Transmission Rate Research Articles

Amidst Cytokine Storm in Metabolic Diseases: Can 2-deoxy-D-glucose (2-DG) Cure COVID-19?

Abstract: The SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2)-related pandemic disease COVID-19, which began in China in 2019, became the leading cause of fatalities globally. The transmission rate of the virus is directly proportional to the so-called ‘dance dynamic’ energy of the spike protein as this phenomenon favours the ligand-receptor binding. The clinical spectrum of the COVID-19 disease, which includes (inflammation, cytokine storm, and multi-organ dysfunction), puts Corona Warriors active in various aspects of the disease, such as the efficient management of critically ill COVID-19 patients, in danger of losing their lives. Due to its effects on an ancient oxygen-independent glycolytic pathway, anti-inflammatory properties, and competitive interaction with viral proteins, 2-deoxy-D-glucose (2-DG), which is being developed in India at the Defence Research and Development Organization (DRDO), has emerged as a ground-breaking agent for COVID-19 treatment. After a virus gains entry into host cells, it is found that metabolic reprogramming takes place to meet the nutritional and energy requirements for virus reproduction. The recent approval of 2-DG for adjunctive emergency usage by the Drug Controller General of India (DCGI) may mark a turning point in the management of mild to moderate COVID-19 infection.

Bayesian decision model based reliable route formation in internet of things

Security provisioning has become an important issue in wireless multimedia networks because of their crucial task of supporting several services. This paper presents Bayesian decision model based reliable route formation in internet of things (BDMI). The main objective of the BDMI approach is to distinguish unreliable sensor nodes and transmit the data efficiently. Active and passive attack recognition methods identify unreliable node sensor nodes. Remaining energy, node degree, and packet transmission rate parameters to observe their node possibilities for recognizing the passive unreliable nodes. In active recognition, the base station (BS) confirms every sensor node identity, remaining energy, supportive node rate, node location, and link efficiency parameters to detect active unreliable sensor nodes. The Bayesian decision model (BDM) efficiently isolates an unreliable sensor node in the multimedia network. Simulation outcomes illustrate that the BDMI approach can efficiently enhance unreliable node detection and minimize the packet loss ratio in the network.

Cost-effectiveness analysis of surgical masks, N95 masks compared to wearing no mask for the prevention of COVID-19 among health care workers: Evidence from the public health care setting in India.

Nonpharmacological interventions, such as personal protective equipment for example, surgical masks and respirators, and maintenance of hand hygiene along with COVID-19 vaccines have been recommended to reduce viral transmission in the community and health care settings. There is evidence from the literature that surgical and N95 masks may reduce the initial degree of exposure to the virus. A limited research that has studied the cost-effective analysis of surgical masks and N95 masks among health care workers in the prevention of COVID-19 in India. The objective of this study was to estimate the cost-effectiveness of N95 and surgical mask compared to wearing no mask in public hospital settings for preventing COVID-19 infection among Health care workers (HCWs) from the health care provider's perspective. A deterministic baseline model, without any mask use, based on Eikenberry et al was used to form the foundation for parameter estimation and to estimate transmission rates among HCWs. Information on mask efficacy, including the overall filtering efficiency of a mask and clinical efficiency, in terms of either inward efficiency(ei) or outward efficiency(e0), was obtained from published literature. Hospitalized HCWs were assumed to be in one of the disease states i.e., mild, moderate, severe, or critical. A total of 10,000 HCWs was considered as representative of the size of a tertiary care institution HCW population. The utility values for the mild, moderate and severe model health states were sourced from the primary data collection on quality-of-life of HCWs COVID-19 survivors. The utility scores for mild, moderate, and severe COVID-19 conditions were 0.88, 0.738 and 0.58, respectively. The cost of treatment for mild sickness (6,500 INR per day), moderate sickness (10,000 INR per day), severe (require ICU facility without ventilation, 15,000 INR per day), and critical (require ICU facility with ventilation per day, 18,000 INR) per day as per government and private COVID-19 treatment costs and capping were considered. One way sensitivity analyses were performed to identify the model inputs which had the largest impact on model results. The use of N95 masks compared to using no mask is cost-saving of $1,454,632 (INR 0.106 billion) per 10,000 HCWs in a year. The use of N95 masks compared to using surgical masks is cost-saving of $63,919 (INR 0.005 billion) per 10,000 HCWs in a year. the use of surgical masks compared to using no mask is cost-saving of $1,390,713 (INR 0.102 billion) per 10,000 HCWs in a year. The uncertainty analysis showed that considering fixed transmission rate (1.7), adoption of mask efficiency as 20%, 50% and 80% reduces the cumulative relative mortality to 41%, 79% and 94% respectively. On considering ei = e0 (99%) for N95 and surgical mask with ei = e0 (90%) the cumulative relative mortality was reduced by 97% and the use of N95 masks compared to using surgical masks is cost-saving of $24,361 (INR 0.002 billion) per 10,000 HCWs in a year. Both considered interventions were dominant compared to no mask based on the model estimates. N95 masks were also dominant compared to surgical masks.

Research on Early Warning of Transmission of Tuberculosis Infectious Diseases from the Perspective of Social Factors

In this study, the infiltration model was established to study the early warning of pulmonary tuberculosis data in Xiamen public hospitals. Based on the gender characteristics of residents in Xiamen, a percolation model was established to analyze the transmission rates of diseases under different contact types. In addition, the calculation method of the percolation threshold is discussed, and the model is verified by a simulation experiment. The results show that the model can predict the spread of epidemic situations well. The early warning value and relevant preventive measures were obtained by simulating the spread of tuberculosis under different exposure numbers. Bond percolation analysis was used to predict the proportion of the eventually infected population, this threshold of percolation was the basic regeneration number of tuberculosis, and the tuberculosis infection situation was effectively predicted.

Unveiling the Complexity of HIV Transmission: Integrating Multi-Level Infections via Fractal-Fractional Analysis

This article presents a non-linear deterministic mathematical model that captures the evolving dynamics of HIV disease spread, considering three levels of infection in a population. The model integrates fractal-fractional order derivatives using the Caputo operator and undergoes qualitative analysis to establish the existence and uniqueness of solutions via fixed-point theory. Ulam-Hyer stability is confirmed through nonlinear functional analysis, accounting for small perturbations. Numerical solutions are obtained using the fractional Adam-Bashforth iterative scheme and corroborated through MATLAB simulations. The results, plotted across various fractional orders and fractal dimensions, are compared with integer orders, revealing trends towards HIV disease-free equilibrium points for infective and recovered populations. Meanwhile, susceptible individuals decrease towards this equilibrium state, indicating stability in HIV exposure. The study emphasizes the critical role of controlling transmission rates to mitigate fatalities, curb HIV transmission, and enhance recovery rates. This proposed strategy offers a competitive advantage, enhancing comprehension of the model’s intricate dynamics.

A Stochastic Semi-Parametric SEIR Model with Infectivity in an Incubation Period

This paper introduces stochastic disturbances into a semi-parametric SEIR model with infectivity in an incubation period. The model combines the randomness of disease transmission and the nonlinearity of transmission rate, providing a flexible framework for more accurate description of the process of infectious disease transmission. On the basis of the discussion of the deterministic model, the stochastic semi-parametric SEIR model is studied. Firstly, we use Lyapunov analysis to prove the existence and uniqueness of global positive solutions for the model. Secondly, the conditions for disease extinction are established, and appropriate stochastic Lyapunov functions are constructed to discuss the asymptotic behavior of the model’s solution at the disease-free equilibrium point of the deterministic model. Finally, the specific transmission functions are enumerated, and the accuracy of the results are demonstrated through numerical simulations.

Bayesian inference for the onset time and epidemiological characteristics of emerging infectious diseases

BackgroundEmerging infectious diseases pose a significant threat to global public health. Timely detection and response are crucial in mitigating the spread of such epidemics. Inferring the onset time and epidemiological characteristics is vital for accelerating early interventions, but accurately predicting these parameters in the early stages remains challenging.MethodsWe introduce a Bayesian inference method to fit epidemic models to time series data based on state-space modeling, employing a stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for transmission dynamics analysis. Our approach uses the particle Markov chain Monte Carlo (PMCMC) method to estimate key epidemiological parameters, including the onset time, the transmission rate, and the recovery rate. The PMCMC algorithm integrates the advantageous aspects of both MCMC and particle filtering methodologies to yield a computationally feasible and effective means of approximating the likelihood function, especially when it is computationally intractable.ResultsTo validate the proposed method, we conduct case studies on COVID-19 outbreaks in Wuhan, Shanghai and Nanjing, China, respectively. Using early-stage case reports, the PMCMC algorithm accurately predicted the onset time, key epidemiological parameters, and the basic reproduction number. These findings are consistent with empirical studies and the literature.ConclusionThis study presents a robust Bayesian inference method for the timely investigation of emerging infectious diseases. By accurately estimating the onset time and essential epidemiological parameters, our approach is versatile and efficient, extending its utility beyond COVID-19.

Enhancing secret key distribution through advanced color modulation in visible light communication

Visible light communication (VLC) has emerged as a dynamic area of research poised to revolutionize high-speed wireless communication. VLC technology uses light-emitting diodes (LEDs) within existing infrastructure to emit light within the visible spectrum. VLC complements traditional radio frequency (RF) communications, addressing its inherent limitations and drawbacks. To navigate the demands of modern urban environments, VLC systems must prioritize secure data transmission, accessibility, and economic feasibility, particularly within the framework of smart cities. We introduce what is to our knowledge a novel privacy-enhanced VLC system for optical wireless communication. Leveraging color data modulation techniques and the intricacies of a hyperchaotic three-dimensional map, this innovative approach ensures robust security. By employing diverse LED colors for data transmission and exploiting the unpredictable mathematical properties of hyperchaotic maps, enhanced privacy is achieved. The performance of the proposed system was rigorously evaluated through various tests, manipulating initial control parameters of the encryption process with the hyperchaotic map, as well as adjusting message length and content. Tests were conducted over a 1 m connection distance at a symbol transmission rate of 2 baud. Remarkably, the proposed system demonstrated high accuracy in message recovery, achieving a symbol error rate (SER) of only 0.02 at an incident optical power of 22 µW. We highlight the critical importance of precise decryption parameter values in the proposed method, demonstrating the necessity for accuracy within the range of 10−15 for each decryption parameter; it underscores the indispensability of meticulous parameter calibration to ensure the correct decryption of transmitted symbols. These results pave the way for applications where absolute security is imperative, particularly in smart city environments, such as for key distribution purposes.

Sorption Isotherm and Effect of Packaging Materials on Proximate, Organoleptic and Lipid Oxidation Quality of Chicken Nuggets Stored at Two Different Temperatures

The study Investigated sorption isotherm features and the effects of packaging materials of both high-density and low-density polyethylene on sensory properties, proximate composition and lipid oxidation of chicken nuggets in storage. Boneless chicken breast was procured from a reputable source and cut into sizeable weight of 50g each to produce the chicken nuggets used for the studies. The experimental setup for sorption isotherm analysis in this study involved using a gravimetric method to equilibrate the product at various relative humidity levels. Five (5g) grams of oven-dried chicken nugget samples of known moisture content were placed in a controlled humidity chamber, and the weight changes of the samples were monitored until equilibrium was reached. GAB equation was used to evaluate the product ware activity and monolayer moisture. Sensory assessment was evaluated using a 9- point hedonic scale while proximate composition of the chicken nuggets samples was determined according to the methods of the Association of Official Analytical Chemists. Thiobarbituric acid reactive substances (TBARS) assay was used to measure malondialdehyde (MDA) levels as a marker of lipid oxidation. The investigation showed that sensory qualities, proximate composition and lipid oxidation of chicken nuggets were markedly affected by the variance in temperature settings, with distinct disparities seen among different materials for packaging. Chicken nuggets stored at 25 0C caused a significant loss in organoleptic properties and some nutritional composition such as protein and fat. Storage of chicken nugget at 25 0C and 40 C showed a varied values in malondialdehyde as content ranged from 0.52 to 0.81 for chicken nugget stored at 250 C and 0.17 to 0.43 for the product stored at 40 C across the packaging materials investigated. The water activity and monolayer moisture results of sorption analysis revealed that good packaging materials of very low water vapour transmission rate should be used for storage of chicken nuggets as high-density polyethylene offered a promising alternative than low density polyethylene.

Fractal Engineering Integration in Antenna Arrays: A Comparative-review for Advanced Transceiver Systems with 5G/IoT Connectivity

The growing demand for space-efficient antennas compatible with portable electronic gadgets inspired the integration of recursively iterated fractal geometries (characterized by self-similarity, space-filling, and multiband/wideband capabilities) in antenna designs. Therefore, this article conducts an extensive survey on fractal-based single-port and multi-port patch antenna designs with multiband and ultrawideband characteristics for their implementation in 5G/IoT (Internet of Things) devices. The survey begins with a basic overview of fractal geometries and the iterated function system (IFS) technique employed for their generation. Further, it highlights the limitation of multipath fading prevalent in single-port antenna arrays that can be overcome by adopting multiple-input multiple-output (MIMO) technology. The MIMO antenna systems are vital for 5G networks to enhance data transmission rate, network capacity, and system reliability. Apart from these admirable attributes, the closely packed antenna elements in the MIMO configuration result in a severe mutual coupling. To address this limitation, various isolation enhancement techniques developed by distinguished researchers are thoroughly discussed in this article, detailing their merits and demerits. At last, this article portrays diverse band-notch structures integrated into the antenna designs to eradicate the existing interfering narrow bands in the ultrawideband (UWB) spectrum. The underlying reason for conducting this survey is to aid antenna designers and academicians with a thorough knowledge of distinct fractal geometries, various isolation improvement approaches, and band-notch techniques on a single platform, desired for designing 5G/IoT-based antenna systems.

Enabling ultra-high bit rate transmission with CFBG as dispersion compensator in an OptiSpan 240 km DWDM network

Abstract In this paper, a dispersion compensation technique for an ultra-long haul optical network utilizing a chirped fiber Bragg grating (CFBG) is presented. A high bit-rate signal of 40 Gbps is inputted into each channel. The CFBG, employed for dispersion compensation, is positioned after demultiplexing, enabling effortless network upgrades. The grating parameters of the implemented CFBG are mathematically analyzed and optimized to counteract net dispersion of over 3153 ps/nm across the channel. The design is verified using the OptiSystem software, resulting in a successful transmission up to 240 km with an average Q-factor of 8.09, utilizing an amplification gain of 49.5 dB. Additionally, the achieved optical signal-to-noise ratio (OSNR) level using the symmetrical amplification technique surpasses the acceptable value, with an average bit error rate of 10−16.

A Flexible Terahertz Metamaterial Sensor for Pesticide Sensing and Detection.

Terahertz (THz) waves have garnered significant interest across various fields, particularly in high-sensitivity sensing applications. Metamaterials can be employed in THz sensors, specifically for refractive index sensing and pesticide detection due to their high-sensitivity characteristics. In this Article, a dual-band flexible THz metamaterial sensor based on polyimide is proposed for refractive index and pesticide sensing, which is fabricated using ultraviolet (UV) lithography technology and measured by a THz time-domain spectroscope (TDS) system. The resonant frequencies of the sensor are at 0.37 and 1.13 THz, with transmission rates of 2.9% and 0.3%, respectively. With an analyte layer attached to the sensor's surface, the sensitivity of refractive index sensing can be calculated as 0.09 and 0.28 THz/RIU (refractive index unit) at the two resonant frequencies. In order to validate the exceptional pesticide sensing performance of the sensor, chlorpyrifos-methyl acetone solutions with various concentrations are added on it. Furthermore, a monolayer of graphene is coated on the sensor's surface, which is proved capable of improving pesticide sensing sensitivity at low concentrations due to strong π-π stacking interactions with π-electrons in chlorpyrifos-methyl solutions. Therefore, the graphene-coated sensor can be utilized in detecting pesticide solutions with low concentrations, and the sensor without graphene is preferred for high concentration detection. This work provides a novel option for the THz metamaterial sensor with high sensitivity covering a wide pesticide concentration range.

Mathematical Modeling of HIV/AIDS Disease Spread with Public Awareness

This study develops mathematical model for the spread of HIV/AIDS by the population is divided into seven sub-populations, namely the susceptible unaware HIV subpopulation, the susceptible aware HIV sub-population, the infected sub-population, the pre-AIDS sub-population, the ARV treatment sub-population, the AIDS sub-population, and unlikely to be infected with HIV/AIDS sub-population. In this mathematical model, two equilibrium points are obtained, namely the disease-free equilibrium point and the disease-endemic equilibrium point and the basic reproduction number . The stability analysis shows that the disease-free equilibrium point is locally asymptotically stable if and the disease-endemic equilibrium point is locally asymptotically stable if . Numerical simulations of the equilibrium points are carried out to provide an overview of the analyzed results with parameter values from several sources. Based on the sensitivity analysis, the parameters that significantly affect the spread of HIV/AIDS are the contact rate of HIV-unaware individuals with infected individuals and the transmission rate of HIV infection

High-security multidimensional data protection system based on the Hartley algorithm-driven chaotic scheme

This paper proposes a high-security multidimensional data protection system based on the Hartley algorithm-driven chaotic scheme. We utilize the fast Hartley algorithm instead of the fast fourier computation, and we employ chaotic sequences generated by the multi-winged chaotic system to achieve chaos-driven 3D constellation mapping, effectively integrating the chaotic system with the stochastic amplitude modulator. We reduce the signal’s peak-to-average power ratio (PAPR) by deploying a random amplitude modulator. Simultaneously, this approach enhances the security of the physical layer of the signal. The PAPR reduction can reach up to 2.6 dB, while the most robust and stable modulator scheme can gain 2 dB. Finally, in the Hartley frequency domain, the signal's frequency is disrupted, providing the entire system with a key space of 10131 to resist violent cracking and thus improving the system's overall security. To validate the feasibility of our scheme in comparison to conventional IFFT-based encrypted 3D orthogonal frequency division multiplexing, We achieved a transmission rate of 27.94 Gb/s over a 2 km multicore fiber. Experimental results show that since the random amplitude generator effectively reduces PAPR, our proposed encryption scheme increases the forward error correction threshold range by 1.1 dB, verifying that our proposed scheme has highly reliable security performance.

Antifungal activity of alginate coatings with essential oil of Mexican oregano incorporated in the stem of tomatoes

SummaryAdding natural antimicrobials such as essential oils (EOs) to alginate coatings on fruits provides an antifungal effect and a semipermeable water vapour barrier. This work aims to evaluate the antifungal effect of Lippia berlandieri S. (Mexican oregano) EO incorporated into alginate to coat tomato stems inoculated with Penicillium commune, Fusarium spp., or Cladosporium herbarum. Alginate films and coatings with EO concentrations (0%, 0.25%, 0.75%, 1%, 2%, or 4% v/v) were prepared to evaluate their properties (physical, mechanical, and water vapour transmission rates) as well as their effect on mould growth on tomato stems for 28 days during refrigerated storage. Mould growth was described with probabilistic and time‐to‐growth predictive models. Two treatment types were assessed (tomato inoculated and coated, TIC, and tomato coated and inoculated, TCI) to provide information about the moment of mould contamination (before or after coating). EO concentration influenced the alginate films' physical, mechanical, and barrier properties. Testing the coatings against moulds revealed varying inhibitory effects. Fusarium spp. exhibited the highest resistance, while C. herbarum was the most susceptible. The predictive models appropriately described the probability of growth or the time‐to‐growth of the studied moulds, identifying critical concentrations of oregano EO needed to inhibit mould growth effectively. The findings suggest that alginate coatings with oregano EO can serve as a natural and effective antifungal treatment for tomatoes, offering insights into optimal concentrations and application methods for extended shelf life.

Asymptotic profiles of a nonlocal dispersal SIS epidemic model with saturated incidence

Infection mechanism plays a significant role in epidemic models. To investigate the influence of saturation effect, a nonlocal (convolution) dispersal susceptible-infected-susceptible epidemic model with saturated incidence is considered. We first study the impact of dispersal rates and total population size on the basic reproduction number. Yang, Li and Ruan (J. Differ. Equ. 267 (2019) 2011–2051) obtained the limit of basic reproduction number as the dispersal rate tends to zero or infinity under the condition that a corresponding weighted eigenvalue problem has a unique positive principal eigenvalue. We remove this additional condition by a different method, which enables us to reduce the problem on the limiting profile of the basic reproduction number into that of the spectral bound of the corresponding operator. Then we establish the existence and uniqueness of endemic steady states by a equivalent equation and finally investigate the asymptotic profiles of the endemic steady states for small and large diffusion rates to provide reference for disease prevention and control, in which the lack of regularity of the endemic steady state and Harnack inequality makes the limit function of the sequence of the endemic steady state hard to get. Finally, we find whether lowing the movements of susceptible individuals can eradicate the disease or not depends on not only the sign of the difference between the transmission rate and the recovery rate but also the total population size, which is different from that of the model with standard or bilinear incidence.

Vector competence of Swedish Culex pipiens mosquitoes for Japanese encephalitis virus

BackgroundJapanese encephalitis virus (JEV) is an emerging mosquito-borne Orthoflavivirus that poses a significant public health risk in many temperate and tropical regions in Asia. Since the climate in some endemic countries is similar to temperate climates observed in Europe, understanding the role of specific mosquito species in the transmission of JEV is essential for predicting and effectively controlling the potential for the introduction and establishment of JEV in Europe.MethodsThis study aimed to investigate the vector competence of colonized Culex pipiens biotype molestus mosquitoes for JEV. The mosquitoes were initially collected from the field in southern Sweden. The mosquitoes were offered a blood meal containing the Nakayama strain of JEV (genotype III), and infection rates, dissemination rates, and transmission rates were evaluated at 14, 21, and 28 days post-feeding.ResultsThe study revealed that colonized Swedish Cx. pipiens are susceptible to JEV infection, with a stable infection rate of around 10% at all timepoints. However, the virus was only detected in the legs of one mosquito at 21 days post-feeding, and no mosquito saliva contained JEV.Conclusions Overall, this research shows that Swedish Cx. pipiens can become infected with JEV, and emphasizes the importance of further understanding of the thresholds and barriers for JEV dissemination in mosquitoes.Graphical

Viral load suppression and its predictor among HIV seropositive people who receive enhanced adherence counseling at public health institutions in Bahir Dar, Northwest Ethiopia. Retrospective follow-up study.

For those HIV seropositive people with high viral loads, the World Health Organization recommends more counseling before changing ART regimens. A high viral load can lead to increased HIV transmission and lower survival rates. Clients with viral loads above 1000 copies/mL should receive enhanced adherence counseling for 3-6 months before switching. Despite enhanced adherence counseling programs, most countries struggle with viral load suppression. Little is known about viral load suppression in Ethiopia and the research area after counseling. This study aims to assess viral load suppression and its predictors among HIV-positive individuals receiving enhanced adherence counseling in Bahir Dar, Northwest Ethiopia, in 2022. An institution-based retrospective follow-up study was conducted among randomly selected 546 clients on Enhanced Adherence Counseling at public health facilities in Bahir Dar city. The Epicollect5 mobile application was used to collect the data, which was then exported to Stata version 14 for analysis. A Log-Binomial regression model was fitted for each explanatory variable. Variables having a p-value <0.25 in bivariate analysis were entered into a multivariable Log-Binomial regression model. Finally, an adjusted risk ratio with a 95% confidence interval and a p-value <0.05 was used to measure the strength of the prediction. Following enhanced adherence counseling, 312 (57.1%) people had their viral load suppressed. Absence of recurrent OI (ARR 1.40; CI 1.03-1.91), EAC stay less than 3 months (ARR 1.54; CI 1.19-1.99), EAC stay 3-6 months (ARR 1.38; CI 1.12-1.69), once-daily ARV dose regimen (ARR 1.28; CI 1.03-1.58), baseline viral load of 2879.00 copies/ml (ARR 1.30, CI 1.06-1.60), being orthodox Tewahido Christian (ARR 0.37; CI 0.18-0.75) were significant predictors of viral load suppression after Enhanced Adherence Counseling. Most importantly, this study found that most people had suppressed viral loads after receiving enhanced adherence counseling. Significant predictors of viral load suppression included recurrent OI, length of stay on EAC, daily ARV dosing regimen, baseline viral load, and religion. Clients with a high baseline viral load and those who experience recurring opportunistic infections should get extra care during EAC sessions.

Flip bifurcation analysis and mathematical modeling of cholera disease by taking control measures

To study the dynamical system, it is necessary to formulate the mathematical model to understand the dynamics of various diseases which are spread in the world wide. The objective of the research study is to assess the early diagnosis and treatment of cholera virus by implementing remedial methods with and without the use of drugs. A mathematical model is built with the hypothesis of strengthening the immune system, and a ABC operator is employed to turn the model into a fractional-order model. A newly developed system SEIBR, which is examined both qualitatively and quantitatively to determine its stable position as well as the verification of flip bifurcation has been made for developed system. The local stability of this model has been explored concerning limited observations, a fundamental aspect of epidemic models. We have derived the reproductive number using next generation method, denoted as “R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_{0}$$\\end{document}”, to analyze its impact rate across various sub-compartments, which serves as a critical determinant of its community-wide transmission rate. The sensitivity analysis has been verified according to its each parameters to identify that how much rate of change of parameters are sensitive. Atangana–Toufik scheme is employed to find the solution for the developed system using different fractional values which is advanced tool for reliable bounded solution. Also the error analysis has been made for developed scheme. Simulations have been made to see the real behavior and effects of cholera disease with early detection and treatment by implementing remedial methods without the use of drugs in the community. Also identify the real situation the spread of cholera disease after implementing remedial methods with and without the use of drugs. Such type of investigation will be useful to investigate the spread of virus as well as helpful in developing control strategies from our justified outcomes.

IMPACT OF 5G TECHNOLOGY ON SATELLITE COMMUNICATION: A PARADIGM SHIFT IN TELECOMMUNICATIONS WITH A FOCUS ON CYBERSECURITY CHALLENGES AND SOLUTIONS

This review investigates the transformative impact of 5G technology on satellite communication, with a particular focus on the cybersecurity challenges introduced by this integration. An analysis of 50 rigorously selected scholarly articles demonstrates that 5G significantly enhances satellite communication by improving data transmission rates, reducing latency, and increasing network efficiency, thereby facilitating extended coverage that bridges the digital divide by delivering high-speed internet to remote areas. Additionally, 5G supports the deployment of new applications such as enhanced Mobile Broadband (eMBB) and extensive Internet of Things (IoT) connectivity. However, this integration also introduces new cybersecurity challenges, such as increased vulnerability to cyber-attacks and the need for robust encryption methods to secure data transmissions. Technical issues like signal interference, regulatory hurdles involving spectrum sharing, and substantial economic investments for infrastructure development also pose significant challenges. These complexities require ongoing research and strategic planning to mitigate risks and fully harness the potential of 5G-enhanced satellite networks. The study highlights a paradigm shift in satellite communications, propelled by 5G's capabilities to create more inclusive, efficient, and secure global communication networks.