Value of gastroscopy combined with serum pepsinogen in the diagnosis of high risk Hp related gastric cancer

Objective:To explore the value of Helicobacter pylori antibody (Hp-IgG) and serum pepsinogen (PG) combined with gastroscopy for screening early gastric cancer and precancerous lesions in high-risk groups, so as to provide references for early clinical prevention and diagnosis.Methods: A retrospective analysis of our hospital from December 2014 to December 2017 were elderly patients with gastric cancer 304 cases, selected admitted 122 cases of elderly patients with gastric precancerous lesion (divided into superficial gastritis group, 70 cases of chronic atrophic gastritis group 52 cases) and 156 cases to the hospital in healthy volunteers as the control group. The status and the positive rate of Helicobacter pylori 13C urea breath test and compared two groups of patients with infection;using enzyme-linked immunosorbent assay of serum pepsinogen I (PG I), II (PG II) and pepsin Hp-IgG quantitative and qualitative diagnosis of individual and combined diagnostic efficiency and the comparison of three kinds of index.Results: The four groups were compared, the serum PG level of I from high to low were superficial gastritis group, normal control group, atrophic gastritis group and gastric cancer group, the differences were statistically significant;serum PG II levels from high to low in gastric cancer group and superficial gastritis group. Atrophic gastritis group, normal control group, the differences were statistically significant. Compared with the three groups, the positive rate of Hp-IgG was 90.7% in the gastric cancer group, 45.6% in the superficial gastritis group, 52.5% in the atrophic gastritis group, and the gastric cancer group was higher than that in the precancerous lesion group, but there was no difference between the precancerous lesions group. In terms of diagnostic efficacy, the specificity and sensitivity of Helicobacter pylori combined with pepsinogen were higher than those of the single diagnosis. Conclusion: Hp-IgG and PG combined with gastroscopy in screening high-risk gastric cancer and its precancerous lesions are of high specificity, high sensitivity and can be popularized in clinic.

Oxide-aperture-dependent output characteristics of circularly symmetric VCSEL structure

The influence of oxidation aperture on the output characteristics of the circularly symmetric vertical-cavity-surface-emitting laser(VCSEL)structure is investigated.To do so,VCSELs with different oxide aperture sizes are simulated by the finite-difference time-domain(FDTD)method.The relationships among the field distribution of mode superposition,mode wavelength,output spectra,and far-field divergence with different oxide apertures are obtained.Further,VCSELs respectively with oxide aperture sizes of 2.7μm,4.4μm,5.9μm,7μm,8μm,9μm,and 18.7μm are fabricated and characterized.The maximum output power increases from 2.4 mW to 5.7 mW with oxide aperture increasing from 5.9μm to 9μm.Meanwhile,the wavelength tuning rate decreases from 0.93 nm/mA to 0.375 nm/mA when the oxide aperture increases from 2.7μm to 9μm.The thermal resistance decreases from 2.815℃/mW to 1.015℃/mW when the oxide aperture increases from 4.4μm to 18.7μm.It is demonstrated theoretically and experimentally that the wavelength spacing between adjacent modes increases with the augment of the injection current and the spacing becomes smaller with the oxide aperture increasing.Thus it can be reported that the aperture size can effectively reduce the mode overlaying but at the cost of the power decreasing and the wavelength tuning rate and thermal resistance increasing.

Emerging memristors and applications in reservoir computing

Recently, with the emergence of ChatGPT, the field of artificial intelligence has garnered widespread attention from various sectors of society. Reservoir Computing (RC) is a neuromorphic computing algorithm used to analyze time-series data. Unlike traditional artificial neural networks that require the weight values of all nodes in the trained network, RC only needs to train the readout layer. This makes the training process faster and more efficient, and it has been used in various applications, including speech recognition, image classification, and control systems. Its flexibility and efficiency make it a popular choice for processing large amounts of complex data. A recent research trend is to develop physical RC, which utilizes the nonlinear dynamic and short-term memory properties of physical systems (photonic modules, spintronic devices, memristors, etc.) to construct a fixed random neural network structure for processing input data to reduce computing time and energy. In this paper, we introduced the recent development of memristors and demonstrated the remarkable data processing capability of RC systems based on memristors. Not only do they possess excellent data processing ability comparable to digital RC systems, but they also have lower energy consumption and greater robustness. Finally, we discussed the development prospects and challenges faced by memristors-based RC systems.

Microstructure evolution of coke under CO2 and H2O atmospheres

The microstructure of coke has an important influence on its thermal properties.The solution loss reactions of coke in CO2 and H2O atmospheres were investigated by in situ observation.The results showed that the isotropic components had a more vigorous reaction than the anisotropic components,and the solution loss reaction of the fine-grained mosaic structure was faster than that of the coarse-grained mosaic structure under the CO2 and H2O atmospheres.The coarse-grained mosaic structure and the flowing structure had a relatively higher anti-erosion ability in the CO2 atmosphere than in the H2O atmosphere,and there was no distinct difference in the solution loss of the isotropic structure under the CO2 and H2O atmospheres.The electron probe microanalysis showed that the Al-Si-Fe compounds in the carbon matrix had positive influence on the solution loss reaction of the anisotropic structure.The iron compounds were able to destroy the pore walls of coke and accelerate the solution loss rate of coke.

Coking properties of thermal soluble constituents of coals by N-methyl-2-pyrrolidone solvent

Four types of coals, KL, XB, ZS and GD with different coal ranks, were dissolved with the organic solvent N-methyl-2- pyrrolidone at 350 ℃ and around 3.0 MPa pressure to obtain thermal soluble constituents （TSCs）. The yield, component and maceral group were investigated as well as their coking properties, including caking index and thermoplasticity. The results indicated that the yields of the four coals were of the following order： KL 〉 XB 〉 ZS 〉 GD. Based on the yield and the vitrinite content, coals were ranked from high to low. The ash contents of TSCs were significantly less than that of raw coals, and the TSCs contain more light components, leading to an increase in volatile matter. The patterns of Fourier transform infrared spectroscopy indicated that carbonyl was enriched in TSCs. Regarding the maceral group, TSCs were mainly composed of vitrinite which is the main reactive material and converts into binder phase in cokemaking process. Higher caking index values and fluidity were obtained in TSCs compared with the raw coals. The coking experiments with different amounts of TSCs addition were carried out. The results demonstrated that the proper TSCs addition could enhance the coke strength due to its high caking index and good fluidity.

A PROPORTIONAL 3-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL FOR SCREENING NEW PRODUCT PROJECTS

It is critically important for companies to screen new product projects before they are launched to the market. So far, many approaches have been developed for tackling the process of screening product innovations. Due to uncertain, vague and incomplete information as well as dynamically complex process regarding to new product development （NPD）, a fuzzy linguistic approach employed linguistic assessments and the fuzzy-set-based computation is reasonable for screening new products. However, such a fuzzy linguistic approach faces with various defects and limitations, such as loss of information, failing in considering the aspects related to human nature on uncertain subjective judgments etc. These defects and limitations lead to a dilemma, i.e., it＇s very difficult to screen new product projects reasonably and precisely. In this paper, we propose a notion of proportional 3-tuple to represent a linguistic assessment and related ignoring information, and a preference-preserving proportional 3-tuple transformation for the unification of linguistic assessments represented by proportional 3-tuples between two different linguistic term sets. On this basis, a proportional 3-tuple fuzzy linguistic representation model for screening new product projects is developed. It is shown that the proposed model is flexible to handle uncertain, vague and incomplete information related to screening new product projects. It not only allows evaluators to express their subjective judgments with different confidence levels, but is also able to deal with incomplete linguistic assessments. Ultimately, the proposed model also improves the precision and reasonability of the screening result.