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The DOE JGI Metagenome Workflow is designed for processing metagenomic data sets starting from Illumina fastq files. It performs data preprocessing, error correction, assembly, structural and functional annotation, and binning. The DOE Joint Genome Institute (JGI) Metagenome Workflow performs metagenome data processing, including assembly; structural, functional, and taxonomic annotation; and binning of metagenomic data sets that are subsequently included into the Integrated Microbial Genomes and Microbiomes (IMG/M) (I.-M. A. Chen, K. Chu, K. Palaniappan, A. Ratner, et al., Nucleic Acids Res, 49:D751–D763, 2021, https://doi.org/10.1093/nar/gkaa939 ) comparative analysis system and provided for download via the JGI data portal ( https://genome.jgi.doe.gov/portal/ ). This workflow scales to run on thousands of metagenome samples per year, which can vary by the complexity of microbial communities and sequencing depth. Here, we describe the different tools, databases, and parameters used at different steps of the workflow to help with the interpretation of metagenome data available in IMG and to enable researchers to apply this workflow to their own data. We use 20 publicly available sediment metagenomes to illustrate the computing requirements for the different steps and highlight the typical results of data processing. The workflow modules for read filtering and metagenome assembly are available as a workflow description language (WDL) file ( https://code.jgi.doe.gov/BFoster/jgi_meta_wdl ). The workflow modules for annotation and binning are provided as a service to the user community at https://img.jgi.doe.gov/submit and require filling out the project and associated metadata descriptions in the Genomes OnLine Database (GOLD) (S. Mukherjee, D. Stamatis, J. Bertsch, G. Ovchinnikova, et al., Nucleic Acids Res, 49:D723–D733, 2021, https://doi.org/10.1093/nar/gkaa983 ). IMPORTANCE The DOE JGI Metagenome Workflow is designed for processing metagenomic data sets starting from Illumina fastq files. It performs data preprocessing, error correction, assembly, structural and functional annotation, and binning. The results of processing are provided in several standard formats, such as fasta and gff, and can be used for subsequent integration into the Integrated Microbial Genomes and Microbiomes (IMG/M) system where they can be compared to a comprehensive set of publicly available metagenomes. As of 30 July 2020, 7,155 JGI metagenomes have been processed by the DOE JGI Metagenome Workflow. Here, we present a metagenome workflow developed at the JGI that generates rich data in standard formats and has been optimized for downstream analyses ranging from assessment of the functional and taxonomic composition of microbial communities to genome-resolved metagenomics and the identification and characterization of novel taxa. This workflow is currently being used to analyze thousands of metagenomic data sets in a consistent and standardized manner.

Main conclusionGenomic selection and its importance in crop breeding. Integration of GS with new breeding tools and developing SOP for GS to achieve maximum genetic gain with low cost and time.The success of conventional breeding approaches is not sufficient to meet the demand of a growing population for nutritious food and other plant-based products. Whereas, marker assisted selection (MAS) is not efficient in capturing all the favorable alleles responsible for economic traits in the process of crop improvement. Genomic selection (GS) developed in livestock breeding and then adapted to plant breeding promised to overcome the drawbacks of MAS and significantly improve complicated traits controlled by gene/QTL with small effects. Large-scale deployment of GS in important crops, as well as simulation studies in a variety of contexts, addressed G × E interaction effects and non-additive effects, as well as lowering breeding costs and time. The current study provides a complete overview of genomic selection, its process, and importance in modern plant breeding, along with insights into its application. GS has been implemented in the improvement of complex traits including tolerance to biotic and abiotic stresses. Furthermore, this review hypothesises that using GS in conjunction with other crop improvement platforms accelerates the breeding process to increase genetic gain. The objective of this review is to highlight the development of an appropriate GS model, the global open source network for GS, and trans-disciplinary approaches for effective accelerated crop improvement. The current study focused on the application of data science, including machine learning and deep learning tools, to enhance the accuracy of prediction models. Present study emphasizes on developing plant breeding strategies centered on GS combined with routine conventional breeding principles by developing GS-SOP to achieve enhanced genetic gain.

Vehicular communication has been envisioned to support a myriad of essential fifth-generation and beyond use-cases. However, the increasing proliferation of smart and intelligent vehicles has generated a lot of design and infrastructure challenges. Of particular interest are the problems of spectrum scarcity and communication security. Consequently, we considered a cognitive radio-enabled vehicular network framework for accessing additional radio spectrum and exploit physical layer security for secure communications. In particular, we investigated the secrecy performance of a cognitive radio vehicular network, where all the nodes in the network are moving vehicles and the channels between them are modeled as double-Rayleigh fading. Furthermore, adopting an underlay approach, the communication between secondary nodes can be performed by employing two interference constraint strategies at the primary receiver; (1) Strategy I: the secondary transmitter power is constrained by the interference threshold of the primary receiver, and (2) Strategy II: the secondary transmitter power is constrained by both the interference threshold of the primary receiver and the maximum transmit power of the secondary network. Under the considered strategies, we derive the exact secrecy outage probability (SOP) and ergodic secrecy capacity (ESC) expressions over double-Rayleigh fading. Moreover, by analyzing the asymptotic SOP behavior, we show that a full secrecy diversity of 1 can be achieved, when the average channel gain of the main link goes to infinity with a fixed average wiretap channel gain. From the ESC analysis, it is revealed that the ESC follows a scaling law of ΘlnΩm2Ωe2 for large Ωm and Ωe, where Ωm and Ωe are the average channel gains of the main link and wiretap link. The numerical and simulation results verify our analytical findings.

Speed of Processing (SoP) represents a fundamental limiting step in cognitive performance which may underlie General Intelligence. The measure of SoP is particularly sensitive to aging, neurological or cognitive diseases, and has become a benchmark for diagnosis, cognitive remediation, and enhancement. Neural efficiency of the Dorsolateral Prefrontal Cortex (DLPFC) is proposed to account for individual differences in SoP. However, the mechanisms by which DLPFC efficiency is shaped by training and whether it can be enhanced remain elusive. To address this, we monitored the brain activity of sixteen healthy participants using functional Near Infrared Spectroscopy (fNIRS) while practicing a common SoP task (Symbol Digit Substitution Task) across 4 sessions. Furthermore, in each session, participants received counterbalanced excitatory repetitive transcranial magnetic stimulation (rTMS) during mid-session breaks. Results indicate a significant involvement of the left-DLPFC in SoP, whose neural efficiency is consistently increased through task practice. Active neurostimulation, but not Sham, significantly enhanced the neural efficiency. These findings suggest a common mechanism by which neurostimulation may aid to accelerate learning. •Left-DLPFC activity is associated with Symbol-Digit Performance.•Practice of SDST increases neural efficiency.•Excitatory rTMS to left-DLPFC further increases neural efficiency.•Neuroimaging may help evaluate the effects of neurostimulation paradigms.

In this paper, we investigate the secrecy outage performance for the two-way integrated satellite unmanned aerial vehicle relay networks with hardware impairments. Particularly, the closed-form expression for the secrecy outage probability is obtained. Moreover, to get more information on the secrecy outage probability in a high signal-to-noise regime, the asymptotic analysis along with the secrecy diversity order and secrecy coding gain for the secrecy outage probability are also further obtained, which presents a fast method to evaluate the impact of system parameters and hardware impairments on the considered network. Finally, Monte Carlo simulation results are provided to show the efficiency of the theoretical analysis.

In series and parallel strings connected Lithium-ion (Li-ion) battery modules or packs, it is essential to equalise each Li-ion cell to enhance the power delivery performance and usable capacity, otherwise, it is restricted by the worst cell in the string. An active cell balancing algorithm based on Charging State-of-Power (CSoP) and Discharging State-of-Power (DSoP) derived from the dynamically estimated State-of-Charge (SoC) or State-of-Health (SoH) is proposed to handle the problem of cell imbalance during both charging and discharging operation. Compared with the voltage-based and SoC -based cell equalization algorithms, the proposed algorithm determines cell imbalance using State-of-Power (SoP) invariance among cells in the battery pack, which allows the Battery Management System (BMS) to regulate the power flow of the Electric Vehicle (EV) with minimum balancing efforts and fully charge/discharge each cell in the battery pack. This ensures the better performance of the proposed cell balancing as compared to other (Voltage/ SoC- based) balancing in maximizing the battery pack capacity and minimizing balancing losses. To validate the efficacy of the novel SoP -based cell equalization algorithm, a simulation is conducted in which a Li-ion battery model is built in MATLAB/Simulink platform. The simulation results show that the usable capacity using the proposed SoP -based method is improved by 16% as compared to the usable capacity of the battery pack without-balancing. An experimental setup using four Li-ion cells is also executed to explore the stability, robustness, and precision of the proposed cell balancing algorithm. The parameters of cells differ in capacity and initial SoC from each other to resemble the imbalance among the cells in the battery pack.

The rapid growth in the technological advancements of the smartphone industry has classified contemporary smartphones as a low-cost and high quality indoor positioning tools requiring no additional infrastructure or equipment. In recent years, the fine time measurement (FTM) protocol, achieved through the Wi-Fi round trip time (RTT) observable, available in the most recent models, has gained the interest of many research teams worldwide, especially those concerned with indoor localization problems. However, as the Wi-Fi RTT technology is still new, there is a limited number of studies addressing its potential and limitations relative to the positioning problem. This paper presents an investigation and performance evaluation of Wi-Fi RTT capability with a focus on range quality assessment. A set of experimental tests was carried out, considering 1D and 2D space, operating different smartphone devices at various operational settings and observation conditions. Furthermore, in order to address device-dependent and other type of biases in the raw ranges, alternative correction models were developed and tested. The obtained results indicate that Wi-Fi RTT is a promising technology capable of achieving a meter-level accuracy for ranges both in line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, subject to suitable corrections identification and adaptation. From 1D ranging tests, an average mean absolute error (MAE) of 0.85 m and 1.24 m is achieved, for LOS and NLOS conditions, respectively, for 80% of the validation sample data. In 2D-space ranging tests, an average root mean square error (RMSE) of 1.1m is accomplished across the different devices. Furthermore, the analysis has shown that the selection of the bandwidth and the initiator–responder pair are crucial for the correction model selection, whilst knowledge of the type of operating environment (LOS and/or NLOS) can further contribute to Wi-Fi RTT range performance enhancement.

The volume of confidential information transmitted over 5G networks has increased rapidly due to the widespread adoption of large machine-type communication and Internet of Things (IoT) devices. Secrecy outage probability (SOP) and strictly positive secrecy capacity (SPSC) parameters are crucial parameters used in evaluating the security of wireless systems, particularly in situations where maintaining secrecy is essential. Also, Non-orthogonal multiple access (NOMA) has the potential to improve the performance of wireless communication systems due to its higher spectral efficiency, improved fairness in resource allocation, and enhanced coverage and connectivity. In this paper, we investigate the secrecy performance of unmanned aerial vehicles (UAV) assisted cooperative NOMA system with a half duplex protocol based amplify and forward relay over the Rayleigh fading channel in presence of two eavesdroppers for downlink communication. We derive SOP and SPSC of the proposed system model and analyze its performance in terms of the illegal SNR of eavesdroppers, power allocation coefficient, information rates and Rayleigh channel parameters. Simulation results demonstrate that SOP decreases with a higher value of power allocation coefficient and lower values of the illegal SNR of eavesdropper and lower information rates. SPSC increases with high values of power allocation coefficient of far destination and decreases with lower values of illegal SNR of eavesdroppers and Rayleigh channel parameters. Analytical simulations are verified using Monte Carlo simulations.

This paper reviews the state of emerging transistor technologies capable of terahertz amplification, as well as the state of transistor modeling as required in terahertz electronic circuit research. Commercial terahertz radar sensors of today are being built using bulky and expensive technologies such as Schottky diode detectors and lasers, as well as using some emerging detection methods. Meanwhile, a considerable amount of research effort has recently been invested in process development and modeling of transistor technologies capable of amplifying in the terahertz band. Indium phosphide (InP) transistors have been able to reach maximum oscillation frequency (fmax) values of over 1 THz for around a decade already, while silicon-germanium bipolar complementary metal-oxide semiconductor (BiCMOS) compatible heterojunction bipolar transistors have only recently crossed the fmax = 0.7 THz mark. While it seems that the InP technology could be the ultimate terahertz technology, according to the fmax and related metrics, the BiCMOS technology has the added advantage of lower cost and supporting a wider set of integrated component types. BiCMOS can thus be seen as an enabling factor for re-engineering of complete terahertz radar systems, for the first time fabricated as miniaturized monolithic integrated circuits. Rapid commercial deployment of monolithic terahertz radar chips, furthermore, depends on the accuracy of transistor modeling at these frequencies. Considerations such as fabrication and modeling of passives and antennas, as well as packaging of complete systems, are closely related to the two main contributions of this paper and are also reviewed here. Finally, this paper probes active terahertz circuits that have already been reported and that have the potential to be deployed in a re-engineered terahertz radar sensor system and attempts to predict future directions in re-engineering of monolithic radar sensors.

Over the last decades, biosecurity has received increasing attention in veterinary medicine and was recently integrated as a competency for One Health field epidemiology framework by international bodies. It is also a standard in the European System of Evaluation of Veterinary Training and in the accreditation of veterinary colleges by the American Veterinary Medical Association Council on Education. To help veterinary students and staff acquire biosecurity skills within veterinary education establishments, we first develop animal biosecurity research, and we spread its results through four interconnected instruments: biosecurity standard operating policies and procedures, a dedicated biosecurity website, an annual biosecurity day, and the production of checklists to assess the biosecurity level of compliance. The use of biosecurity standard operating procedures, the number of visits on the faculty biosecurity website, the number of people trained, and regular biosecurity audits performed are all factors that have contributed to the animal biosecurity to comply with the requirements of the European Association of Establishments for Veterinary Education and by the Council on Outcomes-based Veterinary Education, in the CBVE 2.0 book published by the American Association of Veterinary Medical Colleges. These approaches also contribute to the acquisition and maintenance of the accreditation delivered by the ad hoc bodies. The participation of students in the process allows a better comprehension and appropriation of animal biosecurity.