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Abstract Predicting the dynamic mechanical characteristics of rocks during freeze–thaw cycles (FTC) is crucial for comprehending the damage process of FTC and averting disasters in rock engineering in cold climates. Nevertheless, the conventional mathematical regression approach has constraints in accurately forecasting the dynamic compressive strength (DCS) of rocks under these circumstances. Hence, this study presents an optimized approach by merging the Coati Optimization Algorithm (COA) with Random Forest (RF) to offer a reliable solution for nondestructive prediction of DCS of rocks in cold locations. Initially, a database of the DCS of rocks after a series of FTC was constructed, and these data were obtained by performing the Split Hopkinson Pressure Bar Test on rocks after FTC. The main influencing factors of the test can be summarized into 10, and PCA was employed to decrease the number of dimensions in the dataset, and the microtests were used to explain the mechanism of the main influencing factors. Additionally, the Backpropagation Neural Network and RF are used to construct the prediction model of DCS of rock, and six optimization techniques were employed for optimizing the hyperparameters of the model. Ultimately, the 12 hybrid prediction models underwent a thorough and unbiased evaluation utilizing a range of evaluation indicators. The outcomes of the research concluded that the COA-RF model is most recommended for application in engineering practice, and it achieved the highest score of 10 in the combined score of the training and testing phases, with the lowest RMSE (4.570,8.769), the lowest MAE (3.155,5.653), the lowest MAPE (0.028,0.050), the highest R 2 (0.983,0.94).

From a practical point of view, grain structure heterogeneities are key parameters that control the rock response and still remains a challenge to incorporate in a quantitative manner. One of the less discussed topics in the context of the grain-based model (GBM) in the particle flow code (PFC) is the contact heterogeneities and the appropriate contact model to mimic the grain boundary behavior. Generally, the smooth joint (SJ) model and linear parallel bond (LPB) model are used to simulate the grain boundary behavior. However, the literature does not document the suitability of different models for specific problems. Another challenge in implementing GBM in PFC is that only a single bonding parameter is used at the grain boundaries. The aim of this study is to investigate the responses of a laboratory-scale specimen with SJ and LPB models, considering grain boundary heterogeneous and homogeneous contact parameters. Uniaxial and biaxial compression tests are performed to calibrate the response of Creighton granite. The stress–strain curves, volumetric dilation, inter-crack (crack in the grain boundary), and intra-crack (crack within the grain) development, and failure patterns associated with different contact models are examined. It was found that both the SJ and LPB models can reproduce the pre-peak behavior observed for a granitic rock type. However, the LPB model is unable to reproduce the post-peak behavior. Due to the large interlocking effect originating from the balls in contact and the ball size in the LPB model, local dilation is induced at the grain boundaries. This overestimates the volumetric dilation and residual shear strength. The LPB model tends to result in discontinuous inter-cracks and stress localization in the rock specimen, resulting in fine fragments at the rock surface during failure.

Abstract Bladder urothelial carcinoma (BLCA) presents a persistent challenge in clinical management. Despite recent advancements demonstrating the BLCA efficacy of immune checkpoint inhibitors (ICI) in BLCA patients, there remains a critical need to identify and expand the subset of individuals who benefit from this treatment. Mitochondria, as pivotal regulators of various cell death pathways in eukaryotic cells, exert significant influence over tumor cell fate and survival. In this study, our objective was to investigate biomarkers centered around mitochondrial function and cell death mechanisms to facilitate prognostic prediction and guide therapeutic decision-making in BLCA. Utilizing ssGSEA and LASSO regression, we developed a prognostic signature termed mitochondrial function and cell death (mtPCD). Subsequently, we evaluated the associations between mtPCD score and diverse clinical outcomes, including prognosis, functional pathway enrichment, immune cell infiltration, immunotherapy response analysis and drug sensitivity, within high- and low-risk subgroups. Additionally, we employed single-cell level functional assays, RT-qPCR, and immunohistochemistry to validate the differential expression of genes comprising the mtPCD signature. The mtPCD signature comprises a panel of 10 highly influential genes, strongly correlated with survival outcomes in BLCA patients and exhibiting robust predictive capabilities. Importantly, individuals classified as high-risk according to mtPCD score displayed a subdued overall immune response, characterized by diminished immunotherapeutic efficacy. In summary, our findings highlight the development of a novel prognostic signature, which not only holds promise as a biomarker for BLCA prognosis but also offers insights into the immune landscape of BLCA. This paradigm may pave the way for personalized treatment strategies in BLCA management.

With the accelerated evolution of digital technologies such as big data, cloud computing, and artificial intelligence, the trends of intelligence, informatization, and digitization have become imminent across various domains. Deep earth engineering, as a major strategic scientific and technological issue for the nation, is inevitably poised for intelligent upgrades. However, the complex characteristics of “three highs and one disturbance” in deep rock masses pose some severe challenges to the intelligent transformation of deep earth engineering. In order to achieve an efficient integration of deep earth engineering and digital technology, this study focuses on the intelligent practice path based on “perception, transmission, interpretation, analysis, decision”. The representative research progress in intelligent perception, real-time transmission, information interpretation, data analysis, intelligent decision-making and other fields in underground engineering is systematically reviewed, and the targeted development directions for deep earth engineering intelligent development are proposed, including multi perception, fast response, big data, optimal methods, precise models, strong platforms and easy promotion. Research findings indicate that ① The cutting-edge deep earth engineering perception technologies include fiber optic sensors, MEMS sensors, computer vision, automated robots, etc. After data collection is completed, the real-time response of data is achieved through the wireless communication protocols that combine the advantages of simple configuration, strong fault tolerance, and good mobility, in order to achieve an accurate collection and real-time transmission of deep earth engineering monitoring data. ② Deep earth engineering survey technology yields data types such as images, waves, and point clouds. Numerous models for interpreting and analyzing raw data exist. The application of next-generation artificial intelligence technologies, such as artificial neural networks and deep learning, significantly improves the efficiency of interpretation and analysis. ③ The intelligent decision-making system possesses efficient learning capabilities, adapting to the uncertainty in complex environments through cyclic autonomous learning to provide intelligent solutions for decision-making problems. Currently, China’s policies and industrial systems for the intelligent construction in the deep earth engineering have been essentially established, with a plethora of intelligent construction systems already applied in practical settings. Building upon this foundation, the study envisions the development direction of digital deep earth engineering in four aspects: intelligent collection and information interpretation, surrounding rock evaluation and safety assessment, surrounding rock control and dynamic repair, and platform development and application promotion. Furthermore, a comprehensive evaluation and analysis system for surrounding rock stability of deep earth engineering based on multi-source information is constructed.

BackgroundPatients with distant metastases from neuroblastoma (NB) usually have a poorer prognosis, and early diagnosis is essential to prevent distant metastases. The aim was to develop a machine-learning model for predicting the risk of distant metastasis in patients with neuroblastoma to aid clinical diagnosis and treatment decisions.MethodsWe built a predictive model using data from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2018 on 1,542 patients with neuroblastoma. Seven machine-learning methods were employed to forecast the likelihood of neuroblastoma distant metastases. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for building machine learning models. Secondly, the subject operating characteristic area under the curve (AUC), Precision-Recall (PR) curves, decision curve analysis (DCA), and calibration curves were used to assess model performance. To further explain the optimal model, the Shapley summation interpretation method (SHAP) was applied. Ultimately, the best model was used to create an online calculator that estimates the likelihood of neuroblastoma distant metastases.ResultsThe study included 1,542 patients with neuroblastoma, multifactorial logistic regression analysis showed that age, histology, tumor size, tumor grade, primary site, surgery, chemotherapy, and radiotherapy were independent risk factors for distant metastasis of neuroblastoma (P

INADEQUATE (Incredible Natural Abundance DoublE QUAntum Transfer Experiment) is one of the most important techniques in revealing the carbon skeleton of organic solids in solid-state NMR spectroscopy. Nevertheless, its use for structural analysis is quite limited due to the low natural abundance of 13C–13C connectivity (∼0.01%) and thus low sensitivity. Particularly, in semi-solids like rubbers, the sensitivity will be further significantly reduced by the inefficient cross polarization from 1H to 13C due to molecular motions induced averaging of 1H–13C dipolar couplings. Herein, in this study, we demonstrate that transient nuclear Overhauser effect (NOE) can be used to efficiently enhance 13C signals, and thus enable rapid acquisition of two-dimensional (2D) 13C INADEQUATE spectra of rubbers. Using chlorobutyl rubber as the model system, it is found that an overall signal-to-noise ratio (SNR) enhancement about 22% can be achieved, leading to significant time-saving by about 33% as compared to the direct polarization-based INADEQUATE experiment. Further experimental results on natural rubber and ethylene propylene diene monomer (EPDM) rubber are also shown to demonstrate the robust performance of transient NOE enhanced INADEQUATE experiment.

Abstract Background Bladder urothelial carcinoma (BLCA) is the most common genitourinary cancer and the prognosis of patients is often poor. However, studies of basement membrane-related genes (BM-related genes) in BLCA are less reported. Therefore, we established a BM-related genes signature to explore their functional and prognostic value in BLCA. Methods In this study, a BM-related genes signature was constructed by LASSO-Cox regression analysis, and then a series of bioinformatics methods was used to assess the accuracy and validity of the signature. We constructed a nomogram for clinical application and also screened for possible therapeutic drugs. To investigate the functions and pathways affected by BM-related genes in BLCA, we performed functional enrichment analyses. In addition, we analyzed the immune cell infiltration landscape and immune checkpoint-related genes in the high and low-risk groups. Finally, we confirmed the prognostic value of BM-related genes in BLCA in vitro. Results Combining multiple bioinformatics approaches, we identified a seven-gene signature. The accuracy and validity of this signature in predicting BLCA patients were confirmed by the test cohort. In addition, the risk score was strongly correlated with prognosis, immune checkpoint genes, drug sensitivity, and immune cell infiltration landscape. The risk score is an independent prognostic factor for BLCA patients. Further experiments revealed that all seven signature genes were differentially expressed between BLCA cell lines and normal bladder cells. Finally, overexpression of LAMA2 inhibited the migration and invasion ability of BLCA cell lines. Conclusions In summary, the BM-related genes signature was able to predict the prognosis of BLCA patients accurately, indicating that the BM-related genes possess great clinical value in the diagnosis and treatment of BLCA. Moreover, LAMA2 could be a potential therapeutic target, which provides new insights into the application of the BM-related genes in BLCA patients.

Compound 1 was previously identified by our team as a glycogen phosphorylase (GP) inhibitor with glucose-lowering activity and demonstrated to have protective effects against myocardial and cerebral ischemia. However, its impact on muscle function has not been clarified. This study is the first to evaluate the long-term effects of GP inhibitors on muscle function and metabolism. After a 28-day administration of Compound 1, we performed assays to assess muscle function and biochemical parameters in rats. We observed reductions in peak holding force, duration, tetanic contraction force, single-contraction force, and electromyographic signals under 20 s and 10 min contraction stimuli. The metabolic analysis showed no significant effects on muscle glycogen, ATP, lactic acid, and uric acid levels at low doses. In contrast, medium to high doses resulted in increased glycogen, decreased ATP, and reduced lactic acid (only at high doses), without affecting uric acid. These findings suggest that Compound 1 may adversely affect muscle function in rats, potentially due to the glycogen inhibition effects of GP inhibitors. This study provides crucial safety data and insights into the long-term effects of GP inhibitors on rat muscles, which will guide future developments and applications.

The porcine reproductive and respiratory syndrome virus (PRRSV) belongs to the Arteriviridae family and is a single-stranded, positively stranded RNA virus. The currently available PRRSV vaccines are mainly inactivated and attenuated vaccines, yet none of the commercial vaccines can provide comprehensive, long-lasting, and effective protection against PRRSV. SR717 is a pyridazine-3-carboxamide compound, which is commonly used as a non-nucleoside STING agonist with antitumor and antiviral activities. Nevertheless, there is no evidence that SR717 has any antiviral effects against PRRSV. In this study, a dose-dependent inhibitory effect of SR717 was observed against numerous strains of PRRSV using qRT-PCR, IFA, and WB methods. Furthermore, SR717 was found to stimulate the production of anti-viral molecules and trigger the activation of the signaling cascade known as the stimulator of interferon genes (STING) pathway, which contributed to hindering the reproduction of viruses by a certain margin. Collectively, these results indicate that SR717 is capable of inhibiting PRRSV infection in vitro and may have potential as an antiviral drug against PRRSV.

BackgroundChatGPT, an artificial intelligence (AI) based on large-scale language models, has sparked interest in the field of health care. Nonetheless, the capabilities of AI in text comprehension and generation are constrained by the quality and volume of available training data for a specific language, and the performance of AI across different languages requires further investigation. While AI harbors substantial potential in medicine, it is imperative to tackle challenges such as the formulation of clinical care standards; facilitating cultural transitions in medical education and practice; and managing ethical issues including data privacy, consent, and bias. ObjectiveThe study aimed to evaluate ChatGPT’s performance in processing Chinese Postgraduate Examination for Clinical Medicine questions, assess its clinical reasoning ability, investigate potential limitations with the Chinese language, and explore its potential as a valuable tool for medical professionals in the Chinese context. MethodsA data set of Chinese Postgraduate Examination for Clinical Medicine questions was used to assess the effectiveness of ChatGPT’s (version 3.5) medical knowledge in the Chinese language, which has a data set of 165 medical questions that were divided into three categories: (1) common questions (n=90) assessing basic medical knowledge, (2) case analysis questions (n=45) focusing on clinical decision-making through patient case evaluations, and (3) multichoice questions (n=30) requiring the selection of multiple correct answers. First of all, we assessed whether ChatGPT could meet the stringent cutoff score defined by the government agency, which requires a performance within the top 20% of candidates. Additionally, in our evaluation of ChatGPT’s performance on both original and encoded medical questions, 3 primary indicators were used: accuracy, concordance (which validates the answer), and the frequency of insights. ResultsOur evaluation revealed that ChatGPT scored 153.5 out of 300 for original questions in Chinese, which signifies the minimum score set to ensure that at least 20% more candidates pass than the enrollment quota. However, ChatGPT had low accuracy in answering open-ended medical questions, with only 31.5% total accuracy. The accuracy for common questions, multichoice questions, and case analysis questions was 42%, 37%, and 17%, respectively. ChatGPT achieved a 90% concordance across all questions. Among correct responses, the concordance was 100%, significantly exceeding that of incorrect responses (n=57, 50%; P

BackgroundCopper (Cu) homeostasis are important processes in the cause of metabolic diseases, but the association between Cu and obesity remains unclear.MethodsParticipants were drawn from the 2011-2016 National Health and Nutrition Examination Survey (NHANES). Weighted logistic regression assessed the associations of serum Cu concentrations (tertiles) with obesity and central obesity in individuals without comorbidities. Obesity was defined as a BMI ≥30.0 kg/m2, and central obesity was defined as a waist circumference ≥80 cm for women and ≥95 cm for men.ResultsThis cross-sectional study included 1,665 adults without comorbidities, representing 24,744,034 people (mean age 35.1 years, 48.5% female). High serum Cu levels (tertile 3: ≥19.19 μmol/L) were associated with higher odds of obesity (adjusted odds ratio [OR]: 4.48, 95% CI[confidence interval]: 2.44-8.32) and central obesity (OR: 2.36, 95% CI: 1.19-4.66) compared to low serum Cu levels (tertile 1: ≤15.64 μmol/L). The dose-response curve showed a nonlinear association between Cu levels and obesity (P-nonlinear = 0.02) and a linear association with central obesity (P-nonlinear = 0.21).ConclusionThis study suggests that higher serum Cu levels are associated with increased odds of obesity in healthy American adults.

BackgroundThe benefit of first-line use of sodium-dependent glucose transport 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RAs) in type 2 diabetes mellitus (T2DM) with low risk of cardiovascular diseases are not clear.MethodsPubMed, EMBASE and Cochrane Library databases were searched to identify eligible randomized controlled trials. We used the odds ratio (OR) and mean difference (MD) and the corresponding 95% confidence interval (CI) to assess the dichotomous and continuous variable, respectively.ResultsThirteen studies involving 2,885 T2DM at low risk of cardiovascular diseases were included. Compared to placebo, first line use of SGLT2i significantly reduced glycosylated hemoglobin type A1C (HbA1c) (MD: -0.72), weight (MD: -1.32) and fasting plasma glucose (FPG) (MD: -27.05) levels. Compared with metformin, SGLT2i reduced body weight (MD: -1.50) and FPG (MD: -10.13) more effectively, with similar reduction for HbA1c (MD: -0.05). No significant increased safety adverse was found for SGLT2i, including nasopharyngitis (OR: 1.07), urinary tract infection (OR: 2.31), diarrhea (OR: 1.18) and hypoglycemia (OR: 1.06). GLP-1RAs significantly reduced HbA1c (MD: -1.13), weight (MD: -2.12) and FPG (MD: -31.44) levels as first-line therapy compared to placebo. GLP-1RAs significantly increased occurrence of diarrhea (OR: 2.18), hypoglycemia (OR: 3.10), vomiting (OR: 8.22), and nausea (OR: 4.41).ConclusionFirst line use of SGLT2i and GLP-1RAs is effective in reducing HbA1c, weight, and FPG levels in T2DM patients at low risk for cardiovascular disease. SGLT2i may be superior to metformin in controlling body weight and FPG. GLP-1RAs may increase the occurrence of diarrhea, hypoglycemia, vomiting, and nausea.Systematic review registrationPROSPERO (International Prospective Register of Systematic Reviews. https://www.york.ac.uk/inst/crd, CRD42022347233).

TEM is used to examine the microstructural evolution of the Ti6321 titanium alloy during the contact explosion. A certain number of dislocations and deformation twins are observed after the explosion. When the slips of dislocations are blocked, {10–11} twins are generated to meet the deformation. The twin boundary deviates from the twin plane and is parallel to the (0001) plane of the matrix. The slide of dislocations and twinning both play a role in the deformation resulting from the explosion.

Abstract Background The triglyceride and glucose (TyG) index has been linked to various cardiovascular diseases. However, it's still unclear whether the TyG index is associated with arterial stiffness and coronary artery calcification (CAC). Methods We conducted a systematic review and meta-analysis of relevant studies until September 2022 in the PubMed, Cochrane Library, and Embase databases. We used a random-effects model to calculate the pooled effect estimate and the robust error meta-regression method to summarize the exposure-effect relationship. Results Twenty-six observational studies involving 87,307 participants were included. In the category analysis, the TyG index was associated with the risk of arterial stiffness (odds ratio [OR]: 1.83; 95% CI 1.55–2.17, I2 = 68%) and CAC (OR: 1.66; 95% CI 1.51–1.82, I2 = 0). The per 1-unit increment in the TyG index was also associated with an increased risk of arterial stiffness (OR: 1.51, 95% CI 1.35–1.69, I2 = 82%) and CAC (OR: 1.73, 95% CI 1.36–2.20, I2 = 51%). Moreover, a higher TyG index was shown to be a risk factor for the progression of CAC (OR = 1.66, 95% CI 1.21–2.27, I2 = 0, in category analysis, OR = 1.47, 95% CI 1.29–1.68, I2 = 41% in continuity analysis). There was a positive nonlinear association between the TyG index and the risk of arterial stiffness (Pnonlinearity

The response of the Ti–6Al–3Nb–2Zr–1Mo alloy plate under air blast loading was studied. The deformation of the target plate under explosion increased with the increase of charge. The failure features included inelastic deformation, partial tearing, and tensile tearing under different degrees of loadings. Electron backscatter diffraction (EBSD) and transmission electron microscope (TEM) were used to characterize the evolution of microstructure. The result showed that the density of dislocations has a positive correlation with the blast loadings, meaning the major role of the slip. The twinning would help the slip of dislocations in the deformation. The first type of twins generated under blast loadings were {10–12} extension twins. A high-resolution transmission electron microscope (HRTEM) was employed to study the special boundaries of the {11–24} contraction twins and {11–22} contraction twins. Due to the blast loadings, they were not exactly parallel to the theoretical twinning plane. The twin boundary was parallel to the base plane of the matrix.

Muscle fiber type is a major factor in pork meat quality, however, the role of post-translational protein modifications, especially succinylation, in the regulation of muscle fiber type is not fully understood. Here we performed protein succinylation profiles of fast-type biceps femoris (BF) and slow-type soleus (SOL) muscles. A total of 4,221 succinylation sites were identified from these samples, of which 294 sites were differentially expressed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that these succinylated proteins were mainly involved in glycolysis, tricarboxylic acid cycle, and fatty acid metabolism. Succinylation modification of the CRAT and RAB10 proteins was verified by co-immunoprecipitation. Protein-protein interaction (PPI) network analysis unveiled the interactions of these succinylated proteins that regulate pig myofiber type conversion. This investigation offers fresh perspectives into the molecular roles of protein succinylation in the regulation of pig myofiber type transformation and meat quality.

Explosive welding is widely used in the manufacture of dissimilar metal composite plates. In this work, TC4/TA1/Ti6321 titanium alloy laminated composites were successfully prepared by explosive welding. The interfacial characteristics of the laminated composites were studied by energy dispersive spectroscopy (EDS), electron backscattered diffraction (EBSD), transmission electron microscope (TEM), and other characterization methods. The dynamic mechanical properties of the laminated composites were investigated by using the split Hopkinson pressure bar (SHPB). The results show that the interface of laminated composites was well bonded. There was a high density of crystal defects including dislocations and twins near the interface. The composite plates showed a hard/soft/hard hardness distribution as a whole, and the microhardness increased near the interface. Due to the existence of the interface, the dynamic mechanical properties of laminated composites show different results. The dynamic compressive stress-strain curve of laminated composites showed an equilibrium type, and the strain strengthening effect was lower than that of homogeneous materials. The failure mode of laminated composites was adiabatic shear failure mode.

Click fraud is one of the most common methods of cybercrime in recent years, and the Internet advertising industry suffers huge losses every year because of click fraud.In order to effectively detect fraudulent clicks within massive clicks, a variety of features that fully combine the relationship between advertising clicks and time attributes were constructed.Besides, an ensemble learning framework for click fraud detection was proposed, namely CAT-RFE ensemble learning framework.The CAT-RFE ensemble learning framework consisted of three parts: base classifier, recursive feature elimination (RFE) and voting ensemble learning.Among them, the gradient boosting model suitable for category features-CatBoost was used as the base classifier.RFE was a feature selection method based on greedy strategy, which can select a better feature combination from multiple sets of features.Voting ensemble learning was a learning method that combined the results of multiple base classifiers by voting.The framework obtained multiple sets of optimal feature combinations in the feature space through CatBoost and RFE, and then integrated the training results under these feature combinations through voting to obtain integrated click fraud detection results.The framework adopted the same base classifier and ensemble learning method, which not only overcame the problem of unsatisfactory integrated results due to the mutual constraints of different classifiers, but also overcame the tendency of RFE to fall into a local optimal solution when selecting features, so that it had better detection ability.The performance evaluation and comparative experimental results on the actual Internet click fraud dataset show that the click fraud detection ability of the CAT-RFE ensemble learning framework exceeds that of the CatBoost method, the combined method of CatBoost and RFE, and other machine learning methods, proving that the framework has good competitiveness.The proposed framework provides a feasible solution for Internet advertising click fraud detection.

Background and objectiveSedentary behavior is of increasing concern in older patients with type 2 diabetes mellitus (T2DM) due to its potential adverse effects on cardiovascular health, cognitive function, and motor function. While regular exercise has been shown to improve the health of individuals with T2DM, the most effective exercise program for elderly sedentary patients with T2DM remains unclear. Therefore, the objective of this study was to assess the impact of high-intensity interval training (HIIT), moderate-intensity continuous training (MICT), and guideline-based physical activity programs on the cardiovascular health, cognitive function, and motor function of this specific population.MethodsThis study will be a randomized, assessor-blind, three-arm controlled trial. A total of 330 (1:1:1) elderly sedentary patients diagnosed with T2DM will be randomly assigned the HIIT group (10 × 1-min at 85–95% peak HR, intersperse with 1-min active recovery at 60–70% peak HR), MICT (35 min at 65–75% peak HR), and guideline-based group (guideline group) for 12 weeks training. Participants in the guideline group will receive 1-time advice and weekly remote supervision through smartphones. The primary outcomes will be the change in glycosylated hemoglobin (HbA1c) and brain-derived neurotrophic factor (BDNF) after 12-weeks. Secondary outcomes will includes physical activity levels, anthropometric parameters (weight, waist circumference, hip circumference, and body mass index), physical measurements (fat percentage, muscle percentage, and fitness rate), cardiorespiratory fitness indicators (blood pressure, heart rate, vital capacity, and maximum oxygen), biochemical markers (high-density lipoprotein, low-density lipoprotein, triglycerides, total cholesterol, and HbA1c), inflammation level (C-reactive protein), cognitive function (reaction time and dual-task gait test performance), and motor function (static balance, dynamic balance, single-task gait test performance, and grip strength) after 12 weeks.DiscussionThe objective of this study is to evaluate the effect of 12 weeks of HIIT, MICT, and a guideline-based physical activity program on elderly sedentary patients diagnosed with T2DM. Our hypothesis is that both HIIT and MICT will yield improvements in glucose control, cognitive function, cardiopulmonary function, metabolite levels, motor function, and physical fitness compared to the guideline group. Additionally, we anticipate that HIIT will lead to greater benefits in these areas. The findings from this study will provide valuable insights into the selection of appropriate exercise regimens for elderly sedentary individuals with T2DM.Ethics and disseminationThis study has been approved by the Ethics Review Committee of the Reproductive Hospital Affiliated with China Medical University (approval number: 202203). Informed consent will be obtained from all participants or their guardians. Upon completion, the authors will submit their findings to a peer-reviewed journal or academic conference for publication.Clinical trial registrationChinese Clinical Trial Registry, identifier ChiCTR2200061573.

Efficient fiber‐chip couplers operating at distinct wavelength bands are key components to combine or split different optical bands for emerging data transmission and nonlinear applications. Herein, a dual‐band silicon‐integrated grating coupler (GC) operated at 1.55 and 2 μm wavebands is designed and demonstrated. The proposed device can simultaneously couple 1.55 and 2 μm wavebands light into the in‐plane waveguides at the same incident angle. Numerical simulations indicate that coupling efficiencies (CEs) are −2.5 and −3.9 dB for center wavelengths at 1561 and 1979 nm, respectively. The dual‐band GC is experimentally demonstrated on a commercially available 340 nm silicon‐on‐insulator wafer. The fabricated dual‐band GC with center wavelengths of 1559 and 1968 nm obtains CEs of −4.9 and −6.4 dB, with 3 dB bandwidths of 81 and 80.4 nm, respectively. Also, the first proof‐of‐concept demonstration of 10 Gb s−1 wavelength division multiplexing transmission at 1.55 and 2 μm waveband is presented based on the fabricated dual‐band GC.

Context Waist-to-height ratio (WHtR) is a controversial evaluation index of cardiovascular risk factors (CVRFs) in children and adolescents. Objective To assess the accuracy of WHtR as a measure to screen for clusters of at least one CVRF (CVRF1), two CVRFs (CVRF2), and three CVRFs (CVRF3) in different ages, sexes, regions and cut-offs. Methods The PubMed, Web of Science, EBSCOhost, Springer, Taylor & Francis Online, Wiley Online Library, Wanfang, and CNKI databases were searched for eligible publications up to June 2021. The QUADAS-2 checklist was used to assess the methodology of the included studies. Results Twenty-two studies that evaluated 85281 children and adolescents aged 5–19 years were included in the meta-analysis. The AUSROC values were 0.56 (95% CI: 0.54–0.57), 0.82 (95% CI: 0.81–0.83), and 0.89 (95% CI: 0.89–0.90) for CVRF1, CVRF2, and CVRF3, respectively. Higher AUSROC values were found for adolescents (12–19 years), that is, 0.91 (95% CI: 0.88–0.93), 0.90 (95% CI: 0.87–0.92) for males, and 0.91 (95% CI: 0.90–0.91) for a cut-off of ≥ 0.51 in the identification of CVRF3. Conclusion WHtR can be used as an accurate screening tool for CVRF3 and CVRF2 in children and adolescents, and it is recommended to select different cut-offs according to different ages, sexes, and regions.

Abstract The nitrogen conversion mechanism of swine manure by thermochemical liquefaction with ethanol as solvent was investigated at a lower temperature range (180–300 °C). The fate of nitrogen in liquid phase products, bio-oil and biochar was evaluated by XPS, GC–MS and other methods. After thermochemical liquefaction, most of the nitrogen in swine manure was transferred to biochar (63.75%). As the temperature increased to 220 °C, the biochar-N yields decreased to 43.29%, accompanied by an increase in bio-oil-N and liquid phase product-N by 7.99% and 1.26% respectively. The results indicated that increasing the temperature could facilitate solid nitrogen structure cracking into bio-oil-N. Amines and heterocyclic nitrogen from protein peptide bond cracking and Maillard reactions made up the main nitrogen compounds in bio-oil, and high temperatures favored the further cyclization and condensation of heterocyclic nitrogen (e.g., indole, quinoline). In the case of biochar, the inorganic nitrogen disappeared at 260 °C and was obviously transformed into liquid phase products. The rising temperature promoted the polymerization of pyridine nitrogen and pyrrole nitrogen, which formed more stabilized nitrogen formation (such as quaternary nitrogen). Nitrogen conversion and possible reaction schematics during swine manure thermochemical liquefaction were explored in this study.

Disulfidptosis is a newly discovered mode of cell death induced by disulfide stress. However, the prognostic value of disulfidptosis-related genes (DRGs) in renal cell carcinoma (RCC) remains to be further elucidated. In this study, consistent cluster analysis was used to classify 571 RCC samples into three DRG-related subtypes based on changes in DRGs expression. Through univariate regression analysis and LASSO-Cox regression analysis of differentially expressed genes (DEGs) among three subtypes, we constructed and validated a DRG risk score to predict the prognosis of patients with RCC, while also identifying three gene subtypes. Analysis of DRG risk score, clinical characteristics, tumor microenvironment (TME), somatic cell mutations, and immunotherapy sensitivity revealed significant correlations between them. A series of studies have shown that MSH3 can be a potential biomarker of RCC, and its low expression is associated with poor prognosis in patients with RCC. Last but not least, overexpression of MSH3 promotes cell death in two RCC cell lines under glucose starvation conditions, indicating that MSH3 is a key gene in the process of cell disulfidptosis. In summary, we identify potential mechanism of RCC progression through DRGs -related tumor microenvironment remodeling. In addition, this study has successfully established a new disulfidptosis-related genes prediction model and discovered a key gene MSH3. They may be new prognostic biomarkers for RCC patients, provide new insights for the treatment of RCC patients, and may inspire new methods for the diagnosis and treatment of RCC patients.

Accurate road extraction and recognition of roadside fruit in complex orchard environments are essential prerequisites for robotic fruit picking and walking behavioral decisions. In this study, a novel algorithm was proposed for unstructured road extraction and roadside fruit synchronous recognition, with wine grapes and nonstructural orchards as research objects. Initially, a preprocessing method tailored to field orchards was proposed to reduce the interference of adverse factors in the operating environment. The preprocessing method contained 4 parts: interception of regions of interest, bilateral filter, logarithmic space transformation and image enhancement based on the MSRCR algorithm. Subsequently, the analysis of the enhanced image enabled the optimization of the gray factor, and a road region extraction method based on dual-space fusion was proposed by color channel enhancement and gray factor optimization. Furthermore, the YOLO model suitable for grape cluster recognition in the wild environment was selected, and its parameters were optimized to enhance the recognition performance of the model for randomly distributed grapes. Finally, a fusion recognition framework was innovatively established, wherein the road extraction result was taken as input, and the optimized parameter YOLO model was utilized to identify roadside fruits, thus realizing synchronous road extraction and roadside fruit detection. Experimental results demonstrated that the proposed method based on the pretreatment could reduce the impact of interfering factors in complex orchard environments and enhance the quality of road extraction. Using the optimized YOLOv7 model, the precision, recall, mAP, and F1-score for roadside fruit cluster detection were 88.9%, 89.7%, 93.4%, and 89.3%, respectively, all of which were higher than those of the YOLOv5 model and were more suitable for roadside grape recognition. Compared to the identification results obtained by the grape detection algorithm alone, the proposed synchronous algorithm increased the number of fruit identifications by 23.84% and the detection speed by 14.33%. This research enhanced the perception ability of robots and provided a solid support for behavioral decision systems.

Silicon core fibers (SCFs) offer an exciting opportunity to harness the nonlinear functionality of the semiconductor material within the excellent waveguiding properties of optical fiber systems. Over the past two decades, these fibers have evolved from a research curiosity into established components for use across a wide range of photonic applications. This article provides a comprehensive overview of the evolution of the SCFs, with a focus on the development of the fabrication and post-processing procedures that have helped unlock the nonlinear optical potential of this new technology. As well as reviewing the timeline of advancements in nonlinear performance, a perspective will be provided on the current challenges and future opportunities for in-fiber nonlinear silicon systems.

On-chip polarizers are the essential components for polarization management in integrated systems. Hence, polarizers with broad operation bandwidth (BW), low insert loss (IL), and high polarization extinction ratio (PER) are highly desired. A broadband and ultra-high ER all-silicon transverse-magnetic-pass polarizer is presented and experimentally demonstrated on the 220 nm silicon-on-insulator platform. The proposed device consists of a TE1 mode filter and a multimode anti-symmetric apodized Bragg grating (MASABG). The MASABG works as a Bragg reflector to convert forward TE0 to backward TE1 mode, and then the reflected TE1 gradually evolves into the TE0 mode in the mode filter and finally leaks out. The device exhibits efficient polarization selectivity, facilitated by fully etched rectangular holes inside the waveguide to introduce strong periodic perturbations in the MASABG. Simulation results predict that the designed polarizer achieves ultra-high PER ∼60 dB with low IL < 0.2 dB at around 1550 nm, and the calculated BWs for PER >30 and >40 dB are estimated to be 275 and 268 nm, respectively. More importantly, the reflection of the eliminated TE polarization is suppressed to below −12 dB. For the fabricated polarizer, the measured BWs for PER >30 and >40 dB are about 260 and 150 nm, respectively, and the measured IL is

In previous studies, we reported compound 1 (5-chloro-N-(4-oxo-2,2-dipropyl-3,4-dihydro-2H-benzo[e][1,3]oxazin-6-yl)-1H-indole-2-carboxamide) as a novel PYGB inhibitor, and found that it had better anti-ischemic brain injury activity. In this study, we established and validated a novel UHPLC–MS/MS method for the quantitative determination of compound 1 in plasma, then applied the method to study the pharmacokinetic parameters and brain tissue distribution of compound 1 in SD (Sprague—Dawley) rats after intravenous administration. The experimental results showed that the method met the validation requirements set by the US FDA in terms of linearity, accuracy, precision, and stability. The validated method was then used for pharmacokinetic studies in rat plasma, and it was found that compound 1 exhibited linear pharmacokinetic characteristics when administered in the dose range of 0.8–3.2 mg/kg. Finally, we also conducted a brief preliminary investigation of the brain tissue distribution of compound 1 in rats after injection and found that the brain tissue concentrations at 0.25 h and 2 h of administration were 440 ± 19.1 ng/kg and 111 ± 23.9 ng/kg, respectively. Additionally, the CBrain/CPlasma ratio was 0.112 ± 0.0185 and 0.112 ± 0.0292, respectively. These results indicated that compound 1 was able to cross the blood–brain barrier. This study provides important support for the application of compound 1 in ischemic brain injury diseases.

The automatic classification of complaint work orders is the requirement of the digital and intelligent development of customer service of communication operators.The categories of customer service complaint work orders have multiple levels, each level has multiple labels, and the levels are related, which belongs to a typical hierarchical multi-label text classification (HMTC) problem.Most of the existing solutions are based on classifiers to process all classification labels at the same time, or use multiple classifiers for each level, ignoring the dependence between hierarchies.A matrix factorization and attention-based multi-task learning approach (MF-AMLA) to deal with hierarchical multi-label text classification tasks was proposed.Under the classification data of real complaint work orders in the customer service scenario of communication operators, the maximum Top1 F1 value of MF-AMLA is increased by 21.1% and 5.7% respectively compared with the commonly used machine learning algorithm and deep learning algorithm in this scenario.It has been launched in the customer service system of one mobile operator, the accuracy of model output is more than 97%, and the processing efficiency of customer service agent unit time has been improved by 22.1%.

The proliferation of connected devices in the Internet of Things (IoT) presents a connectivity challenge. The future internet will require a paradigm shift in which content is evaluated on the basis of “What” it is rather than “Where” it originated. ICN’s goal is to provide the benefits of name-based content addressing in order to facilitate scalable content distribution, security, mobility, and trust. NDN is a new internet architecture that evolved from Content-Centric Networking (CCN). NDN is viewed as a solution to the IoT’s challenges, as well as a way to transcend the IP paradigm. With IoT systems that had a number of challenging characteristics to satisfy, including heterogeneous devices, resource constraints, and energy efficiency. Due to the fact that NDN native features deliver data via hierarchically structured names, it offer promising solutions for current research integrating NDN into IoT. The review discusses the significance of naming, its influence, and security factor. Additionally, research challenges in the areas of naming and security will be discussed. The primary objective of this review is to give a new facelift to a new integrating naming convention for NDN.

ObjectivesStudies have established a link between periodontal disease and cardiovascular disease (CVD), but it is unclear whether there is a sex difference in their association.MethodsThe PubMed, Embase, and Cochrane databases were searched until June, 21 2022. Cardiovascular outcomes included any CVD, myocardial infarction (MI), coronary heart disease (CHD), or stroke. Studies reported the prevalence of CVD in patients with periodontal disease and the relationship between periodontal disease and CVD. The study is registered with PROSPERO (CRD42022333663). The level of evidence and recommendations is assessed by the Grading of Recommendations for Assessment, Development and Evaluation (GRADE).ResultsTwenty-six studies were included. In patients with periodontal disease, the prevalence of CVD was 7.2% [9 studies; 95% confidence interval (CI): 2.7–13.6%], and prevalence for CHD, hypertension, stroke, and heart failure was 6.6, 25.3, 1, and 1.1%, respectively. There was a significant association between periodontal disease and CVD in men [odds ratio (OR) = 1.22; 95% CI: 1.12–1.34] and women (OR = 1.11; 95% CI: 1.05–1.17), with no significant sex difference (P > 0.05).ConclusionCardiovascular disease is relatively common in patients with periodontal disease, and an increased risk of CVD is associated with periodontal disease independent of sex. Interventions targeting periodontal disease may be beneficial for CVD.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022333663.

Skeletal muscle of livestock is composed of both fast- and slow-twitch muscle fibers, which are key factors in their meat quality. However, the role of protein phosphorylation in muscle fiber type is not completely understood. Here, a fast-twitch (biceps femoris, BF) and slow-twitch (soleus, SOL) muscle tissue sample was collected from three male offspring of Duroc and Meishan pigs. We demonstrate that the meat quality of SOL muscle is significantly better than that of BF muscle. We further used phosphoproteomic profiling of BF and SOL muscles to identify differences between these muscle types. A total of 2,327 phosphorylation sites from 770 phosphoproteins were identified. Among these sites, 287 differentially expressed phosphorylation sites (DEPSs) were identified between BF and SOL. GO and KEGG enrichment analysis of proteins containing DEPSs showed that these phosphorylated proteins were enriched in the glycolytic process GO term and the AMPK signaling pathway. A protein-protein interaction (PPI) analysis reveals that these phosphorylated proteins interact with each other to regulate the transformation of muscle fiber type. These analyses reveal that protein phosphorylation modifications are involved in porcine skeletal muscle fiber type transformation. This study provides new insights into the molecular mechanisms by which protein phosphorylation regulates muscle fiber type transformation and meat quality in pigs.

BackgroundEvidence from longitudinal studies has shown that influenza infection is linked to an increased risk of arrhythmia. Therefore, we aimed to assess the role of influenza vaccination in arrhythmia prevention.Materials and methodsThe PubMed, Embase, and Cochrane Library databases were searched to identify studies that investigated the potential effects of the influenza vaccine on arrhythmia risk published until October 25th, 2021. The study was registered with PROSPERO (CRD42022300815).ResultsOne RCT with 2,532 patients and six observational studies with 3,167,445 patients were included. One RCT demonstrated a non-significant benefit of the influenza vaccine against arrhythmias [odds ratio (OR) = 0.43, 95% confidence interval (CI): 0.11–1.64; P = 0.20] in patients after myocardial infarction or those with high-risk stable coronary heart disease. A meta-analysis based on observational studies showed that vaccination was associated with a significantly lower risk of arrhythmia (OR: 0.82, 95% CI: 0.70–0.97; P = 0.02; I2 = 76%). Additionally, subgroup analysis showed a decreased risk of atrial fibrillation (AF) (OR: 0.94, 95% CI: 0.90–0.98; P = 0.006; I2 = 0%) and a non-significant but positive trend concerning ventricular arrhythmias (VAs) (OR: 0.68, 95% CI: 0.42–1.11; P = 0.12; I2 = 85%) after influenza vaccination.ConclusionBased on the current evidence, influenza vaccination may be associated with a reduced risk of arrhythmia, especially AF. Influenza vaccination may be an effective tool for the prevention of arrhythmias. The effect of influenza vaccination on the risk of VAs and arrhythmias in patients at low risk for cardiovascular diseases should be further studied.Systematic review registration[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42022300815].

As the most fundamental infrastructure in the current Internet, the Border Gateway Protocol (BGP) supports the inter-connectivity of different Autonomous Systems (ASs) and then the reachability can be achieved from any network in the Internet. However, due to the lack of security consideration during its original design, the BGP suffers from multiple security threats. Another challenge is that it cannot support the future sophisticated applications with deterministic routing. In this article, we propose a novel BGP management architecture, namely BGPChain, which is based on the blockchain in order to establish a secure, smart, and agile routing infrastructure for the future Internet.

Intramuscular fat (IMF) is an important regulator that determines meat quality, and its content is closely related to flavor, tenderness, and juiciness. Many studies have used quantitative proteomic analysis to identify proteins associated with meat quality traits in livestock, however, the potential candidate proteins that influence IMF in donkey muscle are not fully understood. In this study, we performed quantitative proteomic analysis, with tandem-mass-tagged (TMT) labeling, with samples from the longissimus dorsi (LD) muscle of the donkey. A total of 585,555 spectra were identified from the six muscle samples used in this study. In total, 20,583 peptides were detected, including 15,279 unique peptides, and 2,540 proteins were identified. We analyzed differentially abundant proteins (DAPs) between LD muscles of donkeys with high (H) and low (L) IMF content. We identified 30 DAPs between the H and L IMF content groups, of which 17 were upregulated and 13 downregulated in the H IMF group. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of these DAPs revealed many GO terms (e.g., bone morphogenetic protein (BMP) receptor binding) and pathways (e.g., Wnt signaling pathway and Hippo signaling pathway) involved in lipid metabolism and adipogenesis. The construction of protein–protein interaction networks identified 16 DAPs involved in these networks. Our data provide a basis for future investigations into candidate proteins involved in IMF deposition and potential new approaches to improve meat quality in the donkey.

RPKI Relying party needs to synchronizing data from repository periodically to verify information.In general, Rsync and RRDP are the two common means to complete data synchronization, however, each of them has related problems.In order to solve these problems, through analyzingthe way for synchronizing data from repository by the relying party, a mathematical model was established.Furthermore, based on the current problems faced by the two synchronization means, an improved RPKI data synchronization scheme was proposed.The advantages and disadvantages of the improved scheme were analyzed in detail, as well as the applicable scenarios.The improved scheme could provide a reference for optimizing the deployment and application of RPKI.

The high conservation of the three subtypes of glycogen phosphorylase (GP) presents significant challenges for specific inhibitor studies targeting GP. Our prior screening revealed that compound 1 exhibited unequal inhibitory activity against the three GP subtypes, with a noticeable effect against brain GP (PYGB). The commercially available ingliforib demonstrated potent inhibitory activity specifically against liver GP (PYGL). To guide the further design and screening of high-specificity inhibitors, the possible reasons for the differential inhibitory activity of two compounds against different GP subtypes were analyzed, with ingliforib as a reference, through molecular docking and molecular dynamics simulations. Initially, the study predicted the binding modes of ligands with the three GP receptor subtypes using molecular docking. Subsequently, this was validated by molecular dynamics experiments, and possible amino acid residues that had important interactions were explored. The strong correlation between the calculated interaction free energies and experimental inhibitory activity implied the reasonable binding conformations of the compounds. These findings offer insight into the different inhibitory activity of compound 1 and ingliforib against all three GP subtypes and provide guidance for the design of specific target molecules that regulate subtype selectivity.

As the runoff series exhibit nonlinear and nonstationary characteristics, capturing the embedded periodicity and regularity in the runoff series using a single model is challenging. To account for these runoff characteristics and enhance the forecasting precision, this research proposed a new empirical wavelet transform–particle swarm optimization–support vector machine (EWT–PSO–SVM) hybrid model based on “decomposition-forecasting-reconstruction” for runoff forecasting and investigated its effectiveness in the karst area. First, empirical wavelet transform (EWT) was employed to decompose the original runoff series into multiple subseries. Second, the support vector machine (SVM) optimized by particle swarm optimization (PSO) was applied to forecast every signal subseries. Finally, this study summarized the predictions of the subseries to reconstruct the ultimate runoff forecasting. The developed forecasting model was assessed by applying the monthly runoff series of the Chengbi River Karst Basin, and the composite rating index combined with five metrics was adopted as the performance evaluation tool. From the results of this research, it is clear that the EWT–PSO–SVM model outperforms both the PSO–SVM model and the SVM model in terms of the composite rating index, reaching 0.68. Furthermore, verifying the performance stability, the developed model was also compared with PSO–SVM and SVM models under different input data structures. The comparison demonstrated that the hybrid EWT–PSO–SVM model had a robust performance superiority and was an effective model that can be applied to karst area runoff forecasting.

The 21st century is a high-tech information era in which our lives are closely linked by computer networks. Hence, how to effectively supervise networks and reduce the frequency of network security incidents has now become a research hotspot in cyberspace. Specifically, researchers have shown an increased interest in predicting the network traffic before any untoward incident happens. Optimization and decomposition technologies are the core components of network traffic prediction model which plays an important role in network management. This article discusses past network traffic prediction research and critically examines the optimization and decomposition technologies used in the model, lists the model parameter structure based on the research methodology, the data set used, the evaluation criteria and so on. By comparison, digging out the Particle Swarm Optimization (PSO) algorithm and the Variational Mode Decomposition (VMD) decomposition technique will effectively solve the network traffic model predictive difficulties that have proven to be crucial to improving predictive accuracy and convergence speed strategy.The comprehensive review reveals that PSO and VMD are the most suitable optimization algorithm and decomposition technology for network traffic prediction modeling.

Brain-type glycogen phosphorylase (PYGB) inhibitors are recognized as prospective drugs for treating ischemic brain injury. We previously reported compound 1 as a novel glycogen phosphorylase inhibitor with brain-protective properties. In this study, we validated whether PYGB could be used as the therapeutic target for hypoxic-ischemic diseases and investigated whether compound 1 exerts a protective effect against astrocyte hypoxia/reoxygenation (H/R) injury by targeting PYGB. A gene-silencing strategy was initially applied to downregulate PYGB proteins in mouse astrocytes, which was followed by a series of cellular experiments with compound 1. Next, we compared relevant indicators that could prove the protective effect of compound 1 on brain injury, finding that after PYGB knockdown, compound 1 could not obviously alleviate astrocytes H/R injury, as evidenced by cell viability, which was not significantly improved, and lactate dehydrogenase (LDH) leakage rate, intracellular glucose content, and post-ischemic reactive oxygen species (ROS) level, which were not remarkably reduced. At the same time, cellular energy metabolism did not improve, and the degree of extracellular acidification was not downregulated after administration of compound 1 after PYGB knockdown. In addition, it could neither significantly increase the level of mitochondrial aerobic energy metabolism nor inhibit the expression of apoptosis-associated proteins. The above results indicate that compound 1 could target PYGB to exert its protective effect against cellular H/R injury in mouse astrocytes. Simultaneously, we further demonstrated that PYGB could be an efficient therapeutic target for ischemic-hypoxic diseases. This study provides a new reference for further in-depth study of the action mechanism of the efficacy of compound 1.

Inter-domain routing system,domain name system (DNS) and public key infrastructure (PKI) are the fundamental infrastructures of the internet.These infrastructures help to provide network connectivity,service availability and communication trusts between different internet entities.However,these infrastructures are all designed based on a centralized system architecture or a trusted model,which suffers from many vulnerabilities.An architecture called decentralized internet infrastructure (DII) based on decentralization techniques was proposed.The DII architecture consists of three layers.The underlying layer was the distributed ledger layer,providing decentralized trusted foundation for DII.The intermediate layer,called name space management layer,fulfills the management of internet core resources (such as IP addresses,AS numbers and domain names) and provides trustworthy mapping information between different resources.The top layer was an open application layer that could support trustworthy decentralized internet applications.

The vision of the Internet of Things (IoT) covers not only the well-regulated processes of specific applications in different areas but also includes ubiquitous connectivity of more generic objects (or things and devices) in the physical world and the related information in the virtual world. For example, a typical IoT application, such as a smart city, includes smarter urban transport networks, upgraded water supply, and waste-disposal facilities, along with more efficient ways to light and heat buildings. For smart city applications and others, we require unique naming of every object and a secure, scalable, and efficient name resolution which can provide access to any object's inherent attributes with its name. Based on different motivations, many naming principles and name resolution schemes have been proposed. Some of them are based on the well-known domain name system (DNS), which is the most important infrastructure in the current Internet, while others are based on novel designing principles to evolve the Internet. Although the DNS is evolving in its functionality and performance, it was not originally designed for the IoT applications. Then, a fundamental question that arises is: can current DNS adequately provide the name service support for IoT in the future? To address this question, we analyze the strengths and challenges of DNS when it is used to support ubiquitous IoT. First, we analyze the requirements of the IoT name service by using five characteristics, namely security, mobility, infrastructure independence, localization, and efficiency, which we collectively refer to as SMILE. Then, we discuss the pros and cons of the DNS in satisfying SMILE in the context of the future evolution of the IoT environment.

Brain-type glycogen phosphorylase inhibitors are potential new drugs for treating ischemic brain injury. In our previous study, we reported compound 1 as a novel brain-type glycogen phosphorylase inhibitor with cardioprotective properties. We also found that compound 1 has high blood–brain barrier permeability through the ADMET prediction website. In this study, we deeply analyzed the protective effect of compound 1 on hypoxic-ischemic brain injury, finding that compound 1 could alleviate the hypoxia/reoxygenation (H/R) injury of astrocytes by improving cell viability and reducing LDH leakage rate, intracellular glucose content, and post-ischemic ROS level. At the same time, compound 1 could reduce the level of ATP in brain cells after ischemia, improve cellular energy metabolism, downregulate the degree of extracellular acidification, and improve metabolic acidosis. It could also increase the level of mitochondrial aerobic energy metabolism during brain cell reperfusion, reduce anaerobic glycolysis, and inhibit apoptosis and the expression of apoptosis-related proteins. The above results indicated that compound 1 is involved in the regulation of glucose metabolism, can control cell apoptosis, and has protective and potential therapeutic effects on cerebral ischemia-reperfusion injury, which provides a new reference and possibility for the development of novel drugs for the treatment of ischemic brain injury.

Raft is a fast, scalable, understandable consensus algorithm widely used in distributed systems. The Leader handles client requests and interacts with other servers to reach a consensus, so a stable, reliable, and powerful Leader is crucial for the cluster. We designed a policy-based voting mechanism to make the elected Leader as reliable as possible. In order to improve the asymmetric relationship between the Followers and Leader, we designed a mechanism to trigger a new round of the election actively so that the Leader node can actively transform into a Follower under certain conditions and enhance the symmetry between servers. Our proposed Raft-PLUS algorithm makes the elected Leader as reliable as possible through four election policies and designed three opposition policies to trigger a new round of the election. To verify the effectiveness of the Raft-PLUS algorithm, we configure different election and opposition policies on 12 servers to simulate the election and opposition process of the Leader and explain the process. To demonstrate the advantages of the Raft-PLUS algorithm, we built key-value stores based on Raft and Raft-PLUS, and we tested the performance of Raft-PLUS and the Raft algorithm in normal and abnormal states. Experimental results show that the Raft-PLUS algorithm has similar write throughput to the Raft algorithm under normal conditions. Regarding the quality of the Leader network changes, the average write throughput of the Raft-PLUS algorithm is 40% higher than that of the Raft algorithm. The Leader’s CPU usage fluctuated; the average write throughput of Raft-PLUS was 38% higher than Raft.

With the increasing market demand for artificial hip joints, total hip joint replacement has gradually become an effective means of treating a series of hip joint diseases. In order to improve the service life of artificial hip joints, some new artificial hip joint materials, including polyetheretherketone (PEEK) and carbon fiber reinforced polyetheretherketone (CFR-PEEK), have been developed. In this paper, pin-on-plate wear tests under different cross-shear ratios and contact pressures were carried out to study the wear mechanism and worn surface topography of PEEK and CFR-PEEK. The experimental results showed that the wear of PEEK was associated with cross-shear, while CFR-PEEK was not. When the cross-shear ratio was 0.039 and contact pressure was 3.18 MPa, PEEK had poor wear resistance and its wear factor was about eight times that of ultra-high molecular weight polyethylene (UHMWPE). The wear resistance of CFR-PEEK had a significant advantage, since its wear factor was about 30% of that of PEEK. The wear factors of PEEK and CFR-PEEK increased as the contact pressure increased. The arithmetic average of the height amplitude of the surface, Sa, also increased gradually according to the topography of the worn surface. The wear mechanisms of PEEK and CFR-PEEK were scratching, plough cutting, and abrasion Since CFR-PEEK had good wear resistance and insensitivity to cross-shear motion, it is suitable for making artificial hip joints under low contact pressure condition.

Abstract Background Naphthalene is the simplest polycyclic aromatic hydrocarbon (PAH). It is easily emitted into the atmosphere, posing a significant risk to human health. However, limited studies have described the impact of naphthalene exposure on birth outcomes. In this study, we investigated the association between the maternal urinary metabolites of naphthalene, 2-hydroxynaphthalene (2-OH NAP), and birth outcomes. Method In the present study, four urinary PAH metabolites were measured in 263 pregnant women during late pregnancy. Multiple linear regression analysis was used to analyze the relationship between the concentrations of 2-OH NAP and birth outcomes, and restricted cubic spline models were further used to examine the shapes of the dose-response association. Result General linear models showed that prenatal urinary 2-OH NAP was associated with lower birth weight (BW) (− 4.38% for the high vs. low exposure group of 2-OH NAP; p for trend = 0.049) and higher cephalization index (CI) (4.30% for the high vs. low exposure group of 2-OH NAP; p for trend = 0.038). These associations were linear and significant when 2-OH NAP was modeled as a continuous variable in restricted cubic spline models (P linear = 0.0293 for 2-OH NAP and BW; P linear = 0.0326 for 2-OH NAP and CI). Multiple linear regression data indicated that each 1 ln-unit increase in 2-OH NAP was significantly associated with a 2.09 g/cm increase in the CI. The associations among 2-OH NAP, BW, and CI were also observed in a subset of participants residing close to arterial traffic. Conclusion Our data indicated that prenatal exposure to naphthalene had an adverse effect on fetal birth outcomes, especially the brain development index. Reduced exposure to naphthalene may improve newborn health outcomes. In Taiyuan, naphthalene may result from traffic pollution.

Based on the Information-Centric Networking (ICN) concept and the mature model of the current TCP/IP-based Internet, we propose content searching based on universal and scalable resource description, namely ISBORD (Internet Searching based on Resource Description). This novel concept aims to improve the efficiency of content searching and simplifies the end-user functionality to support the evolution of the content-centric Internet.

Two of the most promising candidate solutions for realizing the next-generation all-IP mobile networks are Mobile IPv6 (MIPv6), which is the host-based and global mobility supporting protocol, and Proxy MIPv6 (PMIPv6), which is the network-based and localized mobility supporting protocol. However, the unprecedented growth of mobile Internet traffic has resulted in the development of distributed mobility management (DMM) architecture by the Internet engineering task force DMM working group. The extension of the basic MIPv6 and PMIPv6 to support their distributed and scalable deployment in the future is one of the major goals of the DMM working group. We propose an all-IP-based mobility management architecture that leverages the concept of Named Data Networking (NDN), which is a distributed content management and addressing architecture. In the proposed solution, mobility support services are distributed among multiple anchor points at the edge of the network, thereby enabling a flat architecture that exploits name-based routing in NDN. Our approach overcomes some of the major limitations of centralized IP mobility management solutions, by extending existing routing protocol and mobility management architecture, to distribute the mobility management function of anchor points in the IP network and optimize the transmission path of mobile traffic.

Internet Engineering Task Force (IETF) has proposed an extension based on Mobile IPv6 (MIPv6), named as network mobility basic support protocol (NEMO-BSP), to support NEMO in IPv6 networks. However, NEMO-BSP inherits all the drawbacks of MIPv6, such as inefficient routing path, high handover latency, and packet encapsulation overhead. To address these drawbacks of NEMO-BSP, this paper proposes an NEMO supporting scheme based on a novel Locator/ID Separation (LIDS) architecture, namely LIDS-NEMO. In LIDS-NEMO, Multiple Virtual Mapping (MVM) scheme is proposed to differentiate the intra-NEMO and inter-NEMO mobility. Besides, packets are transmitted through the most optimized route in LIDS-NEMO. The simulation results show that LIDS-NEMO reduces the signaling cost significantly when compared with NEMO-BSP and it will be a promising scheme to provide NEMO support in the LIDS context.

To explore the molecular mechanisms of BAY R3401, four types of novel photoaffinity probes bearing different secondary tags were synthesized. Their potency for glycogenolysis was evaluated in primary human liver HL-7702 cells and HepG2 cells. Probe 2d showed the best activity in primary human liver HL-7702 cells and HepG2 cells, with IC50 values of 4.45 μM and 28.49 μM, respectively. Likewise, probe 5d showed IC50 values of 6.46 μM in primary human liver HL-7702 cells and 15.29 μM in HepG2 cells, respectively. Photoaffinity labeling experiments were also performed and protein bands larger than 170 kDa were specifically tagged by probe 2d. The results suggest that the synthesized probe 2d might be a very promising tool for the isolation of the target proteins of BAY R3401.