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To explore the hypoglycemic effect of Moringa oleifera leaf polysaccharide (MOLP) on diabetic mice and its corresponding mechanism, a streptozotocin (STZ)-induced diabetic mouse was modeled. The mice were then divided into groups exposed to low (100 mg/kg·bw), medium (200 mg/kg·bw), and high dosage (400 mg/kg·bw) of MOLP, with a normal blank group, model group and a positive drug group (hydrochloric acid dimethylbiguanide, 200 mg/kg·bw). Eight mice in each group were gavaged for 28 d. Fasting blood glucose, serum glycated protein, serum insulin, hepatic/myocardial glycogen and other biochemical indexes were determined. Additionally, the key genes of glucose metabolism, including liver X receptor (LXR), pancreatic-duodenal homeobox-1 (PDX-1), glucokinase (GK), phosphoenolpyruvate carboxykinase (PEPCK), glucose 6-phosphatase (G6Pase), glucose transporter type 2 (GLUT2) and insulin receptor substrate 1/2 (IRS1/2) were measured in the liver and the pancreas. Furthermore, the mice's liver and pancreas tissues in each group were stained with HE to observe their histomorphology. The results showed that MOLP exhibited a significant hypoglycemic effect and a dose-response relationship. The level of blood glucose reduction in the MOLP high-dose group (400 mg/kg·bw) was closest to that of the positive drug group. The underlying mechanism was that the significantly upregulated expression of LXR and PDX-1 ameliorated the glucose metabolism disorders in diabetic mice by regulating the expression of their downstream genes including PEPCK, G6Pase, GK, GLUT2 and IRS1/2 mRNA. This regulation facilitated the improvement of the damaged liver and pancreatic tissues, increased serum insulin and hepatic glycogen content and ultimately resulted in a hypoglycemic effect.

Background: In the recent decade, there has been substantial progress in the technologies and philosophies associated with diagnosing and treating anterior cruciate ligament (ACL) injuries in China. The therapeutic efficacy of ACL reconstruction in re-establishing the stability of the knee joint has garnered widespread acknowledgment. However, the path toward standardizing diagnostic and treatment protocols remains to be further developed and refined. Objective: In this context, the Chinese Association of Orthopaedic Surgeons (CAOS) and the Chinese Society of Sports Medicine (CSSM) collaboratively developed an expert consensus on diagnosing and treating ACL injury, aiming to enhance medical quality through refining professional standards. Methods: The consensus drafting team invited experts across the Greater China region, including the mainland, Hong Kong, Macau, and Taiwan, to formulate and review the consensus using a modified Delphi method as a standardization approach. As members of the CSSM Lower Limb Study Group and the CAOS Arthroscopy and Sports Medicine Study Group, invited experts concentrated on two pivotal issues: “Graft Selection” and “Clinical Outcome Evaluation” during the second part of the consensus development. Results: This focused discussion ultimately led to a strong consensus on nine specific consensus terms. Conclusion: The consensus clearly states that ACL reconstruction has no definitive “gold standard” graft choice. Autografts have advantages in healing capability but are limited in availability and have potential donor site morbidities; allografts reduce surgical trauma but incur additional costs, and there are concerns about slow healing, quality control issues, and a higher failure rate in young athletes; synthetic ligaments allow for early rehabilitation and fast return to sport, but the surgery is technically demanding and incurs additional costs. When choosing a graft, one should comprehensively consider the graft's characteristics, the doctor's technical ability, and the patient's needs. When evaluating clinical outcomes, it is essential to ensure an adequate sample size and follow-up rate, and the research should include patient subjective scoring, joint function and stability, complications, surgical failure, and the return to sport results. Medium and long-term follow-ups should not overlook the assessment of knee osteoarthritis.

Wear failure of oil drill bits leads to cost increase, and how to improve the abrasion resistance of cemented carbide (WC–Co) drill bits is an urgent problem, and deep cryogenic treatment (DCT) is a feasible method. The effect of DCT time (i.e., 0, 3, 6, 9, 12, 24, and 48 h) on the Vickers hardness, flexural strength, and wear rate of WC-Co with different Co contents (i.e., 5 wt%, 8 wt%, 10 wt%, and 12 wt%) was investigated. The results showed that the best DCT time for hardness, flexure strength, and abrasion resistance of WC-Co was 12 h. Compared with untreated (e.g., 0 h), the wear rates of WC-Co with different Co contents were reduced by 36%, 34%, 30%, and 19%, respectively at DCT-12. Compared with WC-12Co, the wear rate of WC-5Co with different DCT times was reduced by 75%, 77%, 78%, 78%, 80%, 79%, and 78%, respectively. The precipitation of η phase (Co6W6C), martensite phase transformation (α-Co to ε-Co), and the increase of residual compressive stress (RCS) of WC after DCT improved the hardness, flexural strength and reduced the wear rate of WC-Co. Based on the principle of frictional wear, a micro-cutting wear model considering Co content and DCT time is proposed, which can predict the evolution of the wear rate of WC-Co. The results of the study guide improving the wear resistance of drill materials.

In view of the diversity of equipment failure causes in the field application of coal mine safety monitoring system at the present stage, for some deep-level equipment failure causes, field technicians do not have the ability to conduct in-depth analysis, an intelligent diagnosis method of equipment failure based on intelligent diagnosis model base is proposed. This method first implements an intelligent diagnostic model library, which models various analysis methods collected by collecting indicator data and analysis methods required by technical experts for daily analysis and problem-solving. Then, various models are abstracted into machine programming languages for implementation, forming an intelligent diagnostic model library for equipment; secondly, based on the pre-installed software and hardware probes of the equipment, combined with an intelligent diagnostic model library, a comprehensive analysis of the causes of equipment faults is modeled, and the self-analysis, self-diagnosis, and self-repair functions of sub stations, sensors, power outage controllers, and other equipment are completed; finally, through a series of intelligent diagnostic front-end UI interaction methods such as device automatic topology diagrams, users are provided with convenient diagnostic operations and graphical and graphical data analysis and display of relevant information. While improving the stability and reliability of the coal mine safety monitoring system, it is possible to empower users and assist in the intelligent development of reducing personnel and increasing efficiency.

ObjectiveThis study aims to understand the current status and trend of the disease burden of osteoarthritis (OA) in people over 30 years old in China from 1990 to 2021 and identify the priority population groups, to provide reference data for the prevention and treatment of OA in China.MethodsThe Global Burden of Disease Study 2021 was used to describe the incidence, prevalence, and disability-adjusted life years (DALYs) of OA in adult aged 30 years or older in China by sex and age groups, which was used to analyze the disease burden of OA from 1990 to 2021. The joinpoint regression model and age-period-cohort model were used to characterize the temporal trend.ResultsIn 2021, the number of OA prevalence in China was about 152.85 million, and the number of incidences was about 11.65 million. The age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR) and age-standardized DALYs rate (ASDR) of OA in China are lower than those in developed countries such as Korea, the United States of America and Japan, but higher than those in India. Knee osteoarthritis had the highest ASPR and ASDR. The highest incidence rate was 50–54 years, and the highest prevalence and DALYs rate were in the age group of patients over 95 years old. The incidence rate of women in all age groups is higher than that of men. From 1990 to 2021, the ASIR, ASPR and ASDR of OA in China roughly showed an increasing trend year by year. The age-period-cohort analysis showed that the peak age groups for longitudinal age incidence of OA in China from 1992 to 2021 were 50–54 years and 80–84 years. We found that the OA incidence was highest in the period 2017–2021.ConclusionThe disease burden of OA in those over 30 years old in China from 1990 to 2021 will become more and more serious, and the target population for primary prevention is the female population under 50 years old. The development of a scientific and effective comprehensive prevention and treatment program for OA is imminent.

BackgroundCoronary heart disease (CHD) is one of the leading causes of mortality. The current study aims to assess the association between C-reactive protein-triglyceride glucose index (CTI) and the risk of prevalent CHD and to evaluate the usefulness of CTI to refine the identification of prevalent CHD.Methods19,451 subjects from the National Health and Nutrition Examination Survey 1999–2010 were enrolled. CHD was ascertained according to the questionnaire.ResultsThe prevalent of CHD was 6.23%. After adjusting for conventional cardiovascular risk factors, each SD increase of CTI could cast a 1.357 times risk of CHD. In quartile analysis, the top quartile had a 1.807 times risk of CHD than the bottom quartile. Smooth curving fitting displayed that the association was linear in the entire range of CTI. Subgroup analysis revealed that the association was robust among several common subpopulations but stronger in subjects aged

In this paper, the radial basis function (RBF) neural network was modified by data assimilation method to improve the modeling accuracy of high-dimensional aerodynamics. A correction factor γ was introduced into the kernel function of the traditional RBF neural network. The correction factor was corrected by using the EnKF data assimilation algorithm, and it was applied to the high-dimensional aerodynamic modeling prediction of the CRA309 rotor airfoil. The data assimilation method adopts a non-intrusive method to correct only the correction factor of the kernel function without destroying the overall architecture of the neural network, which greatly reduces the optimization parameters and variables, and significantly improves the modeling accuracy and efficiency of the RBF neural network. The modified RBF neural network model was then applied to high-dimensional aerodynamic modeling, and the aerodynamic parameters were predicted by simulation data instead. The design results verify the feasibility of the prediction model. In the case of less wind tunnel test data, it has certain engineering practical value to improve the utilization efficiency of test data.

There were a variety of high content elements associated with the early Cambrian stone coal in northeastern Hunan province, and the attribute characteristics were distinct. In order to find out the sedimentary sources of stone coal in this area, the contents of major elements and trace elements in 12 stone coal samples were determined by X-ray fluorescence spectrometer (XRF) and inductively coupled plasma mass spectrometer (ICP–MS). Based on the combination of major elements, content characteristics of trace elements, distribution characteristics of rare earth elements and geochemical parameters of related elements, the source regions of the early Cambrian stone coal deposits in northeast Hunan province were discussed. The results showed that the early Cambrian stone coal in northeast Hunan province was mainly composed of inorganic minerals, and the content of SiO2 was the highest in the stone coal. The relationships between SiO2 and other major elements (and other major elements) were not obvious, and the quartz mineral morphology was characterized by terrigenous input. The trace elements (V, As, Sr, Mo, Cd, Sb, Ba, Bi, U) in stone coal were obviously enriched. The distribution characteristics of rare earth elements and the relationship between Nb/Y–Zr/TiO2 indicated that stone coal was influenced by neutral rock. LaN/YbN indicated that the deposition rate of stone coal deposits decreases from southeast to northwest. Means, the source comes from the eastern and southern directions; The w(SiO2)/w(Al2O3), w(Al2O3)/w(Al2O3+Fe2O3), w(Al)/w(Al+Fe+Mn) and K2O/Na2O–SiO2 structural discrimination models showed that the early Cambrian stone coal was deposited in the continental margin area, mainly receiving continental sources. Based on the comparison with the contents of rare earth elements, Rb, Nb and Pb in the middle-acid rocks of Shangshu Group distributed in the southeast direction of the study area, and the contents and combination characteristics of major elements in the magmatic rocks of Shuangxiwu Group, and combined with the evolution history of Jiangnan Orogenic belt, the middle-acid rock belt developed in the southeastern margin of Jiangnan orogenic belt was considered to be the source region of the early Cambrian stone coal deposits in northeast Hunan province. It was also one of the main controlling factors for the enrichment of trace elements in stone coal.

Background: The swift global spread of coronavirus disease 2019 (COVID-19), a respiratory ailment primarily marked by pulmonary symptoms, has been linked to the involvement of various organs, including the intestines, kidneys, throat, and ears. Otitis media with effusion (OME), often succeeding an upper respiratory tract infection, mirrors its incidence. As a respiratory infectious disease, it prompts the query of whether the COVID-19 pandemic has spurred an uptick in OME and whether the COVID-19 virus persists in middle ear effusion (MEE) for an extended period. Methods: To gauge the incidence of OME in the population during the COVID-19 pandemic, a tailored questionnaire was disseminated and subsequently analyzed. Assessing the rise in OME incidence during the pandemic, we compared the proportion of OME cases in the otology outpatient department between pandemic and non-pandemic periods. Statistical analysis involved a t-test. Simultaneously, MEE was collected from patients with COVID-19-associated OME during the pandemic to ascertain the presence of SARS-CoV-2 in MEE via polymerase chain reaction. Results: Based on the questionnaire data, the estimated OME incidence in the population is approximately 31.4 %. In contrast to the non-pandemic period, the percentage variation in the OME outpatient proportion was 71.4 % (P < 0.05). Among the 61 MEE samples, 13 polymerase chain reaction results were positive, constituting 21.31 %. Nasopharyngeal swabs yielded negative results. Notably, only one patient experienced OME recurrence after 1 month of auripuncture. Conclusions: COVID-19 can trigger an escalation in OME cases. Even when nasopharyngeal swabs show negative results, SARS-CoV-2 can endure in MEE for an extended duration, suggesting the potential for asymptomatic COVID-19 transmission and recurrence within the population.

Osteoarthritis (OA) is a degenerative disease potentially exacerbated due to inflammation, cartilage degeneration, and increased friction. Both mesenchymal stem cells (MSCs) and pro-inflammatory macrophages play important roles in OA. A promising approach to treating OA is to modify multi-functional hydrogel microspheres to target the OA microenvironment and structure. Arginyl-glycyl-aspartic acid (RGD) is a peptide widely used in bioengineering owing to its cell adhesion properties, which can recruit BMSCs and macrophages. We developed TLC-R, a microsphere loaded with TGF-β1-containing liposomes. The recruitment effect of TLC-R on macrophages and BMSCs was verified by in vitro experiments, along with its function of promoting chondrogenic differentiation of BMSCs. And we evaluated the effect of TLC-R in balancing OA metabolism in vitro and in vivo. When TLC-R was co-cultured with BMSCs and lipopolysaccharide (LPS)-treated macrophages, it showed the ability to recruit both cells in substantial numbers. As the microspheres degraded, TGF-β1 and chondroitin sulfate (ChS) were released to promote chondrogenic differentiation of the recruited BMSCs, modulate chondrocyte metabolism and inhibit inflammation induced by the macrophages. Furthermore, in vivo analysis showed that TLC-R restored the narrowed space, reduced osteophyte volume, and improved cartilage metabolic homeostasis in OA rats. Altogether, TLC-R provides a comprehensive and novel solution for OA treatment by dual-modulating inflammatory and chondrocyte metabolism.

Ultra-high steel fiber reinforced concrete (UHSFRC) has poor workability and a low cost-performance ratio, and the application of active admixtures can overcome these shortcomings of UHSFRC. This work investigated the feasibility of fly ash (FA) and silica fume (SF) to improve the performance of SFRC and evaluate the effects of FA and SF on the workability, mechanical properties, microstructure, and economic/environmental performance of UHSFRC. The results showed that FA and SF can increase the slump, compressive, and splitting tensile strength of UHSFRC. Compared with control tests, the slump, 28-d compressive, and 28-d splitting tensile strength increased by 43.25 %, 29.35 %, and 55.72 %, respectively. More importantly, microscopic analysis showed that FA and SF have balling, filling, and adsorption effects, and increase peak intensity of C-S-H gel and ettringite, promoting secondary hydration of cement. According to the experimental data and mechanistic analysis, an innovatively optimized ratio prediction model is adopted to establish the relationship between the slump, compressive, and splitting tensile strength of UHSFRC and the content of FA and SF, and the testing error was less than 5 %, indicating that the model is feasible. Moreover, the effect of FA and SF content on cost-performance ratio, carbon emission, and energy consumption of UHSFRC was predicted. The economic/environmental analysis showed the mixing of FA and SF can improve the cost-performance ratio of UHSFRC and reduce carbon emission and energy consumption. This study can provide theoretical guidance for the improvement of the workability and mechanical properties of UHSFRC, and have important research implications for the improvement of the life cycle assessment of UHSFRCs. The results of the study also have some limitations, and further validation is needed for normal steel fiber concrete (compressive strength of 30–60 MPa, with fibers with a length of 30–60 mm and diameter of approx. 1 mm).

This study aims to systematically investigate the deterioration of tensile properties, voltage variation, and voltage-strength theoretical model of CFRP/ conductive ECC composites under coupling effect of anode polarization, load and erosion environment. The effects of testing parameters including conductive ECC mixture type, electric current density, polarization time, tensile stress value, sulfate soak time, and sulfate attack-wet and dry cycle time were synthetically investigated. The experimental results indicated that the voltage increases approximately linearly with the increase of degradation time in the voltage-deterioration time curves. The stress-strain curve can be divided into three stages: the stress-strain linear increase stage, the strain hardening characteristic stage, and the decline stage during failure. The conductive ECC mixture type, polarization time, current density, tensile stress value, sulfate soak time, and sulfate attack-wet and dry cycle time all have significant effects the deterioration of tensile strength and the voltage change ratio of CFRP/ conductive ECC composite. More importantly, an innovative voltage-strength theoretical model was proposed, which can predict the relationship between voltage and material deterioration strength. The theoretical model is in good agreement not only with the experimental results of this study, but also with the results of other studies. The model proposed can be used to predict deterioration degree of materials in real time, which has very important guiding significance for impressed current cathodic protection-structural strengthening technology (ICCP-SS) technology. This study is expected to promote a more comprehensive understanding of the deterioration of mechanical properties and voltage-strength theoretical model of CFRP/conductive ECC composites for ICCP-SS technology.

The coevolution of bacteria and bacteriophages has created a great diversity of mechanisms by which bacteria fight phage infection, and an equivalent diversity of mechanisms by which phages subvert bacterial immunity. Effective and continuous evolution by phages is necessary to deal with coevolving bacteria. In this study, to better understand the connection between phage genes and host range, we examine the isolation and genomic characterization of two bacteriophages, JNUWH1 and JNUWD, capable of infecting Escherichia coli. Sourced from factory fermentation pollutants, these phages were classified within the Siphoviridae family through TEM and comparative genomic analysis. Notably, the phages exhibited a viral burst size of 500 and 1,000 PFU/cell, with latent periods of 15 and 20 min, respectively. They displayed stability over a pH range of 5 to 10, with optimal activity at 37°C. The complete genomes of JNUWH1 and JNUWD were 44,785 bp and 43,818 bp, respectively. Phylogenetic analysis revealed their close genetic relationship to each other. Antibacterial assays demonstrated the phages’ ability to inhibit E. coli growth for up to 24 h. Finally, through laboratory-driven adaptive evolution, we successfully identified strains for both JNUWH1 and JNUWD with mutations in receptors specifically targeting lipopolysaccharides (LPS) and the lptD gene. Overall, these phages hold promise as additives in fermentation products to counter E. coli, offering potential solutions in the context of evolving bacterial resistance.

Abstract In MILCOM 2015, Kelly et al. proposed the authentication encryption algorithm MK-3, which applied the 16-bit S-box. This paper aims to implement the 16-bit S-box with less circuit area. First, we classified the irreducible polynomials over $$\mathbb {F}_{2^n}$$ F 2 n into three kinds. Then we compared the logic gates required for multiplication over the finite field constructed by the three types of irreducible polynomials. According to the comparison result, we constructed the composite fields, $$\mathbb {F}_{(2^4)^2}$$ F ( 2 4 ) 2 and $$\mathbb {F}_{(2^8)^2}$$ F ( 2 8 ) 2 . Based on the isomorphism of finite fields, the operations over $$\mathbb {F}_{2^{16}}$$ F 2 16 can be conducted over $$\mathbb {F}_{(2^8)^2}$$ F ( 2 8 ) 2 . Similarly, elements over $$\mathbb {F}_{2^8}$$ F 2 8 can be mapped to the corresponding elements over $$\mathbb {F}_{(2^4)^2}$$ F ( 2 4 ) 2 . Next, the SAT solver was used to optimize the operations over smaller field $$\mathbb {F}_{2^4}$$ F 2 4 . At last, the architecture of the optimized MK-3 S-box was worked out. Compared with the implementation proposed by the original designer, the circuit area of the MK-3 S-box in this paper is reduced by at least 55.9%.

Abstract Background Mediation analysis aims to determine how intermediate variables affect exposure to disease. In this study, 25-hydroxyvitamin D (25(OH)D) was evaluated to assess its role in mediating heavy metal exposure and cardiovascular disease (CVD). Methods A total of 9,377 participants from the National Health and Nutrition Examination Survey (NHANES) for the years 2011-2018 were included. Firstly, restricted cubic spline (RCS), and multivariable logistic regression model were performed to estimate the association between heavy metal exposure (Cadmium, Lead, Mercury, Manganese, and Selenium), as well as serum 25(OH)D and CVD. Secondly, using generalized linear regression model and generalized additive models with smooth functions, we investigated the correlation between heavy metal exposure and serum 25(OH)D. Finally, the mediation effect of serum 25(OH)D in the associations between heavy metal exposure and CVD was explored. Results The RCS plots revealed that Cadmium, and Lead were positively and linearly associated with CVD, while Mercury, and Manganese were inversely and linearly associated with CVD. Additionally, a roughly L- and U-shaped relationship existed between Selenium, as well as 25(OH)D and CVD. When potential confounding factors were adjusted for, serum 25(OH)D had negative associations with Cadmium, Lead, and Manganese, while serum 25(OH)D had positive relationship with Selenium. There was a mediation effect between Manganese exposure and CVD, which was mediated by 25(OH)D. Conclusion According to the mediation analysis, the negative association between Manganese exposure and incident CVD was increased by 25(OH)D. The increasing dietary intake of Vitamin D could increase the protective effect of manganese intake on CVD.

Unmanned aerial vehicles (UAVs) are becoming more widely used in various industries, raising growing concerns about their safety and reliability. The flight data of UAVs can directly reflect their flight health status; however, the rarity of abnormal flight data and the spatiotemporal characteristics of these data represent a significant challenge for constructing accurate and reliable anomaly detectors. To address this, this study proposes an anomaly detection framework that fully considers the temporal correlations and distribution characteristics of flight data. This framework first combines a one-dimensional convolutional neural network (1DCNN) with an autoencoder (AE) to establish a feature extraction model. This model leverages the feature extraction capabilities of the 1DCNN and the reconstruction capabilities of the AE to thoroughly extract the spatiotemporal features from UAV flight data. Then, to address the challenge of adaptive anomaly detection thresholds, this research proposes a nonlinear model of support vector data description (SVDD) utilizing a 0/1 soft-margin loss, referred to as L0/1-SVDD. This model replaces the traditional hinge loss function in SVDD with a 0/1 loss function, with the goal of enhancing the accuracy and robustness of anomaly detection. Since the 0/1 loss function is a bounded, non-convex, and non-continuous function, this paper proposes the Bregman ADMM algorithm to solve the L0/1-SVDD. Finally, the difference between the reconstructed and the actual value is employed to train the L0/1-SVDD, resulting in a hypersphere classifier that is capable of detecting UAV anomaly data. The experimental results using real flight data show that, compared with methods such as AE, LSTM, and LSTM-AE, the proposed method exhibits superior performance across five evaluation metrics.

This study aims to investigate shear performance and prediction model of CFRP-ECC-concrete composite interface suffered from anodic polarization and environmental degradation. The effect of ECC mixtures, cathodic current densities, polarization period, and the duration of sulfate soaking and sulfate attacking by wet and dry cycles on the interface of the composite were studied. The results showed that three failure modes of CFRP-ECC-concrete composite interface were found. Shear load-slip curves showed double broken lines characteristics, while voltage-deterioration time curves showed an approximate linear increase relationship between voltage and polarization time. The five parameters all had significant effects shear strength deterioration on the CFRP-ECC-concrete composite interface. Moreover, this study proposed an innovative prediction model to the interfacial shear strength by the measured voltage, which can provide an important basic theory for ICCP-SS technology. This work makes a contribution to the ICCP-SS technology on the shear performance and prediction model of composite interface.

Abstract Background The purpose of this study was to describe the knowledge, protective behaviours, and psychological impact of COVID-19 on Chinese residents in Canada, as the emotional and behavioural impacts of the pandemic have not been intensively studied amongst these populations. It was important to determine whether having dependent school-age children (DSAC) aged 16 or under was associated with adverse psychological impacts amongst the Chinese residents living in the country. Methods In April 2020, 757 eligible participants were recruited through a snowball sampling to complete an online survey related to the COVID-19 pandemic. Psychological, behavioural, and sociodemographic variables were collected and first analyzed using descriptive and univariate statistics. Multiple logistic regression analyses were performed to further confirm the observed significant associations in bivariate analyses for selected psychological outcome variables. Results Seven hundred forty-two participants who responded to the “dependent school-age children” question were included in the analysis. Most of them identified as females (65.8%) and 77.2% included receiving a university degree or higher. There were no significant differences in COVID-19 knowledge between those living with or without DSAC. However, participants with DSAC were more likely to perceive themselves as being at greater risk of contracting COVID-19 (p = .023); therefore, having a higher chance of adopting protective behaviours (e.g., hand washing, sanitizing frequently or disinfecting work and living spaces (p

ABSTRACTWe use a case study to illustrate how different acquisition methods can result in different amounts of goodwill recognised on financial statements in China. China Merchants Bank adopted a two-step acquisition method: first, it acquired 53% of the shares of Hong Kong’s Wing Lung Bank to gain corporate control in 2008; second, it acquired the remaining 47% of shares in 2009. Using this method, China Merchants Bank recognised the acquisition premium as goodwill only in the first step and recognised the acquisition premium in the second step as a decrease in additional paid-in capital. This two-step acquisition method significantly reduces the amount of goodwill shown on financial statements and lowers the likelihood and amount of subsequent goodwill impairment. Different acquisition methods can lead to different amounts of goodwill initially recognised when accounting standards permit the partial goodwill method and regard the transactions between the parent and non-controlling shareholders as equity transactions.

Abstract The industrial sector is China's major element of energy consumption and carbon emissions, and carbon emissions reduction in industrial parks has become an important foothold in carbon reduction work. Predicting the future evolution trend of carbon emissions in industrial parks under different policy orientations is of great significance for China to achieve the carbon emissions peaking and carbon neutrality goals. Based on the current status of electricity consumption and carbon emissions in industrial parks, this paper takes a light industrial park as the research object, analyzes the source of carbon emissions in this park, combines the characteristics of resource endowment and industrial structure, and considers the factors influencing society, load curve, energy supply and carbon sink, thus constructing a system dynamics model of carbon emission evolution for this park. Different influencing factors are selected to set multiple target scenarios, and the GDP, carbon emissions, carbon emissions reduction and near‐zero carbon evaluation coefficient of light industrial parks are used as characterization indicators for simulation analysis. The analysis results revealed that the comprehensive scenario set by increasing the maximum installed capacity of renewable energy units and raising the proportions of environmental and science and technology inputs while adjusting the industrial growth rate of the park performed best. In this scenario, the economic development of the park and the process of carbon emissions reduction are considered.

Support vector data description (SVDD) is widely regarded as an effective technique for addressing anomaly detection problems. However, its performance can significantly deteriorate when the training data are affected by outliers or mislabeled observations. This study introduces a universal truncated loss function framework into the SVDD model to enhance its robustness and employs the fast alternating direction method of multipliers (ADMM) algorithm to solve various truncated loss functions. Moreover, the convergence of the fast ADMM algorithm is analyzed theoretically. Within this framework, we developed the truncated generalized ramp, truncated binary cross entropy, and truncated linear exponential loss functions for SVDD. We conducted extensive experiments on synthetic and real-world datasets to validate the effectiveness of these three SVDD models in handling data with different noise levels, demonstrating their superior robustness and generalization capabilities compared to other SVDD models.

Abstract The real-time path planning of unmanned aerial vehicles (UAVs) in dynamic environments with moving threats is a difficult problem. To solve this problem, this paper proposes a time-based rapidly exploring random tree (time-based RRT*) algorithm, called the hierarchical rapidly exploring random tree algorithm based on potential function lazy planning and low-cost optimization (HPO-RRT*). The HPO-RRT* algorithm can guarantee path homotopy optimality and high planning efficiency. This algorithm uses a hierarchical architecture comprising a UAV perception system, path planner, and path optimizer. After the UAV perception system predicts moving threats and updates world information, the path planner obtains the heuristic path. First, the path planner uses the bias sampling method based on the artificial potential field function proposed in this paper to guide sampling to improve the efficiency and quality of sampling. Then, the tree is efficiently extended by the improved time-based lazy collision checking RRT* algorithm to obtain the heuristic path. Finally, a low-cost path optimizer quickly optimizes the heuristic path directly to optimize the path while avoiding additional calculations. Simulation results show that the proposed algorithm outperforms the three existing advanced algorithms in terms of addressing the real-time path-planning problem of UAVs in a dynamic environment.

Abstract The Arabidopsis thaliana Receptor-Like Protein RLP30 contributes to immunity against the fungal pathogen Sclerotinia sclerotiorum. Here we identify the RLP30-ligand as a small cysteine-rich protein (SCP) that occurs in many fungi and oomycetes and is also recognized by the Nicotiana benthamiana RLP RE02. However, RLP30 and RE02 share little sequence similarity and respond to different parts of the native/folded protein. Moreover, some Brassicaceae other than Arabidopsis also respond to a linear SCP peptide instead of the folded protein, suggesting that SCP is an eminent immune target that led to the convergent evolution of distinct immune receptors in plants. Surprisingly, RLP30 shows a second ligand specificity for a SCP-nonhomologous protein secreted by bacterial Pseudomonads. RLP30 expression in N. tabacum results in quantitatively lower susceptibility to bacterial, fungal and oomycete pathogens, thus demonstrating that detection of immunogenic patterns by Arabidopsis RLP30 is involved in defense against pathogens from three microbial kingdoms.

Caloric restriction (CR) or energy restriction, when carefully designed, monitored, and implemented in self-motivated and compliant individuals, proves to be a viable non-pharmacologic strategy for human weight control and obesity management. Beyond its role in weight management, CR has the potential to impede responses involved not only in the pathogenesis of various diseases but also in the aging process in adults, thereby being proposed to promote a healthier and longer life. The core objective of implementing caloric restriction is to establish a balance between energy intake and expenditure, typically involving a reduction in intake and an increase in expenditure—a negative balance at least initially. It may transition toward and maintain a more desired equilibrium over time. However, it is essential to note that CR may lead to a proportional reduction in micronutrient intake unless corresponding supplementation is provided. Historical human case reports on CR have consistently maintained adequate intakes (AI) or recommended dietary allowances (RDA) for essential micronutrients, including vitamins and minerals. Similarly, longevity studies involving non-human primates have upheld micronutrient consumption levels comparable to control groups or baseline measures. Recent randomized controlled trials (RCTs) have also endorsed daily supplementation of multivitamins and minerals to meet micronutrient needs. However, aside from these human case reports, limited human trials, and primate experiments, there remains a notable gap in human research specifically addressing precise micronutrient requirements during CR. While adhering to AI or RDA for minerals and vitamins appears sensible in the current practice, it’s important to recognize that these guidelines are formulated for generally healthy populations under standard circumstances. The adequacy of these guidelines in the setting of prolonged and profound negative energy balance remains unclear. From perspectives of evidence-based medicine and precision nutrition, this field necessitates comprehensive exploration to uncover the intricacies of absorption, utilization, and metabolism and the requirement of each hydrophilic and lipophilic vitamin and mineral during these special periods. Such investigations are crucial to determine whether existing daily dietary recommendations for micronutrients are quantitatively inadequate, excessive, or appropriate when energy balance remains negative over extended durations.

We convert the viscous compressible fluid equations with capillary effect into the equivalent planar dynamical system and illustrate the global qualitative phase diagrams corresponding to its bounded orbits by the qualitative theory of ordinary differential equations. From the evolutionary relationship of bounded orbits in global qualitative phase diagrams and the correspondence between the bounded orbit and traveling wave, we discover the evolutionary rule of the profile of the traveling wave as the viscous coefficient varying and the forming reason for the damped oscillatory traveling wave. Further, we construct the analytical approximate explicit expression of the damped oscillatory traveling waves in accordance with the forming reason and prove its error decreases in exponential form. Finally, we compare the approximate damped oscillatory traveling wave with the numerical solution. The result shows they fit well.

Top managers' past experiences (e.g., foreign experience) significantly impact their decision-making behavior, which may influence firms' sustainable development. The available literature, focusing on the role of the increase in the number of top executives with foreign experience in corporate social responsibility (CSR), yields mixed results. In order to clarify the ambiguous relationship between executive foreign experience and CSR, we empirically examine the effect of the geographic diversity of top executives' foreign experience on CSR. Based on a hand-collected dataset of the top management team's (TMT's) foreign experience, we demonstrate the positive impact of the geographic diversity of returnee executives' foreign experience on firms' CSR using Chinese A-share listed firms from 2009 to 2018. Moreover, this impact is stronger in firms with political connections with the central government and in regions with good market development. Furthermore, the mechanism analysis shows that returnee executives drive firms' CSR by promoting corporate donations and green innovation. This paper offers clear policy implications by suggesting that hiring returnees with a broad geographic scope of foreign experience as corporate executives is an efficient way to enhance firms' CSR.

Research has demonstrated that circular RNAs (circRNAs) exert critical functions in the occurrence and progression of numerous malignant tumors. CircPRMT5 was recently reported to be involved in the pathogenesis of cancers. However, the potential role of circPRMT5 in osteosarcoma needs further investigation. In present study, our results suggested that circPRMT5 was highly upregulated in osteosarcoma cells and mainly localizes in the cytoplasm. CircPRMT5 promoted the proliferation, migration and invasion capacities of osteosarcoma cells, and suppressed cell apoptosis. Knockdown of circPRMT5 exerted the opposite effects. Mechanically, circPRMT5 promoted the binding of CNBP to CDK6 mRNA, which enhanced the stability of CDK6 mRNA and facilitated its translation, thereby promoting the progression of osteosarcoma. Knockdown of CDK6 reversed the promoting effect of circPRMT5 on osteosarcoma cells. These findings suggest that circPRMT5 promotes osteosarcoma cell malignant activity by recruiting CNBP to regulate the translation and stability of CDK6 mRNA. Thus, circPRMT5 may represent a promising therapeutic target for osteosarcoma.

Abstract River sediments are valuable archives of the environmental conditions within their catchments. The Yangtze and Yellow Rivers are the most active fluvial systems for sediment transport in East Asia, and they are regarded as potential sediment sources for the radial sand ridges (RSRs) in the southwestern Yellow Sea. We used the geochemical compositions of size‐fractioned sediment samples from the Yangtze and Yellow Rivers to characterize chemical weathering, the fractionation behavior of provenance tracers, and the sources of RSRs. For the Yangtze and Yellow River sediments, the (Rb + Sr)/Ti ratio is a reliable chemical weathering proxy that is grain‐size independent. The chemical indices of Chemical Index of Alteration, Rb/Sr, (Rb + Sr)/Ti, and acid‐leached elements from common grain‐size fractions together reveal that the Yangtze River basin undergoes stronger chemical weathering than the Yellow River basin, indicating that the chemical weathering is dominated by latitudinally‐dependent climatic variations. The dissolution and precipitation of amorphous Fe‐Mn oxides can result in the significant fractionation of La/Y, La/Sc, Nb/Co, La/Co, (La/Sm)N, (La/Yb)N, Ti/Sc, Zr/Y, Zr/Co, and Cr/Ta, whereas Zr/Ti and Zr/Nb are largely unaffected. Based on the robust provenance tracers of Zr/La, La/Hf, (La/Yb)N, Zr/Nb, Ti/Zr, and Hf/Ta, we conclude that the RSRs in the southwestern Yellow Sea are mainly derived from Yangtze River sediments, and that part of the clay fraction is from the Yellow River. In future research, we suggest that established geochemical indicators of chemical weathering and sediment provenance can be applied to the deposits of the Yangtze and Yellow River Deltas, the Yellow Sea, and the East China Sea.

Trifolium pratense is an important legume forage grass and a key component of sustainable livestock development. Serving as an essential component, the WRKY gene family, a crucial group of regulatory transcription factors in plants, holds significant importance in their response to abiotic stresses. However, there has been no systematic analysis conducted on the WRKY gene family in Trifolium pratense. This study conducted a comprehensive genomic characterization of the WRKY gene family in Trifolium pratense, utilizing the latest genomic data, resulting in the identification of 59 TpWRKY genes. Based on their structural features, phylogenetic characteristics, and conserved motif composition, the WRKY proteins were classified into three groups, with group II further subdivided into five subgroups (II-a, II-b, II-c, II-d, and II-e). The majority of the TpWRKYs in a group share a similar structure and motif composition. Intra-group syntenic analysis revealed eight pairs of duplicate segments. The expression patterns of 59 TpWRKY genes in roots, stems, leaves, and flowers were examined by analyzing RNA-seq data. The expression of 12 TpWRKY genes under drought, low-temperature (4°C), methyl jasmonate (MeJA) and abscisic acid (ABA) stresses was analyzed by RT-qPCR. The findings indicated that TpWRKY46 was highly induced by drought stress, and TpWRKY26 and TpWRKY41 were significantly induced by low temperature stress. In addition, TpWRKY29 and TpWRKY36 were greatly induced by MeJA stress treatment, and TpWRKY17 was significantly upregulated by ABA stress treatment. In this research, we identified and comprehensively analyzed the structural features of the WRKY gene family in T.pratense, along with determined the possible roles of WRKY candidate genes in abiotic stress. These discoveries deepen our understandings of how WRKY transcription factors contribute to species evolution and functional divergence, laying a solid molecular foundation for future exploration and study of stress resistance mechanisms in T.pratense.

To address the negative influence caused by power randomness of distributed PV output on energy system’s economic operation, in this work, an economic operation strategy considering the uncertainty features of PV output has been designed and applied on an integrated hydrogen energy system. First, the thermal system operation model and the thermoelectric output control model are precisely built for the integrated hydrogen energy system and the hydrogen-based fuel cell, respectively. Then, referring to the PV output prediction data, the uncertainty of light intensity variation is analyzed to correct the PV output prediction curve. Finally, a cost–benefit model for the optimal economic operation of the integrated hydrogen energy system including PV, hydrogen fuel cell and cogeneration unit is designed with an objective function of achieving an optimal economic operation of the multi-energy coupling devices. The simulation tests validate that considering the influence of PV output uncertainty on hydrogen fuel cell output can make the system operation more reasonable, which ensures the economic and reliable operation of hydrogen energy systems.

I employ autoethnography to undertake a broader scholarly inquiry on intergenerational relationships and transnational care shaped by global migration and aging. Specifically, I reflect on the dynamics of my relationship with my mother, beginning with my departure from my home and spanning a period of 40 years, 8 in China and 34 outside China. In doing so, I contemplate theoretical models of intergenerational solidarity, ambivalence, and role ambiguity. I also challenge cultural assumptions of filial piety. The geographical distance, passage of time, and acculturation process have profoundly influenced my perception of filial piety, which differs markedly from my mother’s. However, this divergence in consensual solidarity—marked by variations in attitudes, beliefs, and values—does not translate into weakened affectual solidarity, characterized by positive sentiments and emotions. Furthermore, aided by advancements in transportation and social media technology, I have been able to extend crucial emotional and some “instrumental” care to my mother, along with financial support if needed, despite limited hands-on care. Nevertheless, I must negotiate my care for my mother and navigate a delicate balance in coordinating my care efforts with those of my non-migrant siblings.

Cemented carbide used in the rotor of a mud pulser is subjected to the scouring action of solid particles and corrosive mud media for a long time, which causes abrasive wear and electrochemical corrosion. To improve the wear and corrosive resistance of cemented carbide, samples with different cobalt content (WC-5Co, WC-8Co, and WC-10Co) receive deep cryogenic treatment (DCT) at −196 °C for 2.5 h. An optical metalloscope (OM) and X-ray diffractometer (XRD) are used to observe the phase changes of cemented carbides, and the XRD is also used to observe the change in residual stress on the cemented carbide’s surface. A scanning electron microscope (SEM) is used to characterize the wear and electrochemical corrosion surface microstructure of cemented carbides (untreated and DCT). The results show that the DCT promotes the precipitation of the η phase, and the diffraction peak of ε-Co tends to intensify. Compared with the untreated, the wear rates of WC-5Co, WC-8Co, and WC-10Co can be reduced by 14.71%, 37.25%, and 41.01% by DCT, respectively. The wear form of the cemented carbides is mainly the extrusion deformation of Co and WC shedding. The precipitation of the η phase and the increase in WC residual compressive stress by DCT are the main reasons for the improvement of wear resistance. The electrochemical corrosion characteristic is the dissolution of the Co phase. DCT causes the corrosion potential of cemented carbide to shift forward and the corrosion current density to decrease. The enhancement of the corrosion resistance of cemented carbide caused by DCT is due to the Co phase transition, η phase precipitation, and the increase in the compressive stress of cemented carbide.

The separation and recovery of Fe(III) in heavy metal mixtures is a great challenge due to its strong ion exchange property. In this study, we developed a novel cinnamon-like blended fiber (PAN/PEG) using electrostatic spinning and dissolution post-treatment, which exhibited highly selective separation properties and satisfactory adsorption capacity for Fe(III). Owing to the preferential coordination of Fe(III) with both cyanide and hydroxyl groups, PAN/PEG possessed such excellent adsorption capacity as 1.12 mmol/g. Notably, the infinite selective separation coefficient between Fe(III) and other heavy metal ions (HMIs) achieved even from the octa-mixed metal systems. Furthermore, PAN/PEG demonstrated good anti-interference ability against coexisting inorganic salts. In addition, PAN/PEG was highly effective in removing lower concentration Fe(III) from complex PTA wastewater with super-high selectivity, which enabled the subsequent purification of Co(II) and Mn(II). Overall, PAN/PEG could be prepared and recovered facilely, and had great potential in the exclusive separation of Fe(III).

Abstract Osteoarthritis (OA), the commonest arthritis, is characterized by the progressive destruction of cartilage, leading to disability. The Current early clinical treatment strategy for OA often centers on anti‐inflammatory or analgesia medication, weight loss, improved muscular function and articular cartilage repair. Although these treatments can relieve symptoms, OA tends to be progressive, and most patients require arthroplasty at the terminal stages of OA. Recent studies have shown a close correlation between joint pain, inflammation, cartilage destruction and synovial cells. Consequently, understanding the potential mechanisms associated with the action of synovial cells in OA could be beneficial for the clinical management of OA. Therefore, this review comprehensively describes the biological functions of synovial cells, the synovium, together with the pathological changes of synovial cells in OA, and the interaction between the cartilage and synovium, which is lacking in the present literature. Additionally, therapeutic approaches based on synovial cells for OA treatment are further discussed from a clinical perspective, highlighting a new direction in the treatment of OA.

The tunnel collapse occurred during the construction of the Qingdao Metro Line Ⅰ, resulting in a pit measuring approximately 10 m in diameter and 7 m in depth on the ground surface. The collapse inflicted substantial economic losses, casualties, and subsequent disruptions to ongoing construction activities. To clarify the causes of this collapse and investigate the underlying factors, a comprehensive approach combining field surveys and numerical simulations was undertaken. The results show that the collapse was primarily attributed to inadequate support when facing the challenging geological conditions, poor surrounding rocks (Grade VI) and a high volume of groundwater. The combination of abundant water and sand seeped into the tunnel, culminating in a catastrophic ground collapse. Notably, the arch roof experienced extensive deformation and damage due to the significant seepage pressure, which was exacerbated by the absence of timely support. Then, ground grouting was promptly conducted to repair the affected area and reinforce the tunnel structure. Subsequent monitoring of surface deformations following the resumption of tunneling operations indicated the effectiveness of the disaster treatment approach. These achievements constitute a reliable theoretical foundation for similar projects, particularly in terms of environmental protection and ensuring safe construction practices.

Abstract Risk management is an important aspect of financial research because correlations among financial data are essential in evaluating portfolio risk. Among various correlations, spatiotemporal correlations involve economic entity attributes and are interrelated in space and time. Such correlations have therefore drawn increasing attention in financial risk management. However, classical correlation measurements are typically based on either time series correlations or spatial dependence; they cannot be directly applied to financial data with spatiotemporal correlations. The spatiotemporal correlation coefficient model with adaptive weight proposed in this paper can (1) address the absolute quantity, dynamic quantity, and dynamic development of financial data and (2) be used for risk grading, financial risk evaluation, and portfolio management. To verify the validity and superiority of this model, cluster analysis results and portfolio performance are compared with a classical model with time series correlation or spatial correlation, respectively. Empirical findings show that the proposed coefficient is highly effective and convenient compared to others. Overall, our method provides a highly efficient financial risk management method with valuable implications for investors and financial institutions.

Background: Ventricular tachycardia (VT) is a life-threatening heart condition commonly seen in patients with myocardial infarction (MI). Although personalized computational modeling has been used to understand VT and its treatment noninvasively, this approach can be computationally intensive and time consuming. Therefore, finding a balance between mesh size and computational efficiency is important. This study aimed to find an optimal mesh resolution that minimizes the need for computational resources while maintaining numerical accuracy and to investigate the effect of mesh resolution variation on the simulation results. Methods: We constructed ventricular models from contrast-enhanced magnetic resonance imaging data from six patients with MI. We created seven different models for each patient, with average edge lengths ranging from 315 to 645 µm using commercial software, Mimics. Programmed electrical stimulation was used to assess VT inducibility from 19 sites in each heart model. Results: The simulation results in the slab model with adaptive tetrahedral mesh (same as in the patient-specific model) showed that the absolute and relative differences in conduction velocity (CV) were 6.1 cm/s and 7.8% between average mesh sizes of 142 and 600 µm, respectively. However, the simulation results in the six patient-specific models showed that average mesh sizes with 350 µm yielded over 85% accuracy for clinically relevant VT. Although average mesh sizes of 417 and 478 µm could also achieve approximately 80% accuracy for clinically relevant VT, the percentage of incorrectly predicted VTs increases. When conductivity was modified to match the CV in the model with the finest mesh size, the overall ratio of positively predicted VT increased. Conclusions: The proposed personalized heart model could achieve an optimal balance between simulation time and VT prediction accuracy when discretized with adaptive tetrahedral meshes with an average edge length about 350 µm.

Abstract This study investigates the predictability of a fixed uncertainty index (UI) for realized variances (volatility) in the international stock markets from a high-frequency perspective. We construct a composite UI based on the scaled principal component analysis (s-PCA) method and demonstrate that it exhibits significant in- and out-of-sample predictabilities for realized variances in global stock markets. This predictive power is more powerful than those of two commonly employed competing methods, namely, PCA and the partial least squares (PLS) methods. The result is robust in several checks. Further, we explain that s-PCA outperforms other dimension-reduction methods since it can effectively increase the impacts of strong predictors and decrease those of weak factors. The implications of this research are significant for investors who allocate assets globally.

BCL-XL and BCL-2 are key anti-apoptotic proteins and validated cancer targets. 753B is a novel BCL-XL/BCL-2 proteolysis targeting chimera (PROTAC) that targets both BCL-XL and BCL-2 to the von Hippel-Lindau (VHL) E3 ligase, leading to BCLX L/BCL-2 ubiquitination and degradation selectively in cells expressing VHL. Because platelets lack VHL expression, 753B spares on-target platelet toxicity caused by the first-generation dual BCL-XL/BCL-2 inhibitor navitoclax (ABT-263). Here, we report pre-clinical single-agent activity of 753B against different leukemia subsets. 753B effectively reduced cell viability and induced dose-dependent degradation of BCL-XL and BCL-2 in a subset of hematopoietic cell lines, acute myeloid leukemia (AML) primary samples, and in vivo patient-derived xenograft AML models. We further demonstrated the senolytic activity of 753B, which enhanced the efficacy of chemotherapy by targeting chemotherapy-induced cellular senescence. These results provide a pre-clinical rationale for the utility of 753B in AML therapy, and suggest that 753B could produce an added therapeutic benefit by overcoming cellular senescence-induced chemoresistance when combined with chemotherapy.

This study focuses on the decreasing relevance of financial information associated with current financial reporting standards for intangible assets. We summarize and compare three approaches to improving financial reporting standards for internally generated intangibles—the recognition approach, the fair value approach and the disclosure approach, among which we focus on the recognition approach. We investigate the impact of current International Accounting Standard 38 on the R&D capitalization policies of the high-tech industry, particularly among medical device firms in China. We conclude that the current recognition criteria are so stringent that they disincentivize firms from capitalizing their R&D investments. A large variation exists in capitalization timing within the medical device industry. Accordingly, we propose the milestone approach to revising financial reporting standards for intangible assets. We suggest that determining the capitalization criteria for intangibles based on the R&D cycle and capitalization timing should be moved forward.

Abstract With the gradual demographic shift toward an aging and obese society, an increasing number of patients are suffering from bone and cartilage injuries. However, conventional therapies are hindered by the defects of materials, failing to adequately stimulate the necessary cellular response to promote sufficient cartilage regeneration, bone remodeling and osseointegration. In recent years, the rapid development of nanomedicine has initiated a revolution in orthopedics, especially in tissue engineering and regenerative medicine, due to their capacity to effectively stimulate cellular responses on a nanoscale with enhanced drug loading efficiency, targeted capability, increased mechanical properties and improved uptake rate, resulting in an improved therapeutic effect. Therefore, a comprehensive review of advancements in nanomedicine for bone and cartilage diseases is timely and beneficial. This review firstly summarized the wide range of existing nanotechnology applications in the medical field. The progressive development of nano delivery systems in nanomedicine, including nanoparticles and biomimetic techniques, which are lacking in the current literature, is further described. More importantly, we also highlighted the research advancements of nanomedicine in bone and cartilage repair using the latest preclinical and clinical examples, and further discussed the research directions of nano-therapies in future clinical practice. Graphical Abstract

Growing global energy demand and limited reserves of traditional energy resources are causing a growing energy shortage. In order to meet future energy needs, new energy resources must be continuously explored. Deepwater drilling research has emerged as one of the key ways to address this issue, and well structure slimming is an effective way to increase drilling speed and reduce costs. The hole size of the second section of deepwater wells decreases from a conventional 660.4 mm to 444.5 mm and increases from 500–800 m to 800–1200 m, creating problems where the conventional 660.4 mm cone bit cannot be used, the rate of penetration (ROP) of the cone bit is low, and the service life is short. To solve these problems, a 444.5 mm artificial polycrystalline diamond compact (PDC) was designed for the first time for use at home or abroad, and according to the characteristics and operation requirements of the 914.4 mm conductor jetting process, a unique anti-collision gauge protector was designed, an innovative bypass nozzle was configured, and a hydraulic design to prevent bit balling in shallow soft mudstone was formulated. PDC jetting bit-drilling technology based on well structure slimming was successfully applied to eight deepwater wells in the eastern South China Sea, which successfully jetted a 914 mm conductor and greatly improved the ROP of their second-section holes. When the below-mudline depth of the second-section hole increased by 37.01%, the average ROP increased by 227.84%. These technical achievements have successfully realized deep drilling with seawater, increased speed and efficiency, achieved good application results, and accumulated valuable experiences that can be used for reducing the cost and increasing the efficiency of offshore drilling operations.

Dynamic risk assessment is a pivotal tool for enhancing construction safety and minimizing the potential for partial failure during deep and extensive excavation projects. To enhance the efficacy of dynamic risk assessment in deep excavation, this study introduces a novel risk assessment model designed to evaluate instability risk in extensive excavations. It comprises a risk factor selection model for identifying the most pertinent factors and an instability risk assessment model for gauging the extent of instability risk throughout the construction process. Then, the model was deployed in the construction of Anshan Road Station of the Qingdao Metro. To pinpoint the factors with the most pronounced impact on excavation instability, a risk factor selection model was employed, yielding a comprehensive risk evaluation index system. For real-time assessment of risk, the monitoring data were used as the primary source of evidence. A comprehensive comparative analysis involving actual data and predictions from conventional RBF and back propagation neural networks was performed. The outcome of this analysis underscored the superior accuracy and predictive capabilities of the assessment model. The instability risk assessment model offers the ability to dynamically evaluate the instability risk associated with extensive excavations featuring a combination of soil and rock. It can serve as a valuable methodological tool, furnishing essential support for the systematic prevention and mitigation of excavation instability disasters.

To realize unmanned aerial vehicle (UAV) situation assessment, a Bayesian network (BN) for situation assessment is established. Aimed at the problem that the parameters of the BN are difficult to obtain, an improved whale optimization algorithm based on prior parameter intervals (IWOA-PPI) for parameter learning is proposed. Firstly, according to the dependencies between the situation and its related factors, the structure of the BN is established. Secondly, in order to fully mine the prior knowledge of parameters, the parameter constraints are transformed into parameter prior intervals using Monte Carlo sampling and interval transformation formulas. Thirdly, a variable encircling factor and a nonlinear convergence factor are proposed. The former and the latter enhance the local and global search capabilities of the whale optimization algorithm (WOA), respectively. Finally, a simulated annealing strategy incorporating Levy flight is introduced to enable the WOA to jump out of the local optimum. In the experiment for the standard BNs, five parameter-learning algorithms are applied, and the results prove that the IWOA-PPI is not only effective but also the most accurate. In the experiment for the situation BN, the situations of the assumed mission scenario are evaluated, and the results show that the situation assessment method proposed in this article is correct and feasible.

The increasing inshore marine litters (IML) have been jeopardizing the coastal ecology and environment and have attracted widespread concerns. Nevertheless, the accurate detection and quantitative characterization of IML remain a challenge. In this study, a new method is proposed to automatically detect and extract the IML from terrestrial laser scanning (TLS) 3D point clouds. IML are progressively extracted from the surroundings through four major steps by jointly using the radiometric/intensity information and a series of derived geometric features. First, the intensity data are calibrated by a polynomial model for an initial segmentation according to the spectral differences between the IML and surroundings. Second, a new proposed model is used to calibrate the density data for a further discrimination based on the size discrepancies between the IML and surroundings. Third, a connectivity clustering algorithm is used to group the points into different clusters. Cluster geometric features in terms of the shapes and patterns (i.e., linearity, sizes, and verticality) are constructed to identify the IML. Fourth, a geometric self-repairing procedure is used to retrieve the misclassified IML points. An artificially-arranged scene on a bare mudflat and four natural scenes with different circumstances and IML categories are investigated to validate the proposed method. The overall accuracy and kappa coefficient of the proposed method are averagely 98% and 0.69, respectively. Compared with the classical methods, the proposed method shows good robustness performance in different natural scenes with varied IML categories, vegetation coverages, and environmental disturbances. The proposed method shows great promise in IML spatiotemporal interpretation and provides an alternative tool for the validation of large-scale IML products from space-borne or airborne remote sensing platforms.