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High sodium intake is strongly associated with hypertension and obesity. This study aims to investigate the relationship between 24-h urinary sodium (a surrogate measure of sodium intake), ambulatory blood pressure parameters, left atrial function, and left atrioventricular coupling. Further, we intend to examine whether blood pressure and BMI might be mediators of the relationship between 24-h urinary sodium and subclinical cardiac function.Our study had 398 participants, all of whom were subjected to 24-h urine collection, 24-h ambulatory blood pressure measurement, and cardiac magnetic resonance imaging.The average age of the participants was 55.70 ± 11.30 years old. The mean urinary sodium of the participants was 172.01 ± 80.24 mmol/24 h. After adjusting for age, sex, history of diabetes, smoking status, alcohol consumption, and use of diuretics, 24-h urinary sodium was correlated with multiple ambulatory blood pressure parameters, BMI, left atrial function, and the left atrioventricular coupling index (LACI) (P 0.05). Mediation analysis showed that BMI explained 16% of the indirect effect of 24-h urinary sodium and left atrial function and 30% of the indirect effect of LACI. Independent of the mediator, 24-h urinary sodium had a significant direct effect on left atrial function and left atrioventricular coupling.Higher 24-h urinary sodium was associated with a greater BMI as well as poor left atrial function and left atrioventricular coupling, and the BMI mediated the relationship between 24-h urinary sodium and subclinical left cardiac function. Furthermore, and more importantly, 24-h urinary sodium may have directly affected the left atrial function and left atrioventricular coupling independent of intermediary factors.

Background: Obesity is a recognized risk factor for heart failure. People with similar weights may have different metabolic health. Notably, insulin resistance is a hallmark of obesity and a feature of heart failure. We aimed to evaluate the effects of obesity and metabolic health status on subclinical left cardiac function. We also investigated whether insulin resistance (TyG index) plays a role in BMI-linked subclinical left cardiac dysfunction. Methods: The study involved 403 volunteers. Multivariate logistic regression models were used to assess associations between obesity, metabolic health, and overall subclinical left cardiac function .Mediating analysis was used to explore the role of the TyG index in the association between BMI and left cardiac function. Finally, ROC analysis was performed to explore the predictive value of the TyG index in subclinical left cardiac dysfunction. Results: The correlation analysis showed that metabolic unhealth increased the risk of subclinical left ventricular (LV) dysfunction; obesity was associated with an increased risk of global left cardiac dysfunction regardless of metabolic health status. The TyG index mediated 25% of the associations between BMI and Left atrial (LA) function. ROC analysis exhibited that the TyG index can be used as a predictor of LA dysfunction (AUC = 0.63), and the optimal cut-off point for the TyG index is 9.33. Conclusions: Even a "non-obese metabolically unhealthy" is a detrimental state of early LV function; obesity remains a major risk factor for global subclinical left cardiac dysfunction. Using the TyG index could allow early identification of individuals at high risk of subclinical left cardiac dysfunction. Registration number：ChiCTR2200057991；Date of registration: 2022-03-25 URL:http://www.chictr.org.cn/showproj.aspx?proj=162316

Background: Obesity is a recognized risk factor for heart failure. People with similar weights may have different metabolic health. Notably, insulin resistance is a hallmark of obesity and a feature of heart failure. We aimed to evaluate the effects of obesity and metabolic health status on subclinical left cardiac function. We also investigated whether insulin resistance (TyG index) plays a role in BMI-linked subclinical left cardiac dysfunction. Methods: The study involved 403 volunteers. Multivariate logistic regression models were used to assess associations between obesity, metabolic health, and overall subclinical left cardiac function .Mediating analysis was used to explore the role of the TyG index in the association between BMI and left cardiac function. Finally, ROC analysis was performed to explore the predictive value of the TyG index in subclinical left cardiac dysfunction. Results: The correlation analysis showed that metabolic unhealth increased the risk of subclinical left ventricular (LV) dysfunction; obesity was associated with an increased risk of global left cardiac dysfunction regardless of metabolic health status. The TyG index mediated 25% of the associations between BMI and Left atrial (LA) function. ROC analysis exhibited that the TyG index can be used as a predictor of LA dysfunction (AUC = 0.63), and the optimal cut-off point for the TyG index is 9.33. Conclusions: Even a "non-obese metabolically unhealthy" is a detrimental state of early LV function; obesity remains a major risk factor for global subclinical left cardiac dysfunction. Using the TyG index could allow early identification of individuals at high risk of subclinical left cardiac dysfunction. Registration number：ChiCTR2200057991；Date of registration: 2022-03-25 URL:http://www.chictr.org.cn/showproj.aspx?proj=162316

Maintenance strategies aim at reduction of the operation and maintenance cost of wind turbines. An opportunistic maintenance strategy offers cost advantages over the traditional preventive replacement maintenance strategy by considering cost dependency among maintenance activities. A new opportunistic maintenance strategy of wind turbines is proposed here. First, the proposed strategy includes two sets of reliability thresholds to handle subassemblies those are in operational and failed wind turbines. Using the reliability thresholds, ten maintenance modes and their service conditions are presented. Second, the Weibull distribution with an age reduction factor is introduced to describe reliability variation of subassemblies under imperfect maintenance. Third, the maintenance cost in each maintenance mode is expressed by a reliability variation‐based function that is dependent on the stage of maintenance activities. Fourth, due to the randomness of failures, the expected total maintenance cost is determined with Monte Carlo simulation. The proposed approach has been validated with the data provided by a wind farm located in Northern China.

Face detection is playing a pivotal role for crowd counting and abnormal events detection. However, it is vulnerable to face presentation attacks by printed photos, videos, and 3D masks of real human faces. Although numerous detection techniques based on deep learning have been employed to address the problem of face presentation attacks, there are still several weaknesses in these approaches, such as high algorithm complexity and a lack of detection ability. To overcome these weaknesses, a method based on a multilevel fusion network with Laplacian embedding (MFNet‐LE) for the detection of face presentation attacks is proposed. First, a shallow network that contains just three layers was developed, which makes the model faster. Then, an optimised multilevel fusion strategy was developed to combine the input with the output of all previous layers to improve the detection ability of the method. Finally, a Laplacian embedding algorithm is introduced to maintain the inter‐class discrimination and penalise the intra‐class distance. Under the joint supervision of Laplacian loss and softmax loss, the proposed approach can obtain more discriminative features, which enhance the accuracy of attack detection. Experiments were conducted with three public databases for face presentation attacks: CASIA FASD, Idiap Replay Attack database and MSU USSA. The results demonstrate that the MFNet‐LE model can outperform the state‐of‐the‐art methods.

Aqueous batteries that use metal anodes exhibit maximum anodic capacity, whereas the energy density is still unsatisfactory partially due to the high redox potential of the metal anode. Current metal anodes are plagued by the dilemma that the redox potential of Zn is not low enough, whereas Al, Mg, and others with excessively low redox potential cannot work properly in aqueous electrolytes. Mn metal with a suitably low redox potential is a promising candidate, which was rarely explored before. Here, we report a rechargeable aqueous Mn-metal battery enabled by a well-designed electrolyte and robust inorganic-organic interfaces. The inorganic Sn-based interface with a bottom-up microstructure was constructed to preliminarily suppress water decomposition. With this bubble-free interface, the organic interface can be formed via an esterification reaction of sucrose triggered by acyl chloride in the electrolyte, generating a dense physical shield that isolates water while permitting Mn

Objectives The aim of this study is to identify the peri-procedural risk factors and outcomes of hemodynamic instability (HI) after carotid artery stenting (CAS). Methods A single-center, retrospective study was performed in 168 patients who underwent CAS procedure between September 2017 and September 2020. The presence of HI, as defined by hypertension (systolic blood pressure >160 mmHg), hypotension (systolic blood pressure Results Among 168 patients (mean age, 68.2 ± 8.3 years; 81.5% male), the frequency of post-procedural long-period HI was noted in 42 patients (25.0%). Male was prone to experience HI (odds ratio, 9.156, p = 0.021). Aggressive inflation pressure (>7 atm) and 5 mm balloon for pre-dilatation were risk factors of long-period HI (OR, 7.372, p = 0.035; OR, 3.527, p = 0.023). Intraoperative peak blood pressure and larger-sized stents remained independent predictors for the development of HI (OR, 1.043, p = 0.027, and OR, 1.973, p = 0.015). Patients with prolonged HI were more likely to suffer TIA and stroke compared to other patients and significant difference was found in the occurrence of TIA ( p < 0.05). Non-significance was found in mortality rate and other outcomes. Conclusions CAS-induced HI occurs in a considerable percentage while several peri-procedural variables are determined as independent predictors to develop long-period HI. Patients with prolonged HI are associated with increased risk of neurologic events and thus standardized intervention as well as management of long-period HI are of critical importance during clinical process.

BACKGROUND AND OBJECTIVE The influence of cerebral large artery stenosis (CLAS) on ischemic leukoaraiosis (LA) remains elusive. Based on the proposed stages of the preinfarction period, this study aimed to adopt the staging system to assess the correlation between ischemic LA and CLAS. MATERIALS AND METHODS Patients with unilateral CLAS ≥50% and without cerebral stroke were screened. The severity and distribution of stenosis were evaluated on computed tomography angiography images. The degree of regional cerebral perfusion was rated according to the stages of preinfarction period: 0=normal, 1=stage Ia, 2=stage Ib, 3=stage IIa, 4=stage IIb. Stage I included stage Ia and stage Ib. Stage II included stage IIa and stage IIb. LA was scored with Fazakas scale on T2-weighted image and/or fluid-attenuated inversion recovery sequences. RESULTS The cohort consisted of 212 patients (mean age, 66.89±11.39 y), including 145 (68.40%) males. CLAS severity and distribution did not differ between patients with and without LA (P>0.05). Normal, stage I, and stage II had significantly different incidences of LA and hemispheric LA scores in the left and right hemispheres (P

On-line monitoring and fault warning of energy equipment operation performance is very important, and it is also an important part of achieving energy internet. Therefore, the construction of a comprehensive management and control with big data platform system is one of the key research directions of the current energy internet. However, IPv4 network protocol is basically used to the existing application system construction strategy for communication. In the future, there will be scale limitations in the form of big data communication form with multi-energy interconnection. This paper firstly product an integrated management and control platform with big data based on IPv6 for regional multi-energy cooperation, which realizes a method that multiple heterogeneous big data can be saved efficiently and fast in a bandwidth limitation. The platform had realized not only the collection of the complicated multi-energy equipment running data which is structured and unstructured, but also monitoring evaluation and early warning diagnosis to the multi-energy equipment running. That can be referential for the construction of energy internet.

Background A carotid web (CW), an atypical fibromuscular dysplasia, is rare and may cause ischemic stroke. It is challenging to recognize a CW promptly and treat it accordingly. We report a case of an initially misdiagnosed CW. Case Description A 48-year-old man with recurrent cerebral infarction was transferred to our hospital for bypass surgery. Imaging performed at our facility showed multiple old infarct lesions and cerebral tissue hypoperfusion in the occluded left middle cerebral artery territory. Bypass surgery was performed without perioperative complications. While searching for the cause of his stroke, we found a thin intraluminal filling defect along the posterior wall of the left carotid bulb just beyond the carotid bifurcation on sagittal maximal intensity projection images, axial thin-cut images, and volume rendering images. The defect was diagnosed as a CW. It was also detected on follow-up ultrasonography. Owing to our initial unawareness, we did not photograph the carotid bulb during preoperative digital subtraction angiography and postoperative computed tomography angiography. Although the patient was treated with bypass, the persistence of the factors underlying the CW may induce further thrombosis and subsequent occlusion of his ipsilateral anterior cerebral artery. Conclusions Clinicians should be aware of CW as a potential cause of ischemic stroke. Head and neck computed tomography angiography is a reliable imaging method to detect CWs.

Combining the principle of antibody concentration with the idea of biological evolution, this paper proposes an adaptive target detection algorithm for cloud service security based on Bio-Inspired Performance Evaluation Process Algebra (Bio-PEPA). The formal modelling of cloud services is formally modded by Bio-PEPA and the modules are transformed between cloud service internal structures and various components. Then, the security adaptive target detection algorithm of cloud service is divided into two processes, the short-term optimal action selection process which selects the current optimal detective action through the iterative operation of the expected function and the adaptive function, and the long-term detective strategy realized through the updates and eliminations of action planning table. The combination of the two processes reflects the self-adaptability of cloud service system to target detection. The simulating test detects three different kinds of security risks and then analyzes the relationship between the numbers of components with time in the service process. The performance of this method is compared with random detection method and three anomaly detection methods by the cloud service detection experiment. The detection time of this method is 50.1% of three kinds of detection methods and 86.3% of the random detection method. The service success rate is about 15% higher than that of random detection methods. The experimental results show that the algorithm has good time performance and high detection hit rate.

In this paper, a visualization and modeling method for the internal fixation plate in personalized and minimally invasive long bone fracture surgery is presented. This framework mainly includes six sub-steps: firstly, the Principal Component Analysis (PCA) method is used to extract the 3D axis of the broken bone; secondly, the Gauss mapping method is utilized to segment the end surfaces of the broken bone; thirdly, the maximum common subgraph strategy is utilized to complete the end surface matching; fourthly, the OBB (Oriented Bounding Box) method is utilized to accomplish the pre-registration of the fracture surface; fifthly, the ICP (Iterative Closest Point) algorithm is utilized to achieve the fracture surface models’ accurate alignment; lastly, the personalized bent internal fixation plate model can be reconstructed based on anchor points. Via this method, doctors can obtain the accurate and personalized internal fixation plate model that has the best matching geometric form to the patient’s broken bones. This method can provide a well technique base and computational solution for the minimally invasive long bone fracture surgery.