Moderate Effects of Anxiety and Physical Activities on the Relationship Between Body Image and COVID-19 Fear

Improving psychological well-being has been a hot topic in counseling psychology research. However, since the COVID-19 pandemic, people’s lifestyle has been changed that caused series mental health problems. Using a sample of 576 participants from different universities. This study examined whether Covid-19 correlated with Body image a) whether anxiety moderated this relationship. b) whether physical activities moderated this relationship. c) how does different kind of body image avoidance being influenced. Pearson’s correlation test and linear regression analyses were conducted. The result indicated that COVID-19 fear has significantly positive relationship with body image. physical activities level has significantly increase the relationship between COVID-19 fear and body image avoidance-food restriction, body image avoidance-behavior, and body image avoidance-body image concerns. Anxiety has significantly positive moderate effects on the relationship between body image-food restriction and COVID-19 fear. The implication of present findings for college education, clinical psychoeducation was discussed based on the results

N=2\mathcal{N} = 2 Schur index and line operators

4d $\mathcal{N} = 2$ SCFTs and their invariants can be often enriched by non-local BPS operators. In this paper we study the flavored Schur index of several types of N = 2 SCFTs with and without line operators, using a series of new integration formula of elliptic functions and Eisenstein series. We demonstrate how to evaluate analytically the Schur index for a series of $A_2$ class-$\mathcal{S}$ theories and the $\mathcal{N} = 4$ SO(7) theory. For all $A_1$ class-$\mathcal{S}$ theories we obtain closed-form expressions for SU(2) Wilson line index, and 't Hooft line index in some simple cases. We also observe the relation between the line operator index with the characters of the associated chiral algebras. Wilson line index for some other low rank gauge theories are also studied.Comment: 72 pages, 9 figures, 5 table

A Review of Adversarial Attacks in Computer Vision

Deep neural networks have been widely used in various downstream tasks, especially those safety-critical scenario such as autonomous driving, but deep networks are often threatened by adversarial samples. Such adversarial attacks can be invisible to human eyes, but can lead to DNN misclassification, and often exhibits transferability between deep learning and machine learning models and real-world achievability. Adversarial attacks can be divided into white-box attacks, for which the attacker knows the parameters and gradient of the model, and black-box attacks, for the latter, the attacker can only obtain the input and output of the model. In terms of the attacker's purpose, it can be divided into targeted attacks and non-targeted attacks, which means that the attacker wants the model to misclassify the original sample into the specified class, which is more practical, while the non-targeted attack just needs to make the model misclassify the sample. The black box setting is a scenario we will encounter in practice

Mechanism of crack propagation for K9 glass

In order to study the mechanism of crack propagation, the varied cutting-depth scratch experiment is carried out and smoothed particle hydrodynamics (SPH) simulation method is used to assistant the investigation. The SPH simulation results reveal that crack will propagate in the direction where stress concentration exceeds the fracture toughness of K9 glass. The initial crack length in critical transition depth is calculated by combining the critical stress of fracture and the fracture toughness of K9 glass. Based on the effective plastic strain, the relation between scratching depth and crack depth is obtained. The recovery of crack tip is found and explained from the relationship between cutting depth and crack depth. Using the energy balance theory of Griffith, the variation of material internal energy is revealed. Comparing the scratching forces obtained from experiment and simulation, the validity of simulation results is verified. The phenomenon of crack delayed propagation is found in both experiment and simulation. The explanation of mechanism is given

Short-Video Marketing in E-commerce: Analyzing and Predicting Consumer Response

This study analyzes and predicts consumer viewing response to e-commerce short-videos (ESVs). We first construct a large-scale ESV dataset that contains 23,001 ESVs across 40 product categories. The dataset consists of the consumer response label in terms of average viewing durations and human-annotated ESV content attributes. Using the constructed dataset and mixed-effects model, we find that product description, product demonstration, pleasure, and aesthetics are four key determinants of ESV viewing duration. Furthermore, we design a content-based multimodal-multitask framework to predict consumer viewing response to ESVs. We propose the information distillation module to extract the shared, special, and conflicted information from ESV multimodal features. Additionally, we employ a hierarchical multitask classification module to capture feature-level and label-level dependencies. We conduct extensive experiments to evaluate the prediction performance of our proposed framework. Taken together, our paper provides theoretical and methodological contributions to the IS and relevant literature

Quantitative Implementation of Artificial Intelligence Based on Task Completion Analysis

With the further development of the new generation of artificial intelligence science and technology, the new generation of artificial intelligence science and technology has been applied in many fields. AlphaGo program uses high technology of quantitative analysis to realize qualitative research and development of artificial intelligence, which has important reference significance for the research and development of a new generation of artificial intelligence in the future. From the perspective of task accessibility, this paper analyzes the defects of the disturbance, so as to achieve the quantitative implementation of the new generation of artificial intelligence task accessibility analysis method