Researches on a practical system for concentration detection of human exhaled CO₂gas

In clinics, especially in the emergency department, carbon dioxide (CO2) is considered as the sixth vital sign in evaluating a patient's medical status. However, its wide applications in developing countries are dissatisfactory due to their high cost compared to their economic growth. In order to develop a practical system for concentration detection of human exhaled CO2 gas for our own, we studied the detection principle based upon the non-dispersive infrared (NDIR) measuring technique and related Lambert-Beer's equation carefully, gave out our functional circuit design of the system, and provided the corresponding graphical user interface (GUI) for CO2 detection. Finally, the experiment shows that it may be a practical system, and will give benefits for the development of our medical care in the future.

散光双角绘图工具分析散光矫正型人工晶状体的使用

目的散光双角绘图工具分析我院散光型人工晶状体的使用效果。方法回顾性分析2019年4月—2022年2月本院收治的术前存在角膜散光并植入散光型人工晶状体的白内障患者的数据资料。术前采用Carl Zeiss IOLMaster 700测量角膜曲率,TECNIS Toric Calculator和Z CALC Online IOL Calculator计算器预测人工晶状体屈光度和术后残余散光。术后半个月使用TOPCON电脑验光仪验光。使用屈光手术杂志推荐的散光双角绘图工具分析数据,得到图表。结果共29例35眼,男10例11眼,女19例24眼,其中右眼18只,左眼17只。术前角膜散光右眼平均值(2.53D±0.9D),质心值(1.18D@85°±2.52D),左眼平均值(2.09D±0.5D),质心值(1.75D@89°±1.28D);术后半个月验光散光右眼平均值(0.72D±0.47D),质心值(0.37D@97°±0.08D),左眼平均值(0.74D±0.39D),质心值(0.18D@44°±0.84D);术后散光的预测误差右眼平均值(0.61D±0.50D),质心值(0.29D@103°±0.74D),左眼平均值(0.69D±0.47D),质心值(0.17D@28°±0.83D)。术后术眼的等效球镜值为(-0.31±0.46D)。术后,67%和78%的术眼的客观验光散光值分别≤0.75D和≤1.0D。结论散光双角绘图工具可以客观有效的分析白内障手术医师在植入散光型人工晶状体的手术效果。

Cross-diffusion induced Turing instability of Hopf bifurcating periodic solutions in the reaction-diffusion enzyme reaction model

Aiming at the spatial pattern phenomenon in biochemical reactions,an enzyme-reaction Sporns-Seelig model with cross-diffusion is chosen as study object.Applying the central manifold theory,normal form method,local Hopf bifurcation theorem and perturbation theory,we study Turing instability of the spatially homogeneous Hopf bifurcation periodic solutions.At last,the theoretical results are verified by numerical simulations.

A class of natural pinus koraiensis population system with time delay and diffusion term

In this paper,we consider the long-term sustainability of the northeast Korean pine.We propose a class of natural Korean pine population system with time delay and diffusion term.First,by analyzing the roots distribution of the characteristic equation,we study the stability of the model system with diffusion terms and prove the occurrence of Hopf bifurcation.Second,we introduce lactation time delay into a population model with a diffusion term,based on stability theory of ordinary differential equation,norm form methods and center manifold theorem,the stability of bifurcating periodic solutions and the relevant formula for the direction of Hopf bifurcation are given.Finally,some numerical simulations are given.

Image Encryption Application of Chaotic Sequences Incorporating Quantum Keys

This paper proposes an image encryption algorithm LQBPNN（logistic quantum and back propagation neural network）based on chaotic sequences incorporating quantum keys. Firstly, the improved one-dimensional logistic chaotic sequence is used as the basic key sequence. After the quantum key is introduced, the quantum key is incorporated into the chaotic sequence by nonlinear operation. Then the pixel confused process is completed by the neural network. Finally, two sets of different mixed secret key sequences are used to perform two rounds of diffusion encryption on the confusing image. The experimental results show that the randomness and uniformity of the key sequence are effectively enhanced. The algorithm has a secret key space greater than 2182. The adjacent pixel correlation of the encrypted image is close to 0, and the information entropy is close to 8. The ciphertext image can resist several common attacks such as typical attacks, statistical analysis attacks and differential attacks.

Multiple Nontrivial Solutions for Superlinear Double Phase Problems Via Morse Theory

The aim of this paper is the study of a double phase problems involving superlinear nonlinearities with a growth that need not satisfy the Ambrosetti-Rabinowitz condition.Using variational tools together with suitable truncation and minimax techniques with Morse theory,the authors prove the existence of one and three nontrivial weak solutions,respectively.

Reliability analysis of excavated slopes in undrained clay

A novel approach based on the upper bound theory is proposed to assess the stability of excavated slopes with spatially variable clay in undrained conditions.The proposed random limit analysis is a combination of the deterministic slope stability limit analysis together with random field theory and Monte Carlo simulation.A series of analyses is conducted to verify the potential application of the proposed method and to investigate the effects of the soil undrained shear strength gradient and the spatial correlation length on slope stability.Three groups of potential sliding surfaces are identified and the occurrence probability of each sort of failure mechanism is quantified for various slope ratios.The proposed method is found to be feasible for evaluating slope reliability.The obtained results are helpful in understanding the slope failure mechanism from a quantitative point of view.The paper could provide guidance for slope targeted local reinforcement.

Item Cold-Start Recommendation with Personalized Feature Selection

The problem of recommending new items to users(often referred to as item cold-start recommendation)remains a challenge due to the absence of users’past preferences for these items.Item features from side information are typically leveraged to tackle the problem.Existing methods formulate regression methods,taking item features as input and user ratings as output.These methods are confronted with the issue of overfitting when item features are high-dimensional,which greatly impedes the recommendation experience.Availing of high-dimensional item features,in this work,we opt for feature selection to solve the problem of recommending top-N new items.Existing feature selection methods find a common set of features for all users,which fails to differentiate users1 preferences over item features.To personalize feature selection,we propose to select item features discriminately for different users.We study the personalization of feature selection at the level of the user or user group.We fulfill the task by proposing two embedded feature selection models.The process of personalized feature selection filters out the dimensions that are irrelevant to recommendations or unappealing to users.Experimental results on real-life datasets with high-dimensional side information reveal that the proposed method is effective in singling out features that are crucial to top-N recommendation and hence improving performance.