Risk Factors and Prevalence of Helicobacter pylori

Aim. The aim of this study was to investigate the prevalence and risk factors of H. pylori infection in areas with high prevalence of gastric cancer in Jiangsu Province, China. Methods. A prospective epidemiologic survey of H. pylori infection was accomplished in a natural population of 5417 individuals in Yangzhong city. Questionnaires and 13C-urea breath test for H. pylori infection were performed. Results. Among 5417 subjects who completed questionnaires and 13C-urea breath test, 3435 (63.41%) were H. pylori positive. The prevalence reached a peak at the age of 30–39 years (90.82%). There was significant difference between sexes and women had a higher infection rate than men. The prevalence of H. pylori infection was also associated with eating kipper food and fried food. No association between H. pylori prevalence and smoking or drinking was found. Compared to healthy individuals, people with dyspeptic diseases (peptic ulcer, gastroenteritis) presented a high prevalence of H. pylori infection. Using multivariate logistic regression analysis, age and history of peptic ulcer and gastroenteritis were the independent predictors for H. pylori infection. Conclusions. Yangzhong city had a high prevalence of H. pylori infection and was related to several risk factors. The underlying mechanisms are needed to be further investigated

The emerging nanomedicine-based technology for non-small cell lung cancer immunotherapy: how far are we from an effective treatment

Non-small cell lung cancer (NSCLC) is a prominent etiology of cancer-related mortality. The heterogeneous nature of this disease impedes its accurate diagnosis and efficacious treatment. Consequently, constant advancements in research are imperative in order to comprehend its intricate nature. In addition to currently available therapies, the utilization of nanotechnology presents an opportunity to enhance the clinical outcomes of NSCLC patients. Notably, the burgeoning knowledge of the interaction between the immune system and cancer itself paves the way for developing novel, emerging immunotherapies for treating NSCLC in the early stages of the disease. It is believed that with the novel engineering avenues of nanomedicine, there is a possibility to overcome the inherent limitations derived from conventional and emerging treatments, such as off-site drug cytotoxicity, drug resistance, and administration methods. Combining nanotechnology with the convergence points of current therapies could open up new avenues for meeting the unmet needs of NSCLC treatment

Molecular Evidence of Bartonella melophagi in Ticks in Border Areas of Xinjiang, China

Bartonella are gram-negative intracellular bacteria; certain species of Bartonella can cause diseases in mammals and humans. Ticks play a major role in the transmission of Bartonella. Xinjiang is the largest province in China according to land area and has one-third of the tick species in China; the infection rate of Bartonella in ticks in the Xinjiang border areas has not been studied in detail. Therefore, this study investigated tick infections by Bartonella in Xinjiang border areas, and the purpose of the study was to fill in gaps in information regarding the genetic diversity of tick infections by Bartonella in Xinjiang. We tested 1,549 tick samples from domestic animals (sheep and cattle) for Bartonella using ribC-PCR. Positive samples from the ribC-PCR assay for Bartonella spp. were further subjected to PCR assays targeting the ITS, rpoB and gltA genes followed by phylogenetic analyses. Bartonella DNA was detected in 2.19% (34/1,549) of tick samples, and the ITS, rpoB and gltA genes of ribC gene-positive samples were amplified to identify nine samples of Bartonella melophagi. In this study, molecular analysis was used to assess the presence and genetic diversity of B. melophagi in ticks collected from sheep and cattle from Xinjiang, China. This study provides new information on the presence and identity of B. melophagi in ticks from sheep and cattle

Effects of Groundwater Depth on Vegetation Coverage in the Ulan Buh Desert in a Recent 20-Year Period

As a typical desert in the Inner Mongolia Autonomous Region, the Ulan Buh Desert has a dry climate and scarce precipitation all year round. Groundwater has become the main factor limiting the growth of vegetation in this region. It is of great significance to study the influence of groundwater depth on the spatial distribution pattern of vegetation in this region. Based on the PIE-Engine platform and using long-term time-series Landsat data, this paper analyzed the spatial–temporal distribution characteristics and trends in vegetation coverage in the Ulan Buh Desert in the last 20 years using a pixel dichotomy model and the image difference method. The Kriging interpolation method was used to interpolate the groundwater depth data from 106 monitoring wells in the Ulan Buh Desert over the past 20 years, and the spatial distribution characteristics of groundwater depth in the Ulan Buh Desert were analyzed. Finally, the correlation coefficient between changes in vegetation coverage and changes in groundwater depth was calculated. The results showed the following: (1) The vegetation coverage in the Ulan Buh Desert was higher in the periphery and lower in the center of the desert. The overall vegetation level showed an increasing trend year by year; the growth rate was 4.73%/10 years, and the overall vegetation cover showed an improving trend. (2) The overall groundwater depth in the Ulan Buh Desert was deep in the southwest and shallow in the northeast. In the past 20 years, the groundwater depth in the Ulan Buh area has become shallower, and the ecological condition has gradually improved. (3) On the whole, the vegetation coverage varied with the groundwater depth, and the shallower the groundwater depth, the greater the vegetation coverage. When the groundwater depth increased to more than 4 m, the change in the groundwater depth had a significant effect on the vegetation coverage. However, when the groundwater depth was greater than 6 m, the change in the groundwater depth had no significant effect on the change in vegetation coverage

Effect of Particle Size Distribution on the Dynamic Mechanical Properties and Fractal Characteristics of Cemented Rock Strata

To investigate the dynamic mechanics and post-failure characteristics of fault-cemented rock strata, broken rock particles were reshaped to obtain cemented rock samples with various particle size distributions (PSDs). Split Hopkinson pressure bar (SHPB) dynamic impact tests were performed on the cemented rock samples under different strain rates. The test results show that plastic deformation occurs in the cemented rock sample as a result of its porous structure. Therefore, there is no linear phase in the dynamic stress–strain curves. With an increase in the Talbot index and mixture type, more large particles were contained inside the cemented rock sample, and the dynamic strength gradually increased. A power function can effectively describe the relationship between the strain rate and dynamic strength for various Talbot indices. After dynamic impact, the fragments of the cemented rock samples exhibit evident fractal laws, and the breakage of the samples includes breakage of the original rock particle itself and breakage between the rock particles and cementations. The breakage ratio and fractal dimension both decrease with the increase in the number of mixture type and Talbot index but increase with the increase in strain rate. It is worth noting that the breakage ratio and fractal dimension have a linear relationship regardless of the PSD or strain. The relationship between the dynamic strength and fractal dimension has different response laws for the PSD and strain rate effects. The dynamic strength is negatively linearly related to the fractal dimension under the PSD effect but positively linearly related to the fractal dimension under the strain rate effect. This research work can provide foundation support for investigating the instability mechanism of fault cemented rock strata under dynamic stress

Effect of Particle Size Distribution on the Dynamic Mechanical Properties and Fractal Characteristics of Cemented Rock Strata

To investigate the dynamic mechanics and post-failure characteristics of fault-cemented rock strata, broken rock particles were reshaped to obtain cemented rock samples with various particle size distributions (PSDs). Split Hopkinson pressure bar (SHPB) dynamic impact tests were performed on the cemented rock samples under different strain rates. The test results show that plastic deformation occurs in the cemented rock sample as a result of its porous structure. Therefore, there is no linear phase in the dynamic stress–strain curves. With an increase in the Talbot index and mixture type, more large particles were contained inside the cemented rock sample, and the dynamic strength gradually increased. A power function can effectively describe the relationship between the strain rate and dynamic strength for various Talbot indices. After dynamic impact, the fragments of the cemented rock samples exhibit evident fractal laws, and the breakage of the samples includes breakage of the original rock particle itself and breakage between the rock particles and cementations. The breakage ratio and fractal dimension both decrease with the increase in the number of mixture type and Talbot index but increase with the increase in strain rate. It is worth noting that the breakage ratio and fractal dimension have a linear relationship regardless of the PSD or strain. The relationship between the dynamic strength and fractal dimension has different response laws for the PSD and strain rate effects. The dynamic strength is negatively linearly related to the fractal dimension under the PSD effect but positively linearly related to the fractal dimension under the strain rate effect. This research work can provide foundation support for investigating the instability mechanism of fault cemented rock strata under dynamic stress

Support Vector Machine Regression Algorithm Based on Chunking Incremental Learning

Abstract. On the basis of least squares support vector machine regression (LSSVR), an adaptive and iterative support vector machine regression algorithm based on chunking incremental learning (CISVR) is presented in this paper. CISVR is an iterative algorithm and the samples are added to the working set in batches. The inverse of the matrix of coefficients from previous iteration is used to calculate the regression parameters. Therefore, the proposed approach permits to avoid the calculation of the inverse of a large-scale matrix and improves the learning speed of the algorithm. Support vectors are selected adaptively in the iteration to maintain the sparseness. Experimental results show that the learning speed of CISVR is improved greatly compared with LSSVR for the similar training accuracy. At the same time the number of the support vectors obtained by the presented algorithm is less than that obtained by LSSVR greatly

Effects of Strain Rate and Temperature on Physical Mechanical Properties and Energy Dissipation Features of Granite

Dynamic compression tests of granite after thermal shock were performed using the split Hopkinson pressure bar system, to determine the effects of strain rate and temperature on the dynamic mechanical parameters, energy dissipation features and failure modes of granite. The results indicate that the dynamic compressive strength increased exponentially with strain rate and decreased with increasing temperature. Temperature and incident energy can equivalently transform for the same dynamic compressive strength. Dynamic elastic modulus of granite decreased obviously with increasing temperature but did not have a clear correlation with strain rate. As the impact gas pressure increased, the stress-strain curves changed from Class II to Class I behavior, and the failure modes of specimens transformed from slightly split to completely pulverized. The critical temperature at which the stress-strain curves changed from Class II to Class I was determined to be 300 °C, when the impact gas pressure is 0.6 MPa. As the applied temperature increased, density, wave velocity and wave impedance all decreased, meanwhile, the degree of granite specimen crushing was aggravated. Under the same incident energy, as the temperature increased, the reflected energy increased notably and the absorbed energy increased slightly, but the transmitted energy decreased. For the same temperature, the reflected and absorbed energies increased linearly as the incident energy increased, whereas the transmitted energy increased logarithmically. The SEM images of the thermal crack distribution on the granite specimen surface at different temperatures can well explain the essence of mechanical parameters deterioration of granite after thermal shock. This work can provide guidance for impact crushing design of high temperature rocks during excavations

Few-Shot Learning for Small Impurities in Tobacco Stems With Improved YOLOv7

With the increase of public concern about health and smoking, the authorities have gradually tightened the control of tar content in cigarettes, making reconstituted tobacco a growing concern for tobacco companies. Tobacco stems are used as the main raw material for reconstituted tobacco, but they contain a large number of small broken impurities mainly from cigarette butts, which are difficult to remove efficiently by air selection and manual methods. Detection schemes for cigarette butt impurities based on computer vision and deep learning are still difficult. The scarcity of images containing foreign impurities in cigarette butts and the small size of impurities limit the efficient application of deep learning algorithms. In view of the small impurities’ characteristics, this paper optimizes the model structure of the YOLOv7 algorithm, and only retains the two detection head structures with high feature resolution, which reduces the model parameters by 29.68%. Using online data augmentation and transfer learning, the difficulty of small sample datasets is overcome. After the CutMix, Mosaic, Affine transformation, Copy-paste data augmentation in this paper, the model precision is increased by 6.95%, and the recall rate is increased by 10.51%. Detection FPS has been increased from 99 FPS to 111 FPS. Precision and recall rate reached 97.21% and 92.11%. Compared with YOLOv4_csp, the precision is in-creased by 11.58%, and the recall rate is increased by 0.48%. It shows that the improved YOLOv7xs model has the potential for wide application in small target recognition. At the same time, it has shown the potential to avoid the harm of toxic substances produced by cigarette impurities in the combustion process and promotes the application of computer vision and deep learning in industrial production

Effects of Strain Rate and Temperature on Physical Mechanical Properties and Energy Dissipation Features of Granite

Dynamic compression tests of granite after thermal shock were performed using the split Hopkinson pressure bar system, to determine the effects of strain rate and temperature on the dynamic mechanical parameters, energy dissipation features and failure modes of granite. The results indicate that the dynamic compressive strength increased exponentially with strain rate and decreased with increasing temperature. Temperature and incident energy can equivalently transform for the same dynamic compressive strength. Dynamic elastic modulus of granite decreased obviously with increasing temperature but did not have a clear correlation with strain rate. As the impact gas pressure increased, the stress-strain curves changed from Class II to Class I behavior, and the failure modes of specimens transformed from slightly split to completely pulverized. The critical temperature at which the stress-strain curves changed from Class II to Class I was determined to be 300 °C, when the impact gas pressure is 0.6 MPa. As the applied temperature increased, density, wave velocity and wave impedance all decreased, meanwhile, the degree of granite specimen crushing was aggravated. Under the same incident energy, as the temperature increased, the reflected energy increased notably and the absorbed energy increased slightly, but the transmitted energy decreased. For the same temperature, the reflected and absorbed energies increased linearly as the incident energy increased, whereas the transmitted energy increased logarithmically. The SEM images of the thermal crack distribution on the granite specimen surface at different temperatures can well explain the essence of mechanical parameters deterioration of granite after thermal shock. This work can provide guidance for impact crushing design of high temperature rocks during excavations