxymethylfurfural (HMF), significantly hinders microbial fermentation. Therefore, it is crucial to explore genes related to HMF tolerance in Saccharomyces cerevisiae for enhancing the tolerance of ethanol fermentation strains. A comprehensive analysis was conducted using genome-wide deletion library scanning and SGAtools, resulting in the identification of 294 genes associated with HMF tolerance in S. cerevisiae. Further KEGG and GO enrichment analysis revealed the involvement of genes OCA1 and SIW14 in the protein phosphorylation pathway, underscoring their role in HMF tolerance. Spot test validation and subcellular structure observation demonstrated that, following a 3-h treatment with 60 mM HMF, the SIW14 gene knockout strain exhibited a 12.68% increase in cells with abnormal endoplasmic reticulum (ER) and a 22.41% increase in the accumulation of reactive oxygen species compared to the BY4741 strain. These findings indicate that the SIW14 gene contributes to the protection of the ER structure within the cell and facilitates the clearance of reactive oxygen species, thereby confirming its significance as a key gene for HMF tolerance in S. cerevisiae.

Abstract The peak regulation capacity of gas‐fired power plants has always been an important flexibility resource of the power grid. Under the guidance of carbon emission reduction, the coal power units are gradually shut down, making the role of gas‐fired power plants more important. However, in practice, gas‐fired power plants often fail to show satisfactory flexibility. The main reasons are as follows: (1) Part of the capacity mechanism fails to effectively encourage gas‐fired power plants to provide reliable flexibility and (2) the unreliability of fuel supply for gas‐fired power plants. Aiming at these problems, the current capacity mechanism in different countries is first summarised and the applicability of the capacity mechanism for gas‐fired power plants under the government regulation and market‐oriented environment is analysed, respectively. Then, the characteristics of power dispatching and gas dispatching are analysed to explore the internal reasons for the unreliable fuel supply in gas‐fired power plants. Based on the above analysis, the gas‐electric coordination mechanism adapted to different development stages is proposed to solve the problem that the flexibility of gas‐fired power plants cannot be guaranteed. In summary, through the research of this study, it is found that the main reason for the limited flexibility of gas‐fired power plants is the lack of coordination among multiple entities belonging to different energy systems, such as electricity and gas. The cooperation mechanism proposed is an attempt to realise the cooperation between the electric system and the gas system, which provides the reference for closer collaboration among multiple energy systems in the future.

Abstract Water from hydraulic technology affects the desorption of gas from coal seams. Gas desorption behavior is critical information for gas control in coal mines. In this study, a designed coal seam water injection simulation experimental device was utilized to conduct dynamic water injection experiments on coal samples at different adsorption equilibrium pressures, analyzing the gas desorption law under dynamic water injection, as well as the role of water replacement, water imbibition and water blockage in gas desorption. The results showed that water altered the gas desorption rate in coal, causing fluctuating attenuation of the desorption rate of a water-injected coal sample (WCS). Under the same adsorption equilibrium pressure, the relationship between the desorption rate of the WCS and the non-water-injected coal samples (NCS) underwent a transition in desorption time. In contrast to the NCS desorption curves, the WCS desorption curves lacked a rapid growth phase and exhibited only a slow growth phase and a stopping phase. Water imbibition and water replacement promoted the desorption of gas in the non-wet area during the water injection process, while it inhibited the desorption of gas in the wet area. Under the effects of water imbibition, water blockage, and water replacement, the discharge rate of WCS is greater than the desorption rate of NCS, indicating that water injection increases the total amount of gas desorption. The study results have significant implications for gas extraction and the prevention and control of coal and gas outbursts.

Abstract When a transformable B2 precipitate is embedded in an amorphous matrix, it is often experimentally observed that the crystalline-amorphous interface not only serves as an initiation site for the martensitic transformation due to local stress concentrations, but also as an inhibitor to stabilize the transformation, the latter being attributed to the “confinement effect” exerted by the amorphous matrix, according to the Eshelby solution. These two seemingly incongruous factors are examined in this study using molecular dynamics simulations from an atomic interaction perspective. An innate strain gradient in the vicinity of the crystalline-amorphous interface is identified. The actual interface, the compressive/dilatative transition, and the interfacial maximum strain are investigated to differentiate from the conventional “interface” located within a distance of a few nanometers. Our innate interfacial elastic strain field model is applicable for the design of materials with a higher degree of martensitic transformation and controllable stress concentration, even in cryogenic environments.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is characterized by rapid progression and poor prognosis. Understanding the genetic mechanisms that affect cancer properties and reprogram tumor immune microenvironment will develop new strategies to maximize the benefits for cancer therapies. Methods Gene signatures and biological processes associated with advanced cancer and unfavorable outcome were profiled using bulk RNA sequencing and spatial transcriptome sequencing, Caprin-1 was identified as an oncogenesis to expedite pancreatic cancer growth by activating autophagy. The mechanism of Caprin-1 inducing autophagy activation was further explored in vitro and in vivo. In addition, higher level of Caprin-1 was found to manipulate immune responses and inflammatory-related pathways. The immune profiles associated with increased levels of Caprin-1 were identified in human PDAC samples. The roles of CD4+T cells, CD8+T cells and tumor associated macrophages (TAMs) on clinical outcomes prediction were investigated. Results Caprin-1 was significantly upregulated in advanced PDAC and correlated with poor prognosis. Caprin-1 interacted with both ULK1 and STK38, and manipulated ULK1 phosphorylation which activated autophagy and exerted pro-tumorigenic phenotypes. Additionally, the infiltrated CD4+T cells and tumor associated macrophages (TAMs) were increased in Caprin-1High tissues. The extensive CD4+T cells determined poor clinical outcome in Caprin-1high patients, arguing that highly expressed Caprin-1 may assist cancer cells to escape from immune surveillance. Conclusions Our findings establish causal links between the upregulated expression of Caprin-1 and autophagy activation, which may manipulate immune responses in PDAC development. Our study provides insights into considering Caprin-1 as potential therapeutic target for PDAC treatment.

Abstract Intensifying droughts under climatic warming are of widespread concern owing to their devastating impacts on water resources, societies and ecosystems. However, the effects of exogeneous drivers on regional droughts remain poorly understood. Using the Lagrangian method, atmospheric reanalysis data and climate projections from the Coupled Model Inter-comparison Project phase 6 (CMIP6), we show how exogenous precipitation minus evaporation (PME) deficit drives droughts across China. More specifically, we demonstrate that four distinct trajectories of such exogenous PME deficit fuel regional droughts. Three of these trajectories relate to oceanic PME deficit originating from the North Atlantic, eastern Bering Sea and Indian Ocean, and one trajectory characterizes exogenous terrestrial PME deficit from the Siberian Plateau. We show that during 1980–2020, droughts induced by exogenous PME deficit account for 45% of all droughts that occurred in China’s coastal region, and for 7% of all droughts in the northwestern regions. Under climate scenario SSP245 (SSP585), limiting warming to 1.5 °C compared to 2 °C above pre-industrial levels could avoid 60% (84%) of exogenous drought exposure. This would in turn reduce population exposure by 40% (49%), and economic exposure by 73% (66%). Our study unravels how exogenous PME deficit drives droughts in China, underscoring the role that external drivers have on regional droughts and associated future prediction.

Abstract Urban economic development, congestion relief, and traffic efficiency are all greatly impacted by the thoughtful planning of urban metro station layout. with the urban area of Lanzhou as an example, the suitability of the station locations of the built metro stations of the rail transit lines 1 and 2 in the study area have been evaluated using multi-source heterogeneous spatial data through data collection, feature matrix construction, the use of random forest and K-fold cross-validation, among other methods. The average Gini reduction value was used to examine the contribution rate of each feature indicator based on the examination of model truthfulness. According to the study's findings: (1) K-fold cross-validation was applied to test the random forest model that was built using the built metro stations and particular factors. The average accuracy of the tests and out-of-bag data (OOB) of tenfold cross-validation were 89.62% and 91.285%, respectively. Additionally, the AUC area under the ROC curve was 0.9823, indicating that this time, from the perspective of the natural environment, traffic location, and social factors The 19 elements selected from the views of the urban function structure, social economics, and natural environment are closely associated to the locations of the metro station in the research region, and the prediction the findings are more reliable; (2) It becomes apparent that more than half of the built station sites display excellent agreement with the predicted sites in terms of geographical location by superimposing the built metro station sites with the prediction results and tally up their cumulative prediction probability values within the 300 m buffering zone; (3) Based on the contribution rate of each indicator to the model, transport facilities, companies, population density, night lighting, science, education and culture, residential communities, and road network density are identified as the primary influential factors, each accounting for over 6.6%. Subsequently, land use, elevation, and slope are found to have relatively lower contributions. The results of the research provided important information for the local metro's best location selection and planning.

China is not considered as an endemic area of Rickettsia conorii, so there is no routine clinical way to diagnose this infection. This study aims to determine whether 2 febrile patients who had a tick bite in East China were indeed infected with R. conorii. The citrate synthase gene (gltA) was amplified with universal rickettsial primers by real-time fluorescent PCR from the patients’ blood samples. Nested PCR was used to amplify the outer membrane protein A gene (ompA) for positive specimens. PCR products were further identified and analyzed through nucleic acid sequencing. Positive amplification of the gltA and ompA genes was found in both patients. The nucleotide sequences (303 bp) of the ompA gene of the 2 patients had high homology (99%) with the R. conorii Indian tick typhus strain in GenBank. A more than 4-fold increase in IgG against R. conorii provided supportive evidence of SFG Rickettsia infection. And the rapid recovery after doxycycline treatment also supported a rickettsial cause for the disease. Physicians in East China should be aware of human infections with R. conorii. PCR-based diagnostic methods offer a rapid and precise way to diagnose rickettsiosis, improving patient identification and management.

Abstract Non‐invasive, real‐time, dynamic, and quantitative molecular imaging has been developed to facilitate disease diagnosis, drug development, and pathological analysis at the molecular level. Qualitative and quantitative analysis and imaging of physiological processes at the molecular level can be achieved with advanced molecular imaging by employing imaging contrast agents in combination with traditional imaging modalities, such as optical imaging, ultrasound imaging, magnetic resonance imaging, single‐photon emission computed tomography, and positron emission tomography. With the aid of molecular imaging, absorption, distribution, metabolism, excretion, and other processes of drugs in various animals can be monitored quantitatively, and in vivo pharmacokinetics and pharmacodynamics can be simulated before clinical trials, which significantly shorten the period for drug development and reduce the number of animals participating in various tests. Here, the role of molecular imaging in drug target validation, drug screening, drug sensitivity analysis, pharmacokinetics research, drug efficacy evaluation, and other processes of chemical and biological drug research and development is summarized. Molecular imaging has become a powerful and effective tool in the research and development of various drugs for the treatment of a variety of diseases. Advanced molecular imaging can provide important support for disease and drug research, which will accelerate drug discovery and development.

Osteoarthritis (OA) is the most common disabling joint disease with no effective disease modifying drugs. Extracellular vesicles released by several types of mesenchymal stem cells could promote cartilage repair and ameliorate OA pathology in animal models, representing a novel therapeutic strategy. In this study, we demonstrated that extracellular vesicles derived from human umbilical cord mesenchymal stem cells (hUC-EVs) could maintain chondrocyte homeostasis and alleviate OA, and further revealed a novel molecular mechanism of this therapeutic effect. miR-223, which could directly bind with the 3′UTR of NLRP3 mRNA, was found to be a key miRNA for hUC-EVs to exert beneficial effects on inflammation inhibiting and cartilage protecting. For enhancing the effect on mitigating osteoarthritis, exogenous miR-223 was loaded into hUC-EVs by electroporation, and a collagen II-targeting peptide (WYRGRL) was modified onto the surface of hUC-EVs by genetic engineering to achieve a more targeted and efficient RNA delivery to the cartilage. The dual-engineered EVs showed a maximal effect on inhibiting the NLRP3 inflammasome activation and chondrocyte pyroptosis, and offered excellent results for the treatment of OA. This study provides a novel theoretical basis and a promising therapeutic strategy for the application of engineered extracellular vesicles in OA treatment.

Abstract Background This study aimed to apply the backpropagation neural network (BPNN) to develop a model for predicting multidrug-resistant organism (MDRO) infection in critically ill patients. Methods This study collected patient information admitted to the intensive care unit (ICU) of the Affiliated Hospital of Qingdao University from August 2021 to January 2022. All patients enrolled were divided randomly into a training set (80%) and a test set (20%). The least absolute shrinkage and selection operator and stepwise regression analysis were used to determine the independent risk factors for MDRO infection. A BPNN model was constructed based on these factors. Then, we externally validated this model in patients from May 2022 to July 2022 over the same center. The model performance was evaluated by the calibration curve, the area under the curve (AUC), sensitivity, specificity, and accuracy. Results In the primary cohort, 688 patients were enrolled, including 109 (15.84%) MDRO infection patients. Risk factors for MDRO infection, as determined by the primary cohort, included length of hospitalization, length of ICU stay, long-term bed rest, antibiotics use before ICU, acute physiology and chronic health evaluation II, invasive operation before ICU, quantity of antibiotics, chronic lung disease, and hypoproteinemia. There were 238 patients in the validation set, including 31 (13.03%) MDRO infection patients. This BPNN model yielded good calibration. The AUC of the training set, the test set and the validation set were 0.889 (95% CI 0.852–0.925), 0.919 (95% CI 0.856–0.983), and 0.811 (95% CI 0.731–0.891), respectively. Conclusions This study confirmed nine independent risk factors for MDRO infection. The BPNN model performed well and was potentially used to predict MDRO infection in ICU patients.

Abstract Background There is a lack of epidemiological data on depressive morbidity in children and adolescents in rural China. This study determines the frequency and correlates of depression among children and adolescents to offer useful insights for family education and government policy-making in rural China. Methods A cross-sectional online survey was conducted between April 20 to May 10, 2022. Depression was assessed using the Center for Epidemiologic Studies Depression Scale (CES-D), and the correlative factors of depression were analyzed. Results In this study, 23,180 children and adolescents were enrolled (median (range) age: 12 (9–18) years); of them, 8,261 (35.6%) suffered from depression with a CES-D score of > 15. The onset of depression was significantly related to age, grade, gender, parental absence, attending key schools or classes, presence of moderate or severe internet addiction (IA), school record, social relationships, parental occupation, and education status. Furthermore, female gender (OR = 1.175; 95% CI: 1.108–1.247; p

Abstract Background The increasing number of pertussis cases worldwide over the past two decades has challenged healthcare workers, and the role of environmental factors and climate change cannot be ignored. The incidence of pertussis has increased dramatically in mainland China since 2015, developing into a serious public health problem. The association of meteorological factors on pertussis has attracted attention, but few studies have examined the impact of air pollutants on this respiratory disease. Methods In this study, we analyzed the relationship between outdoor air pollution and the pertussis incidence. The study period was from January 2013 to December 2018, and monthly air pollutant data and the monthly incidence of patients in 31 provinces of China were collected. Distributed lag nonlinear model (DLNM) analysis was used to estimate the associations between six air pollutants and monthly pertussis incidence in China. Results We found a correlation between elevated pertussis incidence and short-term high monthly CO2 and O3 exposure, with a 10 μg/m3 increase in NO2 and O3 being significantly associated with increased pertussis incidence, with RR values of 1.78 (95% CI: 1.29-2.46) and 1.51 (95% CI: 1.16-1.97) at a lag of 0 months, respectively. Moreover, PM2.5 and SO2 also played key roles in the risk of pertussis surged. These associations remain significant after adjusting for long-term trend, seasonality and collinearity. Conclusions Overall, these data reinforce the evidence of a link between incidence and climate identified in regional and local studies. These findings also further support the hypothesis that air pollution is responsible for the global resurgence of pertussis. Based on this we suggest that public health workers should be encouraged to consider the risks of the environment when focusing on pertussis prevention and control.

Abstract Background This article summarizes the treatment experience for congenital complete atrioventricular block (CCAVB) in newborns and infants, and discusses the necessity and feasibility of treating CCAVB with permanent pacemaker implantation in this population. Methods In this study, the clinical data and follow-up results of nine children admitted at our center with CCAVB from January 2005 to March 2023 were retrospectively analyzed. Among them, two children received early implantation of permanent pacemakers (within 1 year of age), two children received non-early implantation (1 year or older), and the remaining five children received no pacemaker implantation. CCAVB diagnosis was confirmed by clinical symptoms and clinical examinations, including electrocardiography and echocardiography before surgery. After surgery, the pacing and sensing functions of the pacemaker were observed using electrocardiography, echocardiography, and pacing threshold monitoring. A comprehensive assessment of the treatment efficacy was conducted, encompassing improvements in clinical symptoms, growth and development, as well as the absence of any additional potential complications. The children who did not receive pacemaker implantation were followed up. Results Among the four children who successfully received pacemaker implantation, one child who received non-early implantation died. For the remaining three children, the threshold level, amplitude, impedance, and minute ventilation sensor function of the pacemaker were good during the follow-up period, with a heart rate at the pacing rate. The growth and development of the aforementioned patients who received pacemaker implantation demonstrated adherence to the percentile curve, and their motor and cognitive development remained unaffected. However, among the children who did not undergo pacemaker implantation, two experienced death, while three were lost to follow-up, thereby limiting the evaluation of their long-term outcomes. Conclusions Early implantation of an epicardial pacemaker at an early stage in newborns and infants diagnosed with CCAVB can significantly improve clinical symptoms without affecting their growth and development. These data are in line with current literature and suggest that early implantation of an epicardial pacemaker in newborns and infants diagnosed with CCAVB but further studies are needed.

Abstract Clear cell renal cell carcinoma (ccRCC) is a type of kidney cancer that is both common and aggressive, with a rising incidence in recent decades. Hypoxia is a key factor that plays a vital role in the tumorigenesis and metastasis of malignancy. However, the precise mechanisms of hypoxia driving ccRCC progression were not totally uncovered. Our study found that hypoxia level was elevated in ccRCC and might be an independent risk factor of prognosis in ccRCC patients. We identified a key protein PLOD2 was induced under hypoxic conditions and strongly associated with poor prognosis in ccRCC patients. When PLOD2 was depleted, the proliferation and migration of ccRCC cells were reduced in vitro and in vivo, while overexpression of PLOD2 had the opposite effect. Mechanically, the study further revealed that PLOD2 was transcriptionally activated by HIF1A, which binds to a specific promoter region of the PLOD2 gene. PLOD2 was also shown to interact with EGFR, leading to the phosphorylation of the receptor. Furthermore, PLOD2 was responsible for binding to the extracellular domain of EGFR, which ultimately activated the AKT signaling pathway, thus promoting the malignant progression of ccRCC. Treatment with the PLOD2 inhibitor Minoxidil significantly suppressed ccRCC progression by inactivating the EGFR/AKT signaling axis. In summary, the findings of this study shed light on the molecular mechanisms behind PLOD2 expression in ccRCC and suggest that it may serve as a potential predictor and therapeutic target for the clinical prognosis and treatment of ccRCC.

Abstract Background Genomic sequencing reads compressors are essential for balancing high-throughput sequencing short reads generation speed, large-scale genomic data sharing, and infrastructure storage expenditure. However, most existing short reads compressors rarely utilize big-memory systems and duplicative information between diverse sequencing files to achieve a higher compression ratio for conserving reads data storage space. Results We employ compression ratio as the optimization objective and propose a large-scale genomic sequencing short reads data compression optimizer, named PMFFRC, through novelty memory modeling and redundant reads clustering technologies. By cascading PMFFRC, in 982 GB fastq format sequencing data, with 274 GB and 3.3 billion short reads, the state-of-the-art and reference-free compressors HARC, SPRING, Mstcom, and FastqCLS achieve 77.89%, 77.56%, 73.51%, and 29.36% average maximum compression ratio gains, respectively. PMFFRC saves 39.41%, 41.62%, 40.99%, and 20.19% of storage space sizes compared with the four unoptimized compressors. Conclusions PMFFRC rational usage big-memory of compression server, effectively saving the sequencing reads data storage space sizes, which relieves the basic storage facilities costs and community sharing transmitting overhead. Our work furnishes a novel solution for improving sequencing reads compression and saving storage space. The proposed PMFFRC algorithm is packaged in a same-name Linux toolkit, available un-limited at https://github.com/fahaihi/PMFFRC .

Psoriasis is a common inflammatory skin disease, in which epidermal keratinocytes play a vital role in its pathogenesis by acting both as the responder and as the accelerator to the cutaneous psoriatic immune response. Advanced glycation end products (AGEs) are a class of proinflammatory metabolites that are commonly accumulating in cardiometabolic disorders. Recent studies have also observed the increased level of AGEs in the serum and skin of psoriasis patients, but the role of AGEs in psoriatic inflammation has not been well investigated. In the present study, we initially detected abnormal accumulation of AGEs in epidermal keratinocytes of psoriatic lesions collected from psoriasis patients. Furthermore, AGEs promoted the proliferation of keratinocytes via upregulated Keratin 17 (K17)-mediated p27KIP1 inhibition followed by accelerated cell cycle progression. More importantly, AGEs facilitated the production of interleukin-36 alpha (IL-36α) in keratinocytes, which could enhance T helper 17 (Th17) immune response. In addition, the induction of both K17 and IL-36α by AGEs in keratinocytes was dependent on the activation of signal transducer and activator of transcription 1/3 (STAT1/3) signaling pathways. At last, the effects of AGEs on keratinocytes were mediated by the receptor for AGEs (RAGE). Taken together, these findings support that AGEs potentiate the innate immune function of keratinocytes, which contributes to the formation of psoriatic inflammation. Our study implicates AGEs as a potential pathogenic link between psoriasis and cardiometabolic comorbidities.

Abstract Residual stress engineering is widely used in the design of new advanced lightweight materials. For metallic glasses, attention has been given to structural changes and rejuvenation processes. High-energy scanning X-ray diffraction strain mapping reveals large elastic fluctuations in notched metallic glasses after deformation under triaxial compression. Microindentation hardness mapping hints at a competing hardening–softening mechanism after compression and reveals the complementary effects of stress and structure modulation. Transmission electron microscopy proves that structure modulation and elastic heterogeneity distribution under room temperature deformation are related to shear band formation. Molecular dynamics simulations provide an atomistic understanding of the confined deformation mechanism in notched metallic glasses and the related fluctuations in the elastic and plastic strains. Thus, future focus should be given to stress modulation and elastic heterogeneity, which, together with structure modulation, may allow the design of metallic glasses with enhanced ductility and strain-hardening ability.

As a social-interactional positive behavior, the flow of compassion (i.e., self-compassion, compassion for others, and compassion from others), which refers to sensitivity to suffering in self and others with a commitment to try to alleviate and prevent it, has yet to be investigated in a highly social-interactional context such as foreign language learning classrooms. Thus, the present study adopted an ecological perspective within Bronfenbrenner’s (1979, 1993) analytic nested ecosystems model to explore how the flow of compassion is rooted in such a context. Sixteen Iranian English as a foreign language learners took part in the current study, and data were collected through semi-structured interviews. Employing the framework of the nested ecosystems model, we identified both influential individual and environmental factors underlying the flow of compassion among the participants. The flow of compassion proved to be influenced differently at different ecosystemic levels by individual and environmental factors. At the individual level, negative and positive emotions, fears, non-judgmental attitudes, intimacy, well-being, improvement, motivation, and action were found as influential factors in emerging the flow of compassion. At the contextual level, the identified influential factors included past experiences outside of the classroom, extracurricular activities, institution policy and criteria, cultural and social values, as well as the use of technology and the internet. Limitations and implications of the present study are also discussed.

In multi-vessel collision avoidance decision-making, the collision between merchant and fishing vessels is a significant challenge. This paper proposes a fuzzy fusion method for making avoidance decisions under the influence of the navigation environment. First, C-means clustering was used to collect and analyze Automatic Identification System (AIS) data from fishing vessels. On this basis, the environment collision risk was determined using fuzzy reasoning. Second, the basic collision risk is obtained by calculating the DCPA and TCPA, and the integrated Collision Risk Index (CRI) is concluded by fuzzy logic through basic collision risk and the environment collision risk. The similar cases are extracted from the fuzzy case database, and collision avoidance decisions for merchant vessels are formulated following fuzzy adjustments. Finally, to validate the method, data from Chengshantou coastal waters is employed for verification. The results show that it can provide theoretical guidance and practical value for merchant vessels in making collision avoidance decisions.

This article analyzes the factors causing the precision error of the robot joint module, such as gear meshing disturbance, output elastic deformation, and load mutation. An improved active disturbance rejection control (ADRC) algorithm is proposed to overcome the uncertainty of nonlinear factors and variables of this research topic. The output precision loss of the joint module is introduced as a new input variable of ADRC, combined with the input variable of torque current of the joint module. The extended state observer is redesigned, and the online estimation of disturbance is realized. According to the disturbance estimation results, the current loop algorithm of permanent magnet synchronous motors is improved to compensate the torque disturbance of the robot joint module. The experimental results show that the improved ADRC algorithm can obviously suppress the disturbance of the joint module, weaken the meshing error and torque output deformation of the harmonic reducer gear, and improve the control accuracy of the joint module.

Lateolabrax maculatus iridovirus (LMIV) is a variant strain of red sea bream iridovirus (RSIV), causing serious economic losses in aquaculture. Claudins (CLDNs) are major components of tight junctions (TJs) forming an important line of defense against pathogens. Our pilot miRNA-mRNA joint analysis indicated the degradation of CLDN3, as well as its interaction with miR-181a during LMIV infection. To elucidate the miR-181a/CLDN3/LMIV interactions, in vitro assays were carried out on LMB-L cells. We first confirmed that LMIV infection could decrease the expression of CLDN3, accompanied by the enhancement of permeability, suggesting the dysfunction of TJs. Contrary to the inhibition of CLDN3, the activation of miR-181a was proved, presenting a negative correlation between miR-181a and CLDN3 (Pearson r = −0.773 and p < 0.01). In addition, the influence of CLDN3 on LMIV replication was analyzed by knockdown and over-expression of CLDN3. When CLDN3 was silenced in LMB-L cells with siCLDN3-623 at 9 days post transfection (dpt), LMIV copies and titers were significantly up-regulated by 1.59-fold and 13.87-fold, respectively. By contrast, LMIV replication in LMB-L cells was reduced by 60% and 71%, post transfection with pcDNA3.1-CLDN3 over-expressed plasmid at 6 dpt and 9 dpt, respectively. Ultimately, the regulatory relationship between miR-181a and CLDN3 was further validated by dual luciferase reporter assays. Taking into account the above-described results, we proposed a “miR-181a/CLDN3/LMIV” regulatory relationship. This study provides a new insight for understanding the mechanism of LMIV replication.

Lactobacillus plantarum exhibits a wide range of beneficial physiological functions, including maintaining intestinal microbiota balance, reducing serum cholesterol, and promoting digestive health. According to the specific nutrient requirements of Lactobacillus plantarum P6, we investigated the effects of various carbon sources, nitrogen sources, trace elements, growth-promoting substances, as well as the initial pH and inoculum size on the growth of Lactobacillus plantarum P6 under fermentation conditions. The optimal growth conditions for Lactobacillus plantarum P6 were identified to facilitate high-density fermentation in small-scale fermenter production, achieving a cell concentration of 1.03 × 1011 CFU/mL. This resulted in a 2.5-fold increase in bacterial wet weight, and fermentation time was reduced to 12 h when utilizing a specific medium enriched with 0.2% sodium alginate. It is hypothesized that sodium alginate forms a protective film around the bacterial cells, promoting cell aggregation and enhancing self-coalescence, potentially triggering a bacterial community effect. These results provide a basis for the industrial-scale high-density cultivation of Lactobacillus plantarum, offering potential for enhanced biotechnological applications.

Hyperledger Fabric is one of the most popular permissioned blockchain platforms widely adopted in enterprise blockchain solutions. To optimize and fully utilize the platform, it is desired to conduct a thorough performance analysis of Hyperledger Fabric. Although numerous studies have analyzed the performance of Hyperledger Fabric, three significant limitations still exist. First, existing blockchain performance evaluation frameworks rely on fixed workload rates, which fail to accurately reflect the performance of blockchain systems in real-world application scenarios. Second, the impact of extending the breadth and depth of endorsement policies on the performance of blockchain systems has yet to be adequately studied. Finally, the impact of node crashes and recoveries on blockchain system performance has yet to be comprehensively investigated. To address these limitations, we propose a framework called BlockLoader, which offers seven different distributions of load rates, including linear, single-peak, and multi-peak patterns. Next, we employ the BlockLoader framework to analyze the impact of endorsement policy breadth and depth on blockchain performance, both qualitatively and quantitatively. Additionally, we investigate the impact of dynamic node changes on performance. The experimental results demonstrate that different endorsement policies exert distinct effects on performance regarding breadth and depth scalability. In the horizontal expansion of endorsement policies, the OR endorsement policy demonstrates stable performance, fluctuating around 88 TPS, indicating that adding organizations and nodes has minimal impact. In contrast, the AND endorsement policy exhibits a declining trend in performance as the number of organizations and nodes increases, with an average decrease of 10 TPS for each additional organization. Moreover, the dynamic behaviour of nodes exerts varying impacts across these endorsement policies. Specifically, under the AND endorsement policy, dynamic changes in nodes significantly affect system performance. The TPS of the AND endorsement policy shows a notable decline, dropping from 79.6 at 100 s to 41.96 at 500 s, reflecting a reduction of approximately 47% over time. Under the OR endorsement policy, the system performance remains almost unaffected.

This paper proposes a multiplexing multi-scale features network (MMF-Network) for salient target detection to tackle the issue of incomplete detection structures when identifying salient targets across different scales. The network, based on encoder–decoder architecture, integrates a multi-scale aggregation module and a multi-scale visual interaction module. Initially, a multi-scale aggregation module is constructed, which, despite potentially introducing a small amount of noise, significantly enhances the high-level semantic and geometric information of features. Subsequently, SimAM is employed to emphasize feature information, thereby highlighting the significant target. A multi-scale visual interaction module is designed to enable compatibility between low-resolution and high-resolution feature maps, with dilated convolutions utilized to expand the receptive field of high-resolution feature maps. Finally, the proposed MMF-Network is tested on three datasets: DUTS-Te, HUK-IS, and PSCAL-S, achieving scores of 0.887, 0.811, and 0.031 in terms of its F-value SSIM and MA, respectively. The experimental results demonstrate that the MMF-Network exhibits a superior performance in salient target detection.

For the prompt planting of subsequent crops, most of China’s corn harvest must occur before full maturity, with a grain moisture content above 25%. Harvesting moist corn presents challenges due to significant grain damage during threshing. We conducted a high-speed photography observation test of moist corn threshing. It demonstrated that corn ears, when passing through the threshing cylinder, often break into pieces. Grains on divided corncobs can be threshed more easily and earlier than those on undivided ones, suggesting that pre-dividing corn ears reduces grain damage. An experiment using the Lianchuang 825 variety examined the effect of moisture content and the divided rate of corncobs (DRC) on grain damage. The results showed that as moisture content increased from 25% to 37%, grain damage to undivided ears increased from 3.75% to 37.71%. Dividing corn ears before threshing significantly reduced damage, with an eight-piece division reducing damage by approximately 70% across all moisture levels. Verification with the Jinyu 1233 variety confirmed that a higher DRC consistently reduced damage. This study provides a new approach to reducing damage in moist corn threshing and aids in the development of low-damage threshing devices.

In order to improve the magnetocaloric properties of MnNiSi-based alloys, a new type of high-entropy magnetocaloric alloy was constructed. In this work, Mn0.6Ni1−xSi0.62Fe0.4CoxGe0.38 (x = 0.4, 0.45, and 0.5) are found to exhibit magnetostructural first-order phase transitions from high-temperature Ni2In-type phases to low-temperature TiNiSi-type phases so that the alloys can achieve giant magnetocaloric effects. We investigate why chexagonal/ahexagonal (chexa/ahexa) gradually increases upon Co substitution, while phase transition temperature (Ttr) and isothermal magnetic entropy change (ΔSM) tend to gradually decrease. In particular, the x = 0.4 alloy with remarkable magnetocaloric properties is obtained by tuning Co/Ni, which shows a giant entropy change of 48.5 J∙kg−1K−1 at 309 K for 5 T and an adiabatic temperature change (ΔTad) of 8.6 K at 306.5 K. Moreover, the x = 0.55 HEA shows great hardness and compressive strength with values of 552 HV2 and 267 MPa, respectively, indicating that the mechanical properties undergo an effective enhancement. The large ΔSM and ΔTad may enable the MnNiSi-based HEAs to become a potential commercialized magnetocaloric material.

Deep-sea aquaculture can alleviate the spatial and environmental pressure of near-shore aquaculture and produce higher quality aquatic products, which is the main development direction of global aquaculture. The coastline of China is relatively flat, with aquaculture operations typically operating in sea areas with water depths of approximately 30–50 m. However, with frequent typhoons and poor sea conditions, the design of mooring system has always been a difficult problem. This paper investigated the multiple cages, considering two layouts of 1 × 4 and 2 × 2, and proposed three different mooring system design schemes. The mooring line tension of the mooring systems under the self-storage condition was compared, and it was observed whether the mooring line accumulation and the contact between the mooring line and the steel structure occurred on the leeward side. Additionally, flexible net models were compared with rigid net models to evaluate the impact of net deformation on cage movement and mooring line tension. Finally, based on the optimal mooring design, the dynamic response of the mooring system under irregular wave conditions was analyzed and studied, providing important reference for the safety and economic design of the mooring system of multiple fish cages.

Work-related musculoskeletal disorders (WMSDs) represent a significant health challenge for workers in construction environments, often arising from prolonged exposure to ergonomic risks associated with manual labor, awkward postures, and repetitive motions. These conditions not only lead to diminished worker productivity but also incur substantial economic costs for employers and healthcare systems alike. Thus, there is an urgent need for effective tools to assess and mitigate these ergonomic risks. This study proposes a novel monocular 3D multi-person pose estimation method designed to enhance ergonomic risk assessments in construction environments. Leveraging advanced computer vision and deep learning techniques, this approach accurately captures and analyzes the spatial dynamics of workers’ postures, with a focus on detecting extreme knee flexion, a critical indicator of work-related musculoskeletal disorders (WMSDs). A pilot study conducted on an actual construction site demonstrated the method’s feasibility and effectiveness, achieving an accurate detection rate for extreme flexion incidents that closely aligned with supervisory observations and worker self-reports. The proposed monocular approach enables universal applicability and enhances ergonomic analysis through 3D pose estimation and group pose recognition for timely interventions. Future efforts will focus on improving robustness and integration with health monitoring to reduce WMSDs and promote worker health.

In this study, the extraction, purification and metabolic enzyme inhibition potential of Selaginella doederleinii were investigated. In order to extract the total biflavonoids from S. doederleinii (SDTBs), the optimum extraction process was obtained by optimizing the ultrasonic extraction parameters using response-surface methodology. This resulted in a total biflavonoid content of 22.26 ± 0.35 mg/g. Purification of the S. doederleinii extract was carried out using octadecylsilane (ODS), and the transfer rate of the SDTBs was 82.12 ± 3.48% under the optimum purification conditions. We determined the effect of the SDTBs on α-glucosidase (AG), α-amylase and xanthine oxidase (XOD) and found that the SDTBs had an extremely potent inhibitory effect on AG, with an IC50 value of 57.46 μg/mL, which was much lower than that of the positive control. Meanwhile, they also showed significant inhibition of XOD and α-amylase, with IC50 values of 289.67 μg/mL and 50.85 μg/mL, respectively. In addition, molecular docking studies were carried out to understand the nature of the action of the biflavonoids on AG and XOD. The results showed that robustaflavone had the lowest binding energy to AG (−11.33 kcal/mol) and XOD (−10.21 kcal/mol), while, on the other hand, amentoflavone showed a good binding affinity to AG (−10.40 kcal/mol) and XOD (−9.962 kcal/mol). Moreover, molecular dynamics simulations verified the above results.

Effective safety management is vital for ensuring construction safety. Traditional safety inspections in construction heavily rely on manual labor, which is both time-consuming and labor-intensive. Extensive research has been conducted integrating computer-vision technologies to facilitate intelligent surveillance and improve safety measures. However, existing research predominantly focuses on singular tasks, while construction environments necessitate comprehensive analysis. This study introduces a multi-task computer vision technology approach for the enhanced monitoring of construction safety. The process begins with the collection and processing of multi-source video surveillance data. Subsequently, YOLOv8, a deep learning-based computer vision model, is adapted to meet specific task requirements by modifying the head component of the framework. This adaptation enables efficient detection and segmentation of construction elements, as well as the estimation of person and machine poses. Moreover, a tracking algorithm integrates these capabilities to continuously monitor detected elements, thereby facilitating the proactive identification of unsafe practices on construction sites. This paper also presents a novel Integrated Excavator Pose (IEP) dataset designed to address the common challenges associated with different single datasets, thereby ensuring accurate detection and robust application in practical scenarios.

This paper investigates a parameter-free H∞ differential game approach for nonlinear active vehicle suspensions. The study accounts for the geometric nonlinearity of the half-car active suspension and the cubic nonlinearity of the damping elements. The nonlinear H∞ control problem is reformulated as a zero-sum game between two players, leading to the establishment of the Hamilton–Jacobi–Isaacs (HJI) equation with a Nash equilibrium solution. To minimize reliance on model parameters during the solution process, an actor–critic framework employing neural networks is utilized to approximate the control policy and value function. An off-policy reinforcement learning method is implemented to iteratively solve the HJI equation. In this approach, the disturbance policy is derived directly from the value function, requiring only a limited amount of driving data to approximate the HJI equation’s solution. The primary innovation of this method lies in its capacity to effectively address system nonlinearities without the need for model parameters, making it particularly advantageous for practical engineering applications. Numerical simulations confirm the method’s effectiveness and applicable range. The off-policy reinforcement learning approach ensures the safety of the design process. For low-frequency road disturbances, the designed H∞ control policy enhances both ride comfort and stability.

Objective: The aim of this study was to optimize the formulation of a C60-modified self-microemulsifying drug delivery system loaded with triptolide (C60-SMEDDS/TP) and evaluate the cytoprotective effect of the C60-SMEDDS/TP on normal human cells. Results: The C60-SMEDDS/TP exhibited rapid emulsification, an optimal particle size distribution of 50 ± 0.19 nm (PDI 0.211 ± 0.049), and a near-neutral zeta potential of −1.60 mV. The release kinetics of TP from the C60-SMEDDS/TP exhibited a sustained release profile and followed pseudo-first-order release kinetics. Cellular proliferation and apoptosis analysis indicated that the C60-SMEDDS/TP (with a mass ratio of TP: DSPE-PEG-C60 = 1:10) exhibited lower toxicity towards L02 and GES-1 cells. This was demonstrated by a higher IC50 (40.88 nM on L02 cells and 17.22 nM on GES-1 cells) compared to free TP (21.3 nM and 11.1 nM), and a lower apoptosis rate (20.8% on L02 cells and 26.3% on GES-1 cells, respectively) compared to free TP (50.5% and 47.0%) at a concentration of 50 nM. In comparison to the free TP group, L02 cells and GES-1 cells exposed to the C60-SMEDDS/TP exhibited a significant decrease in intracellular ROS and an increase in mitochondrial membrane potential (ΔψM). On the other hand, the C60-SMEDDS/TP demonstrated a similar inhibitory effect on BEL-7402 cells (IC50 = 28.9 nM) and HepG2 cells (IC50 = 107.6 nM), comparable to that of the free TP (27.2 nM and 90.4 nM). The C60-SMEDDS/TP group also exhibited a similar intracellular level of ROS and mitochondrial membrane potential compared to the SMEDDS/TP and free TP groups. Method: Fullerenol-Grafted Distearoyl Phosphatidylethanolamine-Polyethylene Glycol (DSPE-PEG-C60) was synthesized and applied in the self-microemulsifying drug delivery system. The C60-SMEDDS/TP was formulated using Cremophor EL, medium-chain triglycerides (MCT), PEG-400, and DSPE-PEG-C60, and loaded with triptolide (TP). The toxicity and bioactivity of the C60-SMEDDS/TP were assessed using normal human liver cell lines (L02 cells), normal human gastric mucosal epithelial cell lines (GES-1 cells), and liver cancer cell lines (BEL-7402 cells and HepG2 cells). The production of reactive oxygen species (ROS) after the C60-SMEDDS/TP treatment was assessed using 2′,7′-dichlorofluorescein diacetate (DCFDA) staining. The alterations in mitochondrial membrane potential (ΔψM) were assessed by measuring JC-1 fluorescence. Conclusions: The cytoprotection provided by the C60-SMEDDS/TP favored normal cells (L02 and GES-1) over tumor cells (BEL-7402 and HepG2 cells) in vitro. This suggests a promising approach for the safe and effective treatment of TP.

Stone curtain walls are widely used in contemporary architectures; however, their regular inspection is always labor-intensive, time-consuming, and hazardous due to the complex and enclosed spatial structure of these high-rise building enclosures. To address this issue, this study proposes an automated and novel inspection method, which is composed of the following three steps: First, we utilize 3D laser scanning technology to capture colored point cloud data of the stone curtain wall system; subsequently, by extracting and processing the integration of color and depth information, the stone panels and end sealants are precisely segmented; finally, various defects, such as cracks, unevenness, and irregularities, are automatically identified through artificial intelligence algorithms in a timely manner. To validate the proposed method, an on-site experiment was carried out to demonstrate the effectiveness in detecting multiple defects concurrently on stone curtain walls. The experimental results showed that our proposed method could provide a non-contact and automated inspection alternative for all the stone curtain walls with a high accuracy of anomaly detection, facilitating rational maintenance plans and strategies to ensure the safety and performance of these modern building enclosures.

The quality inspection of each precast utility tunnel segment is crucial, especially the cross-sectional dimensions and surface smoothness, since they influence the assembly precision at the construction site. Traditional manual inspection methods are not only time-consuming and costly but also limited in accuracy. In order to achieve a high-precision and high-efficiency geometric quality inspection for multi-type precast utility tunnel segments, this paper proposes an automated inspection method based on the Building Information Model (BIM) and Light Detection and Ranging (LiDAR). Initially, the point cloud data (PCD) of the precast utility tunnel segment are acquired through LiDAR and preprocessed to obtain independent point clouds of the precast utility tunnel segment. Then, the shape of the precast utility tunnel segment is identified using the proposed Cross-Sectional Geometric Ratio Feature Identification (CSGRFI) algorithm. Subsequently, the geometric features of the components are extracted based on preset conditions, and the geometric dimensions are calculated. Finally, the quality inspection results are obtained by comparing with the design information provided by the BIM. The proposed method was validated in a real precast component factory. The results indicate that the method achieved a 100% success rate in identifying the cross-sectional shapes of the segments. Compared with the manual measurement method, the proposed method demonstrated a higher accuracy in the geometric quality assessment and an improved time efficiency by 44%. The proposed method enables the efficient geometric quality inspection of tunnel segments, effectively addressing the construction industry’s need for large-scale, high-quality tunnel projects.

Background Minimally invasive reduction and fixation of intra‐articular calcaneal fractures poses great challenges for orthopaedic surgeons. The aim of the present study was to report the technical points, evaluate the efficacy of minimally invasive reduction and internal fixation assisted by the temporary limb reconstruction system (LRS) external fixator for intra‐articular calcaneal fractures, and propose the indications of our protocol. Methods In this retrospective study, a series of 34 consecutive closed and displaced intra‐articular calcaneal fractures involving the articular surface were treated by this technology between June 2016 and April 2018. X‐ray and computed tomography (CT) scans were performed before and after surgery to measure Bohler's angle; the length, height, and width of the calcaneus; and the mechanical axis of the hindfoot. Postoperative complications were recorded. Imaging and clinical outcomes were comprehensively evaluated using the American Orthopaedic Foot and Ankle Society (AOFAS) hindfoot‐ankle scoring system. After testing the normality of the data, Bohler's angle and the length of calcaneus were compared using the Wilcoxon signed‐rank test. The height, width of the calcaneus, and the mechanical axis of the hindfoot were compared using the Paired‐Samples t‐test. Results Thirty‐two fractures were followed up for an average of 20.66 months (from 12 to 32 months). All fractures achieved stable reduction and bony union. The articular surface was reduced and fixed with direct vision through the sinus tarsi incision. No failure of internal fixation or loss of reduction was detected during follow‐up. There were no soft tissue complications. Bohler's angle; the length, height, and width of the calcaneus; and the mechanical axis of the hindfoot improved significantly. The AOFAS scores averaged 84.12 points; seven cases were rated excellent, 20 good, four fair, and one poor. Conclusions For intra‐articular calcaneal fractures, minimally invasive surgery assisted with temporary LRS external fixation can reconstruct the calcaneal shape and the sub‐talar articular surface. This simple surgical modality with limited complications may be helpful in the surgical treatment of most type II and III calcaneal fractures except comminuted fractures of the calcaneal tuberosity.

The two successive earthquakes of magnitude 7.8 in Turkey on February 6, 2023, were a remarkable tectonic movement and a particularly typical scientific experiment scene. At present, various observational data are abundant, providing a perfect opportunity for scholars around the world to verify their conjectures, models and conduct experiments. By using the thermal infrared annual mean line difference amplitude enhancement ratio method and the sliding annual moving average method of TEC (Total Electron Content) microscopic anomaly events，which are both created by the writer, we found that there were high intensity thermal infrared anomalies in the east and west sides of the epicenter area in late April to early May and in August 2022, respectively. About one month before the earthquake, the synchronous thermal infrared activity of the east and west sides of the epicenter and the northern region was significantly enhanced. In particular, the annual mean line difference amplitude enhancement ratio of the northern region hit the highest record since 2018 on January 31, 2023, and was 2.5 times the average level of the four years before the earthquake. The sliding annual moving average method of TEC microscopic anomaly events showed that the annual mean value of TEC microscopic anomaly events in the epicentre and its vicinity began to decline rapidly from 2021, and the annual mean value before the earthquake hit the lowest level in history, which was only about a quarter of the previous high since 2000. The two anomalies of thermal infrared and TEC are highly overlapping in time and space, and the earthquake occurred in the above two abnormal regions, indicating that the two anomalies may be closely related to this seismic series.

Abstract Engineering experience shows that for transformers with long service life and serious moisture exposure, the inter‐turn paper insulation inside the winding will precipitate bubbles under the condition of electric field and conductor heating, which will endanger the equipment insulation. In order to explore the influence factors of bubbles formation in the moist insulating paper of transformers, based on the existing research on the influence of moisture content and gas dissolution in transformer oil, this study further considers the influence of air pressure (AP) and electric field and establishes an experimental platform to change the air pressure and electric field, thereby studying the formation characteristics of bubbles in oil‐paper insulation. The results show that air pressure and electric field can affect the initial temperature, volume, and shape of bubble formation. From 0 to −0.05 MPa for air pressure, the initial temperature of bubble generation decreased by 41°C, its maximum two‐dimensional projected area increased by 418.4% with more severe distortion, and the breakdown voltage decreased. When the AC voltage applied on the needle plate electrode increased from 0 to 10 kV, the initial temperature of bubble formation increased by 29°C, and the maximum two‐dimensional projection area increased by 336.6%.

The asperity wear of rock joints significantly affects their shear behaviour. This study discusses the wear damage of the asperities on the joint surface, highlighting the roughness degradation characteristics during the shear process. The direct shear experiment of artificial specimens containing rock joints was conducted under different normal stresses based on three-dimensional scanning technology. These experimental results showed the contribution of joint wear to roughness degeneration, such as the height, zone, and volume of asperity degeneration. The wear coefficient of the rock joint was obtained based on the volume wear of asperities in the laboratory experiment. The functional relationship between the friction coefficient and wear coefficient is subsequently determined. To quantitatively analyse the wear damage of a joint surface, a calculation method for determining the wear depth of the rock joint after shearing was proposed based on wear theory. The relationship between the ultimate dilation and wear depth was analysed. A coefficient m, which can describe the damage degree of the joint surface, and a prediction method of joint surface roughness after shearing are established. Good agreement between analytical predictions and measured values demonstrates the capability of the developed model. Lastly, the sensitivity factors on the wear depth are explored.

Abstract Cannulated screw fixation is essential in treating femoral neck fractures, and the widely used freehand technique has several limitations. Therefore, we designed a new laser-positioning and navigation system and compared its efficacy with that of the traditional freehand technique in the cannulated screw fixation of femoral neck fractures. This randomized controlled single-blind trial recruited patients with femoral neck fracture, who were treated using either the newly designed laser-navigation device or the freehand technique. In in-vitro experiments, using the femoral neck model, the laser group was better than the freehand group in terms of operation time (P = 0.0153) and radiation exposure time (P

Abstract Hypertriglyceridemic pancreatitis (HTGP) is featured by higher incidence of complications and poor clinical outcomes. Gut microbiota dysbiosis is associated with pancreatic injury in HTGP and the mechanism remains unclear. Here, we observe lower diversity of gut microbiota and absence of beneficial bacteria in HTGP patients. In a fecal microbiota transplantation mouse model, the colonization of gut microbiota from HTGP patients recruits neutrophils and increases neutrophil extracellular traps (NETs) formation that exacerbates pancreatic injury and systemic inflammation. We find that decreased abundance of Bacteroides uniformis in gut microbiota impairs taurine production and increases IL-17 release in colon that triggers NETs formation. Moreover, Bacteroides uniformis or taurine inhibits the activation of NF-κB and IL-17 signaling pathways in neutrophils which harness NETs and alleviate pancreatic injury. Our findings establish roles of endogenous Bacteroides uniformis-derived metabolic and inflammatory products on suppressing NETs release, which provides potential insights of ameliorating HTGP through gut microbiota modulation.