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Abstract Background The relationships between BUNCr (blood urea nitrogen and creatinine ratio) and cognitive function, as well as depressive symptoms, remain unclear. We aim to investigate the association between BUNCr and cognition, as well as depressive symptoms, and to identify the mechanisms underlying these relationships. Methods We utilized data from the China Health and Retirement Longitudinal Study (CHARLS) from 2015 to 2020. Cognitive function was assessed using the Telephone Interview of Cognitive Status (TICS) scale, while depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10). We employed multivariate linear regression models to examine the association between BUNCr and cognitive function, as well as depressive symptoms. Additionally, causal mediation analysis was conducted to identify potential mediation effects of depressive symptoms between BUNCr and cognition. Results We observed a negative association between BUNCr and cognitive function (coefficient: -0.192; 95% confidence interval [CI]: -0.326 ∼ -0.059) and a positive relationship between BUNCr and depressive symptoms (coefficient: 0.145; 95% CI: 0.006 ∼ 0.285). In addition, the causal mediation analysis revealed that depressive symptoms (proportion mediated: 7.0%) significantly mediated the association between BUNCr and cognition. Conclusion Our study has unveiled that BUNCr is inversely associated with cognitive function and positively linked to depressive symptoms. Moreover, we found that depressive symptoms significantly mediated the association between BUNCr and cognition. These findings provide new evidence and insights for the prevention and management of cognitive function and dementia.

Some new techniques of aggregating hesitant fuzzy numbers (HFNs) by using monotonic dependent OWA (MDOWA) operators are investigated. By utilizing the score value of HFN, the concepts of hesitant fuzzy configuration vector and hesitant fuzzy hybrid configuration vector are proposed. Then, some methods of calculating variable weights related to the MDOWA operators under hesitant fuzzy environments are presented. Further, some operators, including hesitant fuzzy monotonic dependent OWA (HFMDOWA) operators and hesitant fuzzy hybrid monotonic dependent OWA (HFHMDOWA) operators, are developed, such as balanced HFMDOWA operators, rewarded HFMDOWA operators, balanced HFHMDOWA operators, rewarded HFHMDOWA operators, and so on. These developed operators are applied to multiple criteria group decision making (MCGDM), and a novel MCGDM algorithm is presented. By using the presented operators and algorithm, we can obtain symmetric decision-making results. Finally, an application example is provided to demonstrate the effectiveness of the developed MCGDM techniques.

The CRISPR-associated endonuclease Cas12a has become a powerful genome-editing tool in biomedical research due to its ease of use and low off-targeting. However, the size of Cas12a severely limits clinical applications such as adeno-associated virus (AAV)-based gene therapy. Here, we characterized a novel compact Cas12a ortholog, termed EbCas12a, from the metagenome-assembled genome of a currently unclassified Erysipelotrichia. It has the PAM sequence of 5'-TTTV-3' (V = A, G, C) and the smallest size of approximately 3.47 kb among the Cas12a orthologs reported so far. In addition, enhanced EbCas12a (enEbCas12a) was also designed to have comparable editing efficiency with higher specificity to AsCas12a and LbCas12a in mammalian cells at multiple target sites. Based on the compact enEbCas12a, an all-in-one AAV delivery system with crRNA for Cas12a was developed for both in vitro and in vivo applications. Overall, the novel smallest high-fidelity enEbCas12a, this first case of the all-in-one AAV delivery for Cas12a could greatly boost future gene therapy and scientific research.

Multiple-valued logics (MVL) have abundant operation functions which can be used for encryption. A reconfigurable MVL operator can perform all MVL functions with a universal circuit structure at fast operation speed, based on which a one-time-pad cryptosystem is expected to be built. However, we find that when the existing MVL encryption method is applied to video data encryption, the color edges in the plaintext image will remain in the ciphertext image, resulting in partial leakage of information. To solve this problem, we propose byte reorganization and random mask strategies, forming an improved MVL encryption method for video streaming. For verifying the effectiveness of the method, we implement an FPGA-based experimental system to encrypt and decrypt real-time video streaming data. In this system, 16-quit reconfigurable quaternary logic operators are implemented to encrypt, decrypt and derive keys. The process of either encryption or decryption only takes 34 clock cycles. The encryption and decryption modules are capable of processing streaming data at a speed of 6.21 Gbit/s, showing that the system has real-time processing capability. For proving that our method is secure, we compare our improved MVL encryption method with existing image encryption methods in terms of common security evaluation metrics. Experimental results show that our method solves the problem of remained color edge and the ciphertext exhibits good statistical properties.

With the development of Internet technology, online learning is becoming more and more popular. However, college students have different online learning behaviors and attitudes toward artificial intelligence (AI) learning tools. In this paper, a portrait model is proposed for college students, which focuses on their online learning behavior and attitudes toward AI learning tools. Moreover, the proposed portrait model is built based on AI technology, i.e., random forest algorithm and long short-term memory (LSTM) algorithm are applied. In this model, there are three main parts: data pre-processing, building a multi-dimensional label system, and portrait model of college students. Firstly, the information collected through the questionnaire is quantified and its quality is improved by deleting invalid data. Then, a multi-dimensional label system is built for college students’ portraits, including basic attributes, online behavior attributes, behavioral attributes of using learning software, and psychological attributes of AI learning tools. Since each label consists of multiple indexes, the variance-based filtering method is used to streamline the indexes of online behavior attributes and behavioral attributes of using learning software, the random forest algorithm is applied to reduce the dimension of psychological attributes of AI learning tools. Next, the portrait of college students’ online learning behavior is realized by the K-means clustering algorithm, and the LSTM algorithm is performed to get the mapping mechanism between data and portrait categories. Through the mapping mechanism, the portrait of any new college student who is not included in the original dataset can be obtained quickly. Finally, the validity of the proposed model is verified by analyzing the questionnaire results of college students. Additionally, the portrait results provide a data basis for the development and popularization of AI learning tools.

Abstract Background A major shift in the “dynamic zero-COVID” policy was announced by China’s National Health Commission on December 7, 2022, and the subsequent immediate large-scale outbreak of SARS-CoV-2 infections in the entire country has caused worldwide concern. This observational cross-sectional study aimed to describe the epidemiological characteristics of this outbreak in Sichuan, China. Methods All data were self-reported online by volunteers. We described the epidemic by characterizing the infection, symptoms, clinical duration, severity, spatiotemporal clustering, and dynamic features of the disease. Prevalence ratio (PR), Odds ratios (ORs) and adjusted ORs were calculated to analyze the associations between risk factors and infection and the associations of risk factors with clinical severity using log-binomial and multivariable logistic regression models; 95% confidence intervals (CIs) and Wald test results were reported. The prevalence rates and clinical severity among different subgroups were compared using the Chi-square and trend Chi-square tests. Results Between January 6 and 12, 2023, 138,073 volunteers were enrolled in this survey, and 102,645 were infected with COVID-19, holding a prevalence rate of 74.34%; the proportion of asymptomatic infections was 1.58%. Log-binomial regression revealed that the risk of infection increased among those living in urban areas. Multivariable logistic regression analysis showed that female sex, chronic diseases, older age and the fewer doses of vaccine received were associated with an increased risk of severe clinical outcomes after infection. We estimated the mean reproduction number during this pandemic was 1.83. The highest time-dependent reproduction number was 4.15; this number decreased below 1 after 11 days from December 7, 2022. Temporal trends revealed a single peak curve with a plateau pattern of incidence during the outbreak, whereas spatiotemporal clustering analysis showed that the onset in 21 cities in the Sichuan province had four-wave peaks. Conclusions The peak of the first wave of Omicron infection in Sichuan Province had passed and could be considered a snapshot of China under the new control strategy. There were significant increases in the risk of severe clinical outcomes after infection among females, with chronic diseases, and the elderly. The vaccines have been effective in reducing poor clinical outcomes.

The clustered regularly interspaced short palindromic repeat (CRISPR)-Cas12a system is a powerful tool in gene editing; however, crRNA-DNA mismatches might induce unwanted cleavage events, especially at the distal end of the PAM. To minimize this limitation, we engineered a hyper fidelity AsCas12a variant carrying the mutations S186A/R301A/T315A/Q1014A/K414A (termed HyperFi-As) by modifying amino acid residues interacting with the target DNA and crRNA strand. HyperFi-As retains on-target activities comparable to wild-type AsCas12a (AsCas12aWT) in human cells. We demonstrated that HyperFi-As has dramatically reduced off-target effects in human cells, and HyperFi-As possessed notably a lower tolerance to mismatch at the position of the PAM-distal region compared with the wild type. Further, a modified single-molecule DNA unzipping assay at proper constant force was applied to evaluate the stability and transient stages of the CRISPR/Cas ribonucleoprotein (RNP) complex. Multiple states were sensitively detected during the disassembly of the DNA-Cas12a-crRNA complexes. On off-target DNA substrates, the HyperFi-As-crRNA was harder to maintain the R-loop complex state compared to the AsCas12aWT, which could explain exactly why the HyperFi-As has low off-targeting effects in human cells. Our findings provide a novel version of AsCas12a variant with low off-target effects, especially capable of dealing with the high off-targeting in the distal region from the PAM. An insight into how the AsCas12a variant behaves at off-target sites was also revealed at the single-molecule level and the unzipping assay to evaluate multiple states of CRISPR/Cas RNP complexes might be greatly helpful for a deep understanding of how CRISPR/Cas behaves and how to engineer it in future.

Abstract Background Stress hyperglycemia was positively associated with poor prognosis in individuals with acute myocardial infarction (AMI). However, admission glucose and stress hyperglycemia ratio (SHR) may not be the best indicator of stress hyperglycemia. We performed this study to evaluate the comparative prognostic value of different measures of hyperglycemia (fasting SHR, fasting plasma glucose [FPG], and hemoglobin A1c [HbA1c]) for in-hospital mortality in AMI patients with or without diabetes. Methods In this prospective, nationwide, multicenter China Acute Myocardial Infarction (CAMI) registry, 5,308 AMI patients including 2081 with diabetes and 3227 without diabetes were evaluated. Fasting SHR was calculated using the formula [(first FPG (mmol/l))/(1.59×HbA1c (%)-2.59)]. According to the quartiles of fasting SHR, FPG and HbA1c, diabetic and non-diabetic patients were divided into four groups, respectively. The primary endpoint was in-hospital mortality. Results Overall, 225 (4.2%) patients died during hospitalization. Individuals in quartile 4 had a significantly higher rate of in-hospital mortality compared with those in quartile 1 in diabetic cohort (9.7% vs. 2.0%; adjusted odds ratio [OR] 4.070, 95% CI 2.014–8.228) and nondiabetic cohort (8.8% vs. 2.2%; adjusted OR 2.976, 95% CI 1.695–5.224). Fasting SHR was also correlated with higher in-hospital mortality when treated as a continuous variable in diabetic and nondiabetic patients. Similar results were observed for FPG either as a continuous variable or a categorical variable. In addition, fasting SHR and FPG, rather than HbA1c, had a moderate predictive value for in-hospital mortality in patients with diabetes (areas under the curve [AUC] for fasting SHR: 0.702; FPG: 0.689) and without diabetes (AUC for fasting SHR: 0.690; FPG: 0.693). The AUC for fasting SHR was not significantly different from that of FPG in diabetic and nondiabetic patients. Moreover, adding fasting SHR or FPG to the original model led to a significant improvement in C-statistic regardless of diabetic status. Conclusions This study indicated that, in individuals with AMI, fasting SHR as well as FPG was strongly associated with in-hospital mortality regardless of glucose metabolism status. Fasting SHR and FPG might be considered as a useful marker for risk stratification in this population. Trial registration: ClinicalTrials.gov NCT01874691.

A stereo vision system provides important support for underwater robots to achieve autonomous navigation, obstacle avoidance, and precise operation in complex underwater environments. This article proposes an unsupervised underwater stereo matching method based on semantic attention. By combining deep learning and semantic information, it fills the challenge of insufficient training data, enhances the intelligence level of underwater robots, and promotes the progress of underwater scientific research and marine resource development. This article proposes an underwater unsupervised stereo matching method based on semantic attention, targeting the missing training supervised dataset for underwater stereo matching. An adaptive double quadtree semantic attention model for the initial estimation of semantic disparity is designed, and an unsupervised AWLED semantic loss function is proposed, which is more robust to noise and textureless regions. Through quantitative and qualitative evaluations in the underwater stereo matching dataset, it was found that D1 all decreased by 0.222, EPE decreased by 2.57, 3px error decreased by 1.53, and the runtime decreased by 7 ms. This article obtained advanced results.

The expansion of underwater scenarios and missions highlights the crucial need for autonomous underwater vehicles (AUVs) to make informed decisions. Therefore, developing an efficient decision-making framework is vital to enhance productivity in executing complex tasks within tight time constraints. This paper delves into task planning and reconstruction within the AUV control decision system to enable intelligent completion of intricate underwater tasks. Behavior trees (BTs) offer a structured approach to organizing the switching structure of a hybrid dynamical system (HDS), originally introduced in the computer game programming community. In this research, an intelligent search algorithm, MCTS-QPSO (Monte Carlo tree search and quantum particle swarm optimization), is proposed to bolster the AUV’s capacity in planning complex task decision control systems. This algorithm tackles the issue of the time-consuming manual design of control systems by effectively integrating BTs. By assessing a predefined set of subtasks and actions in tandem with the complex task scenario, a reward function is formulated for MCTS to pinpoint the optimal subtree set. The QPSO algorithm is then leveraged for subtree integration, treating it as an optimal path search problem from the root node to the leaf node. This process optimizes the search subtree, thereby enhancing the robustness and security of the control architecture. To expedite search speed and algorithm convergence, this paper recommends reducing the search space by pre-grouping conditions and states within the behavior tree. The efficacy and superiority of the proposed algorithm are validated through security and timeliness evaluations of the BT, along with comparisons with other algorithms for automatic AUV decision control behavior tree design. Ultimately, the effectiveness and superiority of the proposed algorithm are corroborated through simulations on a multi-AUV complex task platform, showcasing its practical applicability and efficiency in real-world underwater scenarios.

Introduction Postoperative pancreatic fistula (POPF) remains one of the most severe complications of laparoscopic pancreaticoduodenectomy (LPD). Theoretically, transecting the pancreatic neck more distally has both advantages (more blood supply, and more central pancreatic duct) and disadvantages (maybe smaller the pancreatic duct) in preventing POPF. This theoretical contradiction pushed us to organise this trial to explore the impact of the level of pancreatic transection in clinical practice. We conduct this randomised trial with the hypothesis that extended pancreatic neck transection has superiority to conventional pancreatic neck transection.Methods and analysis The LPDEXCEPT (Extended pancreatic neck transection versus conventional pancreatic neck transection during laparoscopic pancreaticoduodenectomy) trial is a multicentre, randomised-controlled, open-label, superiority trial in 4 centres whose annual surgical volume for LPD is more than 25 cases with pancreatic surgeons who had completed their learning curve. A total of 154 patients who meet the inclusive and exclusive criteria are randomly allocated to the extended pancreatic neck transection group or conventional pancreatic neck transection group in a 1:1 ratio. The stratified randomised block design will be applied, with stratified factors are surgical centre and the diameter of the main pancreatic duct measured by preoperative CT scan (preMPD). The primary outcome is the incidence of the clinically relevant pancreatic fistula.Ethics and dissemination Ethics Committee on Biomedical Research of West China Hospital of Sichuan University has approved this trial in March 2023 (approval no. 2023-167). Results of this trial will be published in peer-reviewed journals and conference proceedings.Trial registration number NCT05808894.

Abstract Background Dietary management plays an important role in diabetes care, while the trends in dietary patterns over the last decade in US adults with diagnosed and undiagnosed diabetes remain unknown. This study aims to estimate the dietary patterns over the last decade by baseline diabetes diagnoses and explore their association with long-term prognosis. Methods Participants’ data were extracted from the National Health and Nutrition Examination Survey (NHANES) 2007–2018, which were divided into three groups according to the diabetes diagnosis: without diabetes, undiagnosed diabetes, and diagnosed diabetes. Healthy eating index (HEI) and dietary inflammatory index (DII) were used to evaluate dietary patterns. Survival analyses were adopted to estimate the association between HEI/DII scores and long-term all-cause mortality and cause-specific mortality. Results The prevalence of diabetes was increasing among US adults over the last decade. HEI scores of all three groups presented a downward trend in recent years. Participants with undiagnosed diabetes (weighted mean: 50.58, 95% CI: 49.79, 51.36) got significantly lower HEI score in comparison to participants with diagnosed diabetes (weighted mean: 51.59, 95% CI: 50.93, 52.25). Compared with participants without diabetes, participants in the undiagnosed or diagnosed diabetes group had higher DII scores, indicating a higher dietary inflammatory potential. Survival analysis found a significant association between HEI scores and all-cause mortality and death of heart diseases. Similar correlation was observed in DII scores. Conclusions Along with the growth in diabetes prevalence in the US, dietary management of people with diabetes is decreasing. The management of US adults’ diets needs special attention, and dietary inflammatory potential may be considered in the dietary intervention.

Abstract Objective To summarise the dynamic characteristics of COVID-19 transmissibility; To analyse and quantify the effect of control measures on controlling the transmissibility of COVID-19; To predict and compare the effectiveness of different control measures. Methods We used the basic reproduction number ( $${R}_{0}$$ R 0 ) to measure the transmissibility of COVID-19, the transmissibility of COVID-19 and control measures of 176 countries and regions from January 1, 2020 to May 14, 2022 were included in the study. The dynamic characteristics of COVID-19 transmissibility were summarised through descriptive research and a Dynamic Bayesian Network (DBN) model was constructed to quantify the effect of control measures on controlling the transmissibility of COVID-19. Results The results show that the spatial transmissibility of COVID-19 is high in Asia, Europe and Africa, the temporal transmissibility of COVID-19 increases with the epidemic of Beta and Omicron strains. Dynamic Bayesian Network (DBN) model shows that the transmissibility of COVID-19 is negatively correlated with control measures. Restricting population mobility has the strongest effect, nucleic acid testing (NAT) has a strong effect, and vaccination has the weakest effect. Conclusion Strict control measures are essential for controlling the COVID-19 outbreak; Restricting population mobility and nucleic acid testing (NAT) have significant impacts on controlling the COVID-19 transmissibility, while vaccination has no significant impact. In light of these findings, future control measures may include the widespread use of new NAT technology and the promotion of booster immunization.

Membrane technology holds great promise in separating monovalent cations but the sub-nanometer ion size and the small difference in ion size makes separation of monovalent cations a challenging task. Here, the authors demonstrate the efficient separation of monovalent cations using a COF membrane.

Abstract Aqueous two-phase system features with ultralow interfacial tension and thick interfacial region, affording unique confined space for membrane assembly. Here, for the first time, an aqueous two-phase interfacial assembly method is proposed to fabricate covalent organic framework (COF) membranes. The aqueous solution containing polyethylene glycol and dextran undergoes segregated phase separation into two water-rich phases. By respectively distributing aldehyde and amine monomers into two aqueous phases, a series of COF membranes are fabricated at water–water interface. The resultant membranes exhibit high NaCl rejection of 93.0–93.6% and water permeance reaching 1.7–3.7 L m−2 h−1 bar−1, superior to most water desalination membranes. Interestingly, the interfacial tension is found to have pronounced effect on membrane structures. The appropriate interfacial tension range (0.1–1.0 mN m−1) leads to the tight and intact COF membranes. Furthermore, the method is extended to the fabrication of other COF and metal–organic polymer membranes. This work is the first exploitation of fabricating membranes in all-aqueous system, confering a green and generic method for advanced membrane manufacturing.

Background Serum uric acid (UA) is correlated closely with traditional cardiovascular risk factors, which might interfere with the action of UA, in patients with coronary artery disease. We performed this study to evaluate the prognostic effect of UA levels in individuals with different numbers of standard modifiable cardiovascular risk factors (SMuRFs). Methods and Results In this prospective study, we consecutively enrolled 10 486 patients with coronary artery disease. They were stratified into 3 groups according to the tertiles of UA concentrations and, within each UA tertile, further classified into 3 groups by the number of SMuRFs (0–1 versus 2–3 versus 4). The primary end point was major adverse cardiovascular and cerebrovascular events (MACCEs), including death, myocardial infarction, stroke, and unplanned revascularization. Over a median follow‐up of 2.4 years, 1233 (11.8%) MACCEs were recorded. Patients with high UA levels developed significantly higher risk of MACCEs than those with low UA levels. In addition, UA levels were positively associated with MACCEs as a continuous variable. More importantly, in patients with 0 to 1 SMuRF, the risks of MACCEs were significantly higher in the high‐UA‐level group (adjusted hazard ratio [HR], 1.469 [95% CI, 1.197–1.804]) and medium‐UA‐level group (adjusted HR, 1.478 [95% CI, 1.012–2.160]), compared with the low‐UA‐level group, whereas no significant association was found between UA levels and the risk of MACCEs in participants with 2 to 3 or 4 SMuRFs. Conclusions In patients with coronary artery disease who received evidence‐based secondary prevention therapies, elevated UA levels might affect the prognosis of individuals with 0 to 1 SMuRF but not that of individuals with ≥2 SMuRFs.

The complex underwater environment poses significant challenges for unmanned underwater vehicles (UUVs), particularly in terms of communication constraints and the need for precise cooperative obstacle avoidance and trajectory tracking. Addressing these challenges solely through position information is crucial in this field. This study explores the intricate task of managing a group of UUVs as they navigate obstacles and follow a given trajectory, all based on position information. A new dynamic interactive topology framework utilizing sonar technology has been developed for the UUVs. This framework not only provides position information for the UUV swarm but also for the surrounding obstacles, enhancing situational awareness. Additionally, a bio-inspired cooperative control strategy designed for UUV swarms utilizing sonar interaction topology is introduced. This innovative method eliminates the need for velocity data from neighboring UUVs, instead relying solely on position information to achieve swarm cooperative control, obstacle avoidance, and trajectory adherence. The effectiveness of this method is validated through extensive simulations. The results show that the proposed method demonstrates improved sensitivity in obstacle detection, enabling faster trajectory tracking while maintaining a safer distance compared to traditional methods. Ultimately, this innovative strategy not only enhances operational efficiency but also enhances safety measures in UUV swarm operations.

UUVs (unmanned underwater vehicles) perform tasks in the marine environment under direction from a commander through a mother ship control system. In cases where communication is available, a UUV task re-planning system was designed to ensure task completion despite uncertain events faced by UUVs. First, the XML language standardizes the expression of UUV task elements. Second, considering the time sequence and spatial path planning requirements of human-supervised UUV control tasks, time sequence planning based on a genetic algorithm and spatial path planning based on an improved genetic algorithm were designed to plan near-optimal approximate spatial paths for control tasks. Third, uncertainties encountered during UUV task execution were classified so that the commander could adjust according to the situation or invoke the control task re-planning algorithm to re-plan. Finally, a simulation platform was built using the QT development environment to simulate human-supervised UUV control task planning and re-planning, verifying the algorithm’s design effectiveness.

Deep reinforcement learning is an artificial intelligence technology that combines deep learning and reinforcement learning and has been widely applied in multiple fields. As a type of deep reinforcement learning algorithm, the A3C (Asynchronous Advantage Actor-Critic) algorithm can effectively utilize computer resources and improve training efficiency by synchronously training Actor-Critic in multiple threads. Inspired by the excellent performance of the A3C algorithm, this paper uses the A3C algorithm to solve the UUV (Unmanned Underwater Vehicle) collision avoidance planning problem in unknown environments. This collision avoidance planning algorithm can have the ability to plan in real-time while ensuring a shorter path length, and the output action space can meet the kinematic constraints of UUVs. In response to the problem of UUV collision avoidance planning, this paper designs the state space, action space, and reward function. The simulation results show that the A3C collision avoidance planning algorithm can guide a UUV to avoid obstacles and reach the preset target point. The path planned by this algorithm meets the heading constraints of the UUV, and the planning time is short, which can meet the requirements of real-time planning.

A UUV can perform tasks such as underwater surveillance, reconnaissance, surveillance, and tracking by being equipped with sensors and different task modules. Due to the complex underwater environment, the UUV must have good collision avoidance planning algorithms to avoid various underwater obstacles when performing tasks. The existing path planning algorithms take a long time to plan and have poor adaptability to the environment. Some collision-avoidance planning algorithms do not take into account the kinematic limitations of the UUV, thus placing high demands on the performance and control algorithms of UUV. This article proposes a PPO−DWA collision avoidance planning algorithm for the UUV under static unknown obstacles, which is based on the proximal policy optimization (PPO) algorithm and the dynamic window approach (DWA). This algorithm acquires the obstacle information from forward-looking sonar as input and outputs the corresponding continuous actions. The PPO−DWA collision avoidance planning algorithm consists of the PPO algorithm and the modified DWA. The PPO collision avoidance planning algorithm is only responsible for outputting the continuous angular velocity, aiming to reduce the difficulty of training neural networks. The modified DWA acquires obstacle information and the optimal angular velocity from the PPO algorithm as input, and outputs of the linear velocity. The collision avoidance actions output by this algorithm meet the kinematic constraints of UUV, and the algorithm execution time is relatively short. The experimental data demonstrates that the PPO−DWA algorithm can effectively plan smooth collision-free paths in complex obstacle environments, and the execution time of the algorithm is acceptable.

Collision avoidance planning has always been a hot and important issue in the field of unmanned aircraft research. In this article, we describe an online collision avoidance planning algorithm for autonomous underwater vehicle (AUV) autonomous navigation, which relies on its own active sonar sensor to detect obstacles. The improved particle swarm optimization (I-PSO) algorithm is used to complete the path planning of the AUV under the known environment, and we use it as a benchmark to improve the fitness function and inertia weight of the algorithm. Traditional path-planning algorithms rely on accurate environment maps, where re-adapting the generated path can be highly demanding in terms of computational cost. We propose a deep reinforcement learning (DRL) algorithm based on collision avoidance tasks. The algorithm discussed in this paper takes into account the relative position of the target point and the rate of heading change from the previous timestep. Its reward function considers the target point, running time and turning angle at the same time. Compared with the LSTM structure, the Gated Recurrent Unit (GRU) network has fewer parameters, which helps to save training time. A series of simulation results show that the proposed deep deterministic policy gradient (DDPG) algorithm can obtain excellent results in simple and complex environments.

Background The PRAISE (Prediction of Adverse Events Following an Acute Coronary Syndrome) score is a machine‐learning‐based model for predicting 1‐year all‐cause death, myocardial infarction, and Bleeding Academic Research Consortium (BARC) type 3/5 bleeding. Its utility in an unselected Asian population undergoing percutaneous coronary intervention for acute coronary syndrome remains unknown. We aimed to validate the PRAISE score in a real‐world Asian population. Methods and Results A total of 6412 consecutive patients undergoing percutaneous coronary intervention for acute coronary syndrome were prospectively included. The PRAISE scores were compared with established scoring systems (GRACE [Global Registry of Acute Coronary Events] 2.0, PRECISE‐DAPT (Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy), and PARIS [Patterns of Non‐Adherence to Anti‐Platelet Regimen in Stented Patients]) to evaluate their discrimination, calibration, and reclassification. The risk of all‐cause mortality (hazard ratio [HR], 12.24 [95% CI, 5.32–28.15]) and recurrent acute myocardial infarction (HR, 3.92 [95% CI, 1.76–8.73]) was greater in the high‐risk group than in the low‐risk group. The C‐statistics for death, myocardial infarction, and major bleeding were 0.75 (0.67–0.83), 0.61 (0.52–0.69), and 0.62 (0.46–0.77), respectively. The observed to expected ratio of death, myocardial infarction, and major bleeding was 0.427, 0.260, and 0.106, respectively. Based on the decision curve analysis, the PRAISE score displayed a slightly greater net benefit for the 1‐year risk of death (5%–10%) than the GRACE score did. Conclusions The PRAISE score showed limited potential for risk prediction in our validation cohort with acute coronary syndrome. As a result, new prediction models or model refitting are required with improved discrimination and accuracy in risk prediction.

Evidence shows that some class I human leucocyte antigen (HLA) alleles are related to durable HIV controls. The T18A TCR, which has the alloreactivity between HLA-B∗42:01 and HLA-B∗81:01 and the cross-reactivity with different antigen mutants, can sustain long-term HIV controls. Here the structural basis of the T18A TCR binding to the immunodominant HIV epitope TL9 (TPQDLNTML180-188) presented by HLA-B∗42:01 was determined and compared to T18A TCR binding to the TL9 presented by the allo-HLA-B∗81:01. For differences between HLA-B∗42:01 and HLA-B∗81:01, the CDR1α and CDR3α loops adopt a small rearrangement to accommodate them. For different conformations of the TL9 presented by different HLA alleles, not like the conventional recognition of CDR3s to interact with peptide antigens, CDR3β of the T18A TCR shifts to avoid the peptide antigen but intensively recognizes the HLA only, which is different with other conventional TCR structures. Featured sequence pairs of CDR3β and HLA might account for this and were additionally found in multiple other diseases indicating the popularity of the unconventional recognition pattern which would give insights into the control of diseases with epitope mutating such as HIV.

This study examines the exogenous institutional impact of minimum wage policy on enterprise financialization in China. Empirical results show that an increased minimum wage significantly promotes the financialization of real enterprises. Moreover, the impact is more pronounced in enterprises characterised by a more significant profit margin gap between tangible and financial assets and higher degrees of labour-intensiveness. Further tests reveal that the promotional effect of the minimum wage on the financialization of labour-intensive enterprises tends to be more substantial under the following circumstances: (i) a smaller gap exists between an enterprise’s average wage and the local minimum wage; (ii) an enterprise finds it more challenging to pass on costs to the market; (iii) following the implementation of the Labour Contract Law. Further investigation indicates that raising the minimum wage exacerbates the adverse effects of enterprise financialization on corporate value.

Based on the exogenous shock of the bank lending interest rate ceiling deregulation in China, this paper uses a difference-in-differences model and studies how credit availability affects classification shifting from the perspective of formal debt contract formation. We find that high-risk firms’ classification shifting degree is higher after the bank lending interest rate ceiling deregulation. Cross-sectional heterogeneity tests show that the impact of the deregulation on classification shifting is stronger when the level of financing constraints is higher, the diversity of financing channels is lower, the bank’s need for information is higher, and the bank’s monitoring is higher. Mechanism tests further show that the deregulation enables high-risk firms to increase borrowing through classification shifting. We use the unique setting of China interest rate liberalisation to scientifically identify the debt financing motivation for classification shifting. This study expands and enriches the institutional determinants of accounting information production.

With the development of the economy and real-time embedded systems and the progress of science and technology, people’s economic income forms have undergone tremendous changes, and the concept of financial management has become clearer in people’s property income arrangements. Project investment is one of the most popular financial management methods in the era of big data. Both large enterprise groups and individual petty bourgeoisie groups have begun to pay attention to the risks and benefits brought by the new financial management method of project investment. This paper’s goal is to develop a fuzzy comprehensive evaluation (FCE) model for project investment risk based on computer vision technology and explore the application of computer vision technology in project investment risk evaluation. This article first uses a real-time embedded system to understand the basic process of project investment and select 10 investment experts for risk assessment, risks, and causes of the risks through literature research and case analysis. Then, this paper establishes a model of fuzzy comprehensive evaluation of project investment risk through computer vision technology, real-time embedded systems, and neural network models in big data and artificial intelligence technology to realize the analysis and prediction of project investment risk. The fuzzy comprehensive evaluation method and analytic hierarchy process (AHP) are used in this evaluation model to evaluate and forecast project investment risks. In addition, this paper also trains and tests the risk evaluation model of this research through the support vector machine classification algorithm, the real-time embedded system, and the average random consistency index. The research shows that the fuzzy comprehensive evaluation model of this study has higher accuracy for project investment risk evaluation than other risk evaluation methods. For example, for the investment risk of chemical fiber projects, this research model evaluated the factors such as organization, management, technology, and economy and found that the risks were all higher than 21.36%, which concluded that the overall investment risk of chemical fiber projects was relatively high.

Background: Recommendations for drug treatment of left ventricular thrombus (LVT) are based on the ST-segment elevation myocardial infarction (STEMI) guidelines; however, the etiology of LVT has changed. Due to the lack of evidence regarding LVT treatment in the heart failure population, current heart failure guidelines do not cover LVT treatment. We sought to review the etiology of LVT and changes in antithrombotic therapy over the previous 12 years and explore the impact of anticoagulation treatment from a single center’s experience. Methods: From January 2009 to June 2021, we studied 1675 patients with a discharge diagnosis of LVT at a single center to investigate the clinical characteristics, incidence of all-cause death, cardiovascular death, ischemic stroke, major adverse cardiac and cerebrovascular events (MACCE), systemic embolism (SE), and major bleeding events. Patients were divided into an anticoagulant group and a non-anticoagulant group according to whether they received oral anticoagulant therapy at discharge. Results: The study included 909 patients (anticoagulation, 510; no anticoagulation, 399). While overall antiplatelet therapy dramatically decreased, more patients with LVT received oral anticoagulation in 2021 (74.0%) than in 2009 (29.6%). In addition, more than half of the patients had heart failure with reduced ejection fraction (HFrEF) each year. The all-cause mortality was 17.3% during 3.8 years of follow-up. The incidences of cardiovascular death, stroke, MACCE, SE, and major bleeding were 16.0%, 3.3%, 19.8%, 5.1%, and 1.7%, respectively. The anticoagulation group had a significantly higher proportion of dilated cardiomyopathy than the non-anticoagulation group (24.7% vs. 5.5%, p < 0.001), and a lower LVEF (34.0 vs. 41.0, p < 0.001). The anticoagulation group also had a higher probability of adverse events on long-term follow-up (p > 0.05). A multivariable competing risk regression model found no significant difference in all six endpoints between the groups (all p > 0.05). Similar results were found by matched and weighted data analysis. Diabetes mellitus (hazard ratio (HR), 1.42; 95% confidence interval (CI), 1.04–1.93; p = 0.027), renal insufficiency (HR, 2.36; 95% CI, 1.60–3.50; p < 0.001), history of previous stroke (HR, 1.60; 95% CI, 1.13–2.29; p = 0.009), and HFrEF (HR, 2.54; 95% CI, 1.78–3.64; p < 0.001) were predictors of increased risk of MACCE. Conclusions: Heart failure, rather than acute myocardial infarction, is currently the primary cause of LVT. A trend towards better prognosis in the no anticoagulation group was noted. Multivariable, matching and weighting analysis showed no improvement in prognosis with anticoagulant therapy. Our study does not negate the efficacy of anticoagulation but suggests the need to strengthen the management of anticoagulation in order to achieve better efficacy.

The large amount of recycled asphalt pavement mixture (RAP) generated during renovations has a negative impact on the environment. In recent years, how to rationally recycle and reuse RAP has become a hot research direction in the field of highway construction. However, the recycled asphalt binder has some problems such as instability, easy aging and decreased adhesion. In this paper, carbon nanotubes and waste engine oil were used to modify recycled asphalt binder. Through a high-temperature rutting test, low-temperature bending test and Marshall stability test, the properties of an asphalt mixture with 40% RAP modified by carbon nanotubes and waste engine oil, an asphalt mixture with 40% RAP and an asphalt mixture without RAP were compared and analyzed. The tests showed that 1.5 wt% carbon nanotubes could improve the performance of the old asphalt binder most significantly. After adding 1.5 wt% carbon nanotubes, the high-temperature rutting resistance of the asphalt mixture was increased by 24.3%, and the bending stiffness modulus and the best crack resistance at low temperature increased significantly. In addition, after adding 1.5 wt% carbon nanotubes, the Marshall stability of the waste-engine-oil-modified RAP could be restored to the level of the new asphalt mixture. In summary, carbon nanotubes can improve the high-temperature stability, low-temperature crack resistance and Marshall stability of waste-engine-oil-modified RAP.

The assessment of multiple incoming autonomous underwater vehicles (multi-AUVs) and threat prioritization are critical to underwater defense. To solve problems troubling multi-AUV threat assessment solutions, such as difficult data analysis, high subjectivity, and rigid prioritization logic, we propose the PROMETHEE algorithm based on fusion weights calculated twice by entropy and an analytic network process (ANP), respectively. First, according to AUV detection performance and underwater confrontation situation analysis, the main criteria and indicators of threat assessment are determined. The threat assessment system is provided by unified measurement of these indicators. Then, through analysis and assessment, the weighting algorithm is designed using entropy and ANP. The subjective weight calculated based on ANP and the objective weight obtained based on the entropy method are fused twice to obtain the combined weights, and the influence of subjective and objective factors on problem analysis is considered. Finally, by analyzing the simulation results of a multi-AUV, it is proven that the proposed algorithm is scientific and effective for AUV threat assessment. According to the experimental results, accurate evaluation of the target improved by at least 10%, enabling delivery of results close to the real confrontation situation with high reliability.

Understanding the failure mechanisms of rocks that are exposed to different water contents is important for rock stability in rock engineering applications, and the quantitative analysis of rock behavior is necessary for predicting and preventing the occurrence of rock failure due to water effects. Mechanical tests using real-time acoustic emission (AE) technology were carried out to reveal the damage evolution in sandstone rocks in a dried state, natural state, and saturated state, which includes a quantitative analysis of AE characteristics and cracking properties. The testing results indicate that with the growth of water content, sandstone rocks show a decreasing trend in strength and tend to experience gentle damage with relatively fewer fractures. The crack morphology of the main fracture surfaces is quantitatively described, including a fractal dimension calculation and cracking length measurements. As the water content rises, when rock failure occurs, a higher AE b-value can be obtained, revealing an increasing proportion of large-scale cracks. The fractal dimension of the acoustic emission hit rate shows that the evolution of rock damage and deformation has self-similarity, that is, the transformation from order to disorder to order, and it is affected by different water contents. The AE waveforms of the sandstone have two dominant frequency bands (0~75 kHz and 75~150 kHz) no matter which water-bearing state they are in. The increase in rock water content has resulted in the decline of AE waveforms located in the range of 200–300 kHz, whereas the rise of AE waveforms is located in the range of 0–50 kHz. The findings of this study deepen our understanding of the mechanism behind rock failure and provide a meaningful reference for disaster assessment and control.

The normal operation of aircraft and flights can be affected by various unpredictable factors, such as severe weather, airport closure, and corrective maintenance, leading to disruption of the planned schedule. When a disruption occurs, the airline operation control center performs various operations to reassign resources (e.g., flights, aircraft, and crews) and redistribute passengers to restore the schedule while minimizing costs. We introduce different sources of disruption and corresponding operations. Then, basic models and recently proposed extensions for aircraft recovery, crew recovery, and integrated recovery are reviewed, with the aim of providing models and methods for different disruption scenarios in the practical implementation of airlines. In addition, we provide suggestions for future research directions in these topics.

BackgroundThe objective of our study was to assess whether calculated low-density lipoprotein cholesterol (LDL-C) is inferior to direct LDL-C (dLDL-C) in identifying patients at higher risk of all-cause mortality, recurrent acute myocardial infarction (AMI), and major adverse cardiovascular event (MACE).MethodsA total of 9,751 patients with coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI) in the Fuwai PCI registry were included. DLDL-C was measured by the selective solubilization method (Kyowa Medex, Tokyo, Japan). Correct classification was defined as the proportion of estimated LDL-C in the same category as dLDL-C based on dLDL-C levels: less than 1.4, 1.4–1.8, 1.8–2.6, 2.6–3.0, and 3.0 mmol/L or greater.ResultsUnderestimation of LDL-C was found in 9.7% of patients using the Martin/Hopkins equation, compared with 13.9% using the Sampson equation and 24.6% with the Friedewald equation. Cox regression analysis showed compared the correct estimation group, underestimation of LDL-C by the Martin/Hopkins equation did not reduce all-cause mortality (HR 1.26, 95% CI: 0.72–2.20, P = 0.4), recurrent AMI (HR 1.24, 95% CI: 0.69–2.21, P = 0.5), and MACE (HR 1.02, 95% CI: 0.83–1.26, P = 0.9). Similarly, the overestimated group did not exacerbate all-cause mortality (HR 0.9, 95% CI: 0.45–1.77, P = 0.8), recurrent AMI (HR 0.63, 95% CI: 0.28–1.44, P = 0.3), and MACE (HR 1.07, 95% CI: 0.86–1.32, P = 0.6). The results of the diabetes subgroup analysis were similar to those of the whole population.ConclusionCompared with dLDL-C measurement, misclassification by the Martin/Hopkins and Sampson equations was present in approximately 20% of patients. However, directly measured vs. calculated LDL-C did not identify any more individuals in the PCI population with increased risk of all-cause mortality, recurrent AMI, and MACE, even in high-risk patients such as those with diabetes.

BackgroundThe prognostic effect of admission blood glucose (ABG) for patients with acute myocardial infarction (AMI) has not been well validated, especially in patients with diabetes. We performed this study to assess the predictive value of ABG for all-cause mortality in AMI patients with different glucose metabolism status.MethodsWe evaluated a total of 6,892 AMI patients from the prospective, nationwide, multicenter CAMI registry, of which 2,820 had diabetes, 2,011 had pre-diabetes, and 2,061 had normal glucose regulation (NGR). Patients were divided into high ABG and low ABG groups according to the optimal cutoff values of ABG to predict 2-year mortality for patients with diabetes, pre-diabetes and NGR, respectively. The primary endpoint was all-cause mortality.ResultsThe optimal cutoff values of ABG for predicting 2-year mortality was 9.0mmol/l, 7.2mmol/l and 6.2mmol/l for patients with diabetes, pre-diabetes and NGR, respectively. Overall, the risk of all-cause mortality in high ABG group was significantly increased compared with that in low ABG group among patients with diabetes (15.2% vs. 8.9%; hazard ratio [HR] 1.787, 95% confidence interval [CI] 1.413-2.260; P

Background Lp(a) (lipoprotein[a]) plays an important role in predicting cardiovascular events in patients with coronary artery disease through its proatherogenic and prothrombotic effects. We hypothesized that prolonged dual antiplatelet therapy (DAPT) might be beneficial for patients undergoing percutaneous coronary intervention who had elevated Lp(a) levels. This study aimed to evaluate the effect of Lp(a) on the efficacy and safety of prolonged DAPT versus shortened DAPT in stable patients with coronary artery disease who were treated with a drug‐eluting stent. Methods and Results We selected 3201 stable patients with CAD from the prospective Fuwai Percutaneous Coronary Intervention Registry, of which 2124 patients had Lp(a) ≤30 mg/dL, and 1077 patients had Lp(a) >30 mg/dL. Patients were divided into 4 groups according to Lp(a) levels and the duration of DAPT therapy (≤1 year versus >1 year). The primary end point was major adverse cardiovascular and cerebrovascular event, defined as a composite of all‐cause death, myocardial infarction, or stroke. The median follow‐up time was 2.5 years. Among patients with elevated Lp(a) levels, DAPT >1 year presented lower risk of major adverse cardiovascular and cerebrovascular event and definite/probable stent thrombosis compared with DAPT ≤1 year. In contrast, in patients with normal Lp(a) levels, the risks of major adverse cardiovascular and cerebrovascular event and definite/probable stent thrombosis were not significantly different between the DAPT >1 year and DAPT ≤1 year groups. Prolonged DAPT had 2.4‐times higher risk of clinically relevant bleeding than shortened DAPT in patients with normal Lp(a) levels, although without statistical difference. Conclusions In stable patients with coronary artery disease, who underwent percutaneous coronary intervention with a drug‐eluting stent, prolonged DAPT was associated with reduced risk of cardiovascular events among those with elevated Lp(a) levels, whereas it did not show statistically significant evidence of benefit for reducing ischemic events and tended to increase clinically relevant bleeding among those with normal Lp(a) levels.

Taken the cancellation of the upper limit of loan interest rates as a quasinatural experiment and based on the signal theory of auditor demand, this paper investigates how the improvement of credit availability affects the choice of auditors. Results show that, compared with low-risk enterprises, high-risk enterprises tend to choose high-quality audits because of the increased loan availability after the liberalisation of the loan interest rate ceiling, and this tendency is more pronounced in the corporations with higher financing constraints. The above results are still valid after a series of robustness tests. Further analysis reveals that high-risk companies choosing high-quality auditors do obtain more long-term loans after the loan interest rate ceiling was lifted. This study identifies the causal relationship between credit availability and auditor choice, and also provides empirical evidence for the signal function of high-quality auditors in China’s credit market.

With the vigorous development of deep learning and the widespread use of mobile robots, automatic driving has gradually become a research hotspot. Environment perception is the most important part of automatic driving technology, and the purpose of environment perception is to distinguish the environmental content. Therefore, accurate and efficient image semantic segmentation method is becoming more and more important. In this paper, we introduce a deep semantic segmentation solution: IIE-SegNet: Deep semantic segmentation network with enhanced boundary based on image information entropy. At present, deep learning based on semantic segmentation solutions has some problems, such as low segmentation accuracy for small-scale objects and unclear boundary of segmented objects. Our method preserves the boundary of the segmentation object, and has higher segmentation accuracy for small-scale objects. In our method, the features of the underlying pooling layer are added to the ASPP structure of the encoding module, and the image information entropy of the previous pooling layers is introduced into the decoding module. We also introduce focal loss to solve the problem of imbalance between positive and negative samples. Finally, the test results on the extended Pascal VOC 2012 test set, abbreviated to Exp-Pascal VOC 2012 test set show that the proposed method has better performance on Exp-Pascal VOC 2012 test set compared with the advanced methods at the present stage, the segmentation accuracy of small-scale targets is higher, and the boundary is clearer.

Abstract Background AsCas12a and LbCas12a nucleases are reported to be promising tools for genome engineering with protospacer adjacent motif (PAM) TTTV as the optimal. However, the C-containing PAM (CTTV, TCTV, TTCV, etc.) recognition by Cas12a might induce extra off-target edits at these non-canonical PAM sites. Results Here, we identify a novel Cas12a nuclease CeCas12a from Coprococcus eutactus, which is a programmable nuclease with genome-editing efficiencies comparable to AsCas12a and LbCas12a in human cells. Moreover, CeCas12a is revealed to be more stringent for PAM recognition in vitro and in vivo followed by very low off-target editing rates in cells. Notably, CeCas12a renders less off-target edits located at C-containing PAM at multiple sites compared to LbCas12a and AsCas12a, as assessed by targeted sequencing methods. Conclusions Our study shows that CeCas12a nuclease is active in human cells and the stringency of PAM recognition could be an important factor shaping off-target editing in gene editing. Thus, CeCas12a provides a promising candidate with distinctive characteristics for research and therapeutic applications.

Adaptive array processing technology for a phased array radar is usually based on the assumption of a stationary environment; however, in real-world scenarios, nonstationary interference and noise deteriorate the performance of the traditional gradient descent algorithm, in which the learning rate of the tap weights is fixed, leading to errors in the beam pattern and a reduced output signal-to-noise ratio (SNR). In this paper, we use the incremental delta-bar-delta (IDBD) algorithm, which has been widely used for system identification problems in nonstationary environments, to control the time-varying learning rates of the tap weights. The designed iteration formula for the learning rate ensures that the tap weights adaptively track the Wiener solution. The results of numerical simulations show that in a nonstationary environment, the traditional gradient descent algorithm with a fixed learning rate has a distorted beam pattern and reduced output SNR; however, the IDBD-based beamforming algorithm, in which a secondary control mechanism is used to adaptively update the learning rates, showed a similar beam pattern and output SNR to a traditional beamformer in a Gaussian white noise background; that is, the main beam and null satisfied the pointing constraints, and the optimal output SNR was obtained. Although the proposed algorithm contains a matrix inversion operation, which has considerable computational complexity, this operation could be replaced by the Levinson–Durbin iteration due to the Toeplitz characteristic of the matrix; therefore, the computational complexity could be decreased to O(n), so additional computing resources are not required. Moreover, according to some intuitive interpretations, the reliability and stability of the algorithm are guaranteed.

Background: The focus of this investigation into the impact of type 2 diabetes mellitus (T2DM) on left ventricular thrombus (LVT) is (a) the differences in LVT characteristics, (b) long-term clinical outcomes, and (c) differential effects of direct oral anticoagulants (DOAC) among patients with T2DM and without diabetes. Methods: Patients with confirmed LVT from 2009 to 2021 were included. The primary endpoints were major adverse cardiac and cerebrovascular events (MACCE), composite of cardiovascular death, ischemic stroke, and acute myocardial infarction (AMI). The secondary endpoints were all-cause death and cardiovascular death. Multivariable competing-risk regression and cumulative incidence functions (CIF) were used to evaluate the adverse consequences. Results: In total, 1675 patients were assessed initially. Follow-up data were available for 91.1% of the participants. Median follow-up was 3.8 years. This retrospective study ultimately comprised 1068 participants, of which 429 had T2DM. Significantly higher proportions of comorbidities were observed in the T2DM group. The location, morphology, and size of LVT were similar in the two groups. Multivariable analysis suggested a higher risk of MACCE among patients with T2DM. The difference in risk between the two groups after matching and weighting was not statistically significant. Among the whole sample (n = 638) or the just the non-diabetic patients with LVT and anticoagulation (n = 382), the incidence of MACCE did not differ between DOAC treatment and warfarin treatment. In the diabetic LVT population with anticoagulation (n = 256), DOAC treatment was associated with a significantly higher risk of MACCE than was warfarin treatment. Conclusions: The location and morphology of LVT are similar in T2DM and non-diabetic patients. A higher risk of MACCE was found among patients with diabetes.

The core technology to realize the development of unconventional oil and gas resources is the large-scale volume transformation of shale reservoirs, but volume fracturing is a complex physical and mechanical process, and its mechanism remains to be further studied. In this paper, starting from the current research status of shale volumetric fracturing, the perforation orientation of volumetric fracturing is numerically simulated by using the finite element software. The following conclusions are drawn: ① when the ground stress conditions are equal, with the increase of perforation angle, the maximum principal stress at the front of perforation decreases gradually; that is, when the perforation is along the horizontal minimum principal stress, the maximum principal stress at the front of perforation is the largest, which is most conducive to fracturing of shale reservoirs. ② When the perforation is along the direction of the horizontal minimum principal stress and the horizontal stress difference is zero, the smaller the horizontal stress, the greater the maximum principal stress at the front of the perforation. Therefore, the smaller the horizontal stress, the more conducive to the rupture of shale reservoirs. ③ When the perforation is along the horizontal minimum principal stress, the maximum principal stress at the front of the perforation increases with the increase of the horizontal stress difference. Therefore, the larger the horizontal stress difference, the more favorable for the fracture of shale reservoirs.

This work is aimed at investigating the mechanical behaviors of a fault unwelded bimrock subjected to coupled freeze-thaw (FT) and fatigue loads. The influence of FT cycle on rock strength, deformation, damage evolution, and failure morphology was detailed investigated. The testing results show that the soil-rock interface is sensitive to freeze-thaw condition. Interface damage and cracking contribute a lot to sample strength, volumetric deformation, and damage evolution. In addition, a sudden increase of stress amplitude results in the increase of damage, afterwards, the coupling degree of bimrock improves with the increase of loading cycles. A coupling freeze-thaw and mechanical damage evolution model was proposed using the damage index defined by ultrasonic velocity and axial strain. It is found that the evolution trend of the model is strongly related to the previous freeze-thaw damage. Moreover, failure mode of bimrock changes from shear failure to bulging failure with increasing FT cycles. The failure process of bimrock is the rearrangement of the fine soil particles and rock blocks, the soil matrix and rock block bear axial cyclic loads by their interactions.

Background: Lipoprotein(a) is positively related to cardiovascular events in patients with coronary artery disease (CAD). Given that lipoprotein(a) has a prothrombotic effect, prolonged dual antiplatelet therapy (DAPT) might have a beneficial effect on reducing ischemic events in patients with elevated lipoprotein(a) levels after percutaneous coronary intervention (PCI). We performed this study to assess the efficacy and safety of prolonged DAPT (>1 year) in this population.Methods: We evaluated a total of 3,025 CAD patients with elevated lipoprotein(a) levels who were event-free at 1 year after PCI from the prospective Fuwai PCI Registry, of which 913 received DAPT ≤ 1 year and 2,112 received DAPT>1 year. The primary endpoint was major adverse cardiovascular and cerebrovascular event (MACCE), defined as a composite of all-cause death, myocardial infarction or stroke.Results: After a median follow-up of 2.4 years, patients who received DAPT>1 year were associated with lower risks of MACCE compared with DAPT ≤ 1 year (1.6 vs. 3.8%; hazard ratio [HR] 0.383, 95% confidence interval [CI] 0.238–0.616), which was primarily driven by the lower all-cause mortality (0.2 vs. 2.3%; HR 0.078, 95% CI 0.027–0.227). In addition, DAPT>1 year was also associated with lower risks of cardiac death, and definite/probable stent thrombosis than those who received DAPT ≤ 1 year (P < 0.05). Conversely, no difference was found between the two groups in terms of clinically relevant bleeding. Similar results were observed in multivariate Cox regression analysis and inverse probability of treatment weighting analysis.Conclusions: In patients with elevated lipoprotein(a) concentrations after PCI, prolonged DAPT (>1 year) reduced ischemic cardiovascular events, including MACCE, all-cause mortality, cardiac mortality, and definite/probable stent thrombosis, without increase in clinically relevant bleeding risk compared with ≤ 1-year DAPT. Lipoprotein(a) levels might be a new important consideration when deciding the duration of DAPT after PCI.

IPv6 geolocation is necessary for many location-based Internet services. However, the accuracy of the current IPv6 geolocation methods including machine-learning-based or deep-learning-based location algorithms are unsatisfactory for users. Strong geographic correlation is observed for measurement path features close to the target IP, so previous methods focused more on stable paths in the vicinity of the probe. Based on this, this paper proposes a new IPv6 geolocation algorithm, SubvectorS_Geo, which is mainly divided into three steps: firstly, it filters geographically relevant routing feature codes layer by layer to approximate the fine-grained trusted region of the target; secondly, it extracts delay vectors into the trusted region; thirdly, it evaluates the vector similarity to determine the final target geolocation information. The final experiments show that the median error distance range is 7.025 km to 9.709 km on three real datasets (Shanghai, New York State, and Tokyo). Compared with the advanced method, the median distance error distance is reduced by at least 6.8% and the average error distance is reduced by at least 9.2%.

Background: Clinical guidelines recommend surgical intervention when left ventricular thrombus (LVT) is complicated with left ventricular aneurysm (LVA). Objectives: This study aimed to review the changes in the treatment of LVT combined with LVA over the past 12 years at our center and to compare the efficacy of medical therapy and surgical treatment on patient outcomes. Methods: Between January 2009 and June 2021, 723 patients with LVT combined with LVA were enrolled, of whom 205 received surgical ventricular reconstruction (SVR) therapy and 518 received medical therapy. The following clinical outcomes were gathered via observation: all-cause death, cardiovascular death, and major adverse cardiovascular and cerebrovascular events (MACCEs; defined as the composite of cardiovascular death, ischemic stroke, and acute myocardial infarction). The median follow-up time was 1403 [707, 2402] days. Results: The proportion of SVR dropped yearly in this group of patients, from a peak of 64.5% in 2010 to 7.5% in 2021 (p for trend < 0.001). Meanwhile, the proportion of anticoagulant use increased quickly, from 8.0% in 2016 to 67.9% in 2021 (p for trend < 0.001). The incidence rates of all-cause mortality, cardiovascular death, and MACCEs were 12.9% (n = 93), 10.5% (n = 76), and 14.7% (n = 106), respectively. In the multivariable analysis, there were no significant differences in all-cause death (HR of 0.60, 95% CI of 0.32–1.13, p = 0.11), cardiovascular death (HR of 0.79, 95% CI of 0.41–1.50, p = 0.5), and MACCEs (HR of 0.82, 95% CI of 0.49–1.38, p = 0.5) between the two groups. The competing risk regression performed in the propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analyses was in line with the unmatched analysis. Conclusions: The rate of SVR dropped significantly among patients with both LVT and LVA, while there was an improvement in oral anticoagulant utilization. SVR with thrombus removal did not improve all-cause mortality and cardiovascular outcomes in patients with LVT and LVA. Ventricular aneurysm with thrombus may not be an indication for surgery.

BackgroundIn China, ischemic heart disease is the main cause of mortality. Having cardiac rehabilitation and a secondary prevention program in place is a class IA recommendation for individuals with coronary artery disease. WeChat-based interventions seem to be feasible and efficient for the follow-up and management of chronic diseases. ObjectiveThis study aims to evaluate the effectiveness of a tertiary A-level hospital, WeChat-based telemedicine intervention in comparison with conventional community hospital follow-up on medication adherence and risk factor control in individuals with stable coronary artery disease. MethodsIn this multicenter prospective study, 1424 patients with stable coronary artery disease in Beijing, China, were consecutively enrolled between September 2018 and September 2019 from the Fuwai Hospital and 4 community hospitals. At 1-, 3-, 6-, and 12-month follow-up, participants received healthy lifestyle recommendations and medication advice. Subsequently, the control group attended an offline outpatient clinic at 4 separate community hospitals. The intervention group had follow-up visits through WeChat-based telemedicine management. The main end point was medication adherence, which was defined as participant compliance in taking all 4 cardioprotective medications that would improve the patient’s outcome (therapies included antiplatelet therapy, β-blockers, statins, and angiotensin-converting-enzyme inhibitors or angiotensin-receptor blockers). Multivariable generalized estimating equations were used to compare the primary and secondary outcomes between the 2 groups and to calculate the relative risk (RR) at 12 months. Propensity score matching and inverse probability of treatment weighting were performed as sensitivity analyses, and propensity scores were calculated using a multivariable logistic regression model. ResultsAt 1 year, 88% (565/642) of patients in the intervention group and 91.8% (518/564) of patients in the control group had successful follow-up data. We matched 257 pairs of patients between the intervention and control groups. There was no obvious advantage in medication adherence with the 4 cardioprotective drugs in the intervention group (172/565, 30.4%, vs 142/518, 27.4%; RR 0.99, 95% CI 0.97-1.02; P=.65). The intervention measures improved smoking cessation (44/565, 7.8%, vs 118/518, 22.8%; RR 0.48, 95% CI 0.44-0.53; P

The fabrication of defect-free covalent organic framework (COF) membranes for the separation of small molecules is challenging. Here, the authors report robust COF membranes with precise molecular sieving through a mixed-dimensional assembly, exhibiting high performance for alcohol dehydration and salt rejection.

Background and aims: Our goals in the study were to (1) quantify the discordance in LDL-C levels between equations (the Friedewald, Sampson, and Martin/Hopkins equations) and compare them with direct LDL-C (dLDL-C); and (2) explore the proportion of misclassified patients by calculated LDL-C using these three different equations. Methods: A total of 30,349 consecutive patients with angiographically confirmed coronary artery disease (CAD) were prospectively enrolled. Concordance was defined as if the LDL-C was Results: The concordance was 96.3% (Sampson vs. Martin/Hopkins), 95.0% (Friedewald vs. Sampson), and 91.4% (Friedewald vs. Martin/Hopkins), respectively. This proportion fell to 82.4% in those with hypertriglyceridemia (TG ≥ 1.7 mmol/L). With an accurate classification rate of 73.6%, the Martin/Hopkins equation outperformed the Sampson equation (69.5%) and the Friedewald equation (59.3%) by a wide margin. Conclusions: Comparing it to the validated Martin/Hopkins equation, the Friedewald equation produced the lowest levels of LDL-C, followed by the Sampson equation. In the classification of LDL-C, the Martin/Hopkins equation has also been shown to be more accurate. There is a significant difference between the equations and the direct measurement method, which may lead to overtreatment or undertreatment.

The tight sandstone reservoir in the Qianfoya formation of well PL-3 of the Puguang gas field in Sichuan, China, obtained a high-yield gas flow after a volume fracturing treatment. However, the stimulated reservoir volume (SRV), fracture morphology, scale and formation law still remain unclear. Based on particle flow discrete-element theory in this paper, we carried out a few trials of the Brazilian splitting test, uniaxial compression and triaxial compression of rock mechanics. Meanwhile, the research also testified to the conversion relationship between macroparameters and microparameters, established the numerical simulation on hydraulic fracturing through PFC2D discrete element software, and finally analyzed the influence of difference coefficients on the fracturing effect, in terms of different in-situ stresses. The conclusions are as follows: firstly, the influence of in-situ stress is essential for the direction, shape and quantity of fracture propagation, and the fractures generated by hydraulic fracturing are mainly tension fractures, accounting for over 90% of the total longitudinal fractures. Secondly, it is indicated that when the difference coefficient is small in the in-situ stress, the fractures formed by hydraulic fracturing expand randomly around the wellbore. When the difference coefficient Kh of in-situ stress is above 0.6, the development of hydraulic fractures is mainly controlled by in-situ stress; as a result, the fractures tend to expand in the vertical direction of the minimum horizontal principal stress and the fracture shape is relatively singular. When the difference coefficient of in-situ stress was 0.3, in total, 3121 fractures were generated by fracturing, and the fractal dimension D value of the fracture network complexity was 1.60. In this case, this fracturing effect was the best and it is the easiest to achieve for the purpose of economical and effective development on large-scale volume fracturing.

Suspended particles play a vital role in aquatic environments. We propose a method to rapidly measure the scattered polarization parameters of individual suspended particles with continuously large angular range (PCLAR), from 60° to 120° in one shot. A conceptual setup is built to measure PCLAR with 20 kHz; to verify the setup, 10 μm-diameter silica microspheres suspended in water, whose PCLAR are consistent with those simulated by Mie theory, are measured. PCLAR of 6 categories of particles are measured, which enables high-accuracy classification with the help of a convolutional neural network algorithm. PCLAR of different mixtures of Cyclotella stelligera and silica microspheres are measured to successfully identify particulate components. Furthermore, classification ability comparisons of different angular-selection strategies show that PCLAR enables the best classification beyond the single angle, discrete angles and small-ranged angles. Simulated PCLAR of particles with different size, refractive index, and structure show explicit discriminations between them. Inversely, the measured PCLAR are able to estimate the effective size and refractive index of individual Cyclotella cells. Results demonstrate the method’s power, which intrinsically takes the advantage of the optical polarization and the angular coverage. Future prototypes based on this concept would be a promising biosensor for particles in environmental monitoring.

Shale gas can be commercially produced using the stimulated reservoir volume (SRV) with multistage fracturing or multiwell synchronous fracturing. These fracturing technologies can produce additional stress fields that significantly influence the crack initiation pressure and the formation of an effective fracture network. Therefore, this study primarily investigated the evolution of crack initiation and propagation in a hydraulic rock mass under various stress conditions. Combining the in situ stress characteristics of a shale reservoir and fracturing technology, three types of true triaxial volumetric fracturing simulation experiments were designed and performed on shale, including three-dimensional constant loading, one-dimensional pressurization disturbance, and one-dimensional depressurization disturbance. The results indicate that the critical failure strength of the shale rock increases as the three-dimensional constant loads are increased. The rupture surface is always parallel to the maximum principal stress plane in both the simulated vertical and horizontal wells. Under the same in situ stress conditions in the wellbore direction, if the lateral pressure becomes larger, the critical failure strength of shale rock would increase. Additionally, when the lateral in situ stress difference coefficient is smaller, the rock specimen has an evident trend to form more complex cracks. When the shale rock was subjected to lateral disturbance loads, the critical failure strength was approximately 10 MPa less than that in the state of constant loading, indicating that the specimen with disturbance loads is more likely to be fractured. Moreover, shale rock under the depressurization disturbance load is more easily fractured compared with the pressurization disturbance. These findings could provide a theoretical basis and technical support for multistage or multiwell synchronous fracturing in shale gas production.