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There are some problems in the application of current data analysis methods in international economy and trade, such as low service efficiency, low data utilization, and low degree of intelligence. Based on this, this paper studies the application of the Internet of things data analysis method in international trade development and economic and industrial growth. Firstly, the Internet of things economic data analysis model (IOT-EET model) based on simulated annealing early warning algorithm is established to store and analyze the data in the whole chain of international trade. Then, combined with the analysis methods of international trade economic data over the years, it is fed back to the IOT-EET model for error calibration. Finally, relevant experiments are designed to analyze the correlation between international trade development and national economic growth. The results show that compared with the traditional method based on module data analysis, this IOT-EET model can realize the correlation matching analysis of the data involved in the development of international trade in combination with the Internet of things technology and analyze the factors affecting international trade transactions. Therefore, it has the advantages of good reliability and strong pertinence.

Supplemental material, sj-doc-1-tag-10.1177_17562848221150306 for Clinical significance of neoadjuvant chemotherapy for locally advanced colorectal cancer patients with deficient mismatch repair: possibly residual value in the era of immunotherapy by Mian Chen, Junguo Chen, Jun Huang, Huashan Liu, Wuteng Cao, Shuangling Luo, Zhanzhen Liu, Huanxin Hu, Sicong Lai, Yujie Hou, Liang Kang and Liang Huang in Therapeutic Advances in Gastroenterology

Supplemental material, sj-doc-1-tag-10.1177_17562848221117875 for Clinical significance of adjuvant chemotherapy for pathological complete response rectal cancer patients with acellular mucin pools after neoadjuvant chemoradiotherapy by Mian Chen, Jianwei Zhang, Yujie Hou, Huashan Liu, Xinjuan Fan, Shuangling Luo, Zhanzhen Liu, Huanxin Hu, Sicong Lai, Liang Kang and Liang Huang in Therapeutic Advances in Gastroenterology

The innovation of logistics management mode plays a great role in promoting the operation timeliness of an e-commerce platform. The question of how to realize the research on the innovation mode of logistics management of the e-commerce platform with the integration of “Internet of things + blockchain” is the current development trend. Based on this, this paper studies the influencing factors of logistics management of an e-commerce platform under the discrete analysis strategy of “Internet of things + blockchain.” First, the logistics management analysis model of an e-commerce platform integrating “Internet of things + blockchain” is proposed. The dynamic correlation function is used to simulate the logistics information in the e-commerce platform. Through the extreme value of the dynamic correlation function curve in the detection process, the operation signal is restored, and then its logistics management is analyzed. Second, the influencing factors in the logistics management of the e-commerce platform are analyzed, comprehensive analysis is done by using the “Internet of things + blockchain” integration model, the dynamic logistics information in the operation of the e-commerce platform is accurately gathered, and the multidimensional hierarchical method is used for quality evaluation. Finally, the effectiveness of the logistics management analysis model of the e-commerce platform is verified by many experiments.

Objective Microvascular endothelial dysfunction, which is at the early stage of atherosclerosis, precedes macrovascular endothelial dysfunction. The study is aimed to investigate the mechanism underlying the improvement of microvascular endothelial dysfunction by exercise and diet in obese adolescents. Methods A quasi-randomized study was carried out with 2 cohorts: the experimental group (57 obese male adolescents; age: 15.38 ± 2.82 years, BMI: 33.21 ± 4.23 kg/m2) completed a 6-week exercise program with dietary intervention, and control group (10 normal weight adolescents; age: 15.38 ± 2.82 years, BMI: 23.21 ± 4.23 kg/m2) maintained sedentary. Clinical characteristics, circulating NO, ET-1 and microRNA-126 (miR-126) levels were measured before and after 6 weeks. The Reactive Hyperemia Index (RHI) was measured using EndoPAT-2000 system. Results After 6-weeks intervention, obese adolescents' body circumferences and glucolipid metabolism are significantly improved. RHI (p Conclusions Combination of exercise and diet control can effectively improve glycolipid metabolism of obese adolescents, and thus their microvascular endothelial function, which might be related to changes in serum miRNA-126.

Multi-modal neuroimaging projects are advancing our understanding of human brain architecture, function, connectivity using high-quality non-invasive data from many subjects. However, ground truth validation of connectivity using invasive tracers is not feasible in humans. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.

Hepatopancreatic necrosis disease (HPND) is a newly emerging disease in the Chinese mitten crab, Eriocheir sinensis, which has resulted in large economic losses. However, the underlying cause of this disease remains unclear. To better understand the pathogenesis and pathogenic mechanism of HPND, we compared the transcriptome differences of the hepatopancreas of E. sinensis with and without HPND. The analysis yielded > 30 million reads for each sample of three test (with HPND) and three control groups (without HPND). We observed 978 downregulated genes and 644 upregulated genes. Among the gene ontology categories "biological process," "cellular component," and "molecular function", the subcategories cellular process, single-organism process, biological regulation, metabolic process, cell part, organelle, organelle part, binding, and catalytic were enriched. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that "metabolism of xenobiotics by cytochrome P450," "drug metabolism-cytochrome P450," "chemical carcinogenesis," and "material metabolism" were the "five" most significantly enriched pathways in the hepatopancreas of E. sinensis with HPND. The results revealed that material metabolic abnormalities and drug effects from the external environment might be associated with HPND in the Chinese mitten crab. Considering the wide use of pyrethroids for pond cleaning in Xinghua city, we speculated that pyrethroids might cause HPND in the Chinese mitten crab. Our study provided useful information about the cause and pathogenetic mechanisms of HPND and could help to prevent this disease in production practice.

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The theoretical model and amplification principle of Raman fiber amplifier (RFA) are introduced. The gain curve and gain coefficient function which can accurately reflect the information of Raman gain spectrum (RGS) are obtained by the eighth-order Gaussian fitting of RGS of tellurite-based fiber. Combined with the technique of multi-pump, Raman power coupled wave differential equation is numerically solved by the fourth-order Runge–Kutta method. And Raman gain of each signal wavelength is obtained. According to the requirements of Dense Wavelength Division Multiplexing optical fiber transmission system for RFA, the designed tellurite-based Raman fiber amplifier (T-RFA) has improved the gain and bandwidth, and the smaller gain flatness is guaranteed. Finally, the average gain of the designed T-RFA obtained by Matlab numerical simulation is 25.518 dB, the maximum gain is 26.20 dB, the gain bandwidth is 56 nm and the gain flatness is 1.34 dB.

To preserve more useful information in visible and infrared images and improve the quality of the fused image, a method based on the nonsubsampled shearlet transform (NSST) and fuzzy C-means clustering is proposed. First, the source images are decomposed by NSST so as to get their own low- and high-frequency subbands. Second, the low-frequency subbands are divided into the infrared target part and the background part by fuzzy C-means clustering while different fusion rules are applied to the infrared target part and background part, respectively. Then, a choose-max fusion rule based on the sum-modified Laplacian of source images and local energy of coefficient is proposed to integrate the high-frequency subbands. Finally, the fused image is obtained by inverse NSST. The comparison experiment with the other three state-of-the-art fusion methods shows that the proposed method has good subjective visual effects and superior objective evaluations.

The difference of serum metabolome between hepatitis B virus (HBV) infected patients and healthy controls was explored for the potential metabolite biomarkers of HBV disease using serum metabolomics approach. Totally 30 HBV infected patients and 35 healthy controls were enrolled. Gas chromatography-time-of-flight mass spectrometry (GC-TOFMS), pattern recognition by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied in each group. Several metabolites which were different between the two groups based on variable importance in projection (VIP) value, non-parametric test and screening in databases were identified. Ten variables that were significantly different were considered as the potential biomarkers, among which five variables (citric acid, aconitic acid, glutamine, N,N-dimethylglycine and malonic acid) showed good correlation with HBV patients. The area under the receiver operating characteristic curve was 0.975, with good specificity and sensitivity. A panel of metabolite markers composed of citric acid, aconitic acid, glutamine, N,N-dimethylglycine and malonic acid from GC-TOFMS were selected to discriminate HBV subjects from their healthy counterparts. These biochemical changes provide a novel molecular diagnostic approach which could be helpful to further understand the pathogenesis and identify the therapeutic target of HBV disease.

Deltamethrin is an important pesticide widely used against ectoparasites. Deltamethrin contamination has resulted in a threat to the healthy breeding of the Chinese mitten crab, Eriocheir sinensis. In this study, we investigated transcriptional responses in the hepatopancreas of E. sinensis exposed to deltamethrin. We obtained 99,087,448, 89,086,478, and 100,117,958 raw sequence reads from control 1, control 2, and control 3 groups, and 92,094,972, 92,883,894, and 92,500,828 raw sequence reads from test 1, test 2, and test 3 groups, respectively. After filtering and quality checking of the raw sequence reads, our analysis yielded 79,228,354, 72,336,470, 81,859,826, 77,649,400, 77,194,276, and 75,697,016 clean reads with a mean length of 150 bp from the control and test groups. After deltamethrin treatment, a total of 160 and 167 genes were significantly upregulated and downregulated, respectively. Gene ontology terms "biological process," "cellular component," and "molecular function" were enriched with respect to cell killing, cellular process, other organism part, cell part, binding, and catalytic. Pathway analysis using the Kyoto Encyclopedia of Genes and Genomes showed that the metabolic pathways were significantly enriched. We found that the CYP450 enzyme system, carboxylesterase, glutathione-S-transferase, and material (including carbohydrate, lipid, protein, and other substances) metabolism played important roles in the metabolism of deltamethrin in the hepatopancreas of E. sinensis. This study revealed differentially expressed genes related to insecticide metabolism and detoxification in E. sinensis for the first time and will help in understanding the toxicity and molecular metabolic mechanisms of deltamethrin in E. sinensis.

In this article, the monitoring and measuring of the Xuejiazhuang tunnel of Lingnan freeway is introduced. The fitting regression analysis for the data of curve was done. And the surrounding rock stability is studied with the regression analysis of the convergence displacement data. In order to maintain the existing void between initial lining and surrounding rock, the ground-penetrating radar nondestructive testing technology and polymer grouting technology is presented. The field test results show that the use of polymer grouting technology can repair the tunnel distress and provide an ideal manner for tunnel quick maintenance.