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In the last decade, the market share and user base of social media applications have witnessed significant growth. However, this surge in popularity has inadvertently drawn the attention of criminals aiming to exploit these platforms for illicit activities. The forensic examination of these applications emerges as a pivotal avenue for uncovering valuable insights into criminal behavior and identifying suspects. Discord, a social media platform, has become a significant focal point for such illicit activities. In this paper, we examine the remnants of Discord on both Windows and Linux operating systems, employing storage, memory, and network analysis techniques to review the remnants of Discord. Our investigation reveals a range of crucial artifacts that have been successfully recovered across all three areas of analysis, including login and payment details, chat history, account information, and much more. Collectively, these artifacts constitute a valuable resource for forensic investigations, allowing the reconstruction of most of the user's activity. [ABSTRACT FROM AUTHOR]

This article presents the hardware and software architectures used to implement the Modbus Extension (ModbusE) IIoT gateway, the performance of the acquisition cycle at the PRU real-time programmable core level, the acquisition cycle communication flow—dispatcher—OPC UA server (Linux)—OPC UA client (Windows) as well as the performance analysis of data communications between the IIoT ModbusE gateway and the OPC UA client (Windows). In order to be able to implement both the ModbusE acquisition cycle and the OPC UA server, the BeagleBone Black Board was chosen as the hardware platform. This board uses the Sitara AM335x processor (Texas Instruments (TI), Dallas, TX, USA) from Texas Instruments. Thus, the acquisition cycle was implemented on the PRU0 real-time core, and the OPC UA server, running under the Linux operating system, was implemented on the ARM Cortex A8 processor. From the analysis of the communication speed of the messages between the OPC UA client and the ModbusE servers, it was found that the ModbusE acquisition cycle speed was higher than the acquisition speed of the OPC UA client. [ABSTRACT FROM AUTHOR]

Phylogenetic trees illustrate evolutionary relationships between taxa or genes. Tree figures are crucial when presenting results and data, and by creating clear and effective plots, researchers can describe many kinds of evolutionary patterns. However, producing tree plots can be a time‐consuming task, especially as multiple different programs are often needed to adjust and illustrate all data associated with a tree. We present TreeViewer, a new software to draw phylogenetic trees. TreeViewer is flexible, modular, and user‐friendly. Plots are produced as the result of a user‐defined pipeline, which can be finely customised and easily applied to different trees. Every feature of the program is documented and easily accessible, either in the online manual or within the program's interface. We show how TreeViewer can be used to produce publication‐ready figures, saving time by not requiring additional graphical post‐processing tools. TreeViewer is freely available for Windows, macOS, and Linux operating systems and distributed under an AGPLv3 licence from https://treeviewer.org. It has a graphical user interface (GUI), as well as a command‐line interface, which is useful to work with very large trees and for automated pipelines. A detailed user manual with examples and tutorials is also available. TreeViewer is mainly aimed at users wishing to produce highly customised, publication‐quality tree figures using a single GUI software tool. Compared to other GUI tools, TreeViewer offers a richer feature set and a finer degree of customisation. Compared to command‐line‐based tools and software libraries, TreeViewer's graphical interface is more accessible. The flexibility of TreeViewer's approach to phylogenetic tree plotting enables the program to produce a wide variety of publication‐ready figures. Users are encouraged to create their own custom modules to expand the functionalities of the program. This sets the scene for an ever‐expanding and ever‐adapting software framework that can easily adjust to respond to new challenges. [ABSTRACT FROM AUTHOR]

This work evaluates the use of a programmable logic controller (PLC) from Phoenix Contact's PLCnext ecosystem as an image processing platform. PLCnext controllers provide the functions of "classical" industrial controllers, but they are based on the Linux operating system, also allowing for the use of software tools usually associated with computers. Visual processing applications in the Python programming language using the OpenCV library are implemented in the PLC using this feature. This research is focused on evaluating the use of this PLC as an image processing platform, particularly for industrial machine vision applications. The methodology is based on comparing the PLC's performance against a computer using standard image processing algorithms. In addition, a demonstration application based on a real-world scenario for quality control by visual inspection is presented. It is concluded that despite significant limitations in processing power, the simultaneous use of the PLC as an industrial controller and image processing platform is feasible for applications of low complexity and undemanding cycle times, providing valuable insights and benchmarks for the scientific community interested in the convergence of industrial automation and computer vision technologies. [ABSTRACT FROM AUTHOR]

Creotech Instruments is advancing a game-changing sCMOS camera series. The Final Prototype Model of an astronomical camera for Space Surveillance and Tracking (SST) is in the test campaign phase. Designed for SST, NEO, and debris detection, its adaptable platform suits quantum tech and biological microscopy. Edge computing sets it apart, leveraging FPGA-based SoC for real-time processing and Linux-based pre-processing. Operating autonomously, it supports on-camera ML algorithms, revolutionizing astronomy. Data pre-processing, like frame stacking, reduces data load. This paper introduces the camera's concept, architecture, and prototype test results, emphasizing specific use cases and future product line development. [ABSTRACT FROM AUTHOR]

Sequence motif discovery algorithms enhance the identification of novel deoxyribonucleic acid sequences with pivotal biological significance, especially transcription factor (TF)-binding motifs. The advent of assay for transposase-accessible chromatin using sequencing (ATAC-seq) has broadened the toolkit for motif characterization. Nonetheless, prevailing computational approaches have focused on delineating TF-binding footprints, with motif discovery receiving less attention. Herein, we present Cis rEgulatory Motif Influence using de Bruijn Graph (CEMIG), an algorithm leveraging de Bruijn and Hamming distance graph paradigms to predict and map motif sites. Assessment on 129 ATAC-seq datasets from the Cistrome Data Browser demonstrates CEMIG's exceptional performance, surpassing three established methodologies on four evaluative metrics. CEMIG accurately identifies both cell-type-specific and common TF motifs within GM12878 and K562 cell lines, demonstrating its comparative genomic capabilities in the identification of evolutionary conservation and cell-type specificity. In-depth transcriptional and functional genomic studies have validated the functional relevance of CEMIG-identified motifs across various cell types. CEMIG is available at https://github.com/OSU-BMBL/CEMIG , developed in C++ to ensure cross-platform compatibility with Linux, macOS and Windows operating systems. [ABSTRACT FROM AUTHOR]

Network attacks, such as botnets stealing sensitive data, constitute a critical concern for administrators in the Internet area. Such attacks can be prevented using a network access control (NAC) scheme. However, existing NAC mechanisms all rely on the user account mechanism provided by the operating system. Herein, we propose a protocol involving a Linux security module for user-based NAC. The module requires neither user accounts nor secure user space; it loads signed rules and keys for a user from a USB security key, securely authenticates the user, and controls network permissions directly from the Linux kernel. Moreover, we present extensions for the protocol, developed using additional authentication methods and devices (such as a smartphone), to prevent man-in-the-middle, replay, and phishing attacks. The protocol can securely authenticate users from kernel space by using USB security keys and a user smartphone despite an insecure user space, is resistant to various attacks, and can guarantee that authorized users obtain their corresponding network privileges. At the same time, the analysis of Linux operating system security enhancement technology is proposed to achieve the goal of trusting machines. Through the use of empirical algorithm analysis, enhanced virtualization technology, and other methods, the risk of hacker intrusion on information platforms is reduced in multiple aspects, and management mechanisms are used to set and use resource permissions. On the other hand, after mastering the key technologies for network blocking development in the core layer of the system, there is also an opportunity to independently build modules for the security core of operating systems in special fields and future 5G/6G SDNs. [ABSTRACT FROM AUTHOR]

This article explores the presence of biofilms on penile prostheses and challenges the assumption that biofilms are always linked to infection. The authors conducted studies that found no significant difference in biofilm composition based on the reason for removal, and that a greater variety of species was associated with a lower risk of infection. They also discovered that biofilm composition varied depending on the manufacturer of the device and the individual patient. These findings suggest that biofilms can be found on both infected and non-infected penile prostheses, and further research is needed to understand their significance and develop prevention and treatment strategies. The article also discusses the Ramon Guiteras Lecture at AUA2024, where the speaker explores the advancements in urology technology, particularly focusing on generative AI like ChatGPT. The speaker believes that urologists will find ways to utilize AI like ChatGPT to improve urological health. The text also emphasizes the accessibility and usefulness of tools such as Arduinos, Raspberry Pis, and 3D printers in teaching innovation to medical students and urological learners. These tools enable problem-solving and the creation of devices for patient care. [Extracted from the article]

"Hacking Diversity: The Politics of Inclusion in Open Technology Cultures" by Christina Dunbar-Hester explores the lack of diversity within open technology communities and the efforts of activists and social change advocates to address this issue. The book takes an ethnographic approach, focusing on the everyday practices of the respondents. It critically examines power dynamics within these communities and highlights the need for social justice. The book also discusses the limitations of representation politics and calls for a deeper understanding of global equity. Overall, "Hacking Diversity" provides valuable insights into diversity issues in the North American tech industry and serves as a useful resource for historians of technology. [Extracted from the article]

The number of Internet of Things (IoT) devices has increased dramatically in recent years, and Bluetooth technology is critical for communication between IoT devices. It is possible to protect electronic communications, the Internet of Things (IoT), and big data from malware and data theft with BlueZ's Bluetooth File Transfer Filter (BTF). It can use a configurable filter to block unauthorized Bluetooth file transfers. The BTF is available for various Linux distributions and can protect many Bluetooth-enabled devices, including smartphones, tablets, laptops, and the Internet of Things. However, the increased number and density of Bluetooth devices have also created a serious problem—the Bluetooth worm. It poses a severe threat to the security of Bluetooth devices. In this paper, we propose a Bluetooth OBEX Proxy (BOP) to filter malicious files transferred to devices via the OBEX system service in BlueZ. The method described in this article prevents illegal Bluetooth file transfers, defending big data, the Internet of Things (IoT), and electronic communications from malware and data theft. It also protects numerous Bluetooth devices, including smartphones, tablets, laptops, and the Internet of Things, with many Linux distributions. Overall, the detection findings were entirely accurate, with zero false positives and 2.29% misses. [ABSTRACT FROM AUTHOR]

Background: Antibiotic resistance is a major public health concern around the globe. As a result, researchers always look for new compounds to develop new antibiotic drugs for combating antibiotic-resistant bacteria. Bacteriocin becomes a promising antimicrobial agent to fight against antibiotic resistance, due to cases of both broad and narrow killing spectra. Sequence matching methods are widely used to identify bacteriocins by comparing them with the known bacteriocin sequences; however, these methods often fail to detect new bacteriocin sequences due to their high diversity. The ability to use a machine learning approach can help find new highly dissimilar bacteriocins for developing highly effective antibiotic drugs. The aim of this work is to develop a machine learning-based software tool called BaPreS (Bacteriocin Prediction Software) using an optimal set of features for detecting bacteriocin protein sequences with high accuracy. We extracted potential features from known bacteriocin and non-bacteriocin sequences by considering the physicochemical and structural properties of the protein sequences. Then we reduced the feature set using statistical justifications and recursive feature elimination technique. Finally, we built support vector machine (SVM) and random forest (RF) models using the selected features and utilized the best machine learning model to implement the software tool. Results: We applied BaPreS to an established dataset and evaluated its prediction performance. Acquired results show that the software tool can achieve a prediction accuracy of 95.54% for testing protein sequences. This tool allows users to add new bacteriocin or non-bacteriocin sequences in the training dataset to further enhance the predictive power of the tool. We compared the prediction performance of the BaPreS with a popular sequence matching-based tool and a deep learning-based method, and our software tool outperformed both. Conclusions: BaPreS is a bacteriocin prediction tool that can be used to discover new highly dissimilar bacteriocins for developing highly effective antibiotic drugs. This software tool can be used with Windows, Linux and macOS operating systems. The open-source software package and its user manual are available at https://github.com/suraiya14/BaPreS. [ABSTRACT FROM AUTHOR]

In the current research on data query for two-tiered WSN, the privacy-preservation range query is one of the hotspots. However, there are some problems in the existing researches in two-tiered wireless sensor networks such as high computational and communication costs for security comparison items and high energy consumption of sensing nodes. In this paper, a privacy-preservation range query protocol based on the integration reversal 0-1 encoding with Bloom filter is researched and designed. In the sensing data submission stage, the optimized reversal 0-1 encoding, HMAC algorithm, AES encryption algorithm and variable-length Bloom filter are used for generating the maximum–minimum comparison encoding and constructing a shorter verification index chain to reduce computational and communication costs of sensing nodes; in the private data range query stage, the base station uses the HMAC algorithm to convert the plaintext query range into the ciphertext query range and sends it to the storage node. In the storage node, the bitmap encoding information of the verification index chain is calculated with the comparison rule of the reversal 0-1 encoding and it is returned to the base station together with the verification index chain and the data ciphertext that compliance with the query rule; in the data integrity verification stage, the integrity of the query results using the verification index chain and bitmap encoding is verified at the base station. In the experimental section, the Cortex-M4 development board equipped with the Alios-Things operating system as sensing node and the Cortex-A9 development board equipped with the Linux operating system as storage node are implemented in this protocol, which is compared with the existing protocols in three aspects: the number of data collected in each cycle, the length of data and the number of data dimensions. The experimental results show that the energy consumption of this protocol is lower under the same experimental environment. [ABSTRACT FROM AUTHOR]

The automated video tracking of the activity/movement of an experimental organism is essential for reliable, repeatable quantitative analyses in behavioral ecology and also in other disciplines. There are only some open-access, open-source automated tracking software applications that can track unmarked organisms. Moreover, several of these software applications are substantially affected by brightness and differences in the lighting conditions of the video recording. Our Python-based software, called BugTracker, uses the latest innovations in computer vision technologies to solve these problems. By analyzing videos with considerably different lighting conditions with BugTracker and other available software, we demonstrate that our software could reliably track the studied organisms of any size and speed. Additionally, the results provide accurate measures of the organism's movements. BugTracker is the most reliable currently available, easy-to-use, and automated tracking software compatible with the Windows, Linux, and MacOS operating systems. [ABSTRACT FROM AUTHOR]

In the few years since the Raspberry Pi was released in 2012, countless microcomputers based on the ARM architecture have been introduced. Their small size, high performance relative to their power consumption, and the ability to run the popular Linux operating system make them ideal for a wide range of tasks. Information security is an area of particular importance. Different encryption and encoding algorithms play an important role in almost all areas of information security. However, these algorithms are very computationally intensive, so it is important to investigate which microcomputers can be used for these tasks, and under which trade-offs. The performance of ten different microcomputers is investigated and presented for the application of common symmetric and public-key encryption and decryption, digest creation and message authentication protocols, such as RSA, AES, HMAC, MD5, SHA. Reliable encryption requires the generation of reliable (pseudo)random numbers (Cryptographically Secure Random Numbers, CSRN), and microcomputers based on ARM SoCs usually have hardware implemented (pseudo)random number generators. The applicability of the random number generators of different microcomputers are investigated and presented; test methods are described, and recommendations are made. [ABSTRACT FROM AUTHOR]

Background: Modeling the whole cardiac function involves the solution of several complex multi-physics and multi-scale models that are highly computationally demanding, which call for simpler yet accurate, high-performance computational tools. Despite the efforts made by several research groups, no software for whole-heart fully-coupled cardiac simulations in the scientific community has reached full maturity yet. Results: In this work we present life x -fiber, an innovative tool for the generation of myocardial fibers based on Laplace-Dirichlet Rule-Based Methods, which are the essential building blocks for modeling the electrophysiological, mechanical and electromechanical cardiac function, from single-chamber to whole-heart simulations. life x -fiber is the first publicly released module for cardiac simulations based on life x , an open-source, high-performance Finite Element solver for multi-physics, multi-scale and multi-domain problems developed in the framework of the iHEART project, which aims at making in silico experiments easily reproducible and accessible to a wide community of users, including those with a background in medicine or bio-engineering. Conclusions: The tool presented in this document is intended to provide the scientific community with a computational tool that incorporates general state of the art models and solvers for simulating the cardiac function within a high-performance framework that exposes a user- and developer-friendly interface. This report comes with an extensive technical and mathematical documentation to welcome new users to the core structure of life x -fiber and to provide them with a possible approach to include the generated cardiac fibers into more sophisticated computational pipelines. In the near future, more modules will be successively published either as pre-compiled binaries for x86-64 Linux systems or as open source software. [ABSTRACT FROM AUTHOR]

A new graphical user interface (GUI) for the parsimony program TNT is presented that works under the Linux and Mac operating systems, as well as the Cygwin environment (which runs under Windows). The new interface is based on the GIMP Tool Kit, GTK (version 3). Formerly, only Windows versions of TNT had a GUI. The new interface improves upon the existing Windows GUI in several respects. These changes, together with several additions to the program since the publication of version 1.5, warrant a change in minor version, thus moving from version 1.5 to 1.6. Among the most notable improvements are the possibility to access graphical user dialogs by means of simple commands, to easily save trees in SVG format ("Scalable Vector Graphics") directly from any tree‐diagram being displayed, and to manage analyses in parallel (using multiple processors, by means of the PVM system or "Parallel Virtual Machine"), as well as a generally more stable and consistent behaviour. As the binaries for the new version are compiled as native 64‐bit applications, this removes the limitations for accessing large amounts of memory in the previous GUI Windows interface (which is a 32‐bit application). [ABSTRACT FROM AUTHOR]

In this study we consider linear and nonlinear Volterra integral equations (VIEs) of the second kind with discontinuous kernel. A novel iterative method using floating point arithmetic (FPA) is presented to solve the problem. Also a convergence theorem and error analysis of the method are presented. The main novelty of this study is to validate the results using the CESTAC (Controle et Estimation Stochastique des Arrondis de Calculs) method which is based on stochastic arithmetic (SA). Moreover instead of applying usual mathematical softwares we use the CADNA (Control of Accuracy and Debugging for Numerical Applications) library which must be done on Linux operating system using C, C++ or Fortran codes. Applying the method and the library we will be able to find the optimal results such as optimal error, optimal iteration of the method and optimal approximation. Proving the main theorem of the CESTAC method we show the equality between the number of common significant digits (NCSDs) of two successive iterations with the exact and approximate solutions. Thus it can help us to apply a new termination criterion instead of absolute error to show the accuracy and efficiency of the method. [ABSTRACT FROM AUTHOR]

Recording technologies for rodents have seen huge advances in the last decade, allowing users to sample thousands of neurons simultaneously from multiple brain regions. This has prompted the need for digital tool kits to aid in curating anatomical data, however, existing tools either provide limited functionalities or require users to be proficient in coding to use them. To address this we created HERBS (Histological E-data Registration in rodent Brain Spaces), a comprehensive new tool for rodent users that offers a broad range of functionalities through a user-friendly graphical user interface. Prior to experiments, HERBS can be used to plan coordinates for implanting electrodes, targeting viral injections or tracers. After experiments, users can register recording electrode locations (e.g. Neuropixels and tetrodes), viral expression, or other anatomical features, and visualize the results in 2D or 3D. Additionally, HERBS can delineate labeling from multiple injections across tissue sections and obtain individual cell counts. Regional delineations in HERBS are based either on annotated 3D volumes from the Waxholm Space Atlas of the Sprague Dawley Rat Brain or the Allen Mouse Brain Atlas, though HERBS can work with compatible volume atlases from any species users wish to install. HERBS allows users to scroll through the digital brain atlases and provides custom-angle slice cuts through the volumes, and supports free-transformation of tissue sections to atlas slices. Furthermore, HERBS allows users to reconstruct a 3D brain mesh with tissue from individual animals. HERBS is a multi-platform open-source Python package that is available on PyPI and GitHub, and is compatible with Windows, macOS, and Linux operating systems. [ABSTRACT FROM AUTHOR]

The GPRO suite is an in-progress bioinformatic project for -omics data analysis. As part of the continued growth of this project, we introduce a client- and server-side solution for comparative transcriptomics and analysis of variants. The client-side consists of two Java applications called "RNASeq" and "VariantSeq" to manage pipelines and workflows based on the most common command line interface tools for RNA-seq and Variant-seq analysis, respectively. As such, "RNASeq" and "VariantSeq" are coupled with a Linux server infrastructure (named GPRO Server-Side) that hosts all dependencies of each application (scripts, databases, and command line interface software). Implementation of the Server-Side requires a Linux operating system, PHP, SQL, Python, bash scripting, and third-party software. The GPRO Server-Side can be installed, via a Docker container, in the user's PC under any operating system or on remote servers, as a cloud solution. "RNASeq" and "VariantSeq" are both available as desktop (RCP compilation) and web (RAP compilation) applications. Each application has two execution modes: a step-by-step mode enables each step of the workflow to be executed independently, and a pipeline mode allows all steps to be run sequentially. "RNASeq" and "VariantSeq" also feature an experimental, online support system called GENIE that consists of a virtual (chatbot) assistant and a pipeline jobs panel coupled with an expert system. The chatbot can troubleshoot issues with the usage of each tool, the pipeline jobs panel provides information about the status of each computational job executed in the GPRO Server-Side, while the expert system provides the user with a potential recommendation to identify or fix failed analyses. Our solution is a ready-to-use topic specific platform that combines the user-friendliness, robustness, and security of desktop software, with the efficiency of cloud/web applications to manage pipelines and workflows based on command line interface software. [ABSTRACT FROM AUTHOR]

Background This article presents the Container Profiler , a software tool that measures and records the resource usage of any containerized task. Our tool profiles the CPU, memory, disk, and network utilization of containerized tasks collecting over 60 Linux operating system metrics at the virtual machine, container, and process levels. The Container Profiler supports performing time-series profiling at a configurable sampling interval to enable continuous monitoring of the resources consumed by containerized tasks and pipelines. Results To investigate the utility of the Container Profiler , we profile the resource utilization requirements of a multistage bioinformatics analytical pipeline (RNA sequencing using unique molecular identifiers). We examine profiling metrics to assess patterns of CPU, disk, and network resource utilization across the different stages of the pipeline. We also quantify the profiling overhead of our Container Profiler tool to assess the impact of profiling a running pipeline with different levels of profiling granularity, verifying that impacts are negligible. Conclusions The Container Profiler provides a useful tool that can be used to continuously monitor the resource consumption of long and complex containerized applications that run locally or on the cloud. This can help identify bottlenecks where more resources are needed to improve performance. [ABSTRACT FROM AUTHOR]

In this scientific paper modified scripts, implementing linear algorithms for discovering wireless networks in Linux based operating systems are presented. [ABSTRACT FROM AUTHOR]

In this scientific paper modified sniffer scripts, implementing linear algorithms for detection of network port scan attacks in Linux based operating systems are presented. [ABSTRACT FROM AUTHOR]

Motivation The multispecies coalescent model is now widely accepted as an effective model for incorporating variation in the evolutionary histories of individual genes into methods for phylogenetic inference from genome-scale data. However, because model-based analysis under the coalescent can be computationally expensive for large datasets, a variety of inferential frameworks and corresponding algorithms have been proposed for estimation of species-level phylogenies and associated parameters, including speciation times and effective population sizes. Results We consider the problem of estimating the timing of speciation events along a phylogeny in a coalescent framework. We propose a maximum a posteriori estimator based on composite likelihood (MAP CL) for inferring these speciation times under a model of DNA sequence evolution for which exact site-pattern probabilities can be computed under the assumption of a constant θ throughout the species tree. We demonstrate that the MAP CL estimates are statistically consistent and asymptotically normally distributed, and we show how this result can be used to estimate their asymptotic variance. We also provide a more computationally efficient estimator of the asymptotic variance based on the non-parametric bootstrap. We evaluate the performance of our method using simulation and by application to an empirical dataset for gibbons. Availability and implementation The method has been implemented in the PAUP* program, freely available at https://paup.phylosolutions.com for Macintosh, Windows and Linux operating systems. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Background: Metagenomics is an expanding field within microbial ecology, microbiology, and related disciplines. The number of metagenomes deposited in major public repositories such as Sequence Read Archive (SRA) and Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST) is rising exponentially. However, data mining and interpretation can be challenging due to mis-annotated and misleading metadata entries. In this study, we describe the Marine Metagenome Metadata Database (MarineMetagenomeDB) to help researchers identify marine metagenomes of interest for re-analysis and meta-analysis. To this end, we have manually curated the associated metadata of several thousands of microbial metagenomes currently deposited at SRA and MG-RAST. Results: In total, 125 terms were curated according to 17 different classes (e.g., biome, material, oceanic zone, geographic feature and oceanographic phenomena). Other standardized features include sample attributes (e.g., salinity, depth), sample location (e.g., latitude, longitude), and sequencing features (e.g., sequencing platform, sequence count). MarineMetagenomeDB version 1.0 contains 11,449 marine metagenomes from SRA and MG-RAST distributed across all oceans and several seas. Most samples were sequenced using Illumina sequencing technology (84.33%). More than 55% of the samples were collected from the Pacific and the Atlantic Oceans. About 40% of the samples had their biomes assigned as 'ocean'. The 'Quick Search' and 'Advanced Search' tabs allow users to use different filters to select samples of interest dynamically in the web app. The interactive map allows the visualization of samples based on their location on the world map. The web app is also equipped with a novel download tool (on both Windows and Linux operating systems), that allows easy download of raw sequence data of selected samples from their respective repositories. As a use case, we demonstrated how to use the MarineMetagenomeDB web app to select estuarine metagenomes for potential large-scale microbial biogeography studies. Conclusion: The MarineMetagenomeDB is a powerful resource for non-bioinformaticians to find marine metagenome samples with curated metadata and stimulate meta-studies involving marine microbiomes. Our user-friendly web app is publicly available at https://webapp.ufz.de/marmdb/. [ABSTRACT FROM AUTHOR]

Next-generation sequencing (NGS) is widely used in all areas of genetic research, such as genetic disease diagnosis and breeding, and it can produce massive amounts of data. The identification of sequence variants is an important step when processing large NGS datasets; however, currently, the process is complicated, repetitive, and requires concentration, which can be taxing on the researcher. Therefore, to support researchers who are not familiar enough with bioinformatics to identify sequence variations regularly from large datasets, we have developed a fully automated desktop software, NGSpop. NGSpop includes functionalities for all the variant calling and visualization procedures used when processing NGS data, such as quality control, mapping, filtering details, and variant calling. In the variant calling step, the user can select the GATK or DeepVariant algorithm for variant calling. These algorithms can be executed using pre-set pipelines and options or customized with the user-specified options. NGSpop is implemented using JavaFX (version 1.8) and can thus be run on Unix-like operating systems such as Ubuntu Linux (version 16.04, 18.0.4). Although several pipelines and visualization tools are available for NGS data analysis, most integrated environments do not support batch processes; thus, variant detection cannot be automated for population-level studies. The NGSpop software developed in this study has an easy-to-use interface and helps in rapid analysis of multiple NGS data from population studies. According to a benchmark test, it effectively reduced the carbon footprint in bioinformatics analysis by expending the least central processing unit heat and power. Additionally, this software makes it possible to use the GATK and DeepVariant algorithms more flexibly and efficiently than other programs by allowing users to choose between the algorithms. As a limitation, NGSpop currently supports only the sequencing reads in fastq format produced by the Illumina platform. NGSpop is freely available at https://sourceforge.net/projects/ngspop/. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) makes it possible for tiny devices with sensing and communication capabilities to be interconnected and interact with the cyber–physical world. However, these tiny devices have limited computing power and memory, so they often cannot run commodity operating systems, such as Windows and Linux. IoT devices are deployed everywhere, from smart home appliances to self-driving vehicles, and their applications impose ever-increasing and more heterogeneous demands on software architecture. There are many special-purpose and embedded operating systems built to satisfy these wildly different requirements, from early sensor network operating systems, such as TinyOS and Contiki, to more modern robot and real-time control systems, such as FreeRTOS and Zephyr. However, the rapid evolution and heterogeneity of IoT applications calls for a different solution. Specifically, this work introduces Tinkertoy, a collection of standard operating system modules from which developers can easily assemble customized operating systems. A customized operating system provides precisely the functionality needed by an application and consumes up to four times less memory than other IoT operating systems without sacrificing performance. [ABSTRACT FROM AUTHOR]

"Four Shades of Gray: The Amazon Kindle Platform" by Simon Peter Rowberry is a book that explores the history and development of the Kindle e-reading device as a platform. The book traces the evolution of the Kindle in terms of hardware, software, and cultural reception, starting from its first iteration with only four shades of gray. It also delves into how the Kindle represents Amazon's shift from being an online retailer to a provider of infrastructure and services. The book examines the Kindle's impact on the publishing industry and its role in creating an entire ecosystem within the Amazon platform. [Extracted from the article]

This paper describes the concept and analysis of virtualization technology and possible virtualization scenarios, which can be used to create a new generation of Intelligent Electronic Devices (IEDs). The concept overview was based on solutions used in conventional IT systems. A general conception of virtualization is presented. A solution based on KVM virtualization is described. Synchronizing the time of virtual machines, as well as creating and testing virtual machines under Linux operating systems are described. Time delays of communication when sending SV messages between the IEDs using SV packages are compared. Communication and operation of virtual protections with physical IEDs devices were verified. [ABSTRACT FROM AUTHOR]

Summary: Highly accurate protein structure predictors have generated hundreds of millions of protein structures; these pose a challenge in terms of storage and processing. Here, we present Foldcomp, a novel lossy structure compression algorithm, and indexing system to address this challenge. By using a combination of internal and Cartesian coordinates and a bi-directional NeRF-based strategy, Foldcomp improves the compression ratio by a factor of three compared to the next best method. Its reconstruction error of 0.08 Å is comparable to the best lossy compressor. It is five times faster than the next fastest compressor and competes with the fastest decompressors. With its multi-threading implementation and a Python interface that allows for easy database downloads and efficient querying of protein structures by accession, Foldcomp is a powerful tool for managing and analysing large collections of protein structures. Availability and implementation: Foldcomp is a free open-source software (GPLv3) and available for Linux, macOS, and Windows at https://foldcomp.foldseek.com. Foldcomp provides the AlphaFold Swiss-Prot (2.9GB), TrEMBL (1.1TB), and ESMatlas HQ (114GB) database ready-for-download. [ABSTRACT FROM AUTHOR]

Background: Biological sequences are increasing rapidly and exponentially worldwide. Nucleotide sequence databases play an important role in providing meaningful genomic information on a variety of biological organisms. Results: The getSequenceInfo software tool allows to access sequence information from various public repositories (GenBank, RefSeq, and the European Nucleotide Archive), and is compatible with different operating systems (Linux, MacOS, and Microsoft Windows) in a programmatic way (command line) or as a graphical user interface. getSequenceInfo or gSeqI v1.0 should help users to get some information on queried sequences that could be useful for specific studies (e.g. the country of origin/isolation or the release date of queried sequences). Queries can be made to retrieve sequence data based on a given kingdom and species, or from a given date. This program allows the separation between chromosomes and plasmids (or other genetic elements/components) by arranging each component in a given folder. Some basic statistics are also performed by the program (such as the calculation of GC content for queried assemblies). An empirically designed nucleotide ratio is calculated using nucleotide information in order to tentatively provide a "NucleScore" for studied genome assemblies. Besides the main gSeqI tool, other additional tools have been developed to perform various tasks related to sequence analysis. Conclusion: The aim of this study is to democratize the use of public repositories in programmatic ways, and to facilitate sequence data analysis in a pedagogical perspective. Output results are available in FASTA, FASTQ, Excel/TSV or HTML formats. The program is freely available at: https://github.com/karubiotools/getSequenceInfo. getSequenceInfo and supplementary tools are partly available through the recently released Galaxy KaruBioNet platform (http://calamar.univ-ag.fr/c3i/galaxy_karubionet.html). [ABSTRACT FROM AUTHOR]

Edge computing is a recent computing paradigm that brings cloud services closer to the client. Among other features, edge computing offers extremely low client/server latencies. To consistently provide such low latencies, services should run on edge nodes that are physically as close as possible to their clients. Thus, when the physical location of a client changes, a service should migrate between edge nodes to maintain proximity. Differently from cloud nodes, edge nodes integrate CPUs of different Instruction Set Architectures (ISAs), hence a program natively compiled for a given ISA cannot migrate to a server equipped with a CPU of a different ISA. This hinders migration to the closest node. We introduce H-Container, a system that migrates natively compiled containerized applications across compute nodes featuring CPUs of different ISAs. H-Container advances over existing heterogeneous-ISA migration systems by being (a) highly compatible -- no user's source-code nor compiler toolchain modifications are needed; (b) easily deployable -- fully implemented in user space, thus without any OS or hypervisor dependency, and (c) largely Linux-compliant -- it can migrate most Linux software, including server applications and dynamically linked binaries. H-Container targets Linux and its already-compiled executables, adopts LLVM, extends CRIU, and integrates with Docker. Experiments demonstrate that H-Container adds no overheads during program execution, while 10-100 ms are added during migration. Furthermore, we show the benefits of H-Container in real-world scenarios, demonstrating, for example, up to 94% increase in Redis throughput when client/server proximity is maintained through heterogeneous container migration. [ABSTRACT FROM AUTHOR]

The advances in developing more accurate and fast smoke detection algorithms increase the need for computation in smoke detection, which demands the involvement of personal computers or workstations. Better detection results require a more complex network structure of the smoke detection algorithms and higher hardware configuration, which disqualify them as lightweight portable smoke detection for high detection efficiency. To solve this challenge, this paper designs a lightweight portable remote smoke front-end perception platform based on the Raspberry Pi under Linux operating system. The platform has four modules including a source video input module, a target detection module, a display module, and an alarm module. The training images from the public data sets will be used to train a cascade classifier characterized by Local Binary Pattern (LBP) using the Adaboost algorithm in OpenCV. Then the classifier will be used to detect the smoke target in the following video stream and the detected results will be dynamically displayed in the display module in real-time. If smoke is detected, warning messages will be sent to users by the alarm module in the platform for real-time monitoring and warning on the scene. Case studies showed that the developed system platform has strong robustness under the test datasets with high detection accuracy. As the designed platform is portable without the involvement of a personal computer and can efficiently detect smoke in real-time, it provides a potential affordable lightweight smoke detection option for forest fire monitoring in practice. [ABSTRACT FROM AUTHOR]

The Python programming language has various module libraries for network scanning of hosts. In this paper the performance and implementation of a modified script for Linux based operating systems using a linear algorithm for network port scanning is presented. [ABSTRACT FROM AUTHOR]