A universal approach to coverage probability and throughput analysis for cellular networks

This paper proposes a novel tractable approach for accurately analyzing both the coverage probability and the achievable throughput of cellular networks. Specifically, we derive a new procedure referred to as the equivalent uniformdensity plane-entity (EUDPE)method for evaluating the other-cell interference. Furthermore, we demonstrate that our EUDPE method provides a universal and effective means to carry out the lower bound analysis of both the coverage probability and the average throughput for various base-station distribution models that can be found in practice, including the stochastic Poisson point process (PPP) model, a uniformly and randomly distributed model, and a deterministic grid-based model. The lower bounds of coverage probability and average throughput calculated by our proposed method agree with the simulated coverage probability and average throughput results and those obtained by the existing PPP-based analysis, if not better. Moreover, based on our new definition of cell edge boundary, we show that the cellular topology with randomly distributed base stations (BSs) only tends toward the Voronoi tessellation when the path-loss exponent is sufficiently high, which reveals the limitation of this popular network topology

A08: Effects of Participation in Sports Clubs Activity on College Students’ Perceived Stress and Well-Being

Purpose: Mandated social distancing to prevent the spread of COVID-19 pandemic has brought more anxiety and stress to college students. The primary purpose of this study was to examine whether college students\u27 participation in sports club activities can reduce anxiety and stress. The secondary purpose was to compare the effects of different types of sport clubs. Methods: The sample consisted of 242 college students (143 males; mean age=22.63 years old) in an academically prestigious university. They were voluntarily enrolled in either team sports clubs, such as volleyball, football, baseball, and softball, etc. (n=96), or individual sports clubs, such as squash, cycling, mountaineering, etc. (n=146). They responded to validated scales to assess perceived stress (Sheldon Cohen, 1983) and well-being (Diener & Biswas-Diener, 2009). Self-compiled questionnaires on motivation to join sports clubs and basic information on club organization activities were collected. All surveys were conducted in October 2021. Results: A considerable proportion of students (34.7%) participated in sports clubs to reduce academic pressure. Most of them (72.26%) have already recognized the physical and mental health benefits of physical activity. Significant decreases were observed for perceived stress in both groups: team sports group (ΔM = -0.76, p \u3c 0.01), and individual sports group (ΔM= -0.77, p \u3c 0.01). A significant increase in well-being was observed in two types of courses led by the team sports group (ΔM=1.55, p \u3c 0.01) followed by the individual sports group (ΔM=1.34, p \u3c 0.01). Individual sports clubs have a more pronounced effect on reducing negative emotions than team sports clubs (ΔM = -2.01, p \u3c 0.05). Conclusion: Participation in both team sports clubs and individual sports clubs reduced perceived stress and increased well-being. Individual sports clubs had more decreases in negative emotions compared to team sports clubs

Life fingerprints of nuclear reactions in the body of animals

Nuclear reactions are a very important natural phenomenon in the universe. On the earth, cosmic rays constantly cause nuclear reactions. High energy beams created by medical devices also induce nuclear reactions in the human body. The biological role of these nuclear reactions is unknown. Here we show that the in vivo biological systems are exquisite and sophisticated by nature in influence on nuclear reactions and in resistance to radical damage in the body of live animals. In this study, photonuclear reactions in the body of live or dead animals were induced with 50-MeV irradiation. Tissue nuclear reactions were detected by positron emission tomography (PET) imaging of the induced beta+ activity. We found the unique tissue "fingerprints" of beta+ (the tremendous difference in beta+ activities and tissue distribution patterns among the individuals) are imprinted in all live animals. Within any individual, the tissue "fingerprints" of 15O and 11C are also very different. When the animal dies, the tissue "fingerprints" are lost. The biochemical, rather than physical, mechanisms could play a critical role in the phenomenon of tissue "fingerprints". Radiolytic radical attack caused millions-fold increases in 15O and 11C activities via different biochemical mechanisms, i.e. radical-mediated hydroxylation and peroxidation respectively, and more importantly the bio-molecular functions (such as the chemical reactivity and the solvent accessibility to radicals). In practice biologically for example, radical attack can therefore be imaged in vivo in live animals and humans using PET for life science research, disease prevention, and personalized radiation therapy based on an individual's bio-molecular response to ionizing radiation

Physics-Assisted Reduced-Order Modeling for Identifying Dominant Features of Transonic Buffet

Transonic buffet is a flow instability phenomenon that arises from the interaction between the shock wave and the separated boundary layer. This flow phenomenon is considered to be highly detrimental during flight and poses a significant risk to the structural strength and fatigue life of aircraft. Up to now, there has been a lack of an accurate, efficient, and intuitive metric to predict buffet and impose a feasible constraint on aerodynamic design. In this paper, a Physics-Assisted Variational Autoencoder (PAVAE) is proposed to identify dominant features of transonic buffet, which combines unsupervised reduced-order modeling with additional physical information embedded via a buffet classifier. Specifically, four models with various weights adjusting the contribution of the classifier are trained, so as to investigate the impact of buffet information on the latent space. Statistical results reveal that buffet state can be determined exactly with just one latent space when a proper weight of classifier is chosen. The dominant latent space further reveals a strong relevance with the key flow features located in the boundary layers downstream of shock. Based on this identification, the displacement thickness at 80% chordwise location is proposed as a metric for buffet prediction. This metric achieves an accuracy of 98.5% in buffet state classification, which is more reliable than the existing separation metric used in design. The proposed method integrates the benefits of feature extraction, flow reconstruction, and buffet prediction into a unified framework, demonstrating its potential in low-dimensional representations of high-dimensional flow data and interpreting the "black box" neural network