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Abstract Reconfigurable intelligent surface (RIS)‐assisted physical layer key generation plays an important role in the eavesdropping problem on a typical multi‐user scenario of wireless networks. Existing RIS‐assisted physical key generation technology mainly solved the security issues in the single‐antenna and multi‐user scenario, which is based on the idealistic assumption of a spatially independent channel model at the RIS. It limits the degrees of freedom and neglects the existence of channel spatial correlation, which would possibly degrade the sum key generation rate (SKGR). To solve the above problem, this paper proposes a secret key generation scheme for RIS‐assisted multiple‐input single‐output multi‐user system. This scheme establishes a spatial correlation channel model, which comprehensively considers the influence of spatial correlation among antennas of the base station (BS), multi‐user, and RIS elements on SKGR. Based on this, a key generation framework is designed to generate a more secure secret key with the maximum SKGR. Specifically, a closed‐form SKGR expression and an optimization problem formulation are obtained to obtain the joint optimal coefficient of the BS and RIS. Then, the difference convex‐successive convex approximation based alternating optimization algorithm is proposed to solve this optimization problem. The simulation results show that the proposed scheme has improved 10‐bit/channel use compared with the randomization scheme of BS precoding and RIS reflection coefficient. It also has an improvement of 12‐bit/channel use compared with the spatially independent scheme.

Abstract Background Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) are prevalent metabolic disorders with overlapping pathophysiological mechanisms. A comprehensive understanding of the shared molecular pathways involved in these conditions can advance the development of effective therapeutic interventions. Methods We used two datasets sourced from the Gene Expression Omnibus (GEO) database to identify common differentially expressed genes (DEGs) between T2D and NAFLD. Subsequently, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to identify the enriched biological processes and signaling pathways. In addition, we performed a protein-protein interaction (PPI) network analysis to identify hub genes with pivotal roles. To validate our findings, we established a type 2 diabetic mouse model with NAFLD. Results Our analysis identified 53 DEGs shared between T2D and NAFLD. Enrichment analysis revealed their involvement in signal transduction, transcriptional regulation, and cell proliferation as well as in the ferroptosis signaling pathways. PPI network analysis identified ten hub genes, namely CD44, CASP3, FYN, KLF4, HNRNPM, HNRNPU, FUBP1, RUNX1, NOTCH3, and ANXA2. We validated the differential expression of FYN, HNRNPU, and FUBP1 in liver tissues of a type 2 diabetic mouse model with NAFLD. Conclusions Our study offers valuable insights into the shared molecular mechanisms underlying T2D and NAFLD. The identified hub genes and pathways present promising prospects as therapeutic targets to address these prevalent metabolic disorders.

Background and AimsThis study aimed to develop a prognostic model based on DNA methylation-driven genes for patients with early-stage gastric cancer and to examine immune infiltration and function across varying risk levels.MethodsWe analyzed data from stage I/II gastric cancer patients in The Cancer Genome Atlas which included clinical details, mRNA expression profiles, and level 3 DNA methylation array data. Using the empirical Bayes method of the limma package, we identified differentially expressed genes (DEGs), and the MethylMix package facilitated the identification of DNA methylation-driven genes (DMGs). Univariate Cox regression and LASSO (least absolute shrinkage and selector operation) analyses were utilized to pinpoint critical genes. A risk score prediction model was formulated using two genes that demonstrated the most significant hazard ratios (HRs). Model performance was evaluated within the initial cohort and verified in the GSE84437 cohort; a nomogram was also constructed based on these genes. We further examined 50 methylation sites associated with three CpG islands in C1orf35 and 14 methylation sites linked to one CpG island in FAAH. The CIBERSORT package was employed to identify immune cell clusters in the prediction model.ResultsA total of 176 DNA methylation-driven genes were refined down to a four-gene signature (ZC3H12A was hypermethylated; GATA3, C1orf35, and FAAH were hypomethylated), which exhibited a significant correlation with overall survival (OS), as evidenced by p-values below 0.05 following univariate Cox regression and LASSO analysis. Specifically, for the risk score prediction model, C1orf35, which had the highest hazard ratio (HR = 2.035, p = 0.028), and FAAH, with the lowest hazard ratio (HR = 0.656, p = 0.012), were selected. The Kaplan–Meier analysis demonstrated distinct survival outcomes between the high-risk and low-risk score groups. The model’s predictive accuracy was confirmed with an area under the curve (AUC) of 0.611 for 3-year survival and 0.564 for 5-year survival. Notably, the hypomethylation of the three CpG islands in C1orf35 and the single CpG island in FAAH was significantly different in stage I/II gastric cancer patients compared to normal tissues. Additionally, the high-risk score group showed a notable association with resting CD4 memory T cells.ConclusionPromoter hypomethylation of C1orf35 and FAAH in early-stage gastric cancer underscores their potential as biomarkers for accurate diagnosis and treatment. The developed predictive model employing genes affected by DNA methylation serves as a crucial independent prognostic factor in early-stage gastric cancer.

The prevalence of ship deficiencies continues to be a significant issue. Data from the Tokyo Memorandum of Understanding reveals that ship detentions in 2023 surged by more than 80% compared with the previous year. The significant number of detained ships not only disrupts ships’ daily operations but also strains port resources, leading to increased additional costs. In light of this issue, predicting the duration of ship detention becomes crucial, as accurate predictions can assist port managers in resource allocation and provide shipping companies with critical information for operational planning. This study is the first to predict ship detention duration, specifically distinguishing between long-term and short-term detained ships. Initially, key deficiency types influencing the ship detention duration were identified using an improved entropy weight–grey relational analysis. Subsequently, in consideration of the imbalance in data distribution between long-term and short-term detentions, a random forest model capable of handling imbalanced data was applied to classify these two types. The study found that fire safety, propulsion and auxiliary machinery, and pollution prevention are the three most critical deficiency types impacting detention duration; and the random forest model sampled and processed from the data level possessed the best model performance, achieving prediction accuracies of 0.71, 0.72, and 0.85 for bulk carriers, containers, and oil tankers, respectively. This research offers a comprehensive analysis of ship detention duration, making a significant contribution to both the theoretical understanding and practical applications in the maritime industry. Accurately predicting ship detention duration provides valuable insights for stakeholders, enabling them to anticipate potential detention scenarios and thus supporting shipping companies in effective fleet management while assisting port authorities in the optimal allocation of berth resources.

The need for an accurate inventory of ship emissions is vital for atmospheric scientists assessing the environmental impact of shipping and for policymakers aiming to regulate and incentivize emission reduction. This study used data from 189 international ports, related to ship arrivals and departures, to develop emissions inventories. Emission characteristics were examined in detail, classifying emissions by factors like ship type, month, and region. The analysis identified oil tankers and container ships as main emitters among ship categories. A detailed analysis of the monthly distribution of emissions from vessels at berth worldwide was conducted based on precise arrival and departure times. Singapore, Rotterdam, and Antwerp were the ports with the highest emissions from ships at berth. Overall, this study presents the spatial and temporal emission characteristics of ships at berth in 3912 ports around the world, which can support the development of emission reduction strategies in port management.

Background and purposeFavorable wall apposition of a flow diverter (FD) is essential for the treatment of intracranial aneurysms. The irretrievability and final drop point uncertainty of the proximal tail of the FD increase the difficulty of achieving good tail apposition. Therefore, understanding the factors associated with FD tail malapposition would be helpful for clinical practice.MethodsA total of 153 patients with 161 FD deployments in the carotid artery between 2020 and 2023 were retrospectively collected from our center’s database for this study. Patient demographics, aneurysm characteristics, FDs, carotid artery anatomy, periprocedural complications, discharge modified Rankin scale (MRS) scores, and follow-up outcomes were investigated by comparing patients with and without FD tail malapposition. Comparisons were made with t tests or Kruskal–Wallis tests for continuous variables and the Pearson χ2 or Fisher exact test for categorical variables. Logistic regression was conducted to determine the predictors of malapposition.ResultsTail malapposition occurred for 41 out of the 161 FDs (25.5%). Univariate analysis revealed that the FD brand, FD length, FD distal to proximal vessel diameter ratio, FD tail position (straight or curved), and curvature of the vessel curve were significantly associated with FD tail malapposition (p

Abstract Objective Systemic lupus erythematosus (SLE) patients are at risk during the COVID‐19 pandemic, yet the underlying molecular mechanisms remain incompletely understood. This study sought to analyze the potential molecular connections between COVID‐19 and SLE, employing a bioinformatics approach to identify effective drugs for both conditions. Methods The data sets GSE100163 and GSE183071 were utilized to determine share differentially expressed genes (DEGs). These DEGs were later analyzed by various bioinformatic methods, including functional enrichment, protein–protein interaction (PPI) network analysis, regulatory network construction, and gene–drug interaction construction. Results A total of 50 common DEGs were found between COVID‐19 and SLE. Gene ontology (GO) functional annotation revealed that “immune response,” “innate immune response,” “plasma membrane,” and “protein binding” were most enriched in. Additionally, the pathways that were enriched include “Th1 and Th2 cell differentiation.” The study identified 48 genes/nodes enriched with 292 edges in the PPI network, of which the top 10 hub genes were CD4, IL7R, CD3E, CD5, CD247, KLRB1, CD40LG, CD7, CR2, and GZMK. Furthermore, the study found 48 transcription factors and 8 microRNAs regulating these hub genes. Finally, four drugs namely ibalizumab (targeted to CD4), blinatumomab (targeted to CD3E), muromonab‐CD3 (targeted to CD3E), and catumaxomab (targeted to CD3E) were found in gene–drug interaction. Conclusion Four possible drugs that targeted two specific genes, which may be beneficial for COVID‐19 patients with SLE.

Objective: Construction of a simple and rapid method for the analysis of ganoderic acid A （GAA）. Methods: The molecular imprinted polymer （MIP） that can specifically recognize ganoderic acid A （GAA） were prepared by cyclic voltammetric deposition using GAA as template molecule and o-phenylenediamine as functional monomer. The structure, morphology and electrochemical behavior of MIP were characterized by infrared spectroscopy, scanning electron microscopy and electrochemical methods. Using [Fe（CN）6]3-/4- as the active indicator, the analytical performance of the sensor for GAA was investigated. Porous MIP for GAA can be prepared on the electrode surface by one-step electropolymerization. Results: The results of quantitative analysis showed that the electrochemical signal of [Fe（CN）6]3-/4- had a good linear relationship with the logarithm of GAA concentration in the range of 1.0 pmol/L～1.0 μmol/L, and the detection limit was 0.21 pmol/L. The measured values of GAA in ethanol and water-soluble solution of Ganoderma lucidum powder were 1.15 nmol/L and 3.00 pmol/L, respectively. Conclusion: The MIP-based GAA electrochemical sensor can be used for the rapid determination of GAA in extract solution of Ganoderma lucidum powder.

On the basis of systematically sorting out the potential risk sources of underground structure construction, this paper describes the surrounding medium of underground structure as soil mass and rock mass. The main risk source of the underground structure based on soil medium comes from the construction mechanics analysis in the construction stage, and the leading factor of the underground structure loading in the construction stage is the stress-strain relationship of soil based on the unloading path. The deep underground engineering structure is faced with a series of disasters such as high-strength water escape, high-strength rock burst, large deformation of soft rock, boulder collapse and rock burst under the action of unloading. In view of the unloading paths faced by the above two different media, the corresponding physical models are developed to describe the above phenomena according to their respective disaster evolution mechanism and disaster breeding mechanism, and the corresponding indexes required for the safety of engineering structures are obtained by solving the physical equations. According to the above indicators, the engineering structure and surrounding media in the construction process are monitored accordingly, and the feedback of the monitoring data is used to obtain the risk assessment and modify the current construction sequence, so as to provide a reference for better serving the construction safety of underground engineering structures.

IntroductionThe expansion of maritime trade has led to the introduction of invasive species into aquatic ecosystems through ballast water discharge. China, being a major player in global trade and manufacturing, has experienced negative impacts on its coastal ecosystems and marine biodiversity.MethodsThis study examines the cost‒benefit trade-offs of ballast water management policies for major port clusters in China and other global ports. This paper evaluates compliance costs for individual vessels and fleets under different policy scenarios and ballast water treatment system (BWTS) installation strategies.ResultsThe onboard BWTS installation strategy appears to be more cost-effective under the existing International Maritime Organization (IMO) policy. However, with stricter global discharge requirements or a substantial increase in BWTS capital and operating costs, strategies based on port location could prove more beneficial due to potential economies of scale. Notably, ships with high ballast water discharge volumes, like bulk carriers, are potentially better equipped to cope with future policy shifts. In the face of stricter regulations in China, projected annual compliance cost increases range from $456 million (cost data based on China) to $1.205 billion (cost data based on US).DiscussionPolicymakers are advised to adopt a comprehensive view of ballast water management policies, taking into account the trade-offs between compliance costs and environmental risks. Other essential factors, such as advancements in BWTS technology, fuel consumption, emissions, and maintenance costs, also demand careful consideration in policy development.

ObjectiveTo elucidate the clinicopathological characteristics and prognostic factors of poorly differentiated thyroid carcinoma.MethodA total of 24912 thyroid carcinoma patients admitted to the First Medical Center of Chinese People’s Liberation Army General Hospital from 2005 to 2020 were retrospectively reviewed. A total of 94 patients (39 males and 55 females, a male-female ratio of 1:1.4) fulfilled the selection criteria. Of these, 73 patients had undergone surgery. The clinical and pathological data were collected from each enrolled patient. Univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors. All analyses were performed with the SPSS version 26.0 and R version 1.2.5033 in the R Studio environment.ResultsThe specimens included 20 cases of poorly differentiated thyroid carcinoma complicated with papillary thyroid carcinoma, 17 cases complicated with follicular thyroid carcinoma, 34 cases complicated with other pathological types and 23 with a separate entity. The patient demonstrated a large age span, median age was 57 years (range 8–85 years, average 55.20 ± 15.74 years). The survival time of the 94 cases was calculated, and the mean Overall survival time was 33 (range, 1-170) months, and the mean Recurrence-free survival time was 14 (range, 1-90) months. Recurrence-free mortality is related to the age at diagnosis, extrathyroidal extension and Associated thyroid cancer (p

Cabotegravir is an integrase strand transfer inhibitor (INSTI) for HIV treatment and prevention. Cabotegravir-based long-acting pre-exposure prophylaxis (PrEP) presents an emerging paradigm for infectious disease control. In this scheme, a combination of a high efficacy and low solubility of anti-infection drugs permits the establishment of a pharmaceutical firewall in HIV-vulnerable groups over a long period. Although the structure-activity-relationship (SAR) of cabotegravir as an INSTI is known, the structural determinants of its low solubility have not been identified. In this work, we have integrated multiple experimental and computational methods, namely X-ray diffraction, solid-state NMR (SSNMR) spectroscopy, solution NMR spectroscopy, automated fragmentation (AF)-QM/MM and density functional theory (DFT) calculations, to address this question. The molecular organization of cabotegravir in crystal lattice has been determined. The combination of very-fast magic-angle-sample-spinning (VF MAS) SSNMR and solution NMR, as supported by AF-QM/MM and DFT calculations, permits the identification of structural factors that contribute to the low aqueous solubility of cabotegravir. Our study reveals the multitasking nature of pharmacophores in cabotegravir, which controls the drug solubility and, meanwhile, the biological activity. By unraveling these function-defining molecular features, our work could inspire further development of long-acting HIV PrEP drugs.

BackgroundThe primitive hypoglossal artery (PHA) is an anastomotic vessel of the carotid-basilar artery system that is prevalent only transiently during the embryonic period. Persistent primitive hypoglossal artery (PPHA) is a rare vessel variation in which PHA exists persistently in adulthood and occurs in approximately 0.02–0.1% of the population. Tortuosity of the extracranial internal carotid artery (ICA) is relatively common, impacting 10–43% of the population, and is caused by either congenital or acquired factors. It is still unknown whether PPHA and tortuosity of extracranial ICA are associated. Here, we present a case report of the concurrence of three types of pathologies of the carotid artery: extreme coiling of the extracranial internal carotid artery, multiple aneurysms and persistent primitive hypoglossal artery.Case descriptionA 66-year-old woman suffered intermittent headaches, dizziness and numbness of the right eyelid for 5 years. Magnetic resonance angiography performed in a local hospital reported an aneurysm of the posterior communicating artery segment of the left ICA and a left PPHA. Digital subtraction angiography conducted after admission showed a PPHA originating from the left cervical ICA and an extremely coiling segment of the ICA distal to the beginning of PPHA. Except for the aneurysm of the posterior communicating artery segment of the left ICA, multiple aneurysms were found at the coiling segment of the ICA.ConclusionTo the best of our knowledge, this is the first report of PPHA accompanied by an adjacent, extremely coiling ICA. There are no reports of similar tortuous ICAs to this extent or at this position. Including aneurysms, three types of pathologies suggest their congenital origin, and a review of the literature infers the probable association of these lesions.

ObjectiveTo develop a web-based machine learning server to predict lateral lymph node metastasis (LLNM) in papillary thyroid cancer (PTC) patients.MethodsClinical data for PTC patients who underwent primary thyroidectomy at our hospital between January 2015 and December 2020, with pathologically confirmed presence or absence of any LLNM finding, were retrospectively reviewed. We built all models from a training set (80%) and assessed them in a test set (20%), using algorithms including decision tree, XGBoost, random forest, support vector machine, neural network, and K-nearest neighbor algorithm. Their performance was measured against a previously established nomogram using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), precision, recall, accuracy, F1 score, specificity, and sensitivity. Interpretable machine learning was used for identifying potential relationships between variables and LLNM, and a web-based tool was created for use by clinicians.ResultsA total of 1135 (62.53%) out of 1815 PTC patients enrolled in this study experienced LLNM episodes. In predicting LLNM, the best algorithm was random forest. In determining feature importance, the AUC reached 0.80, with an accuracy of 0.74, sensitivity of 0.89, and F1 score of 0.81. In addition, DCA showed that random forest held a higher clinical net benefit. Random forest identified tumor size, lymph node microcalcification, age, lymph node size, and tumor location as the most influentials in predicting LLNM. And the website tool is freely accessible at http://43.138.62.202/.ConclusionThe results showed that machine learning can be used to enable accurate prediction for LLNM in PTC patients, and that the web tool allowed for LLNM risk assessment at the individual level.

BackgroundDynamic artificial intelligence (AI) ultrasound intelligent auxiliary diagnosis system (Dynamic AI) is a joint application of AI technology and medical imaging data, which can perform a real-time synchronous dynamic analysis of nodules. The aim of this study is to investigate the value of dynamic AI in differentiating benign and malignant thyroid nodules and its guiding significance for treatment strategies.MethodsThe data of 607 patients with 1007 thyroid nodules who underwent surgical treatment were reviewed and analyzed, retrospectively. Dynamic AI was used to differentiate benign and malignant nodules. The diagnostic efficacy of dynamic AI was evaluated by comparing the results of dynamic AI examination, preoperative fine needle aspiration cytology (FNAC) and postoperative pathology of nodules with different sizes and properties in patients of different sexes and ages.ResultsThe sensitivity, specificity and accuracy of dynamic AI in the diagnosis of thyroid nodules were 92.21%, 83.20% and 89.97%, respectively, which were highly consistent with the postoperative pathological results (kappa = 0.737, p < 0.001). There is no statistical difference in accuracy between people with different ages and sexes and nodules of different sizes, which showed the good stability. The accuracy of dynamic AI in malignant nodules (92.21%) was significantly higher than that in benign nodules (83.20%) (p < 0.001). The specificity and positive predictive value were significantly higher, and the misdiagnosis rate was significantly lower in dynamic AI than that of preoperative ultrasound ACR TI-RADS (p < 0.001). The accuracy of dynamic AI in nodules with diameter ≤ 0.50 cm was significantly higher than that of preoperative ultrasound (p = 0.044). Compared with FNAC, the sensitivity (96.58%) and accuracy (94.06%) of dynamic AI were similar.ConclusionsThe dynamic AI examination has high diagnostic value for benign and malignant thyroid nodules, which can effectively assist surgeons in formulating scientific and reasonable individualized diagnosis and treatment strategies for patients.

There are many influencing factors present in different situations of power load. There is also a strong imbalance in the number of load samples. In addition to examining the problem of low training efficiency of existing algorithms, this paper proposes a short-term power load prediction method based on feature selection and error compensation under imbalanced samples. After clustering the load data, we expand some sample data to balance the sample categories and input the load data and filtered feature sequences into the improved GRU for prediction. At the same time, the errors generated during the training process are used as training data. An error correction model is constructed and trained, and the results are used for error compensation to further improve prediction accuracy. The experimental results show that the overall prediction accuracy of the model has increased by 80.24%. After expanding a few samples, the prediction accuracy of the region where the samples are located increased by 59.41%. Meanwhile, due to the improvement of the algorithms, the running time was reduced by approximately 14.92%.

Abstract The existing secret key generation (SKG) techniques are not applicable for frequency division duplex (FDD) Internet of Things networks due to the low power constraints and limited computing resources. This letter proposes a SKG scheme based on the channel covariance matrix in FDD systems. First of all, a novel algorithm is proposed for inferring the downlink channel covariance matrix from the observed uplink channel covariance matrix with the aid of the transformation matrix. Then, a complete SKG scheme for low‐power terminals in FDD systems is designed to generate keys from the downlink channel covariance matrix. Finally, simulation results show that this scheme can generate high‐agreement secret keys in FDD systems. Compared with the loopback mechanism‐based SKG scheme, this scheme is suitable for low‐power terminals and can achieve significant performance improvement in terms of the key disagreement ratio.

Abstract Aims/Introduction We aimed to investigate the relationship between glycemic status and coronary artery disease (CAD) extent and severity in ST‐elevation myocardial infarction (STEMI) patients, and further examine whether diabetes patients could benefit from glycosylated hemoglobin (HbA1c) below the recommended level. Materials and Methods Consecutive STEMI patients admitted in 2015–2017 across 244 hospitals were included in the China STEMI Care Project‐2. We carried out a cross‐sectional study comprising 8,370 participants with a record of HbA1c testing after admission. CAD extent and severity were assessed by admission heart rate, Killip classification and the number of stenosed vessels based on the coronary angiogram. Results Diabetes patients showed a greater risk for higher Killip class, admission tachycardia (admission heart rate ≥100 b.p.m.) and multivessel CAD (presence of left main and/or triple vessel disease). Likewise, HbA1c level was significantly associated with CAD extent and severity. While dividing diabetes patients according to general HbA1c targets (HbA1c ≤6.5, 6.5–7.0 and ≥7.0%), diabetes patients with HbA1c ≤6.5% showed a 1.30‐fold higher risk for multivessel CAD (adjusted odds ratio 1.30, 95% confidence interval 1.05–1.62). In stratified analysis, the association was even stronger in patients with hypertension (adjusted odds ratio 1.41, 95% confidence interval 1.08–1.86) or hyperlipidemia (adjusted odds ratio 1.57, 95% confidence interval 1.17–2.12). Conclusions HbA1c level is independently correlated with CAD extent and severity in STEMI patients. HbA1c below generally recommended levels might still increase the risk of CAD progression, especially for diabetes patients with hypertension or hyperlipidemia.

The international crude oil maritime transportation system has always been disturbed by the external environment and its own mechanism of supply and demand, which can sometimes last for a long time. BDTI (Baltic Exchange Dirty Tanker Index) is one of the most typical indexes in the crude oil maritime transportation market, which is affected by many uncertain events and often lasts for a long time. So it is very significant to study fluctuation characteristics of the crude oil maritime transportation system and assess the impact of critical events, which have been referred to in this paper by improving the R/S model and selecting three international transportation lines in marine shipping ranging from 2008 to 2019. Through model applications, numerical results validate the effectiveness of this method, showing all of the three transportation lines possess long-term memory. The impact of the four critical events has also been evaluated. The study will help crude oil enterprises make investment decision on potential transportation lines and give policymakers advice to maintain stability of the crude oil industry.

The rapid development of Internet technology meant that online supply chain finance has become an important source of small- and medium-sized enterprise (SME) finance. From a review of associated studies, this study constructed an online supply chain financial credit risk evaluation index system that had eleven level 2 indicators and 28 level 3 indicators for the four dimensions of financing enterprise qualification, core enterprise qualification, supply chain operations, and the macroenvironment. To assess the viability of this indicator system, data on 368 SMEs in four industries, clothing, home appliances, pharmaceutical, and construction, were selected as research samples. An online supply chain financial credit risk evaluation model for the different industries was then constructed using principal component analysis (PCA) and logistic regression methods. It was concluded that when evaluating online supply chain financial credit risk, it is necessary to focus on the solvency, profitability, and asset structure efficiencies of the financing enterprises. Due to the different production and operating characteristics of industries, significant variations in the degree and direction of the credit risk factors between industries were found; therefore, evaluating credit risks by industry significantly improved the accuracy of the model’s credit risk predictions. For example, home appliance SMEs need to pay greater attention to their inventory turnover and construction industry SMEs should pay greater attention to their sales growth rate, return on common stockholders’ equity, and GDP growth rate. Based on these results, some suggestions for commercial banks, supply chain core enterprises, and SMEs are given to improve supply chain financing. The conclusion of this study enriches the related research on credit risk assessment of SMEs and also provides decision support for improving SMEs to prevent credit risk.

The similarity of logistics functions of ports and the overlapped economic hinterlands, as well as the competition and mutual effects between port infrastructure contribute to the extremely complex service effect between logistics services of ports. How to define the complex network evolution patterns of service effect between different ports becomes essential. This study builds a BBV(Barrat, Barthélemy and Vespignani model) weighted network evolution model to analysis the complex network evolution laws of the service effect of typical seaports in coastal China. We select key assessment factors that affect the service effect of ports, establish a complex network analysis model for port service effect. 15 typical seaports in coastal China are selected for empirical research to verify the practicality and effectiveness of the established model in analysis for complex networks of ports' service effect. The results show that the network presents a hub-and-spoke spatial pattern featuring a small world and no scales, and presents polarized and complex evolution characteristics. The results of this study are conducive to government departments and policy makers for understanding port development and evolution laws, so as to roll out effective strategies as appropriate to manage and promote sustainable development of ports.

Abstract Background Primary cutaneous malignant melanoma is a cancer of the pigment cells of the skin, some of which are accompanied by BRAF mutation. Melanoma incidence and mortality rates have been rising around the world. As the current knowledge about pathogenesis, clinical and genetic features of cutaneous melanoma is not very clear, we aim to use bioinformatics to identify the potential key genes involved in the expression and mutation status of BRAF. Methods Firstly, we used UCSC public hub datasets of melanoma (Lin et al., Cancer Res 68(3):664, 2008) to perform weighted genes co-expression network analysis (WGCNA) and differentially expressed genes analysis (DEGs), respectively. Secondly, overlapping genes between significant gene modules and DEGs were screened and validated at transcriptional levels and overall survival in TCGA and GTEx datasets. Lastly, the functional enrichment analysis was accomplished to find biological functions on the web-server database. Results We performed weighted correlation network and differential expression analyses, using gene expression data in melanoma samples. We identified 20 genes whose expression was correlated with the mutation status of BRAF. For further validation, three of these genes (CYR61, DUSP1, and RNASE4) were found to have similar expression patterns in skin tumors from TCGA compared with normal skin samples from GTEx. We also found that weak expression of these three genes was associated with worse overall survival in the TCGA data. These three genes were involved in the nucleic acid metabolic process. Conclusion In this study, CYR61, DUSP1, and RNASE4 were identified as potential genes of interest for future molecular studies in melanoma, which would improve our understanding of its causes and underlying molecular events. These candidate genes may provide a promising avenue of future research for therapeutic targets in melanoma.

Physical-layer key generation technology requires information reconciliation to correct channel estimation errors between two legitimate users. However, sending the reconciliation signals over the public channel increases the communication overhead and the risk of information leakage. Aiming at the problem, integrated secure communication schemes using non-reconciled keys have attracted extensive attention. These schemes exploit channel coding to correct both inconsistent keys and transmission error bits. Meanwhile, more redundant code bits must be added to correct errors, which results in a lower secure transmission rate. To address the problem, we analyze the merit of channel correlation between non-reconciled key generation and secure transmission. Inspired by this, we propose a non-reconciled physical-layer keys-assisted secure communication scheme based on channel correlation. First of all, the signal frame is designed to make use of channel correlation between non-reconciled key generation and secure transmission. Based on the channel correlation, non-reconciled keys are then generated from the wireless channel to encrypt transmitted data. Moreover, an adaptive coding algorithm based on the equivalent channel is presented to encode the data bits before encryption, to guarantee reliable transmission. Finally, theoretical analysis and simulations demonstrate the significant performance of the proposed scheme in terms of low bit error ratio and high secure transmission rate.

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement.

Regional container port operation plays a crucial role in international trade and economic development. Amid fierce competition, orderly running of regional ports is vital. The rank-size status of the regional container ports indicates the orderliness and distribution concentration of port system development and is the focus of port administrations and port operators. This paper introduces the rank-size distribution rule into studies on the development of regional container port systems and proves that Zipf's three-parameter model can effectively describe the evolvement of the rank-size system of regional container ports, taking the container port group in the Yangtze River Delta as an example. This paper finds that the regional container ports tend to become concentrated in high ranks during evolvement. Moreover, the macroeconomic environment has a great impact on the distribution concentration of regional container ports. Economic procyclicality can accelerate port concentration. On the other hand, economic counter-cyclicality will induce port decentralization. The results of this paper are conducive to port administrations and enterprises to gain a more comprehensive understanding of the development of regional container ports and to formulate the proper development plans. The results are also helpful for government departments to well design the development strategies for port and shipping development and better steer the benign development of regional container port groups.

This work used the natural ingredient stigmasterol as an oleogelator to explore the effect of concentration on the properties of organogels. Organogels based on rapeseed oil were investigated using various techniques (oil binding capacity, rheology, polarized light microscopy, X-ray diffraction, and Fourier transform infrared spectroscopy) to better understand their physical and microscopic properties. Results showed that stigmasterol was an efficient and thermoreversible oleogelator, capable of structuring rapeseed oil at a stigmasterol concentration as low as 2% with a gelation temperature of 5 °C. The oil binding capacity values of organogels increased to 99.74% as the concentration of stigmasterol was increased to 6%. The rheological properties revealed that organogels prepared with stigmasterol were a pseudoplastic fluid with non-covalent physical crosslinking, and the G’ of the organogels did not change with the frequency of scanning increased, showing the characteristics of strong gel. The microscopic properties and Fourier transform infrared spectroscopy showed that stigmasterol formed rod-like crystals through the self-assembly of intermolecular hydrogen bonds, fixing rapeseed oil in its three-dimensional structure to form organogels. Therefore, stigmasterol can be considered as a good organogelator. It is expected to be widely used in food, medicine, and other biological-related fields.

Melting and gasification behavior of Ca Al cored wire with 0.74-mm steel sheet and better feeding process in 1873 K molten steel in 150 t ladle was simulated, and the influence of different Ca cored wire and composition of liquid steel on Ca recovery were analyzed.The results show that calcium alloy of Ca Al cored wire has smelted before its covering steel sheet melts when cored wire is fed into molten steel, melting time of Ca Al cored wire is 0.92 s, then liquid Ca alloy diffuses into liquid steel.Liquid Ca alloy floats upward to 1.22 m below the liquid steel surface and gasifies when alloy has get enough steam pressure of gasification.The feeding speed of 3.22-4.83 m·s-1for Ca Al cored wire is appropriate to get ideal feeding depth of 2.96 m in ladle with liquid steel.When the elements contents of carbon, silicon and manganese in liquid steel are high, pure Ca cored wire should be used to get bigger Ca recovery, on the contrary, Ca Al cored wire is a better option for low carbon liquid steel with low elements contents of silicon and manganese.

The recent European Union Ship Recycling Regulation and other existing conventions aimed to reduce harmful environmental and health impacts of ship shipbreaking, may push the shipbreaking industry further to South Asian countries, where ecosystem and public health are threatened due to the lack of monitoring for dirty beaching methods for ship breaking. Such unsustainable patterns may continue to expand due to the mismatch of economic beneficiaries and environmental costs in the shipbreaking industry, the ineffectiveness of existing conventions and regulations, and the prospect of a large number of ships to be dismantled in the near future. Our study focuses on these emerging issues and raises the urgency of joint actions for the shipbreaking industry.

Background. As a multifaceted disease, atherosclerosis is often characterized by the formation and accumulation of plaque anchored to the inner wall of the arteries and causes some cardiovascular diseases and vascular embolism. Numerous studies have reported on the pathogenesis of atherosclerosis. However, fewer studies focused on both genes and immune cells, and the correlation of genes and immune cells was evaluated via comprehensive bioinformatics analyses. Methods. 29 samples of atherosclerosis-related gene expression profiling, including 16 human advanced atherosclerosis plaque (AA) and 13 human early atherosclerosis plaque (EA) samples from the Gene Expression Omnibus (GEO) database, were analyzed to get differentially expressed genes (DEGs) and the construction of protein and protein interaction (PPI) networks. Besides, we detected the relative fraction of 22 immune cell types in atherosclerosis by using the deconvolution algorithm of “cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT).” Ultimately, based on the significantly changed types of immune cells, we executed the correlation analysis between DEGs and immune cells to discover the potential genes and pathways associated with immune cells. Results. We identified 17 module genes and 6 types of significantly changed immune cells. Correlation analysis showed that the relative percentage of T cell CD8 has negative correlation with the C1QB expression (R=−0.63, p=0.02), and the relative percentage of macrophage M2 has positive correlation with the CD86 expression (R=0.57, p=0.041) in EA. Meanwhile, four gene expressions (CD53, C1QC, NCF2, and ITGAM) have a high correlation with the percentages of T cell CD8 and macrophages (M0 and M2) in AA samples. Conclusions. In this study, we suggested that the progression of atherosclerosis might be related to CD86, C1QB, CD53, C1QC, NCF2, and ITGAM and that it plays a role in regulating immune-competent cells such as T cell CD8 and macrophages M0 and M2. These results will enable studies of the potential genes associated with immune cells in the progression of atherosclerosis, as well as provide insight for discovering new treatments and drugs.

Neurodegenerative diseases are disorders that are characterized by a progressive decline of motor and/or cognitive functions caused by the selective degeneration and loss of neurons within the central nervous system. The most common neurodegenerative diseases are Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD). Neurons have high energy demands, and dysregulation of mitochondrial quality and function is an important cause of neuronal degeneration. Mitochondrial quality control plays an important role in maintaining mitochondrial integrity and ensuring normal mitochondrial function; thus, defects in mitochondrial quality control are also significant causes of neurodegenerative diseases. The mitochondrial deacetylase SIRT3 has been found to have a large effect on mitochondrial function. Recent studies have also shown that SIRT3 has a role in mitochondrial quality control, including in the refolding or degradation of misfolded/unfolded proteins, mitochondrial dynamics, mitophagy, and mitochondrial biogenesis, all of which are affected in neurodegenerative diseases.

Introduction Successful ST-segment elevation myocardial infarction (STEMI) management is time-sensitive and is based on prompt reperfusion mainly to reduce patient mortality. It has evolved from a single hospital care to an integrated regional network approach over the last decades. This prospective study, named the China STEMI Care Project (CSCAP), aims to show how implementation of different types of integrated regional STEMI care networks can improve the reperfusion treatment rate, shorten the total duration of myocardial ischaemia and lead to mortality reduction step by step.Methods and analysis The CSCAP is a prospective, multicentre registry study of three phases. A total of 18 provinces, 4 municipalities and 2 autonomous regions in China were included. Patients who meet the third universal definition of myocardial infarction and the Chinese STEMI diagnosis and treatment guidelines are enrolled. Phase 1 (CSCAP-1) focuses on the in-hospital process optimisation of primary percutaneous coronary intervention (PPCI) hospitals, phase 2 (CSCAP-2) focuses on the PPCI hospital-based regional STEMI care network construction together with emergency medical services and adjacent non-PPCI hospitals, while phase 3 (CSCAP-3) focuses on the whole-city STEMI care network construction by promoting chest pain centre accreditation. Systematic data collection, key performance index assessment and subsequent improvement are implemented throughout the project to continuously improve the quality of STEMI care.Ethics and dissemination The study has been reviewed and approved by the Ethics Committee of Peking University First Hospital. Ranking reports of quality of care will be generated available to all participant affiliations. Results will be disseminated via peer-reviewed scientific journals and presentations at congresses.Trial registration number NCT03821012.

To understand the refinement mechanisms of inclusions in steel,the morphology,size,composition and number of inclusions in low C-Mn steel were characterized by scanning electron microscopy and energy dispersive spectroscopy. The predominance area diagram of deoxidation products was calculated. Some factors which influence the growth of inclusions was discussed. It is found that inclusions in Ti-Mg deoxidized steel are composed of MgO-Al2O3-TiOx,then MnS encapsulated and precipitated on them,isolated Al2O3 and TiOxdo not appear in the steel. The inclusions' morphology is spherical,the average size is about 1.0 μm,and the number is more than 1000 mm-2. Few MgO-Al2O3 and MgO inclusions exist in the steel with high Mg content. Therefore,high Mg content in molten steel is harmful to the control of sphericizing,and it should be restricted to below 50 × 10-6. Magnesium has strong deoxidation ability,and the deoxidation products have the characteristics of small critical radius,large number of nucleation,and the formation of Al-Ti-Mg-O complex inclusions,which both control the supersaturation of oxygen and the growth of inclusions in the steel.

The morphology, size, composition, and number of inclusions in pipeline steel were characterized by scanning electron microscopy and energy dispersive spectroscopy. The characteristics of the inclusions with different Ti/Mg ratios as well as the influence of sulfur content and the number of deoxidation products on the precipitation behavior of MnS were investigated, and the corresponding thermodynamic calculations were carried out. It is found that the core of the inclusions is mainly composed of MgO-Al2O3-Ti2O3, MgO-Ti2O3 or MgO, and then MnS wraps or locally precipitates on them. The inclusions have the average size smaller than 1.3 txm and the number of 300 to 450 mm-2; moreover, their morphology is diverse such as round, polygonal and square. When the Ti/Mg atomic ratio is 0.05 to 0.2, the inclusions are round and small. With the decrease of sulfur content, MnS less tends to precipitate during solidification, its ways of precipitation on the inclusion surface will change from wrapped to local precipitated. A great number of oxides is conducive to the heterogeneous nucleation of more finely MnS on the surface of complex oxides. The Ti-Mg complex deoxidation products are small and dispersed, can become the heterogeneous nucleation core of MnS, and may reduce the harm of MnS and oxides at the same time.

Broadcasting is a common and basic operation used to support various network protocols in wireless networks. To achieve energy-efficient broadcasting is especially important for ad hoc wireless sensor networks because sensors are generally powered by batteries with limited lifetimes. Energy consumption for broadcast operations can be reduced by minimizing the number of relay nodes based on the observation that data transmission processes consume more energy than data reception processes in the sensor nodes, and how to improve the network lifetime is always an interesting issue in sensor network research. The minimum-energy broadcast problem is then equivalent to the problem of finding the minimum Connected Dominating Set (CDS) for a connected graph that is proved NP-complete. In this paper, we introduce an Efficient Minimum CDS algorithm (EMCDS) with help of a proposed ordered sequence list. EMCDS does not concern itself with node energy and broadcast operations might fail if relay nodes are out of energy. Next we have proposed a Minimum Energy-consumption Broadcast Scheme (MEBS) with a modified version of EMCDS, and aimed at providing an efficient scheduling scheme with maximized network lifetime. The simulation results show that the proposed EMCDS algorithm can find smaller CDS compared with related works, and the MEBS can help to increase the network lifetime by efficiently balancing energy among nodes in the networks.

The reliability of wireless sensor networks (WSNs) can be greatly affected by failures of sensor nodes due to energy exhaustion or the influence of brutal external environment conditions. Such failures seriously affect the data persistence and collection efficiency. Strategies based on network coding technology for WSNs such as LTCDS can improve the data persistence without mass redundancy. However, due to the bad intermediate performance of LTCDS, a serious ‘cliff effect’ may appear during the decoding period, and source data are hard to recover from sink nodes before sufficient encoded packets are collected. In this paper, the influence of coding degree distribution strategy on the ‘cliff effect’ is observed and the prioritized data storage and dissemination algorithm PLTD-ALPHA is presented to achieve better data persistence and recovering performance. With PLTD-ALPHA, the data in sensor network nodes present a trend that their degree distribution increases along with the degree level predefined, and the persistent data packets can be submitted to the sink node according to its degree in order. Finally, the performance of PLTD-ALPHA is evaluated and experiment results show that PLTD-ALPHA can greatly improve the data collection performance and decoding efficiency, while data persistence is not notably affected.

In view of problem that current underground explosion-proof computer has no monitoring function for electric quantity of battery, a design scheme of electric quantity of battery monitoring system of underground explosion-proof computer based on USB protocol was proposed. In the system, small single-chip microcomputer with AD conversion is used to collect and process electric quantity of battery, the collected data is transmitted to module of USB to serial port，then sampling value of electric quantity of battery can be got by upper computer through virtual serial port. The test result showed that the indexes of the system accord with working time of load, data transmission has higher reliability and relative error of AD conversion can meet with demands of collection of electric quantity of battery.

In order to solve the problem that rescue communication system, which is laid casually in process of emergency rescue for mine accident, has no function of real-time communication among satellite, ground and underground and remote command center cannot directly get information of disaster situation, a mine communication device for emergency rescue commanding which combined with underground wired audio and video communication system and ground satellite video communication system was proposed and realization scheme of audio and video transmission by satellite of the device was mainly introduced. The prototype test result showed the device has stable networking, long communication distance and strong anti-disaster ability, which solves the problem of real-time communication among satellite, ground and underground in emergency rescue commanding.

Based on the velocities of waves near the surface in concrete, the propagation path and travel time of different waves were calculated, and the influence of crack on these waves was analyzed. Some theoretical conclusions were verified by FEM. The ultrasonic waves were received by array transducers and the velocities of different waves were calculated and distinguished according to wave velocity in the simulation. Simulation results show that when sound wave propagates through the crack, longitudinal waves will arrive at the receiving arrays, and the crack will diffract transverse wave to generate new longitudinal wave and transverse wave by mode conversion, and Rayleigh wave will propagate along the surface (including the crack side wall). Finally, it is found that the relationship between crack depth and amplitude and energy is approximately linearly monotone decreasing by studying the waves near surface with different crack depths.