Improving BER Performance of Massive MIMO Scheme over Rayleigh Fading Channel

In massive multiple input multiple output (mMIMO) scheme, the system capacity can be improved without additional bandwidth or transmit power by using a huge antenna array at base station with as much separation between antenna elements as possible. Unfortunately, its performance depends on having a perfect channel state estimate between the base state and the users. In this paper, the bit error rate (BER) performance of a mMIMO scheme is improved using genetic algorithm-based optimization with simulation performed in MATLAB software environment. The genetic algorithm used selects the best signal required for effective transmission. Four different antenna configurations in the order of 2x2, 4x4, 8x8 and 16x16 were considered for the simulation. The encoding and decoding were done using an STBC coded. Also, filter bank multicarrier-offset quadrature amplitude modulation (FBMC-OQAM) scheme was used and simulation was carried out for 4-FBMC-OQAM, 16 FBMC-OQAM, and 64 FBMC-OQAM order. The BER is computed for both the optimized and un-optimized mMIMO schemes, and the performance of both schemes is compared. Simulation results show a significant improvement in the BER of the optimized mMIMO compared to the normal (coded) MIMO scheme. The overall results show that the optimized mMIMO experience a reduced BER when compared to the normal mMIMO. In both cases, the BER reduces gradually as the number of antenna increases.

Prioritizing interventions for preventing COVID-19 outbreaks in military basic training

Like other congregate living settings, military basic training has been subject to outbreaks of COVID-19. We sought to identify improved strategies for preventing outbreaks in this setting using an agent-based model of a hypothetical cohort of trainees on a U.S. Army post. Our analysis revealed unique aspects of basic training that require customized approaches to outbreak prevention, which draws attention to the possibility that customized approaches may be necessary in other settings, too. In particular, we showed that introductions by trainers and support staff may be a major vulnerability, given that those individuals remain at risk of community exposure throughout the training period. We also found that increased testing of trainees upon arrival could actually increase the risk of outbreaks, given the potential for false-positive test results to lead to susceptible individuals becoming infected in group isolation and seeding outbreaks in training units upon release. Until an effective transmission-blocking vaccine is adopted at high coverage by individuals involved with basic training, need will persist for non-pharmaceutical interventions to prevent outbreaks in military basic training. Ongoing uncertainties about virus variants and breakthrough infections necessitate continued vigilance in this setting, even as vaccination coverage increases.

Molecular interactions between parasite and mosquito during midgut invasion as targets to block malaria transmission

Despite considerable effort, malaria remains a major public health burden. Malaria is caused by five Plasmodium species and is transmitted to humans via the female Anopheles mosquito. The development of malaria vaccines against the liver and blood stages has been challenging. Therefore, malaria elimination strategies advocate integrated measures, including transmission-blocking approaches. Designing an effective transmission-blocking strategy relies on a sophisticated understanding of the molecular mechanisms governing the interactions between the mosquito midgut molecules and the malaria parasite. Here we review recent advances in the biology of malaria transmission, focusing on molecular interactions between Plasmodium and Anopheles mosquito midgut proteins. We provide an overview of parasite and mosquito proteins that are either targets for drugs currently in clinical trials or candidates of promising transmission-blocking vaccines.

A generic method and software to estimate the transmission advantage of pathogen variants in real-time : SARS-CoV-2 as a case-study

Recent months have demonstrated that emerging variants may set back the global COVID-19 response. The ability to rapidly assess the threat of new variants in real-time is critical for timely optimisation of control strategies. We extend the EpiEstim R package, designed to estimate the time-varying reproduction number (Rt), to estimate in real-time the effective transmission advantage of a new variant compared to a reference variant. Our method can combine information across multiple locations and over time and was validated using an extensive simulation study, designed to mimic a variety of real-time epidemic contexts. We estimate that the SARS-CoV-2 Alpha variant is 1.46 (95% Credible Interval 1.44-1.47) and 1.29, (95% CrI 1.29-1.30) times more transmissible than the wild type, using data from England and France respectively. We further estimate that Beta and Gamma combined are 1.25 (95% CrI 1.24-1.27) times more transmissible than the wildtype (France data). All results are in line with previous estimates from literature, but could have been obtained earlier and more easily with our off-the-shelf open-source tool. Our tool can be used as an important first step towards quantifying the threat of new variants in real-time. Given the popularity of EpiEstim, this extension will likely be used widely to monitor the co-circulation and/or emergence of multiple variants of infectious pathogens.

MiA-CODER: A Multi-Intelligent Agent-Enabled Reinforcement Learning for Accurate Coverage Hole Detection and Recovery in Unequal Cluster-Tree-Based QoSensing WSN

Coverage is an important factor for the effective transmission of data in the wireless sensor networks. Normally, the formation of coverage holes in the network deprives its performance and reduces the lifetime of the network. In this paper, a multi-intelligent agent enabled reinforcement learning-based coverage hole detection and recovery (MiA-CODER) is proposed in order to overcome the existing challenges related to coverage of the network. Initially, the formation of coverage holes is prevented by optimizing the energy consumption in the network. This is performed by constructing the unequal Sierpinski cluster-tree topology (USCT) and the cluster head is selected by implementing multi-objective black widow optimization (MoBWo) to facilitate the effective transmission of data. Further, the energy consumption of the nodes is minimized by performing dynamic sleep scheduling in which Tsallis entropy enabled Bayesian probability (TE2BP) is implemented to switch the nodes between active and sleep mode. Then, the coverage hole detection and repair are carried out in which the detection of coverage holes if any, both inside the cluster and between the clusters, is completed by using the virtual sector-based hole detection (ViSHD) protocol. Once the detection is over, the BS starts the hole repair process by using a multi-agent SARSA algorithm which selects the optimal mobile node and replaces it to cover the hole. By doing so, the coverage of the network is enhanced and better QoSensing is achieved. The proposed approach is simulated in NS 3.26 and evaluated in terms of coverage rate, number of dead nodes, average energy consumption and throughput.

Sexual Development in Non-Human Parasitic Apicomplexa: Just Biology or Targets for Control?

The phylum Apicomplexa is a major group of protozoan parasites including gregarines, coccidia, haemogregarines, haemosporidia and piroplasms, with more than 6000 named species. Three of these subgroups, the coccidia, hemosporidia, and piroplasms, contain parasites that cause important diseases of humans and animals worldwide. All of them have complex life cycles involving a switch between asexual and sexual reproduction, which is key to their development. Fertilization (i.e., fusion of female and male cells) results in the formation of a zygote that undergoes meiosis, forming a new generation of asexual stages. In eukaryotes, sexual reproduction is the predominant mode of recombination and segregation of DNA. Sex is well documented in many protist groups, and together with meiosis, is frequently linked with transmission to new hosts. Apicomplexan sexual stages constitute a bottleneck in the life cycle of these parasites, as they are obligatory for the development of new transmissible stages. Consequently, the sexual stages represent attractive targets for vaccination. Detailed understanding of apicomplexan sexual biology will pave the way for the design and implementation of effective transmission-blocking strategies for parasite control. This article reviews the current knowledge on the sexual development of Apicomplexa and the progress in transmission-blocking vaccines for their control, their advantages and limitations and outstanding questions for the future.

An Effective Transmission Scheme Based on Early Congestion Detection for Information-Centric Network

As one of the candidates for future network architecture, Information-Centric Networking (ICN) has revolutionized the manner of content retrieval by transforming the communication mode from host-centric to information-centric. Unlike a traditional TCP/IP network, ICN uses a location-independent name to identify content and takes a receiver-driven model to retrieve the content. Moreover, ICN routers not only perform a forwarding function but also act as content providers due to pervasive in-network caching. The network traffic is more complicated and routers are more prone to congestion. These distinguished characteristics pose new challenges to ICN transmission control mechanism. In this paper, we propose an effective transmission scheme by combining the receiver-driven transport protocol and the router-driven congestion detection mechanism. We first outline the process of content retrieval and transmission in an IP-compatible ICN architecture and propose a practical receiver-driven transport protocol. Then, we present an early congestion detection mechanism applied on ICN routers based on an improved Active Queue Management (AQM) algorithm and design a receiver-driven congestion control algorithm. Finally, experiment results show that the proposed transmission scheme can maintain high bandwidth utilization and significantly reduce transmission delay and packet loss rate.

Limited genomic reconstruction of SARS-CoV-2 transmission history within local epidemiological clusters

A detailed understanding of how and when SARS-CoV-2 transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced 49 SARS-CoV-2 patient samples from ten local clusters for which partial epidemiological information was available, and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be 1-2 viral particles for sample pairs whose donor-recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.