A Study of Wolf Pack Algorithm for Test Suite Reduction

Modern smart meter programs are iterating at an ever-increasing rate, placing higher demands on the software testing of smart meters. How to reduce the cost of software testing has become a focus of current research. The reduction of test overhead is the most intuitive way to reduce the cost of software testing. Test suite reduction is one of the necessary means to reduce test overhead. This paper proposes a smart meter test suite reduction technique based on Wolf Pack Algorithm. First, the algorithm uses the binary optimization set coverage problem to represent the test suite reduction of the smart meter program; then, the Wolf Pack Algorithm is improved by converting the positions of individual wolves into a 0/1 matrix; finally, the optimal test case subset is obtained by iteration. By simulating different smart meter programs and different size test suites, the experimental result shows that the Wolf Pack Algorithm achieves better results compared to similar algorithms in terms of the percentage of obtaining both the optimal solution and the optimal subset of test overhead

Solving a Class of Singular Fifth-Order Boundary Value Problems Using Reproducing Kernel Hilbert Space Method

We use the reproducing kernel Hilbert space method to solve the fifth-order boundary value problems. The exact solution to the fifth-order boundary value problems is obtained in reproducing kernel space. The approximate solution is given by using an iterative method and the finite section method. The present method reveals to be more effective and convenient compared with the other methods

Prevalence of sexual dysfunction and its association with psychological symptoms in drug-naive major depressive disorder patients in West China

BackgroundSexual dysfunction is commonly observed in individuals with Major Depressive Disorder (MDD), along with various psychological symptoms such as anxiety, somatic complaints, interpersonal sensitivity, and obsessive-compulsive tendencies. However, there is a research gap in understanding the impact of these psychological symptoms on sexual functioning in MDD. Furthermore, there is limited data on the incidence of sexual dysfunction among drug-naive MDD patients in West China. This study aims to determine the prevalence of sexual dysfunction in this patient population and explore its association with other psychological indicators.MethodsWe conducted a retrospective analysis of patient data from October 2020 to September 2022 using propensity score matching. A focused group of 165 males and 490 females was selected from a total of 1941 MDD patients. This allowed for a comparative analysis of demographic data, as well as scores from the Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), and Symptom Checklist-90 (SCL-90), the Arizona Sexual Experience Scale (ASEX).ResultsOur findings reveal that 46.2% of drug-naive MDD patients experienced sexual dysfunction. Notably, there was a higher prevalence of sexual dysfunction among female patients (50.3%) compared to males (37.5%). MDD patients without sexual dysfunction consistently exhibited higher SDS scores than those with sexual dysfunction (p < 0.01), There were no statistically significant differences between male and female MDD patients with or without concomitant sexual dysfunction in terms of Somatic complaints, Obsessive-compulsive, Interpersonal sensitivity, Anxiety, Phobic anxiety, Paranoid ideation, Psychoticism and Diet/sleep difficulties (p > 0.05). In addition, male MDD patients with sexual dysfunction showed a emerging trend towards elevated Hostility scores on the SCL-90 (p = 0.058), male MDD patients with sexual dysfunction showed an increasing trend in hostility scores on the SCL-90, whereas female MDD patients with sexual dysfunction did not show such a trend.ConclusionThe study highlights a significant gender difference in the prevalence of sexual dysfunction among MDD patients, with females being more susceptible than males. There is a positive correlation between the severity of depression and sexual dysfunction in both genders. Interestingly, male MDD patients demonstrated a potential protective effect of hostility against sexual dysfunction, which was not observed in female patients

The Solution of a Class of Third-Order Boundary Value Problems by the Reproducing Kernel Method

This paper expands the application of reproducing kernel method to a class of third-order boundary value problems with mixed nonlinear boundary conditions. The analytical solution is represented in the form of series in the reproducing kernel space. The n-term approximation is obtained and is proved to converge to the analytical solution. The numerical examples are given to demonstrate the computation efficiency of the presented method. Results obtained by the method indicate that the method is simple and effective

The Solution of a Class of Third-Order Boundary Value Problems by the Reproducing Kernel Method

This paper expands the application of reproducing kernel method to a class of third-order boundary value problems with mixed nonlinear boundary conditions. The analytical solution is represented in the form of series in the reproducing kernel space. The n-term approximation is obtained and is proved to converge to the analytical solution. The numerical examples are given to demonstrate the computation efficiency of the presented method. Results obtained by the method indicate that the method is simple and effective

Using an Effective Numerical Method for Solving a Class of Lane-Emden Equations

We use the reproducing kernel method to solve the well-known classes of Lane-Emden-type equations. These classes of equations have the form of Lane-Emden problem. Comparing the results of the reproducing kernel method with the analytical solutions by means of some typical examples, we can affirm that the reproducing kernel method is an efficient and accurate method

The Solution of a Class of Singularly Perturbed Two-Point Boundary Value Problems by the Iterative Reproducing Kernel Method

In (Wang et al., 2011), we give an iterative reproducing kernel method (IRKM). The main contribution of this paper is to use an IRKM (Wang et al., 2011), in singular perturbation problems with boundary layers. Two numerical examples are studied to demonstrate the accuracy of the present method. Results obtained by the method indicate that the method is simple and effective

Research on Intelligent Analysis of Illegal Food Safety Behavior Based on Deep Learning Algorithm

Food safety has been a major concern in recent years as a result of numerous food safety events in many nations. This could increase the health risks associated with eating low-quality food, lowering customer confidence in food safety. It is critical to overcome this challenge and gain consumer trust in order to improve food quality and safety. To address this issue, we suggested an intelligent deep learning method for identifying which foods are potentially harmful to human health based on chemical and additive qualities, which could have a significant impact on consumer health. The findings of our survey show that deep learning surpasses other methods such as manual feature extractors, as well as the promising findings of categorization of hazardous food, further research efforts to apply deep learning to the field of food will be made in the future

Three-Dimensional Structure Analysis and Droplet Spectrum Characteristics of Southwest Vortex Precipitation System Based on GPM-DPR

This study is the first in the region to use Global Precipitation Mission Dual-Frequency Precipitation Radar (GPM-DPR) and Fengyun-2G (FY-2G) observations to qualitatively and quantitatively study the Southwest Vortex evolution characteristics during the flood season from 2019 to 2021. Furthermore, vertical characteristics of the two main precipitation types in the Southwest Vortex, stratiform and convective, were statistically analyzed at different life stages, including horizontal and vertical distribution of precipitation particles, droplet spectrum characteristics, and vertically layered precipitation contribution. The results showed that: (1) The typical convective precipitation (CP) in the developing and mature stages has strong reflectivity distribution centers in the upper and lower layers, showing characteristics related to terrain. Additionally, the high-level hydrometeor particles are mainly solid precipitation particles, and particles in the lower layers collide and coalesce in the violent vertical motion of the airflow. (2) For the three stages of CP, the reflectivity below melting layer (ML) first showed a rapid weakening trend toward the surface and then remained unchanged, significantly changing its vertical structure. The main rainfall type of the Southwest Vortex system was stratiform precipitation (SP) in the three stages. (3) In the two types of cloud precipitation, the developing stage is generally composed of large and sparse precipitation particles, the mature stage of large and dense precipitation particles, and the dissipating stage of small and sparse precipitation particles. The findings of this study reveal the three-dimensional refined structure and vertical variation characteristics of different life stages of the Southwest Vortex precipitation cloud system and provide important tools and references for improving the accuracy of numerical models and the forecast level of short-term heavy precipitation under complex terrain

Subjective and objective cognitive functioning in untreated late-life depression: An exploration centered on comorbid generalized anxiety disorder

Background: Late-Life Depression (LLD) is a prevalent mental health disorder that is often accompanied by cognitive impairments. The objective of this study is to investigate the influence of coexisting Generalized Anxiety Disorder (GAD) on both subjective and objective cognitive abilities in untreated LLD individuals. Methods: A total of 77 participants aged 60 years and above were recruited for this study, comprising 31 individuals with Major Depressive Disorder (LLD group), 46 with MDD and coexisting Generalized Anxiety Disorder (LLDA group), and 54 healthy controls (HC). Prior to the study, all patients had abstained from psychotropic medication for a minimum of two weeks. Comprehensive neuropsychological assessments were administered to all participants. Results: The LLDA group exhibited substantial disparities in memory, attention, processing speed,executive function,overall cognitive functioning, and subjective cognitive functioning when compared to the HC group. The LLD group displayed deficits in memory, SCWT-W in attention, SCWT-C in processing speed,overall cognitive functioning, and subjective cognitive functioning in comparison to the healthy controls. Although the LLD group achieved lower average scores in executive function, TMTA in processing speed, and DSST in attention than the HC group, no significant distinctions were identified between these groups in these domains. Linear regression analysis unveiled that anxiety symptoms had a significant impact on subjective cognitive deficits among MDD patients, but exhibited a milder influence on objective cognitive performance. After adjusting for the severity of depression, anxiety symptoms were found to affect TMTA in processing speed and subjective cognitive functioning in LLD patients. Conclusion: Late-Life Depression (LLD) exhibits pervasive cognitive impairments, particularly in individuals with generalized anxiety disorder, presenting a crucial target for future therapeutic interventions. Among elderly individuals with depression, anxiety symptoms significantly impact subjective cognitive functioning, suggesting its potential utility in distinguishing between depression-associated cognitive decline and pre-dementia conditions