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Bolted joints are extensively used in a wide range of industrial and commercial structures, making their condition monitoring essential for ensuring structural integrity and operational safety. Under the influence of vibration, cyclic loading, and environmental factors, bolts may gradually lose preload, which can degrade joint stiffness and eventually lead to structural failure. To address this issue, this study presents a smart percussion system developed on a Raspberry Pi platform that integrates acoustic signal acquisition, real-time signal processing, and visualization of diagnostic results. A bolt looseness detection strategy combining audio feature extraction with unsupervised learning is proposed. In contrast to traditional percussion-based approaches that depend on supervised learning and predefined baseline datasets, the proposed method does not require prior reference data, significantly improving its adaptability and ease of deployment across different structures, which shows essential practical significance. Experimental investigations demonstrate the effectiveness and advantages of the proposed system, indicating its strong potential to enhance percussion-based bolt looseness detection and to support real-time structural health monitoring, which are real-world engineering applications.

Aortic dissection (AD), characterized by rupture of the aortic wall, presents significant diagnostic challenges due to its rapid onset and nonspecific clinical symptoms. Although conventional imaging techniques are clinically useful, they typically lack sensitivity for early AD detection, are often unavailable in resource-limited settings, and cannot elucidate the mechanistic basis of AD pathogenesis. In this study, we used metabolomics and lipidomics to analyze serum samples from healthy controls, hypertensive AD patients, and normotensive AD patients, revealing distinct metabolic and lipidomic perturbations associated with AD, independent of blood pressure status. Notably, mitochondrial dysfunction was a pivotal factor in AD pathogenesis, and key metabolites such as acetylcarnitine served as both an AD biomarker and an indicator of disrupted lipid metabolism. Lipidomic profiling further revealed a consistent accumulation of specific fatty acids in AD patients, including elevated levels of FA(16:1), FA(20:1), FA(22:5), and FA(20:2) in both hypertensive and normotensive subgroups. Additionally, the sphingolipid signaling pathway was the most markedly altered lipidomic pathway between the two AD groups. These findings offer new insights into the complex lipidomic and metabolic mechanisms underlying AD pathogenesis, paving the way for improved diagnostics and targeted therapeutic strategies.

Bolted joints are extensively used in mechanical and civil engineering structures because of their low cost, standardized design, and ease of installation and maintenance. The preload in a bolted connection is critical for ensuring joint stability and service reliability; however, preload degradation commonly occurs under complex operating conditions, particularly in environments involving sustained or cyclic vibration. To tackle this problem, this study proposes a portable, force-controllable percussion system for bolt looseness detection. The system integrates a solenoid-driven automatic percussion device, acoustic signal acquisition, onboard data-processing, and real-time visualization of diagnostic results. By adjusting the driving current of the solenoid, the percussion force can be accurately controlled, ensuring stable and repeatable excitation. Benefiting from its compact structure and low cost, the proposed system is suitable for real-time, on-site inspection of bolt looseness. Furthermore, a novel audio-processing approach based on a Siamese Capsule Network is developed to identify bolt looseness conditions. Compared with existing percussion-based techniques, the proposed method exhibits improved classification performance, especially in recognizing bolt states that are unseen during training. Exploratory experimental results validate the effectiveness of the proposed system and demonstrate its strong potential for practical engineering applications.

This study aimed to investigate the clinical response and short-term survival and further explore the comprehensive factors for predicting clinical outcomes in patients with liver cancer treated by drug-eluting beads transarterial chemoembolization . Forty-nine patients with liver cancer who received drug-eluting beads transarterial chemoembolization treatment were consecutively enrolled in this cohort study. Demographic features, medical histories, clinicopathological properties, biochemical indexes, previous treatments, and chemoembolization reagents were recorded. Ten (20.4%) patients achieved complete response and 31 (63.3%) patients achieved partial response after drug-eluting beads transarterial chemoembolization treatment, with overall response rate of 83.7%. Logistic analysis revealed that high aspartate aminotransferase (P = .041), high carbohydrate antigen 199 (P = .030), and low hemoglobin (P = .020) could independently predict less possibility for complete response achievement. As to survival analysis, high alkaline phosphatase (P = .040), low albumin (P = .033) low hemoglobin (P = .018), portal vein invasion (P = .025), higher Eastern Cooperative Oncology Group performance status (P = .011), and higher Child-pugh stage (P = .001) were independent predictors for worse overall survival. In conclusion, the present study validated that drug-eluting beads transarterial chemoembolization was effective and well tolerated for patients with liver cancer, and high aspartate aminotransferase, high alkaline phosphatase, low albumin, low hemoglobin, portal vein invasion, higher Child-pugh stage, higher Barcelona Clinic Liver Cancer stage, higher Eastern Cooperative Oncology Group performance status were correlated with worse outcomes.

In the article, the power oscillation problem of the virtual synchronous generator (VSG) is studied. To facilitate a solution for this problem, an optimized virtual synchronous generator (OVSG) control method in view of forward atonement is designed. Tunable variables for atonement segment changing realize the purpose of suppressing the steps of the operating system and inhibiting active power oscillation of VSG. Virtual simulation and experiment test the availability of the designed method.

Background: Acute type A aortic dissection complicated by mesenteric malperfusion syndrome (ATAAD-MMPS) is a highly lethal emergency with diagnostic challenges due to rapid progression and non-specific symptoms. This pilot study aimed to characterize the serum metabolomic and lipidomic alterations specific to ATAAD-MMPS and identify potential early diagnostic biomarkers. Methods: Serum samples from healthy controls, patients with uncomplicated ATAAD, and patients with ATAAD-MMPS were analyzed using targeted metabolomics and lipidomics. Multivariate statistical analyses were performed to discriminate between groups and identify differentially abundant metabolites and lipids. Pathway analysis was conducted to explore underlying pathological mechanisms. Results: Metabolomic profiles clearly distinguished ATAAD-MMPS from uncomplicated ATAAD, whereas lipidomic changes were primarily associated with ATAAD itself rather than the presence of mesenteric malperfusion. Metabolic pathway analysis revealed significant perturbations in the citric acid cycle, suggesting mitochondrial involvement as a potential pathological feature. Notably, methylguanidine was uniquely and markedly elevated in the ATAAD-MMPS group, demonstrating potential diagnostic value in distinguishing this lethal complication from uncomplicated ATAAD in this exploratory cohort (AUC = 0.923). Conclusions: This pilot study identifies distinct metabolic signatures associated with mesenteric malperfusion in ATAAD, with mitochondrial metabolic perturbations emerging as a potential contributing mechanism. Methylguanidine represents a candidate early diagnostic biomarker for ATAAD-MMPS, warranting validation in larger prospective studies. These findings provide a foundation for improved diagnostic strategies for this devastating condition.

The base station（BS） configuration is a key factor to improve energy efficiency（EE）. In this paper,we focus on designing the network deployment parameters（i.e., BS densities） for biased K-tier heterogeneous cellular network（HCN） with quality of service（Qo S） provisioning. Using appropriate approximations, we derive the closed-form expressions of optimal BS density across all tiers to minimize the area power consumption（APC） by applying the stochastic geometry theory, while satisfying the users＇ Qo S requirements. These results are used to obtain some new insights into the EE performance of biased HCN deployment. With the aid of this approach, the best type of BSs to be deployed or switched off for energy saving purposes can be identified from the perspectives of BS transmission power. More precisely, if the BS transmission power ratio between an arbitrary pair of tiers of K-tier HCN, e.g., the small cell BS and macro BS tiers, is higher than a threshold which is a function of path loss exponent, bias factor and power consumption, the small cell BSs are preferred.The opposite situation takes place otherwise. Furthermore, it is also shown that, compared to the unbiased HCN scenario, significant energy savings are possible by appropriately biasing the HCN and optimizing the BS density, subject to the Qo S constraints among all tiers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron sublineages BA.2.12.1, BA.4 and BA.5 exhibit higher transmissibility than the BA.2 lineage 1 . The receptor binding and immune-evasion capability of these recently emerged variants require immediate investigation. Here, coupled with structural comparisons of the spike proteins, we show that BA.2.12.1, BA.4 and BA.5 (BA.4 and BA.5 are hereafter referred collectively to as BA.4/BA.5) exhibit similar binding affinities to BA.2 for the angiotensin-converting enzyme 2 (ACE2) receptor. Of note, BA.2.12.1 and BA.4/BA.5 display increased evasion of neutralizing antibodies compared with BA.2 against plasma from triple-vaccinated individuals or from individuals who developed a BA.1 infection after vaccination. To delineate the underlying antibody-evasion mechanism, we determined the escape mutation profiles 2 , epitope distribution 3 and Omicron-neutralization efficiency of 1,640 neutralizing antibodies directed against the receptor-binding domain of the viral spike protein, including 614 antibodies isolated from people who had recovered from BA.1 infection. BA.1 infection after vaccination predominantly recalls humoral immune memory directed against ancestral (hereafter referred to as wild-type (WT)) SARS-CoV-2 spike protein. The resulting elicited antibodies could neutralize both WT SARS-CoV-2 and BA.1 and are enriched on epitopes on spike that do not bind ACE2. However, most of these cross-reactive neutralizing antibodies are evaded by spike mutants L452Q, L452R and F486V. BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1. Nevertheless, these neutralizing antibodies are largely evaded by BA.2 and BA.4/BA.5 owing to D405N and F486V mutations, and react weakly to pre-Omicron variants, exhibiting narrow neutralization breadths. The therapeutic neutralizing antibodies bebtelovimab 4 and cilgavimab 5 can effectively neutralize BA.2.12.1 and BA.4/BA.5, whereas the S371F, D405N and R408S mutations undermine most broadly sarbecovirus-neutralizing antibodies. Together, our results indicate that Omicron may evolve mutations to evade the humoral immunity elicited by BA.1 infection, suggesting that BA.1-derived vaccine boosters may not achieve broad-spectrum protection against new Omicron variants. Biochemical and structural studies of the interactions between antibodies and spike proteins from SARS-CoV-2 Omicron subvariants indicate how these variants have evolved to escape antibody-mediated neutralization.

ObjectiveThe purpose of this article was to perform a systematic review and meta-analysis regarding the diagnostic test accuracy of chest CT for detecting coronavirus disease 2019 (COVID-19).MethodsPubMed, Embase, Web of Science, and CNKI were searched up to March 12, 2020. We included studies providing information regarding diagnostic test accuracy of chest CT for COVID-19 detection. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity were pooled.ResultsSixteen studies (n = 3186 patients) were included. The risks of bias in all studies were moderate in general. Pooled sensitivity was 92% (95% CI = 86–96%), and two studies reported specificity (25% [95% CI = 22–30%] and 33% [95% CI = 23–44%], respectively). There was substantial heterogeneity according to Cochran’s Q test (p < 0.01) and Higgins I2 heterogeneity index (96% for sensitivity). After dividing the studies into two groups based on the study site, we found that the sensitivity of chest CT was great in Wuhan (the most affected city by the epidemic) and the sensitivity values were very close to each other (97%, 96%, and 99%, respectively). In the regions other than Wuhan, the sensitivity varied from 61 to 98%.ConclusionChest CT offers the great sensitivity for detecting COVID-19, especially in a region with severe epidemic situation. However, the specificity is low. In the context of emergency disease control, chest CT provides a fast, convenient, and effective method to early recognize suspicious cases and might contribute to confine epidemic.Key Points• Chest CT has a high sensitivity for detecting COVID-19, especially in a region with severe epidemic, which is helpful to early recognize suspicious cases and might contribute to confine epidemic.

Moiré superlattices (MSLs) are modulated structures produced from homogeneous or heterogeneous 2D layers stacked with a twist angle and/or lattice mismatch. Expanding the range of available materials, methods for fabricating MSL, and realization of unique emergent properties are key challenges. Here we report a facile bottom-up synthesis of homogeneous MSL based on a wide-gap 2D semiconductor, BiOCl, using a one-pot solvothermal approach with robust reproducibility. Unlike previous MSLs usually prepared by directly stacking two monolayers, our BiOCl MSLs are realized in a scalable, direct way through chemical growth of spiral-type nanosheets driven by screw-dislocations. We find emergent properties including large band gap reduction (∼0.6 eV), two-fold increase in carrier lifetime, and strongly enhanced photocatalytic activity. First-principles calculations reveal that such unusual properties can be ascribed to the locally enhanced inter-layer coupling associated with the Moiré potential modulation. Our results demonstrate the promise of MSL materials for chemical and physical functions. Expanding the range of available materials, methods for fabricating Moiré superlattices, and realization of new emergent properties are key challenges. Here the authors report a facile bottom-up synthesis of homogeneous Moiré superlattices based on a wide-gap 2D semiconductor, bismuth oxychloride.