An Improved Coupled Level Set and Continuous Moment-of-Fluid Method for Simulating Multiphase Flows with Phase Change

An improved algorithm for computing multiphase flows is presented in which the multimaterial Moment-of-Fluid(MOF)algorithm for multiphase flows,initially described by Li et al.(2015),is enhanced addressing existing MOF difficulties in computing solutions to problems in which surface tension forces are crucial for understanding salient flow mechanisms.The Continuous MOF(CMOF)method is motivated in this article.The CMOF reconstruction method inherently removes the"checkerboard instability"that persists when using the MOF method on surface tension driven multiphase(multimaterial)flows.The CMOF reconstruction algorithm is accelerated by coupling the CMOF method to the level set method and coupling the CMOF method to a decision tree machine learning(ML)algorithm.Multiphase flow examples are shown in the two-dimensional(2D),three-dimensional(3D)axisymmetric"RZ",and 3D coordinate systems.Examples include two material and three material multiphase flows:bubble formation,the impingement of a liquid jet on a gas bubble in a cryogenic fuel tank,freezing,and liquid lens dynamics.

Edge enhanced depth perception with binocular meta-lens

The increasing popularity of the metaverse has led to a growing interest and market size in spatial computing from both academia and industry.Developing portable and accurate imaging and depth sensing systems is crucial for advancing next-generation virtual reality devices.This work demonstrates an intelligent,lightweight,and compact edge-enhanced depth perception system that utilizes a binocular meta-lens for spatial computing.The miniaturized system comprises a binocular meta-lens,a 532 nm filter,and a CMOS sensor.For disparity computation,we propose a stereo-matching neural network with a novel H-Module.The H-Module incorporates an attention mechanism into the Siamese network.The symmetric architecture,with cross-pixel interaction and cross-view interaction,enables a more comprehensive analysis of contextual information in stereo images.Based on spatial intensity discontinuity,the edge enhancement eliminates illposed regions in the image where ambiguous depth predictions may occur due to a lack of texture.With the assistance of deep learning,our edge-enhanced system provides prompt responses in less than 0.15 seconds.This edge-enhanced depth perception meta-lens imaging system will significantly contribute to accurate 3D scene modeling,machine vision,autonomous driving,and robotics development.

The Development of the “Monitoring Application for Inappropriate Expressions in Nursing Records”for PsyNACS©

Lengthening periods of hospitalization, increasing numbers of patients with age-related complications, and a shortage of nursing staff have been of great concern in medical psychiatry in Japan. Under these circumstances, countries such as Japan that face a super-aging society and a decline in the working-age population, have been recommended for use of advanced information and communications technology (ICT) to improve the efficiency of medical treatment and care. This study aims to develop the “Monitoring Application for Inappropriate Expressions in Nursing Records” for using PsyNACS©, which will enable psychiatric nursing plans to harness the advantages of ICT. The functions considered necessary are as follows: 1) identification of users who enter information;2) a necessary database for lists of inappropriate expressions;3) development of a matching function to recommend proper writing input and a warning function;and 4) a management function for an inappropriate expression list database. A demonstration experiment for developing the application in this study was conducted at a specialized psychiatric hospital. To introduce them to the application, nurses and nurse managers were informed about the system developed in this study, and a survey regarding their opinions on the functions of the application was conducted with ten nurse managers. The results were evaluated in terms of usefulness for nursing care, documentation, and the education of nurses from an ethical perspective. This study suggests that matching their input with an inappropriate expression database will allow nurses to record more appropriate expressions. From an ethical perspective, the ability to use appropriate expressions makes records more likely to withstand disclosure requests from patients and their families.

Advancing Early Detection of Colorectal Adenomatous Polyps via Genetic Data Analysis: A Hybrid Machine Learning Approach

In this study, a hybrid machine learning (HML)-based approach, incorporating Genetic data analysis (GDA), is proposed to accurately identify the presence of adenomatous colorectal polyps (ACRP) which is a crucial early detector of colorectal cancer (CRC). The present study develops a classification ensemble model based on tuned hyperparameters. Surpassing accuracy percentages of early detection approaches used in previous studies, the current method exhibits exceptional performance in identifying ACRP and diagnosing CRC, overcoming limitations of CRC traditional methods that are based on error-prone manual examination. Particularly, the method demonstrates the following CRP identification accuracy data: 97.7 ± 1.1, precision: 94.3 ± 5, recall: 96.0 ± 3, F1-score: 95.7 ± 4, specificity: 97.3 ± 1.2, average AUC: 0.97.3 ± 0.02, and average p-value: 0.0425 ± 0.07. The findings underscore the potential of this method for early detection of ACRP as well as clinical use in the development of CRC treatment planning strategies. The advantages of this approach are highly expected to contribute to the prevention and reduction of CRC mortality.

Relationships of Handgrip Strength with Menstruation-Related Symptoms in Female University Students in Japan

Introduction: Some somatic and psychological disorders have been associated with handgrip strength, which is an easy, inexpensive and noninvasive method for assessment of muscle strength. We conducted a cross-sectional study to clarify the relationship of handgrip strength and menstruation-related symptoms. Material and Methods: Handgrip strength was measured and a self-administered questionnaire was performed in female university students in Japan. Results: Handgrip strength did not significantly differ among the menstrual phases. The mean handgrip strength level (n = 260) was 26.0 ± 3.9 kg. We divided the subjects into three groups according to the handgrip strength level. Handgrip strength was associated with degrees of depression and anxiety during menstruation. Conclusion: This can be used as fundamental data in further clarifying the relationship between muscle strength and menstruation-related symptoms.

Japanese University Teachers’ Depression Status and Its Influence Factors

Risk factors of the depression are the occupational stress. The mental health condition of university teachers who participate in the socialization of diverse students is an important issue;however, there are few studies on depression among university teachers. The purpose of this study is to clarify Japanese university teachers’ depression status assessed by the Patient Health Questionnaire-9 and its influence factors: Japanese university teachers’ depression status depression status, personal background, job situation, social support, and stress coping behavior. The self-administered questionnaire survey was mailed to 924 university teachers in Japan, with a survey return rate of 43.8% (N = 405). A total of 342 surveys were completed and valid. The Patient Health Questionnaire 9 (PHQ-9), Multidimensional Scale of Perceived Social Support (MSPSS), the Japanese version of the Brief Coping Orientation to Problems Experienced (COPE) and the Work Situation Questionnaire (WSQ) were analyzed to clarify the depression status and its influence factors. Multivariate logistic regression analysis was used to examine factors related to the major depression. The subjects included 274 men (80.1%) and 68 women (19.9%), 105 professors (30.7%), 52 associate professors (15.2%), 53 lecturers (15.5%) and 132 assistants (38.6%). The subjects’ mean of age and teaching experiences were 44.1 ± 9.7 years, 15.6 ± 10.1 years. The mean PHQ score was 3.9 ± 4.1, and 307 subjects (89.8%) were 0 - 9 points and 35 subjects (10.2%) were over 10 points (10 points or over). For women [OR = 7.009, 95% CI 2.387 - 20.584;p < 0.001], religion [OR = 1.813, 95% CI 1.175 - 2.798;p = 0.007], self-blame [OR = 1.808, 95% CI 1.280 - 2.556;p = 0.001], substance use [OR = 1.453, 95% CI 1.103 - 1.913;p = 0.008] were risk factors of depression status. On the other hand, high job satisfaction level [OR = 0.945, 95% CI 0.921 - 0.969;p < 0.001], higher age [OR = 0.927, 95% CI 0.873 - 0.984;p =0.014], use of instrumental support [OR = 0.622, 95% CI 0.399 - 0.969;p = 0.036], and use of social support [OR = 0.588, 95% CI 0.376 - 0.921;p = 0.020] were factors that reduced the risk of depression. These findings suggested that in order to improve the depression status of university teachers, and to develop mental health measures for university faculty members based on such risk factors are necessary in the future.

Associations between Sensitivity to Cold, Menstruation-Related Symptoms and Handgrip Strength in Female University Students in Japan

Sensitivity to cold, which is a popular symptom in Japanese women, is associated with various symptoms such as shoulder stiffness and general fatigue. However, an association of sensitivity to cold with muscle strength has not been reported. The aim of the study was to clarify the associations of sensitivity to cold with handgrip strength and with menstruation-related symptoms in female university students in Japan. We recruited 278 female university students in Japan. Sensitivity to cold and menstruation-related symptoms including physical and psychological symptoms were assessed by using a self-administered questionnaire that we designed. Handgrip strength was measured by using a handgrip strength dynamometer. We received responses from 269 students. The prevalence rate of sensitivity to cold in the subjects was 54.3%. The students who had sensitivity to cold had a lower handgrip strength level (25.5 ± 3.8 kg) than did the students who did not have sensitivity to cold (26.7 ± 3.9 kg) (p = 0.017). Sensitivity to cold was associated with low body mass index. In addition, the students who had sensitivity to cold tended to have low back pain and constipation during menstruation. In conclusion, sensitivity to cold is an important symptom associated with muscle strength as well as menstruation-related symptoms for young women.

Relationship between Lifestyle, Quality of Sleep, and Daytime Drowsiness of Nursing Students of University A

The harmful effects of technological devices, including smart phones have been increasingly suspected among university students;bedtimes have become increasingly later at night, and leisure activities often extend through the night. Likewise, availability and need of increasing part-time job hours have been considered. The purpose of this research was to determine the relationship among lifestyles, quality of sleep, and daytime drowsiness of nursing students of University A. The research was conducted in June 2015, when student life rhythms were considered stable after two months of lectures. Responses with missing values or with inappropriate answers were excluded. Of the data collected from 96 respondents, only 71 were acceptable. The survey focused on lifestyle, daytime sleepiness (using ESS: Epworth Sleepiness Scale) and quality of subjective sleep (using the PSQI: Pittsburgh Sleep Quality Index). Approval was obtained from the Research Ethics Committee of Shikoku University. While in this study, more than half (63.4%) of the students had poor quality of sleep, however, there was no relationship between their quality of sleep and daytime drowsiness, or between their lifestyles and the quality of sleep. These findings suggest that while university students’ use of technological devices is suspected to influence on sleep deprivation and consequent daytime drowsiness, the findings did not provide the evidence.

Spectra-assisted laser focusing in quantitative analysis of laser-induced breakdown spectroscopy for copper alloys

Laser-induced breakdown spectroscopy(LIBS)is a capable technique for elementary analysis,while LIBS quantitation is still under development.In quantitation,precise laser focusing plays an important role because it ensures the distance between the laser and samples.In the present work,we employed spectral intensity as a direct way to assist laser focusing in LIBS quantitation for copper alloys.It is found that both the air emission and the copper line could be used to determine the position of the sample surface by referencing the intensity maximum.Nevertheless,the fine quantitation was only realized at the position where the air emission(e.g.O(I)777.4 nm)reached intensity maximum,and also in this way,a repeatable quantitation was successfully achieved even after 120 days.The results suggested that the LIBS quantitation was highly dependent on the focusing position of the laser,and spectra-assisted focusing could be a simple way to find the identical condition for different samples’detection.In the future,this method might be applicable in field measurements for LIBS analysis of solids.

Analysis of Emotions Using Multimodal Data: A Case Study

In this case study, we hypothesized that sympathetic nerve activity would be higher during conversation with PALRO robot, and that conversation would result in an increase in cerebral blood flow near the Broca’s area. The facial expressions of a human subject were recorded, and cerebral blood flow and heart rate variability were measured during interactions with the humanoid robot. These multimodal data were time-synchronized to quantitatively verify the change from the resting baseline by testing facial expression analysis, cerebral blood flow, and heart rate variability. In conclusion, this subject indicated that sympathetic nervous activity was dominant, suggesting that the subject may have enjoyed and been excited while talking to the robot (normalized High Frequency < normalized Low Frequency: 0.22 ± 0.16 < 0.78 ± 0.16). Cerebral blood flow values were higher during conversation and in the resting state after the experiment than in the resting state before the experiment. Talking increased cerebral blood flow in the frontal region. As the subject was left-handed, it was confirmed that the right side of the brain, where the Broca’s area is located, was particularly activated (Left < right: 0.15 ± 0.21 < 1.25 ± 0.17). In the sections where a “happy” facial emotion was recognized, the examiner-judged “happy” faces and the MTCNN “happy” results were also generally consistent.

Characteristics of Sleep and Autonomic Activity in Active Older Adults Based on Metabolic Age: A Comparative Case Study

Background: The balance of autonomic nervous system activity and its relationship with body composition, sleep quality, and activities of daily living among older people is still unclear. Purpose: This comparative case study examined the characteristics of body composition, sleep quality, and autonomic nerve activity in active older adults with a younger body age-calculated from age trends in body composition and basal metabolic rate. Methods: We selected two cases with a metabolic age younger than their actual age. They had good sleep quality, no sarcopenia, strong muscle and grip strength, and balanced autonomic nervous system activity. They were compared with two other age- and gender-matched cases, who had poor sleep quality, unbalanced autonomic nervous system activity, and had a physical age closer to their actual age. Results: Older adults with more muscle mass and higher basal metabolism were younger than their actual age, had a better sleep status, and had a good balance of autonomic nervous activity during exercise stimulation. They also had lower percentages of body and visceral fat and higher percentages of body water. Conclusion: Two cases had a metabolic age younger than their actual age were found to be much younger than their actual age. However, the older adults with normal muscle mass and basal metabolic rate had poor sleep status and no sympathetic hyperactivity during exercise simulation.

原代培养猪冠状动脉平滑肌的电压依赖和钙激活钾通道(英文)

目的 :研究原代培养的猪冠状动脉平滑肌电压依赖性和钙激活外向钾通道的特性。方法 :离子通道电流采用膜片钳技术进行记录。结果 :在内面向外式膜片构型 ,当膜内外K+ 浓度梯度类似生理状态时 ,该通道单位电导值约为 10 0pS ,而当膜内外K+ 浓度为对称的 140mM浓度时 ,该通道单位电导值约为 2 70pS。其平均电流显示该通道具时间和电压依赖性激活特性 ,而无任何时间和电压依赖性失活特性。另外 ,通道的开放时间常数和开放概率随除极及胞内Ca2 + 的增加而显著增加。通过用EGTA降低胞浆内Ca2 + 浓度 ,可使外向电流抑制。动力学分析显示通道激活时存在一种开放状态和至少两种关闭状态。四乙胺 (TEA)可在胞外侧阻断该电流 ,但高达 15mM的 4-氨基吡啶 (4-AP)在胞内外都对通道无影响。在全细胞构型 ,对细胞膜进行除极可引出宏观外向电流。随着细胞的除极 ,该电流的激活时间常数逐渐缩短 ,并显示快速激活动力学特性。结论 :在原代培养的猪冠状动脉平滑肌上存在有电压依赖和Ca2 + 激活的K+ 选择性离子通道。该类通道具有非常高的单位电导值 ,除极时快速开放 ,对胞内Ca2 + 高度敏感 。

一种基于度量距离学习的图像检索方法

CBIR系统由于受图像低层特征的限制,制约了它的检索效果。机器学习和统计方法是一种有效的提高检索性能的方法,但通常需要大量的训练样本才能达到满意的检索精度。提出一种理想的距离度量函数,在对图像进行简单分类并提供少量训练样本的基础上,通过类的距离度量矩阵M的学习来考虑分量之间的相关性。这个度量导入二次最佳化问题的解,将训练样本类结构的倾斜最小化。试验结果表明,该方法能在学习样本极少的情况下提高检索的性能。

减少二氧化碳对LIBS检测飞灰中未燃碳含量影响的研究

通常热力发电厂将飞灰中未燃碳的含量作为评价锅炉燃烧效率的重要指标,通过测量飞灰中未燃碳的含量来评价煤粉燃烧的充分程度,进而实现优化燃烧、提高机组效率。基于激光诱导击穿光谱技术(LIBS)无接触、快速响应、高灵敏度、可以在线测量等特点,备用来测量飞灰中未燃碳的含量。由于烟气中CO_2气体的存在,碳谱线强度会随CO_2浓度的变化而改变。为了减少CO_2气体对飞灰未燃碳测量结果的影响,提出并设计了具有二级旋风分离器的LIBS测量飞灰未燃碳含量实验系统,飞灰从给粉机流出后通过二级旋风分离器进入测量腔体,脉冲激光经过透镜作用于飞灰样品进而产生等离子体。LIBS系统采用双中心波长光谱仪,可测得飞灰中C,Si,Mg,Fe,Ca和Al等主要元素谱线,同时高分辨率通道可分辨出相邻C和Fe的元素谱线,可以在获得充分的飞灰光谱信息的同时保证了测量的精度。实验结果表明该系统可有效分离和收集飞灰颗粒,减少CO_2气体对测量结果的干扰,为LIBS技术的工程应用提供了更准确的依据。

Problems associated with glucose toxicity:Role of hyperglycemia-induced oxidative stress

Glucose homeostasis deficiency leads to a chronic increase in blood glucose concentration. In contrast to physiological glucose concentration, chronic super-physiological glucose concentration negatively affects a large number of organs and tissues. Glucose toxicity means a decrease in insulin secretion and an increase in insulin resistance due to chronic hyperglycemia. It is now generally accepted that glucose toxicity is involved in the worsening of diabetes by affecting the secretion of B-cells. Several mechanisms have been proposed to explain the adverse effects of hyperglycemia. It was found that persistent hyperglycemia caused the functional decline of neutrophils. Infection is thus the main problem resulting from glucose toxicity in the acute phase. In other words, continued hyperglycemia is a life-threatening risk factor, not only in the chronic but also the acute phase, and it becomes a risk factor for infection, particularly in the perioperative period.

Role of regulatory T cell in the pathogenesis of inflammatorybowel disease

Regulatory T(Treg) cells play key roles in various immune responses. For example, Treg cells contribute to the complex pathogenesis of inflammatory bowel disease(IBD), which includes Crohn's disease and ulcerative colitis during onset or development of that disease. Many animal models of IBD have been used to investigate factors such as pathogenic cytokines, pathogenic bacteria, and T-cell functions, including those of Treg cells. In addition, analyses of patients with IBD facilitate our understanding of the precise mechanism of IBD. This review article focuses on the role of Treg cells and outlines the pathogenesis and therapeutic strategies of IBD based on previous reports.

Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion

AIM: To investigate and compare the efficacy of two machine-learning technologies with deep-learning(DL) and support vector machine(SVM) for the detection of branch retinal vein occlusion(BRVO) using ultrawide-field fundus images. METHODS: This study included 237 images from 236 patients with BRVO with a mean±standard deviation of age 66.3±10.6 y and 229 images from 176 non-BRVO healthy subjects with a mean age of 64.9±9.4 y. Training was conducted using a deep convolutional neural network using ultrawide-field fundus images to construct the DL model. The sensitivity, specificity, positive predictive value(PPV), negative predictive value(NPV) and area under the curve(AUC) were calculated to compare the diagnostic abilities of the DL and SVM models. RESULTS: For the DL model, the sensitivity, specificity, PPV, NPV and AUC for diagnosing BRVO was 94.0%(95%CI: 93.8%-98.8%), 97.0%(95%CI: 89.7%-96.4%), 96.5%(95%CI: 94.3%-98.7%), 93.2%(95%CI: 90.5%-96.0%) and 0.976(95%CI: 0.960-0.993), respectively. In contrast, for the SVM model, these values were 80.5%(95%CI: 77.8%-87.9%), 84.3%(95%CI: 75.8%-86.1%), 83.5%(95%CI: 78.4%-88.6%), 75.2%(95%CI: 72.1%-78.3%) and 0.857(95%CI: 0.811-0.903), respectively. The DL model outperformed the SVM model in all the aforementioned parameters(P<0.001). CONCLUSION: These results indicate that the combination of the DL model and ultrawide-field fundus ophthalmoscopy may distinguish between healthy and BRVO eyes with a high level of accuracy. The proposed combination may be used for automatically diagnosing BRVO in patients residing in remote areas lacking access to an ophthalmic medical center.

A review on photoelectrochemical cathodic protection semiconductor thin films for metals

Photoelectrochemical(PEC) cathodic protection is considered as an environment friendly method for metals anticorrosion. In this technology, a n-type semiconductor photoanode provides the photogenerated electrons for metal to achieve cathodic protection. Comparing with traditional PEC photoanode for water splitting, it requires the photoanode providing a suitable cathodic potential for the metal, instead of pursuit ultimate photon to electric conversion efficiency, thus it is a more possible PEC technology for engineering application. To date, great efforts have been devoted to developing novel n-type semiconductors and advanced modification method to improve the performance on PEC cathodic protection metals. Herein, recent progresses in this field are summarized. We highlight the fabrication process of PEC cathodic protection thin film, various nanostructure controlling, doping, compositing methods and their operation mechanism. Finally, the current challenges and future potential works on improving the PEC cathodic protection performance are discussed.

Multi-Strategy Dynamic Spectrum Access in Cognitive Radio Networks: Modeling, Analysis and Optimization

Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA(MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain(CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.

Adaptive Resources Allocation Algorithm Based on Modified PSO for Cognitive Radio System

Radio spectrum has become a rare resource due to the rapid development of wireless communication technique. Cognitive radio is one of important techniques to deal with this radio spectrum problem. But the resource allocation in cognitive radio also has its own issues, such as the flexibility of the allocation algorithm, the performance of resource allocation, and so on. In order to increase the flexibility of the allocation algorithm for cognitive radio, more and more researches are focusing on the evolutionary algorithms, such as genetic algorithm(GA), particle swarm optimization(PSO). Evolutionary algorithm can greatly improve the flexibility of the allocation algorithm for cognitive radio system in different communication scenarios, but the performances are relatively lower than the original mathematical methods. So in this paper, we proposed an adaptive resource allocation algorithm based on modified PSO for cognitive radio system to solve these problems. Modified particle swarm optimization(Modified PSO) has both genetic algorithm(GA) and particle swarm optimization(PSO)’s updating processes which makes this modified PSO overcame PSO’s own disadvantages and keep advantages. Simulation results showed our proposed algorithm has enough flexibility to meet cognitive radio systems’ requirements, and also has a better performance than original PSO.