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In the internet of vehicles systems that combining mobile edge computing (MEC) with non-orthogonal multiple access (NOMA) technology,to solve the high latency problem when user processes computationally intensive and latency-sensitive task,a strategy of task offloading,migration and cache optimization based on game theory and Q learning is proposed.Firstly,the mo-del of offloading delay,migration delay and cache delay of the internet of vehicles task based on NOMA-MEC is established.Se-condly,we use the cooperative game method to obtain the optimal user group to optimize the offloading delay.Finally,in order to avoid local optima,the Q learning algorithm is utilized to optimize the joint delay of the migration cache in the user group.The simulation results show that compared with other solutions,the proposed algorithm can effectively improve the offloading efficiency and reduce the task delay by about 22% to 43%.

Cerebral small vessel disease (CSVD) is a type of intracranial vascular disease characterized by recurrent stroke and neurodegenerative progression. The pathogenesis of CSVD is still unclear, and immunoinflammatory mechanisms such as blood⁃brain barrier leakage, chronic inflammation and leukocyte infiltration play an important role in the development of CSVD. At present, there is no effective method to prevent and treat CSVD except for controlling risk factors. This paper aims to review the progression of immunoinflammatory mechanisms in CSVD.

In view of problem of low reliability caused by single-factor gradient method for predicting gas content in coal mine, the paper proposed a method of visualization multivariable prediction for gas content based on grey system theory, and established overall framework of the prediction model, presented flow of grey modeling numerical algorithm realized by dynamic link database. It detailedly introduced realization process of the prediction method combined with real condition of a Mine as follows: obtaining original data of gas content from digital gas geologic map, setting up related parameters for modeling, establishing multivariable prediction model for gas content, choosing point or batch prediction for gas content prediction, analyzing error of prediction result and displaying the result with graphic information. The prediction method improves prediction efficiency and scientificity of decision making, provides an intuitive, convenient and efficient visualization prediction method for daily gas content prediction, management and decision making in coal mine.

To discriminate the ship targets in SAR images, this paper proposed the method based on combination of Hu moment feature and texture feature. Firstly,7 Hu moment features should be extracted, while gray level co-occurrence matrix is then used to extract the features of mean, variance, uniformity, energy, entropy, inertia moment, correlation and differences. Finally the k-neighbour classifier was used to analysis the 15 dimensional feature vectors. The experimental results show that the method of this paper has a good effect.

More and more attentions were being paid to the study of tumor stem cells. It has been demonstrated that tumor stem cells were present in both differentiated thyroid cancer with a good prognosis as papillary or follicular cancer and undifferentiated ones with poor prognosis. Thyroid cancer stem cells (TCSCs) play a major role in tumor genesis, progression and metastasis, and may even be the root of recurrence and drug resistance in thyroid cancers. Therefore, the study of TCSCs is great importance to thyroid cancer treatment. In this paper, the authors reviewed the latest researches progress on the origin and survival pathways of TCSCs.

The present study aimed to determine the diagnostic concordance of plasma epidermal growth factor receptor (EGFR) mutation using droplet digital polymerase chain reaction (ddPCR) with tumor tissue samples and the predictive clinical significance of plasma EGFR mutation concentration. Plasma DNA samples from patients with non-small cell lung cancer (NSCLC) were analyzed for EGFR exon 21 codon 858 (L858R) mutation, deletion of exon 19 (ex19del) and exon 20 codon 790 (T790M) mutation using ddPCR. Firstly, the mutations in the plasma samples were compared with the matched tumor samples to determine the concordance. Secondly, image examination follow-ups were analyzed to assess the association between plasma EGFR mutation concentration and patients' response to EGFR-tyrosine kinase inhibitors (TKIs). A total of 51 patients with NSCLC were enrolled, including 48 newly diagnosed patients. Compared with tumor tissue samples, the sensitivity and specificity of ddPCR were 76.19% (16/21) and 96.55% (28/29) for mutant L858R, and 88.89% (8/9) and 100% (41/41) for ex19del, respectively. No patient exhibited the T790M mutation in the tumor tissue or plasma samples. Furthermore, 5 patients with the L858R mutation and 4 patients with ex19del in plasma and tumor tissue samples had been followed up with image examination for ≥3 months following EGFR-TKI treatment. The baseline mutant EGFR concentrations were positively correlated with a reduction in tumor burden (Spearman's r=0.7000, P=0.0358). When analyzed separately, ex19del concentrations (Spearman's r=1.0000, P

Detection of circulating tumor DNA using droplet digital polymerase chain reaction (ddPCR) is a highly-sensitive, minimally invasive alternative to serial biopsies for assessment and management of cancer. We used ddPCR to assess the utility of measuring plasma concentrations of common epidermal growth factor receptor (EGFR) mutations (L858R, exon 19 deletion, and T790M) in 57 non-small cell lung cancer (NSCLC) patients treated with EGFR tyrosine kinase inhibitors (EGFR-TKIs). High baseline plasma EGFR mutation (pEGFRmut) concentrations were associated with shorter progression-free survival (8.43 months) than low baseline pEGFRmut (16.23 months; p = 0.0019). By contrast, there were no differences in tumor shrinkage or overall survival between groups. During EGFR-TKI treatment, pEGFRmut levels decreased to zero in 89.58% of patients. Twenty-five of the 27 patients who progressed had basal pEGFRmut, and 18 also had circulating T790M. All 20 patients with dramatic progression (according to a categorization system for EGFR-TKIs failure) had basal pEGFRmut, and 13 had T790M mutation at progression. These results support the use of ddPCR for analysis of plasma EGFR mutations for prediction of PFS and to monitor clinical responses to EGFR-TKIs in NSCLC patients.