Average Transmission Rate Research Articles

Estimating the population-level effects of nonpharmaceutical interventions when transmission rates of COVID-19 vary by orders of magnitude from one contact to another

Statistical physicists have long studied systems where the variable of interest spans many orders of magnitude, the classic example is the relaxation times of glassy materials, which are often found to follow power laws. A power-law dependence has been found for the probability of transmission of COVID-19, as a function of length of time a susceptible person is in contact with an infected person. This is in data from the United Kingdom's COVID-19 app. The amount of virus in infected people spans many orders of magnitude. Inspired by this, I assume that the power-law behavior found in COVID-19 transmission is due to the effective transmission rate varying over orders of magnitude from one contact to another. I then use a model from statistical physics to estimate that if a population all wear FFP2/N95 masks, this reduces the effective reproduction number for COVID-19 transmission by a factor of approximately nine. Published by the American Physical Society 2024

Scattering-Free and Fast Response Polymer Brush-Stabilized Liquid Crystals Beam Steering Using Surface-Initiated Polymerization Technique.

Nonmechanical fast response optical beam steering technology is increasingly essential for telecommunications, imaging systems, optical sensing, displays, and military applications. Polymer network liquid crystal (PNLC) beam steering can achieve submillisecond response times but faces limitations due to scattering issues arising from the refractive index mismatch between the polymer network and the liquid crystals (LCs). In this article, we demonstrate a scattering-free, fast-response LC beam steering by using polymer brushes to stabilize the gradient refractive index. First, the initiator is incorporated into the alignment layer and the monomer is mixed into the LC layer. Surface-initiated polymerization (SIP) is then employed to grow the polymer brushes exclusively on the substrate's surface, thus confining the polymer network's growth to the LC bulk and reducing interfacial scattering. For polymer brush stabilized liquid crystal (PBSLC) beam steering device with a period size of 225 μm and a cell gap of 7.2 μm, the average transmission rate reaches 88% in the visible light spectrum with a haze value of only 6.91. The steering angle is 0.16, and the diffraction efficiency is 80.3%. When a voltage of 35 Vrms is applied, the primary energy can be tuned to the zeroth order, with a response time close to 1 ms. By cascading two PBSLC beam steering devices with opposite steering directions, the primary energy of the beam can be adjusted between zeroth, +1, and -1 order. This method requires only a UV light source, a precision displacement stage, a power supply, and a mask, avoiding the need for expensive equipment and complex electrode fabrication. By adjustment of the phase change period, step width, and number of steps during fabrication, the steering angles and diffraction efficiency of the PBSLC beam steering device can be easily controlled, highlighting its significant potential for industrial production.

Inter-beam handover schemes for LEO satellites in 5G satellite–terrestrial integrated networks

Unlike terrestrial handover schemes, the handover schemes in 5G satellite–terrestrial integrated network (STIN) face several challenges, such as large propagation delay, complex channel environment, and fast satellite movement. Therefore, the handover schemes designed in the 5G terrestrial network is not suitable for the 5G STIN. In view of this, this paper considers the inter-beam handover problem for the 5G STIN with a low earth orbit satellite and a ground user. We establish the satellite channel model, which includes path loss, rain attenuation, and multi-beam antenna gain. To model the mobile feature of the user, we consider a two-dimensional random walk model. Then, we propose A5 event-based conditional handover (CHO) scheme, time factor-based CHO scheme, and load factor-based CHO scheme to achieve efficient inter-beam handover. Considering that there may be multiple beams that meet the triggering condition in each handover scheme, we also propose three kinds of beam selection schemes, namely random beam selection scheme, maximum power-based beam selection scheme, and minimum distance-based beam selection scheme. To evaluate the performance of the proposed handover schemes, key performance indicators, such as handover frequency, ping-pong handover rate, unnecessary handover rate, handover failure rate, and average transmission rate are analyzed. Simulation results verify the superiority of the proposed handover schemes by comparing them with the benchmark scheme.

Infection fronts in randomly varying transmission-rate media.

We numerically investigate the geometry and transport properties of infection fronts within the spatial SIR model in two dimensions. The model incorporates short-range correlated quenched random transmission rates. Our findings reveal that the critical average transmission rate for the steady-state propagation of the infection is overestimated by the naive mean-field homogenization. Furthermore, we observe that the velocity, profile, and harmfulness of the fronts, given a specific average transmission, are sensitive to the details of randomness. In particular, we find that the harmfulness of the front is larger the more uniform the transmission rate is, suggesting potential optimization in vaccination strategies under constraints like fixed average-transmission rates or limited vaccine resources. The large-scale geometry of the advancing fronts presents nevertheless robust universal features and, for a statistically isotropic and short-range correlated disorder, we get a roughness exponent α≈0.42±0.10 and a dynamical exponent z≈1.6±0.10, which are roughly compatible with the one-dimensional Kardar-Parisi-Zhang (KPZ) universality class. We find that the KPZ term and the disorder-induced effective noise are present and have a kinematic origin.

Computational analysis of magnetohydrodynamic ternary-hybrid nanofluid flow and heat transfer inside a porous cavity with shape effects

The current study aims to analyze the magnetohydrodynamic natural convective fluid flow and heat transmission features of the ternary-hybrid nanofluid filled the partially heated porous square cavity under the impacts of heat absorption/generation and thermal radiation. The governing equations are solved using the Marker and Cell method. In the present study, three different types of nanoparticles, such as molybdenum disulfide (MoS2), single-walled carbon nanotube (SWCNT), and silver (Ag), are suspended in an inorganic (water) or non-polar organic (kerosene) solvent. Nine different shapes of nanoparticles are utilized in this study. The outcomes show that for the fixed pertinent parameter values of the existence and nonexistence of heat generation/absorption, the MoS2+SWCNT+Ag/water ternary-hybrid nanofluids synthesized by lamina-shaped nanoparticles, the average thermal transmission rate is increased by 40.8523%, 36.329%, and 38.7025%, respectively, than sphere-shaped nanoparticles. In addition, utilizing the MoS2+SWCNT+Ag/kerosene ternary-hybrid nanofluids synthesized by lamina-shaped nanoparticles, the average heat transmission rate is augmented by 38.0322%, 33.0464%, and 35.5868%, respectively, than sphere-shaped nanoparticles. The current study reveals that the fluid flow and heat transfer efficiency are significantly increased by improving the nanoparticle volume fraction and shape factors depending upon the existence of heat absorption/generation. The high average heat transfer efficiency is observed when lamina-shaped nanoparticles are dispersed into the water compared to kerosene in the presence of a heat source. This study can enhance heat transmission efficiency in various industrial and engineering fields, such as heat exchangers, solar collectors, and fuel cells.

Bovine leukemia virus transmission rates in persistent lymphocytotic infected dairy cows.

Bovine leukemia virus (BLV) establishes a lifelong persistent infection in dairy cattle. White blood cell count (WBC) is correlated with proviral load in the blood and milk of BLV-infected cattle, and testing WBC can be used to assess both BLV infectiousness levels and risk of BLV transmission from different types of infected animals. The objective of the study was to compare effective transmission rates (β) and the basic reproduction ratio (R o) among two types of BLV-infected dairy cows in Chile: those affected with persistent lymphocytosis (PL) vs. aleukemic (AL).The estimated (β) coefficient was higher in PL cattle [1.1; 95% Confidence interval (CI) (-1.6, 3.8)], compared to AL cattle (-3.1; 95% CI = -3.7, -2.5). In addition, the R o was higher in PL cattle (60.4; 95% CI = 3.5; 820.6), compared to AL cattle (1.5; 95% CI = 0.7, 3.1). The ratio between PL/AL expected rate of cases was 73.9. The estimated effective transmission rate and the Ro were higher in PL cattle compared to AL cattle. The WBC test is a convenient alternative that can be considered for risk identification and risk management of BLV infection in dairy herds; particularly in livestock regions where laboratory capacity is limited (e.g., use of PCR or gene sequencing techniques) and/or molecular tests are not cost-effective. Therefore, when prevalence of infection is high, the removal of PL cattle should be engaged to control BLV within-herds.

Cloud platform-based design of automatic monitoring and alarm system for integrated meteorological observation

This study designs an automatic monitoring and alarm system for integrated meteorological observation based on the cloud platform to improve the automatic monitoring ability for integrated meteorological observation and the operation and maintenance management level of meteorological departments. A meteorological data collector was used to collect comprehensive meteorological observation data, transmit the collected comprehensive meteorological observation data to the main control processing module, preprocess the comprehensive meteorological observation data, and finally transmit the pre-processed comprehensive meteorological observation data to the cloud service module through the data transmission module. In the cloud service module, cloud computing and an improved K-means algorithm were used to analyze the comprehensive meteorological observation data, mine abnormal comprehensive meteorological observation data, and send alarm information to the application module. Users can view the comprehensive meteorological observation data in the cloud server on the client in real-time, thus realizing automatic monitoring and alarm for comprehensive meteorological observation. Results show that the average transmission rate of various meteorological comprehensive observation data transmitted by the system is as high as 99.48%, thereby achieving clustering of abnormal meteorological comprehensive observation data. Upon detecting abnormal meteorological data, the system sends alarm information to the mobile phone client to complete the monitoring of abnormal meteorological information.

Ефективність адаптивних протоколів множинного доступу пакетних радіомереж в умовах самоподібного трафіку

Introduction. Self-similar traffic in modern telecommunication radio networks requires new methods for calculating parameters of adaptive Carrier Sense Multiple Access (CSMA) protocols, different from those adopted in classical teletraffic theory based on Poisson distribution models. Purpose. Construction of a mathematical model of the operation of adaptive synchronous CSMA protocols in conditions of self-generating traffic for three strategies for changing the length of data packets, and obtaining equations for the average transmission rate and comparing the effectiveness of adaptive control with the results of studies of the same protocols for traffic with a Poisson distribution. Methods. This goal is achieved by creating and analyzing a mathematical model of the operation of the flexible and rigid synchronous adaptive CSMA protocol for three strategies for changing the length of data packets under traffic conditions with a Pareto distribution. The model is described by the average protocol transmission rate equations, which are a function of traffic intensity, Pareto distribution parameters, and strategies for changing the length of data packets. Results. It has been proven that self-similar traffic significantly reduces the stability limit of adaptive CSMA protocols, which must be taken into account when using these protocols in radio networks with long-term dependence in traffic distribution. At the same time, the throughput of adaptive CSMA protocols remains virtually unchanged compared to the traffic model with a Poisson distribution. Conclusions. The proposed mathematical model of adaptive CSMA protocols allows to calculate the real values of the average speed, stability limit and throughput of these protocols under conditions of self-similar traffic for the proposed strategies for changing the length of data packets. The considered strategies (except for the second) are effective for adaptive control in conditions of self-generating traffic, but at a significantly lower value of traffic intensity compared to the Poisson distribution.

POSS/PVTMS aerogels for passive cooling and THz communication via cross-linking density regulation and nanoscale bimodal design

POSS@PVTMS aerogels with bimodal nano-sized cavities for highly efficient passive cooling (ΔT = 3.7 °C) and high-frequency THz communication (average transmission rate 88.7%).

Unveiling the dynamics of drug transmission: A fractal-fractional approach integrating criminal law perspectives

<abstract><p>The excessive use of drugs has become a growing concern in the current century, with the global toll of drug-related deaths and disabilities posing a significant public health challenge in both developed and developing countries. In pursuit of continuous improvement in existing strategies, this article presented a nonlinear deterministic mathematical model that encapsulates the dynamics of drug addiction transmission while considering the legal implications imposed by criminal law within a population. The proposed model incorporated the fractal-fractional order derivative using the Atangana-Baleanu-Caputo ($ \mathbb{ABC} $) operator. The objectives of this research were achieved by examining the dynamics of the drug transmission model, which stratifies the population into six compartments: The susceptible class to drug addicts, the number of individuals receiving drug misuse education, the count of mild drug addicts, the population of heavy-level drug addicts, individuals subjected to criminal law, and those who have ceased drug use. The qualitative analysis of the devised model established the existence and uniqueness of solutions within the framework of fixed-point theory. Furthermore, Ulam-Hyer's stability was established through nonlinear functional analysis. To obtain numerical solutions, the fractional Adam-Bashforth iterative scheme was employed, and the results were validated through simulations conducted using MATLAB. Additionally, numerical results were plotted for various fractional orders and fractal dimensions, with comparisons made against integer orders. The findings underscored the necessity of controlling the effective transmission rate to halt drug transmission effectively. The newly proposed strategy demonstrated a competitive advantage, providing a more nuanced understanding of the complex dynamics outlined in the model.</p></abstract>

Numerical simulation of thermosolutal natural convection of power-law non-Newtonian fluids in a parallelogram with sensitivity analysis by response surface methodology

Thermosolutal natural convection originates in a fluid when the density changes due to the presence of two distinct components with varying rates of diffusion. This convection is driven by buoyancy resulting from concurrent temperature and concentration gradients. This study focuses on the thermosolutal free convection flow within a parallelogrammic enclosure. The functioning fluid under consideration is non-Newtonian and formulated by the viscosity model (power-law). The top and bottom walls of the chamber are adiabatic and are assumed to be impermeable. The temperature and concentration on the left side are maintained at a high level, while the conditions on the right side are cold and low. The controlling parameters for the present case include Rayleigh number Lewis number (Le = 5, 10), Prandtl number (Pr = 6.2), buoyancy ratio (N = 0.8, −0.8) along with power-law index (n = 0.6, 1, 1.4). The results obtained from this numerical study are validated with existing results and indicate the correctness of the code. The output of the study is shown in terms of velocity and temperature profiles, streamlines, isotherms, and iso-concentrations, the average rate of heat and mass transmission in terms of the average Nusselt number () and the average Sherwood number (). The correlation equation derived from the RSM approach demonstrates the relationship between the output responses and the input parameters. It concludes that n negatively affects both heat and mass transfer, while Ra affects positively. The findings of this study could be helpful for understanding of thermosolutal natural convection behavior of non-Newtonian (power-law) fluid in an enclosure and therefore accelerate the industrial application of such fluid in the relevant field, such as HVAC (heating, ventilation, and air conditioning) system.

A hybrid one-vertex model for susceptible–infected–susceptible diseases on networks with partial connection information

We analyze the propagation of the susceptible–infected–susceptible model on the network, where the partial connection information is known. In order to analyze the spread of network epidemics, the quenched mean-field method requires complete connection information, while the heterogeneous mean-field method requires complete topology information. When only partial connection information is available, the quenched mean-field method may be disabled. In view of this situation, a hybrid model consisting of connection and topology information is proposed. The theoretical results are in good agreement with stochastic simulations on scale-free networks. In addition, as the proportion of connection information in the network increases, model predictions about final epidemic size become more accurate when the effective transmission rate is slightly larger than the simulation threshold.

Evaluation of Seed Transmission Rates of Wheat Streak Mosaic Virus in Mechanically Inoculated Winter and Spring Wheat Cultivars in Montana.

Wheat streak mosaic disease is caused by wheat streak mosaic virus (WSMV) and two other viruses and persistently limits wheat yields in the Great Plains region of the United States. Seed transmission of viruses is an important consideration in international movement and is important epidemiologically. Seed transmission of WSMV in wheat was first reported from Australia in 2005, but there is little data from United States cultivars on the rate of seed transmission. In 2018, mechanically inoculated winter and spring wheat cultivars were evaluated in Montana. We found differences in WSMV seed transmission rates between winter and spring wheat, with average transmission rates in spring wheat (3.1%) being five times higher compared to winter wheat (0.6%). Seed transmission rates in spring wheat were twice as high as the highest previously reported transmission rate for individual genotypes, 1.5%. The results from this study provide a strong argument for increasing the current testing of seed for breeding purposes prior to international movement when WSMV has been observed and caution against using grain from WSMV-infected fields as seed source because it can heighten the risk of wheat streak mosaic outbreaks.

Modelling the impact of vaccination on transmission dynamics of Typhoid fever

In this work, in order to evaluate the immediate and long-term impacts of vaccination on the transmission dynamics of TF, we develop a compartmental mathematical model which takes into account vaccination and medically hygienic compartments for the dynamics of TF transmission in a population. Based on the positivity and boundedness of the model solutions, the model is shown to be mathematically well posed. The next generation matrix method is used to determine the control reproduction number, R0π, of the model. It is shown that the model has a unique disease-free equilibrium, which is proved to be locally asymptotically stable when R0π is less than unity. Further analysis suggests that the model admits a unique endemic equilibrium when R0π is greater than unity. To investigate the effect of the model parameters on the transmission and spread of the disease in the population, sensitivity analysis is conducted. The dynamics of TF spread within the populations under the varying effects of some key sensitive parameters, such as the effective diseases transmission rate in human, bacteria shedding rate from symptomatic infectious humans, vaccine efficacy, decay rate of bacteria from the environment and recovery rate of symptomatic infectious humans, is further studied using numerical simulations. The study suggests some measures that can be put in place to guide against the menace of TF in the population.

Research on Resource Allocation Strategy of Indoor Visible Light Communication and Radio Frequency Systems Integrating Orthogonal Frequency-Division Multiple Access Technology

Aiming at the problem of resource allocation strategies limiting the system transmission rate in indoor visible light communication and radio frequency (VLC/RF) systems, a new resource allocation method is proposed, and orthogonal frequency-division multiple access (OFDMA) technology is introduced. The capacity of the communication system is effectively increased. In the VLC/RF system model based on OFDMA, the Lyapunov optimization method is used to transform the time averaging problem into a series of single-slot online problems to reduce its computational complexity, the optimization problem is decomposed into three independent subproblems, and the Lagrange relaxation method and convex optimization theory are used to solve the subproblems to maximize the average transmission rate of the system, and the Lyapunov drift is used to ensure the stability of the system. Simulation verifies that the Lyapunov optimization algorithm does not require iteration, which improves the optimization speed to a high extent. The simulation results show that the proposed resource allocation strategy effectively balances the system queue length and transmission rate, improves the average transmission rate of the system to the greatest extent under the premise of ensuring the stability of the system, and compares with other algorithms from the aspects of system stability and transmission rate, which proves the effectiveness of the Lyapunov optimization algorithm.

Resource Allocation Strategy Based On Tripartite Graph in Vehicular Social Networks

Owing to the limited spectrum of vehicular social networks and the fragmented distribution of caching resources, problems such as low vehicle data transmission rate, poor service quality, and low service content delivery efficiency of streaming media are encountered. To solve these problems, we propose a resource allocation strategy based on tripartite graph in vehicular social networks (RATG). This strategy establishes a mobile vehicular social network model based on vehicle mobility and social similarity. To maximize the content delivery efficiency and transmission rate, one-to-one stable matching based on mobile social connections and one-to-one stable matching based on channel state are established. The proposed strategy incorporates a heuristic optimization algorithm based on the maximum spanning tree, such that the matching results of the two tripartite graphs can reach the approximate global optimal simultaneously and further improve the service quality of vehicles. The simulation results show that the content delivery efficiency of the RATG strategy is 6.05%, 5.00%, and 10.64% higher than those of the randomized resources allocation strategy, local search strategy, and local ratio strategy, respectively, and the average transmission rate is at least 2.7% higher for the RATG strategy, relative to those of the other strategies.

Research on the integration of online teaching resources in higher education institutions under the perspective of industry-education integration

Abstract The purpose of exploring the development mode of online teaching resources in colleges and universities is to enhance the utilization rate of online teaching resources to promote the diversification of teaching methods. In this paper, based on big data technology, a cloud education platform integrating online teaching resources in colleges and universities is constructed under the perspective of integrating industry and education, and the architecture and functions of the cloud education platform are explained. Then the collaborative filtering algorithm is used to filter and collect the information on online teaching resources, and the Pearson correlation formula is used to pre-process the data and help users to recommend teaching resources. Finally, the pre-processed data are filtered and analyzed using the multilayer perceptron technology under the deep learning model. To verify the practicality of the cloud education platform proposed in this paper, the platform’s performance is evaluated by combining MAE metrics with RMSE metrics. In terms of load capacity, the platform has the best load capacity when the number of users is 200. From the performance test, the average transmission rate of the cloud education platform is 8.1% and 0.93% higher than that of NetEase Cloud Classroom and Tencent Classroom, and the average transmission time is 7.09 s. From the practicality analysis, the average value of the MAE index is 0.317%, and the average value of the RMSE index is 0.232%. This shows that the cloud education platform can effectively integrate university online teaching resources and help universities achieve diversified development of teaching methods.

Detection model transfer of apple soluble solids content based on NIR spectroscopy and deep learning

Transfer and updating of near infrared (NIR) spectroscopy model of fruit internal quality has become the focus of the industrial application. Internet of Things (IoT) and deep learning (DL) were proposed to perform soluble solids content (SSC) model transfer of apple by NIR. A model transfer platform including low-power handheld internal quality terminal and interacting cloud data system had been constructed. An autoencoder (AE) neural network model was developed for the spectral correction and model transfer. The average time for transmitting detection results to the detection terminal was 1.5 to 2.0 s, with a 100% effective transmission rate. After 5000 iterations of training, the correlation coefficient of different detection terminals improved by 55%, and the root mean square error was reduced by 94%. Selected samples from the second batch of apples detected by the No. 1 detection terminal were added to the original neural network for training. After adding 30 samples, the correlation coefficient increased by 13% and the root mean square error decreased by 90%. The results demonstrated that the AE neural network for spectral correction was effective in eliminating differences between devices and significantly reducing the impact of different detection terminals on the accuracy of NIR detection of SSC in apples. Therefore, the NIR detection model transfer technique could be practically exploited for fruit quality control assessment using different detection terminals.

Study on the Evolution of Risk Contagion in Urban River Ecological Management Projects Based on SEIRS

The risk transmission mechanisms of urban river ecological management engineering projects are examined in this study. Using the Susceptible Exposed Infectious Recovered Susceptible (SEIRS) model for risk transmission, a model of risk propagation delay for urban river ecological management engineering projects on scale-free networks is developed, which takes into account the effects of risk propagation and delay. We conducted a steady-state analysis of the model and obtained the basic reproduction number R. When R > 1, the equilibrium point of risk outbreak is stable, and when R < 1, the equilibrium point of risk disappearance is stable. Numerical simulations of the model were conducted using the MATLAB2022b to reveal the dynamic propagation patterns of risk in urban river ecological management engineering projects. The research results show that the steady-state density of the infected nodes in the network increases with the increase in the effective propagation rate and the propagation delay time; the propagation delay reduces the risk propagation threshold in the network and accelerates the occurrence of the equilibrium state of risk outbreak. There is a correlation between the transmission rate of latent nodes and the transmission rate of infected nodes, and the effective transmission rate of latent nodes has a greater influence on risk propagation. The spread of risk in the network can be effectively controlled and mitigated with targeted immunity for susceptible nodes. This article, based on the theory of complex networks and the mean-field theory, takes into account the propagation delay and spreading of latent nodes. Building a D-SEIRS model for risk propagation broadens the research perspective on urban river ecological management risk propagation.

Communication With Unreliable Entanglement Assistance

Entanglement resources can increase transmission rates substantially. Unfortunately, entanglement is a fragile resource that is quickly degraded by decoherence effects. In order to generate entanglement for optical communication, the transmitter and the receiver first prepare entangled spin-photon pairs locally, and then the photon at the transmitter is sent to the receiver through an optical fiber or free space. Without feedback, the transmitter does not know whether the entangled photon has reached the receiver. The present work introduces a new model of unreliable entanglement assistance, whereby the communication system operates whether entanglement assistance is present or not. While the sender is ignorant, the receiver knows whether the entanglement generation was successful. In the case of a failure, the receiver decodes less information. In this manner, the effective transmission rate is adapted according to the assistance status. Regularized formulas are derived for the classical and quantum capacity regions with unreliable entanglement assistance, characterizing the tradeoff between the unassisted rate and the excess rate that can be obtained from entanglement assistance. It is further established that time division between entanglement-assisted and unassisted coding strategies is optimal for the noiseless qubit channel, but can be strictly suboptimal for a noisy channel.