Search

To solve the problems of low efficiency of network service caching and computing-networking resource allocation caused by tasks differentiation, highly dynamic network environment, and decentralized computing-networking resource deployment in edge networks, a decentralized service arrangement and computing offloading model for mobile edge computing was investigated and established.Considering the multidimensional resource constraints, e.g., computing power, storage, and bandwidth, with the objective of minimizing task processing latency, the joint optimization of service caching and computing-networking resource allocation was abstracted as a partially observable Markov decision process.Considering the temporal dependency of service request and its coupling relationship with service caching, a long short-term memory network was introduced to capture time-related network state information.Then, based on recurrent multi-agent deep reinforcement learning, a distributed service arrangement and resource allocation algorithm was proposed to autonomously decide service caching and computing-networking resource allocation strategies.Simulation results demonstrate that significant performance improvements in terms of cache hit rate and task processing latency achieved by the proposed algorithm.

ObjectiveTo investigate the performance of deep neural network (DNN) and Klemera-Doubal method (KDM) in assessment of biological age (BA) among middle-aged and elderly Chinese population and to select the optimal scheme for evaluating the accuracy of two methods in BA estimation. MethodsThe study data on people aged 45 – 85 years were extracted from the baseline survey of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011/2012. The extracted data (including blood marker samples from 11 513 people, physical measurements from 13 603 people, and both blood marker samples and physical measurements from 9 904 people) were used to estimate BA by DNN and KDM. Pearson correlation coefficient, mean absolute error (MAE) and root mean square error (RMSE) were adopted in the evaluation on accuracy of BA estimation and the selection of optimal scheme. Complex sampling logistic regression model and linear regression model were constructed using calculated residual (ΔBA) of regression analysis of estimated BA and chronological age (CA), mortality data, and cognitive function assessment of the people. Receiver operating characteristics (ROC) area under curve (AUC) was used to evaluate the performance of ΔBA in predicting mortality risk. ResultsCompared with the estimations based only on blood marker samples or physical measurements, the DNN- and KDM-derived BA estimations based on blood marker sample and physical measurement showed the highest correlation with CA (rDNN = 0.91, rKDM = 0.48), but the lowest MAE (MAEDNN = 3.11, MAEKDM = 13.74) and RMSE (RMSEDNN = 4.15, RMSEKDM = 17.76). The accuracy of DNN-derived BA estimation was better than that of KDM-derived estimation. The mortality risk increased but the scores of overall cognition, memory and mental status decreased with the increment of DNN-derived ΔBA and KDM-derived ΔBA based on blood marker samples and physical measurements and of CA. KDM-derived ΔBA showed a slightly higher accuracy in mortality risk prediction compared to DNN-derived ΔBA (AUCKDM-ΔBA = 0.717; AUCDNN-ΔBA = 0.699). Compared with those having normal aging (with the ΔBA of ≥ – 5 and ≤ 5), the people having accelerated aging (with the ΔBA of > 5) were at an increased risk of mortality (odds ratio [OR]DNN = 1.760, 95% confidence interval [95%CI]: 1.207 – 2.567; ORKDM = 1.872, 95%CI: 1.308 – 2.679) and having a low score of overall cognition (βDNN = – 0.631, 95%CI: – 1.124 – – 0.139; βKDM = – 0.374, 95%CI: – 0.680 – – 0.068). ConclusionThe predictive BA could be more accurate when derived from blood marker sample and physical measurement than that from either one of the two samples. The BA estimated by DNN modeling method is of higher accuracy than that by KDM but the performance in BA prediction of the two methods is similar. The results suggest that DNN modeling method could be used in evaluating individual aging among middle-aged and elderly Chinese populations.

Objective: The edible fungi with high calcium enrichment rate and calcium organic degree were screened from sulfur fungus, Poria cocos, Monascus and Armillaria, and the effect of calcium enrichment on the content of the main active ingredient, dentate acid, was studied when the sulfur fungus with high calcium enrichment were cultured in liquid. Methods: The bioaccumulation method was used to study the effect of inorganic calcium on the growth of four edible fungi. The organic degree of calcium in mycelia was analyzed by static leaching method, and the content of the main active ingredient, dentate acid, was analyzed by HPLC. Results: In solid culture, the growth of sulfur fungus was better than that of Poria cocos, Armillaria and Monascus at the right amount of calcium addition. When the calcium addition amount was 100 mg/L in liquid culture, the calcium enrichment rate of sulfur fungus was significantly higher than those of Poria cocos, Armillaria and Monascus. When the calcium concentration of sulfur fungus liquid culture was 100 mg/L, the calcium enrichment rate was 93.51%, the degree of calcium organization was 85.85%, and the content of the dentate acid was 18.34 mg/g. Therefore, sulfur fungus has the potential to become a new functional calcium supplement product.

To address the problem of high filling cost in an open pit to an underground mine, based on the machine learning method, the filling cementitious material needed for subsequent backfill mining method was developed using the available industrial wastes around the mine, and the ratio of filling slurry was optimized. First, the physical and chemical properties of the materials were analyzed. Unconfined compressive strength tests were conducted with different activator formulations to analyze the influence of each component on the strength of the backfill body. A genetic algorithm and support vector machine (GA−SVM) model was established to predict the steel-slag-based cementitious material formula using the experimental data, and the optimal ratio was determined based on the model prediction results. X-ray diffraction (XRD) and scanning electron microscope (SEM) were used to analyze the hydration products and microstructure characteristics of steel-slag-based cementitious materials at different curing ages and slag dosage conditions and determine the hydration mechanism of steel-slag-based cementitious materials. Finally, the slurry proportion was optimized by strength (i.e., 7 and 28 days) and working characteristics (i.e., slump and bleeding rate) based on the principle of gray target decision. Results revealed that the relative errors of the GA−SVM model for predicting the steel-slag-based cementitious materials strength at 7 and 28 days are 3.6%–12.62% and 6.9%–10.19%, respectively, thereby indicating high prediction accuracy. The optimal proportion of steel-slag-based cementitious materials determined by prediction analysis is steel slag content of 30%, desulfurized gypsum content of 4%, cement clinker content of 12%, and mirabilite content of 1%. The main hydration products of steel-slag-based cementitious materials are amorphous C−S−H gel, ettringite, tricalcium aluminate hydrate, Ca(OH)2, and CaCO3. The calcium hydroxide content increases with the steel slag content, which generates a large number of pores and deteriorates the structure and strength of the sample. When the new steel-slag-based cementitious material is applied to the actual backfilling of the mine, the optimal ratio parameters of filling slurry are obtained through the optimization of the model of the gray target decision (i.e., cement−sand ratio of 1∶4 and mass concentration of 72%). Corresponding verification experiments were conducted, and the corresponding strength and working characteristic parameters were 1.74 MPa, 3.61 MPa, 24.2 cm, and 5.91%, which all met the requirements of subsequent filling. With this proportion, the filling cost is 113 ¥·m−3, which is 38.92% lower than that of the cement filler. The research results will benefit the comprehensive utilization of solid waste and provide support for safe, clean, and efficient mining.

In order to improve the dissolution of azithromycin, azithromycin nanocrystals tablets are studied based on the nanocrystal technology. The media milling method is employed to prepare azithromycin nanocrystals, from which azithromycin nanocrystals tablets are made. The quality of the tablets is evaluated referring to Chinese Pharmacopoeia, the dissolution rates are measured by paddle method, and the content and related substances are determined by HPLC. The stabilities are investigated by impact factors test, short-time test and retention samples test. The results show that the quality of the homemade tablets meets the requirements of tablets in Appendix of volume Ⅱ of Chinese Pharmacopoeia (2010), and their dissolution rates increases significantly compared with the reference preparations. Impact factors test indicates that the homemade tablets are stable in the condition of high temperature or strong light but sensitive to environmental humidity. Short-time test and retention samples test results show that the homemade tablets are stable within 6 months, so they should be sealed and stored in a cool dry place.

The molecular docking-based virtual screening technique evaluates the binding abilities between multiple ligand compounds and receptors to screen for the active compounds. In the context of the global spread of the COVID-19 pandemic, large-scale and rapid drug virtual screening is crucial for identifying potential drug molecules from massive datasets of ligand structures. The powerful computing power of supercomputer provides hardware guarantee for drug virtual screening, but the super large-scale drug virtual screening still faces many challenges that affects the effective execution of the calculation. Based on the analysis of the challenges, this paper proposes a centralized task distribution scheme with a central database, and designs a multi-level task distribution framework. The challenges are effectively solved through multi-level intelligent scheduling, multi-level compression processing of massive small molecule files, dynamic load balancing and high error tolerance management technology. An easy-to-use “tree” multi-level task distribution system is implemented. A fast, efficient and stable drug virtual screening task distribution, calculation and result analysis function is realized, and the computing efficiency is nearly linear. Then, heterogeneous computing technology is used to complete the drug virtual screening of more than 2 billion compounds, for two different active sites for COVID-19, on the domestic super computing system, which provides a powerful computing guarantee for the super large-scale rapid virtual screening of explosive malignant infectious diseases.

ObjectiveTo explore spatiotemporal distribution of pulmonary tuberculosis (TB) morbidity and mortality and their changing trend in China from 2004 to 2018 and to provide evidence for conducting relevant studies and developing strategies on TB prevention and treatment. MethodsNationwide data of 2004 – 2018 on TB surveillance were collected and demographic data of the same period were extracted from China Statistical Yearbook. The 15-year period was divided into three stages. The spatial characteristics of TB morbidity was analyzed with Excel 2010 software and Stata 14.0 was used to analyze spatial autocorrelation. Results During the period, totally 14 816 329 TB incidents were reported in China, with an average incidence rate of 73.9029/100 000 and an average annual reported mortality of 0.2114/100 000. Spatial autocor-relation of TB morbidity in different regions was observed. ConclusionDuring 2004 – 2018 in China, the incidence rate of pulmonary tuberculosis was decreasing generally and there were aggregations and significant regional differences in TB morbidity.

ObjectiveTo investigate relationships among turnover intention, occupational stress and trait coping style and to explore mediating role of trait coping style on the correlation between occupational stress and turnover intention among employees in centers for disease control and prevention (CDCs). MethodsA network-based survey was conducted during July – September 2020 among 2 201 professionals recruited with random cluster sampling at 21 CDCs at various administrative levels in Jiangsu province. A general questionnaire, Core Occupational Stress Scale (COSS), Trait Coping Style Questionnaire (TCSQ), and a turnover intention scale developed by other researches were adopted in the survey. Statistical analyses were performed with SPSS 22.0. ResultsValid information were collected from 2 036 respondents. Among all the respondents, the median score (25th percentile, 75th percentile) was 42.0 (37.0, 48.0) for COSS, 6.0 (1.0, 13.0) for TCSQ, and 2.0 (1.3, 2.5) for turnover intention. The turnover intention score was correlated positively with COSS dimension scores of organization-reward (correlation coefficient [r] = 0.46) and demand-effort (r = 0.22) but inversely with the dimension scores of social support (r = – 0.38) and independence (r = – 0.08) and the score of TCSQ (r = – 0.442). The results of mediating effect analysis revealed mediating effect of trait coping style on the correlation of turnover intention with occupation stress′s dimension variables of social support (effect value = 0.0237, the value′s 95% confidence interval [95% CI]: 0.0193 – 0.0287; effect percentage = 26.60%) , organization-reward (effect value = 0.0158, 95% CI: 0.0127 – 0.0189; effect percentage = 21.94%), and demand-effort (effect value = 0.0161, 95% CI: 0.0117 – 0.0207; effect percentage = 31.88%). ConclusionThe trait coping style could exert mediating effect on the correlations of turnover intention with occupation stress-related social support, organization-reward and demand-effort among professionals in disease control and prevention institutions. The improvement in trait coping style may reduce the professional′s turnover intention.

Based on the new seismic and logging data, this paper identifies the location and shape of the platform margin belt in Tazhong, Tarim Basin and studies its structural characteristics and reservoir-forming conditions using isochronous sequence framework, structural analysis, sedimentary evolution, and other methods. The platform margin belt is a large composite slope break belt formed from the end of the early Ordovician to the early of the Late Ordovician. Its east section is a complicated faulted slope break resulted from erosion before Late Ordovician, and its west is a carbonate sedimentary slope break in which the platform margin reef flat complex was developed in the Lianglitage Formation of the Upper Ordovician. The belt can be divided into six parts with different structural and sedimentary characteristics. The first and second parts are the superimposed segments of the on-lap trigonal zone and the erosional trigonal zone, in which karst and lithologic reservoirs were well-developed. Platform margin reef flats were well-developed in the fifth part. These three zones are the main exploration targets. Key words: platform margin belt, paleo-geographic environment, geologic structure, trigonal zone, reservoir-forming condition

Objective: Loss of response (LOR) has become an important clinical problem in patients with Crohn's disease receiving infliximab (IFX) treatment. Neutrophil-lymphocyte ratio (NLR) has been shown to correlate with the activity of inflammatory bowel disease (IBD), and NLR at the 14th week of IFX therapy potentially allows the prediction of sustained response to IFX in Crohn's patients. The aim of this study was to explore whether NLR at the 14th week of IFX therapy could predict the occurrence of LOR to IFX in Crohn's patients., Methods: Between January, 2012 and December, 2016, 54 patients with Crohn's disease underwent a 52-week treatment with IFX and successfully achieved response to the induction treatment in Zhongnan Hospital. We retrospectively examined their medical records and assessed the association between NLR at 14 weeks and LOR during IFX therapy., Results: Of the 54 patients, 15 (27.8%) showed LOR to IFX during the follow-up. We noted a significant increase in NLR at 14 weeks in the patients with LOR as compared with the patients with sustained response to IFX[3.51 (2.9-6.25) vs 1.77 (1.23-2.56), P =0.00]. Receiver-operating characteristic analysis showed that at the cut-off value of 2.75, NLR at 14 weeks was predictive of LOR within 52 weeks of IFX therapy with a sensitivity of 93.33% and a specificity of 84.62%, and the area under curve (AUC) of NLR was 0.903 (0.731-0.959). Univariate analysis revealed a significant correlation between relapse-free survival and the NLR at 14 weeks ( P =0.00). Multivariate analysis identified NLR at 14 weeks as an independent prognostic factor for LOR with a hazard ratio of 1.851 (95% CI :1.096-3.026, P =0.021)., Conclusions: NLR at the 14th week during IFX therapy is a useful predictor for LOR in patients with Crohn's disease.

Objective: To identify a myeloid differentiation factor 88 (MyD88) in Oncomelania hupensis , and characterize the role of MyD88 against Schistosoma japonicum infection., Methods: The complete cDNA of MyD88 in O. hupensis was obtained by using rapid amplification of cDNA ends (RACE), and homologues sequences and conserved domains were aligned and the structure of MyD88 was predicted either. A phylogenetic tree of MyD88 was further constructed with other species. In addition, the mRNA expression level of O. hupensis MyD88 before and after S. japonicum infection was investigated by real-time quantitative PCR (RT-qPCR)., Results: The cDNA of O. hupensis MyD88 consisted of 1 406 bp open reading frame (ORF), encoding 468 amino acid residues, which contained death domain and Toll/interlrukin-1 receptor (TIR) domain, the typical features of MyD88 family proteins. The predicted amino acid sequence of O. hupensis MyD88 shared 38%-52% identity with other mollusc. O. hupensis MyD88 was phylogenetically closeted to Biomphalaria glabrata MyD88. The O. hupensis MyD88 existed in all selected tissues and expressed highly in hemocyte, up-regulated after S. japonicum infection in all selected tissues except cephalopodium, especially higher in whole snail and hemocyte., Conclusions: MyD88-dependent signaling pathway is present in O. hupensis and plays an important role in innate immune response against S. japonicum infection.