Search

This survey introduces 101 new publications on applications of Clifford's geometric algebras (GAs) newly published during 2022 (until mid‐January 2023). The selection of papers is based on a comprehensive search with Dimensions.ai, followed by detailed screening and clustering. Readers will learn about the use of GA for mathematics, computation, surface representations, geometry, image, and signal processing, computing and software, quantum computing, data processing, neural networks, medical science, physics, electric engineering, control and robotics. [ABSTRACT FROM AUTHOR]

Since its first release in 2016, the Cambridge Structural Database Python application programming interface (CSD Python API) has seen steady uptake within the community that the Cambridge Crystallographic Data Centre serves. This article reviews the history of scripting interfaces, demonstrating the need, and then briefly outlines the technical structure of the API. It describes the reach of the CSD Python API, provides a selected review of its impact and gives some illustrative examples of what scientists can do with it. The article concludes with speculation as to how such endeavours will evolve over the next decade. [ABSTRACT FROM AUTHOR]

Summary: The use of cutting‐edge omics technology to edible fruits has transformed the disciplines of fruit biology, pre‐ and post‐harvest investigations, metabolite biosynthesis and the identification of novel therapeutic fruit bioactives for health by leveraging varied omics data. Combining modern analytical chromatography tools (LC, GC) with mass spectrometry has significantly improved our ability to examine complex fruit tissues or extracted components, advancing our understanding of the fruit metabolome. Studies aiming at understanding the full metabolome and future quality characteristics have concentrated on quantifying the number of metabolites in edible fruit species and cultivars from diverse geographical locations. These studies have also helped to develop new databases for precise and comprehensive qualitative analysis of metabolites, allowing for the analysis of metabolite biosynthesis pathways to identify differences in metabolites among developed hybrids, metabolite origins and potential derivatives. Bioactive metabolite information is currently being utilised to manage illnesses, provide nutrition and creation of novel food products. Furthermore, this research has helped us better understand fruit quality and how metabolites interact with biological systems. In conclusion, this review emphasises the importance of metabolomics approaches in studying fruit metabolomes in the context of current research perspectives. [ABSTRACT FROM AUTHOR]

Over the last few years, sustainability has become increasingly relevant in different areas of industry. However, from the point of view of the software companies, the concept of software sustainability is still underdeveloped, as software emissions are not as easily observable as in other sectors, such as the power generation. A starting point for software development companies to tackle software sustainability is the inclusion of actions focused on improving software sustainability within their corporate social responsibility (CSR). For this reason, in this work, a set of specific software sustainability actions aligned with ISO 26000 corporate social responsibility standard is proposed. By including these actions in the CSR of software companies, they can improve sustainability aspects associated with software. In addition, the proposal was applied to six leading companies in the software sector in order to check its suitability and applicability. [ABSTRACT FROM AUTHOR]

Genome‐wide association studies (GWAS) have significantly enhanced our understanding of the genetic basis of complex diseases. Despite the technological advancements, gaps in our understanding remain, partly due to small effect sizes and inadequate coverage of genetic variation. Multiancestry GWAS meta‐analysis (MAGMA) addresses these challenges by integrating genetic data from diverse populations, thereby increasing power to detect loci and improving fine‐mapping resolution to identify causal variants across different ancestry groups. This review provides an overview of the protocols, statistical methods, and software of MAGMA, as well as highlighting some challenges associated with this approach. [ABSTRACT FROM AUTHOR]

The gravimetric forward method is crucial in geophysical applications for a gravimetric interpretation of the Earth's inner structure. In this study, we present the gravimetric forward modelling open‐source software that incorporates a graphical user interface. This software allows data preparation, manipulation and result interpretation both spatially and spectrally. For spatial domain modelling, it uses prism and tesseroid elements, whereas in the spectral domain, it extends Parker's formulas within specified boundaries. The software's utility is demonstrated through synthetic models and real‐world applications, including calculating corrections for topography, sediments and consolidated crust using ETOPO1 and CRUST1.0 models. Performance comparisons show that Parker's method delivers computation speed superior to that of the prism, tesseroid and Terrain gravity forward (TGF) software, with variances ranging within ±12 mGal for Gz${{G}_z}$ and ±0.3 E for Gzz${{G}_{zz}}$ across different geological scenarios. [ABSTRACT FROM AUTHOR]

Despite progress in computer automated solutions, constitutional isomer verification by NMR using one‐ and two‐dimensional data sets is still, in the main, a manual, user‐intensive activity that is challenging for a number of reasons. These include the problem of simultaneously keeping track of the information from a number of separate NMR experiments and the difficulty of another researcher subsequently verifying the assignments made without having to independently repeat the whole analysis. This paper describes a graphical interactive approach that overcomes some of these problems. By using concepts used to visualise graph networks, we have been able to represent the NMR data in a manner that highlights directly the link between the different NMR experiments and the molecule of interest. Furthermore, by making the graph networks interactive, a user can easily validate and correct the assignment and understand the decisions made in arriving at the solution. We have developed a usable proof‐of‐concept computer program, 'simpleNMR', written in Python to illustrate the ideas and approach. [ABSTRACT FROM AUTHOR]

The study of animal sounds in biology and ecology relies heavily upon time–frequency (TF) visualisation, most commonly using the short‐time Fourier transform (STFT) spectrogram. This method, however, has inherent bias towards either temporal or spectral details that can lead to misinterpretation of complex animal sounds. An ideal TF visualisation should accurately convey the structure of the sound in terms of both frequency and time, however, the STFT often cannot meet this requirement. We evaluate the accuracy of four TF visualisation methods (superlet transform [SLT], continuous wavelet transform [CWT] and two STFTs) using a synthetic test signal. We then apply these methods to visualise sounds of the Chagos blue whale, Asian elephant, southern cassowary, eastern whipbird, mulloway fish and the American crocodile. We show that the SLT visualises the test signal with 18.48%–28.08% less error than the other methods. A comparison between our visualisations of animal sounds and their literature descriptions indicates that the STFT's bias may have caused misinterpretations in describing pygmy blue whale songs and elephant rumbles. We suggest that use of the SLT to visualise low‐frequency animal sounds may prevent such misinterpretations. Finally, we employ the SLT to develop 'BASSA', an open‐source, GUI software application that offers a no‐code, user‐friendly tool for analysing short‐duration recordings of low‐frequency animal sounds for the Windows platform. The SLT visualises low‐frequency animal sounds with improved accuracy, in a user‐friendly format, minimising the risk of misinterpretation while requiring less technical expertise than the STFT. Using this method could propel advances in acoustics‐driven studies of animal communication, vocal production methods, phonation and species identification. [ABSTRACT FROM AUTHOR]

Population‐adjusted indirect comparison (PAIC) is an increasingly used technique for estimating the comparative effectiveness of different treatments for the health technology assessments when head‐to‐head trials are unavailable. Three commonly used PAIC methods include matching‐adjusted indirect comparison (MAIC), simulated treatment comparison (STC), and multilevel network meta‐regression (ML‐NMR). MAIC enables researchers to achieve balanced covariate distribution across two independent trials when individual participant data are only available in one trial. In this article, we provide a comprehensive review of the MAIC methods, including their theoretical derivation, implicit assumptions, and connection to calibration estimation in survey sampling. We discuss the nuances between anchored and unanchored MAIC, as well as their required assumptions. Furthermore, we implement various MAIC methods in a user‐friendly R Shiny application Shiny‐MAIC. To our knowledge, it is the first Shiny application that implements various MAIC methods. The Shiny‐MAIC application offers choice between anchored or unanchored MAIC, choice among different types of covariates and outcomes, and two variance estimators including bootstrap and robust standard errors. An example with simulated data is provided to demonstrate the utility of the Shiny‐MAIC application, enabling a user‐friendly approach conducting MAIC for healthcare decision‐making. The Shiny‐MAIC is freely available through the link: https://ziren.shinyapps.io/Shiny_MAIC/. [ABSTRACT FROM AUTHOR]

Preparation of DNA polymorphism datasets for analysis is an important step in evolutionary genetic and molecular ecology studies. Ever‐growing dataset sizes make this step time consuming, but few convenient software tools are available to facilitate processing of large‐scale datasets including thousands of sequence alignments. Here I report "processor of sequences v4" (proSeq4)—a user‐friendly multiplatform software for preparation and evolutionary genetic analyses of genome‐ or transcriptome‐scale sequence polymorphism datasets. The program has an easy‐to‐use graphic user interface and is designed to process and analyse many thousands of datasets. It supports over two dozen file formats, includes a flexible sequence editor and various tools for data visualization, quality control and most commonly used evolutionary genetic analyses, such as NJ‐phylogeny reconstruction, DNA polymorphism analyses and coalescent simulations. Command line tools (e.g. vcf2fasta) are also provided for easier integration into bioinformatic pipelines. Apart of molecular ecology and evolution research, proSeq4 may be useful for teaching, e.g. for visual illustration of different shapes of phylogenies generated with coalescent simulations in different scenarios. ProSeq4 source code and binaries for Windows, MacOS and Ubuntu are available from https://sourceforge.net/projects/proseq/. [ABSTRACT FROM AUTHOR]

Nanospray desorption electrospray ionization (nano‐DESI) is an ambient ionization mass spectrometry imaging (MSI) approach that enables spatial mapping of biological and environmental samples with high spatial resolution and throughput. Because nano‐DESI has not yet been commercialized, researchers develop their own sources and interface them with different commercial mass spectrometers. Previously, several protocols focusing on the fabrication of nano‐DESI probes have been reported. In this tutorial, we discuss different hardware requirements for coupling the nano‐DESI source to commercial mass spectrometers, such as the safety interlock, inlet extension, and contact closure. In addition, we describe the structure of our custom software for controlling the nano‐DESI MSI platform and provide detailed instructions for its usage. With this tutorial, interested researchers should be able to implement nano‐DESI experiments in their labs. [ABSTRACT FROM AUTHOR]

Purpose: To develop and pilot test an App to help family and paid caregivers perform high quality oral hygiene care. Methods: A prototype of the App was refined based on stakeholder feedback (e.g., dental care professionals, direct care providers, nursing home administrator, family caregivers). The refined App was pilot tested with 16 family caregivers and 15 paid care providers of persons living with dementia (PLWD). Participants completed a pre‐test, watched an App demonstration, used it for 2 weeks, and completed a post‐test. Surveys included both structured and open‐ended questions. Results: Phase 1 data informed the refinement of the App that led to high acceptability and usability by the Phase 2 participants. Both family and paid caregivers reported a significant increase in attitudes toward providing oral hygiene care to frail older adults (p =.05 and p =.02 for family and paid providers, respectively), knowledge about oral health and care (p =.01 and p =.02), and ability to identify oral health problems (p =.005 and p =.01). Additionally, paid caregivers reported increase in perceived support available in providing oral hygiene care (p <.001). Conclusion: Stakeholder engaged approach helped increase the acceptability and usability of the App that successfully increase caregivers' attitude, knowledge, and abilities in oral hygiene care provision. [ABSTRACT FROM AUTHOR]

Multifitting is a computer program that was originally designed to model the reflection and transmission of shortwave radiation by multilayer nanofilms. Three years have passed since the introduction of this software, and in this paper the focus is on describing the possibilities of Multifitting with regard to off‐specular diffuse scattering and grazing‐incidence small‐angle scattering. The approach to the user interface and to working with the structure model remains the same, and the emphasis is on the ergonomics, calculation speed and intensive use of the program for technological and research tasks. However, the scope of the program has been expanded to make it more useful to existing users, and it may also be of interest to a wider audience. [ABSTRACT FROM AUTHOR]

The pair angle distribution function (PADF) is a three‐ and four‐atom correlation function that characterizes the local angular structure of disordered materials, particles or nanocrystalline materials. The PADF can be measured using X‐ray or electron fluctuation diffraction data, which can be collected by scanning or flowing a structurally disordered sample through a focused beam. It is a natural generalization of established pair distribution methods, which do not provide angular information. The software package pypadf provides tools to calculate the PADF from fluctuation diffraction data. The package includes tools for calculating the intensity correlation function, which is a necessary step in the PADF calculation and also the basis for other fluctuation scattering analysis techniques. [ABSTRACT FROM AUTHOR]

The Swiss Light Source facilitates fragment‐based drug‐discovery campaigns for academic and industrial users through the Fast Fragment and Compound Screening (FFCS) software suite. This framework is further enriched by the option to utilize the Smart Digital User (SDU) software for automated data collection across the PXI, PXII and PXIII beamlines. In this work, the newly developed HEIDI webpage (https://heidi.psi.ch) is introduced: a platform crafted using state‐of‐the‐art software architecture and web technologies for sample management of rotational data experiments. The HEIDI webpage features a data‐review tab for enhanced result visualization and provides programmatic access through a representational state transfer application programming interface (REST API). The migration of the local FFCS MongoDB instance to the cloud is highlighted and detailed. This transition ensures secure, encrypted and consistently accessible data through a robust and reliable REST API tailored for the FFCS software suite. Collectively, these advancements not only significantly elevate the user experience, but also pave the way for future expansions and improvements in the capabilities of the system. [ABSTRACT FROM AUTHOR]

Diffuse scattering is a promising method to gain additional insight into protein dynamics from macromolecular crystallography experiments. Bragg intensities yield the average electron density, while the diffuse scattering can be processed to obtain a three‐dimensional reciprocal‐space map that is further analyzed to determine correlated motion. To make diffuse scattering techniques more accessible, software for data processing called mdx2 has been created that is both convenient to use and simple to extend and modify. mdx2 is written in Python, and it interfaces with DIALS to implement self‐contained data‐reduction workflows. Data are stored in NeXus format for software interchange and convenient visualization. mdx2 can be run on the command line or imported as a package, for instance to encapsulate a complete workflow in a Jupyter notebook for reproducible computing and education. Here, mdx2 version 1.0 is described, a new release incorporating state‐of‐the‐art techniques for data reduction. The implementation of a complete multi‐crystal scaling and merging workflow is described, and the methods are tested using a high‐redundancy data set from cubic insulin. It is shown that redundancy can be leveraged during scaling to correct systematic errors and obtain accurate and reproducible measurements of weak diffuse signals. [ABSTRACT FROM AUTHOR]

Purpose: Software has a substantial impact on quantitative perfusion MRI values. The lack of generally accepted implementations, code sharing and transparent testing reduces reproducibility, hindering the use of perfusion MRI in clinical trials. To address these issues, the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI) aimed to establish a community‐led, centralized repository for sharing open‐source code for processing contrast‐based perfusion imaging, incorporating an open‐source testing framework. Methods: A repository was established on the OSIPI GitHub website. Python was chosen as the target software language. Calls for code contributions were made to OSIPI members, the ISMRM Perfusion Study Group, and publicly via OSIPI websites. An automated unit‐testing framework was implemented to evaluate the output of code contributions, including visual representation of the results. Results: The repository hosts 86 implementations of perfusion processing steps contributed by 12 individuals or teams. These cover all core aspects of DCE‐ and DSC‐MRI processing, including multiple implementations of the same functionality. Tests were developed for 52 implementations, covering five analysis steps. For T1 mapping, signal‐to‐concentration conversion and population AIF functions, different implementations resulted in near‐identical output values. For the five pharmacokinetic models tested (Tofts, extended Tofts‐Kety, Patlak, two‐compartment exchange, and two‐compartment uptake), differences in output parameters were observed between contributions. Conclusions: The OSIPI DCE‐DSC code repository represents a novel community‐led model for code sharing and testing. The repository facilitates the re‐use of existing code and the benchmarking of new code, promoting enhanced reproducibility in quantitative perfusion imaging. [ABSTRACT FROM AUTHOR]

Software for realistically simulating complex population genomic processes is revolutionizing our understanding of evolutionary processes, and providing novel opportunities for integrating empirical data with simulations. However, the integration between standalone simulation software and R is currently not well developed. Here, we present slimr, an R package designed to create a seamless link between standalone software SLiM >3.0, one of the most powerful population genomic simulation frameworks, and the R development environment, with its powerful data manipulation and analysis tools. We show how slimr facilitates smooth integration between genetic data, ecological data and simulation in a single environment. The package enables pipelines that begin with data reading, cleaning and manipulation, proceed to constructing empirically based parameters and initial conditions for simulations, then to running numerical simulations and finally to retrieving simulation results in a format suitable for comparisons with empirical data – aided by advanced analysis and visualization tools provided by R. We demonstrate the use of slimr with an example from our own work on the landscape population genomics of desert mammals, highlighting the advantage of having a single integrated tool for both data analysis and simulation. slimr makes the powerful simulation ability of SLiM directly accessible to R users, allowing integrated simulation projects that incorporate empirical data without the need to switch between software environments. This should provide more opportunities for evolutionary biologists and ecologists to use realistic simulations to better understand the interplay between ecological and evolutionary processes. [ABSTRACT FROM AUTHOR]

The continuous evolution of molecular biology and gene synthesis methods paired with an ever‐increasing potential of synthetic biology approaches and genome engineering toolkits enables the rapid design of genetic bioparts and genetically modified organisms. Although various software solutions assist with specific design tasks and challenges, lab internal documentation and ensuring compliance with governmental regulations on biosafety assessment of the generated organisms remain the responsibility of individual academic researchers. This results in inconsistent and redundant documentation regimes and a significant time and labor burden. GMOCU (GMO documentation) is a standardized semi‐automatic user‐oriented software approach —written in Python and freely available— that unifies lab internal data documentation on genetic parts and genetically modified organisms (GMOs). It automatizes biological risk evaluations and maintains a shared up‐to‐date inventory of bioparts for team‐wide data navigation and sharing. GMOCU further enables data export into customizable formats suitable for scientific publications, official biosafety documents, and the research community. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this study was to assess the diagnostic accuracy and the inter‐rater agreement among general dentists when staging and grading periodontitis cases with the aid of a software application (SA) developed by the Italian Society of Periodontology and Implantology. Materials and methods: Ten general dentists were asked to independently assess 25 periodontitis cases using the SA. Accuracy was estimated using quadratic weighted kappa and examiners' percentage of agreement with a reference diagnosis provided by a gold standard examiner. Inter‐rater agreement was evaluated using Fleiss kappa statistics. Results: The overall case definition agreed with the reference diagnosis in 53.6% of cases. The agreements for each general dentist's pairwise comparisons against the reference definition were at least substantial in 100% of cases for stage, in 70% of cases for grade and in none of the cases for extent. Fleiss kappa was 0.818, 0.608, and 0.632 for stage, extent, and grade, respectively. The study recognized possible reasons that could lead to decreased accuracy using the SA. Conclusions: Supported by the SA, general dentists have reached substantial inter‐rater agreement and highly accurate assignments of stage and grade. However, complete case definitions were correctly diagnosed in slightly over half of the cases. [ABSTRACT FROM AUTHOR]

Key Clinical Message: This research investigates the trueness and precision of 3D printing technology in dental applications, specifically focusing on dimensional variations observed in models printed at different angles. The methodology involved importing a dental model into slicing software, adjusting its orientation, and implementing support structures for stability. Subsequently, the model underwent 3D printing five times for each orientation using appropriate equipment and underwent post‐processing steps, including cleaning, washing, and UV‐light post‐curing. The printed models were then scanned using a specialized desktop scanner for further analysis. Accuracy assessment was carried out using dedicated software, employing an algorithm for precise alignment by comparing the scanned files. Color deviation maps were utilized to visually represent variations, aiming to evaluate how positioning during printing influences the trueness and precision of 3D‐printed dental models. Trueness and precision analyses involved the Shapiro–Wilk test for normality and a one‐way ANOVA to compare means of three independent groups, with statistical analyses conducted using IBM SPSS Statistics software. The color maps derived from 3D comparisons revealed positive and negative deviations, represented by distinct colors. Comparative results indicated that models positioned at 0° exhibited the least dimensional deviation, whereas those at 90° showed the highest. Regarding precision, models printed at 0° demonstrated the highest reproducibility, while those at 15° exhibited the lowest. Based on the desired level of precision, it is recommended that printed models be produced at an inclination angle of 0°. [ABSTRACT FROM AUTHOR]

Knowledge of the photon spectrum emitted from an x-ray tube is frequently needed in imaging and dosimetry contexts.As the spectrum characteristics are influenced by several parameters and routine measurement of a spectrum is often impractical, a variety of software programs have been developed over the decades for convenient calculations.SpekPy is a state-of-the-art software package containing several spectrum models, and was created to estimate photon spectra originating from x-ray tubes using a small set of input parameters (e.g., anode material,anode angle,tube potential, filtration, etc.).SpekPy is distributed as a Python toolkit and is available free of charge.The toolkit does,however, lack a graphical user interface and a user is required to write a Python script to make use of it. In this work this limitation is addressed by introducing a web application called SpekPy Web: a graphical user interface together with an application programmable interface (API). These developments both make the SpekPy spectrummodels accessible to a broader set of users and increases the ease of use for existing users. SpekPy Web is hosted at: https://spekpy.smile.ki.se. The functionality of the software is demonstrated, using its API, by estimating first half-value layers (HVLs) for 15 standard beam qualities from the International Bureau of Weights and Measures (BIPM). The estimated HVLs were found to all be within 3.5% agreement when compared to experimental values, with an average calculation time of 2.5 s per spectrum. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Charge transport characterization of single‐molecule junctions is essential for the fundamental research of single‐molecule physical chemistry and the development towards single‐molecule electronic devices and circuits. Among the single‐molecule conductance characterization techniques, the single‐molecule break junction technique is widely used in tens of worldwide research laboratories which can generate a large amount of experimental data from thousands of individual measurement cycles. However, data interpretation is a challenging task for researchers with different research backgrounds, and the different data analysis approaches sometimes lead to the misunderstanding of the measurement data and even reproducibility issues of the measurement. It is thus a necessity to develop a user‐friendly all‐in‐one data analysis tool that automatizes the basic data analysis in a standard and widely accepted way. In this work, we present the XMe Code (Xiamen Molecular Electronics Code), an intelligent all‐in‐one data analysis tool for the comprehensive analysis of single‐molecule break junction data. XMe code provides end‐to‐end data analysis that takes in the original experimental data and returns electronic characteristics and even charge transport mechanisms. We believe that XMe Code will promote the transparency of the data analysis in single‐molecule electronics and the collaborations among scientists with different research backgrounds. [ABSTRACT FROM AUTHOR]

We extensively survey applications of Clifford Geometric algebra in recent years (mainly 2019–2022). This includes engineering; electric engineering; optical fibers; geographic information systems; geometry; molecular geometry; protein structure; neural networks; artificial intelligence; encryption; physics; signal, image, and video processing; and software. [ABSTRACT FROM AUTHOR]

Head motion correction is particularly challenging in diffusion‐weighted MRI (dMRI) scans due to the dramatic changes in image contrast at different gradient strengths and directions. Head motion correction is typically performed using a Gaussian Process model implemented in FSL's Eddy. Recently, the 3dSHORE‐based SHORELine method was introduced that does not require shell‐based acquisitions, but it has not been previously benchmarked. Here we perform a comprehensive evaluation of both methods on realistic simulations of a software fiber phantom that provides known ground‐truth head motion. We demonstrate that both methods perform remarkably well, but that performance can be impacted by sampling scheme and the extent of head motion and the denoising strategy applied before head motion correction. Furthermore, we find Eddy benefits from denoising the data first with MP‐PCA. In sum, we provide the most extensive known benchmarking of dMRI head motion correction, together with extensive simulation data and a reproducible workflow. Practitioner points: Both Eddy and SHORELine head motion correction methods performed quite well on a large variety of simulated data.Denoising with MP‐PCA can improve head motion correction performance when Eddy is used.SHORELine effectively corrects motion in non‐shelled diffusion spectrum imaging data. [ABSTRACT FROM AUTHOR]

Colour pattern variation provides biological information in fields ranging from disease ecology to speciation dynamics. Comparing colour pattern geometries across images requires colour segmentation, where pixels in an image are assigned to one of a set of colour classes shared by all images. Manual methods for colour segmentation are slow and subjective, while automated methods can struggle with high technical variation in aggregate image sets. We present recolorize, an R package toolbox for human‐subjective colour segmentation with functions for batch‐processing low‐variation image sets and additional tools for handling images from diverse (high‐variation) sources. The package also includes export options for a variety of formats and colour analysis packages. This paper illustrates recolorize for three example datasets, including high variation, batch processing and combining with reflectance spectra, and demonstrates the downstream use of methods that rely on this output. [ABSTRACT FROM AUTHOR]

Summary: The aim of this study was to evaluate the safety and efficacy of digital therapeutic application of Sleep Index‐Based Treatment for Insomnia (dSIBT‐I) and compare them with those of digital application of Cognitive Behavioural Therapy for Insomnia (dCBT‐I). This randomised prospective pilot study was conducted at the Asan Medical Center. A total of 50 patients with insomnia were recruited between December 2022 and January 2023 and randomly allocated to the dSIBT‐I or dCBT‐I group. The study was carried out for one month. The primary outcome was the significant reduction in Insomnia Severity Index score at Week 4 compared to baseline, while the secondary outcome was proportion of participants whose Insomnia Severity Index scores were reduced to <15 at Week 4. We performed linear mixed model and generalised estimating equation analyses. Both dSIBT‐I and dCBT‐I groups showed significant improvements in Insomnia Severity Index scores at Week 4. There was no significant difference between two groups in terms of Insomnia Severity Index scores at Week 4 (group × time effect, F = 1.07, p = 0.382) and proportion of participants whose Insomnia Severity Index scores were reduced to <15 at Week 4 (group × time effects, F = 1.80, p = 0.615). However, at Week 2, the dSIBT‐I group showed better results than the dCBT‐I group in terms of both Insomnia Severity Index scores (p = 0.044) and proportion of participants whose Insomnia Severity Index scores were reduced to <15 (82.6% vs. 48.0%, p = 0.017). No treatment‐emergent adverse events were reported in either group. The dSIBT‐I is a safe and effective therapy for insomnia, with rapid treatment effects. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Charge transport characterization of single‐molecule junctions is essential for the fundamental research of single‐molecule physical chemistry and the development towards single‐molecule electronic devices and circuits. Among the single‐molecule conductance characterization techniques, the single‐molecule break junction technique is widely used in tens of worldwide research laboratories which can generate a large amount of experimental data from thousands of individual measurement cycles. However, data interpretation is a challenging task for researchers with different research backgrounds, and the different data analysis approaches sometimes lead to the misunderstanding of the measurement data and even reproducibility issues of the measurement. It is thus a necessity to develop a user‐friendly all‐in‐one data analysis tool that automatizes the basic data analysis in a standard and widely accepted way. In this work, we present the XMe Code (Xiamen Molecular Electronics Code), an intelligent all‐in‐one data analysis tool for the comprehensive analysis of single‐molecule break junction data. XMe code provides end‐to‐end data analysis that takes in the original experimental data and returns electronic characteristics and even charge transport mechanisms. We believe that XMe Code will promote the transparency of the data analysis in single‐molecule electronics and the collaborations among scientists with different research backgrounds. [ABSTRACT FROM AUTHOR]

Tectonic plate motions are a prime constraint on lithosphere dynamics and on the torques acting upon plates. Researchers typically test hypotheses on the controlling torques via forward computer models, which allow accepting or rejecting hypotheses on the basis of the fit of model–output plate velocities to kinematic reconstructions. Such models typically require a significant amount of input information (e.g., tectonic boundaries, structure of the lithosphere, lateral variations of rheology, among others) to appropriately model the tectonic system, and obtain sufficiently–realistic realizations of plate motions. Alternatively, the inverse problem approach takes the difference between the plate torque–balance at two distinct moments in time. This results in an equation in which (a) torques that have not varied through time are canceled out and (b) torques that instead have varied through time are linked to the resulting plate–motion change through a term that accounts for the plate shape and the rheology of the underlying asthenosphere. This approach sacrifices the capability to describe the different individual forces/torques acting upon a plate. Instead, it focuses on determining torque temporal variations, which significantly reduces the amount of input knowledge required. In this technical note we introduce MYRIAM, an open–source software that implements such an inverse approach. MYRIAM takes plate–motion temporal changes, and outputs an estimate of the torque variation required upon a plate to generate the input kinematic change. MYRIAM is released as an open–source repository hosted at GitHub, complete with source code and executable files for Windows and Unix–based operating systems. Plain Language Summary: The outermost layer of the Earth, known as the lithosphere, is fragmented into plates that are in motion relative to each other. Through geological history, the motion of tectonic plates did not remain steady, and in fact important changes are now known to have occurred relatively fast, within a few million years. By virtue of Newton's laws of motion, these changes are all necessarily caused by the variation in one or more forces acting upon the plates, and therefore disrupt their force balance. Changing the motion of a plate is not an easy feat—for plates it requires overcoming the frictional resistance exerted by the underlying asthenosphere, a low–viscosity layer beneath the plates. The resulting motion change will depend on (a) the mechanical properties of the asthenosphere and (b) the amount of plate surface interacting with said asthenosphere (i.e., the basal area of the plate). All these considerations are taken into account by MYRIAM, an open–source, computationally–inexpensive software that estimates the force/torque variations required to produce a given change of plate motion. Key Points: MYRIAM is an open‐source software that links plate kinematics to plate dynamicsMYRIAM allows estimating torque variations required to generate known plate‐motion changesUser Manual, OS‐specific executables, C# source‐code files, and example files are available in a GitHub public repository [ABSTRACT FROM AUTHOR]

Compound identification in complex mixtures by NMR and MS is best achieved through experimental databases (DB) mining. Experimental DB frequently show limitations regarding their completeness, availability or data quality, thus making predicted database of increasing common use. Querying large databases may lead to select unlikely structure candidates. Two approaches to dereplication are thus possible: filtering of a large DB before search or scoring of the results after a large scale search. The present work relies on the former approach. As far as we know, nmrshiftdb2 is the only open‐source 13NMR chemical shift predictor that can be freely operated in batch mode. CFM‐ID 4.0 is one of the best‐performing open‐source tools for ESI‐MS/MS spectra prediction. LOTUS is a freely usable and comprehensive collection of secondary metabolites. Integrating the open source database and software LOTUS, CFM‐ID, and nmrshiftdb2 in a dereplication workflow requires presently programming skills, owing to the diversity of data encoding and processing procedures. A graphical user interface that integrates seamlessly chemical structure collection, spectral data prediction and database building still does not exist, as far as we know. The present work proposes a stand–alone software tool that assists the identification of mixture components in a simple way. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease. Cognitive functions and communication skills worsen as the disease progresses, thereby reducing patients' independence levels. Therefore, recommending software that can be used at home may be a useful means of slowing down the cognitive and communicative decline in AD. Aims: To develop software that can be used at home to slow down the cognitive and communicative decline and increase independence in individuals with AD; and to examine the effect of this software on the cognitive communication skills of individuals with AD. Methods & Procedures: The study was completed in four stages: the development of the application; the evaluation of the participants and their training for the application; their use of the application at home; and the re‐evaluation of the participants. A total of 32 individuals who met the inclusion criteria were included in the study. These individuals were randomly divided into study and control groups, each consisting of a total of 16 participants, including six in the mild stage, six in the moderate stage, and four in the severe stages. The developed software was loaded on tablets and given to the participants in the study group. The participants in the control group only received their pharmacological treatment, while those in the study group received both their pharmacological treatment and used the developed application. All participants were evaluated with the Mini‐Mental State Examination (MMSE) and Language Assessment Test for Aphasia (LATA) before and after application use. A survey was administered to the caregivers of the participants in the study group after the use of the application. Outcomes & Results: The results revealed a positive change in the cognitive–communication skills of the individuals in the study group, even if they were in the severe stage, according to the LATA and MMSE, as well as the survey. The application led to the greatest improvements in grammar on the LATA and orientation on the MMSE. No rapid cognitive decline was seen in individuals at all stages in the control group. Conclusions & Implications: In this study, software was developed in Turkish that can be used in every stage of AD as part of a holistic cognitive‐communication intervention programme offering alternative and supportive communication for individuals with AD, even those in the severe stage. Results prove the effectiveness of the developed software on the cognitive–communication skills of individuals with AD. What This Paper Adds: What is already known on the subject: There are a few (as far as is known, three) applications developed in English for cognitive–communication disorders due to dementia. What this study adds to the existing literature: In this study, for the first time in Turkish, mobile‐compatible software has been developed for both cognitive and communication disorders that is specific to individuals with AD and can be used by individuals at all stages of the disease. The effects of the application we developed on the cognitive–communication skills of individuals with AD were shown in a randomised controlled trial. What are the potential or actual clinical implications of this work?: Using the app can help people with all stages of AD keep their cognitive and communication skills and have a better prognosis in terms of cognitive–communication skills, especially grammar and orientation. [ABSTRACT FROM AUTHOR]

Melt electrowriting (MEW) is a young and promising additive manufacturing technology for producing high‐precision scaffolds. In this study, we develop an intuitive visualization system enabling users to measure MEW jet diameters along the spinline without programming knowledge. The digital measurement adopts the same theory as our reported manual measurement. The maximum error between the digitally and manually measured data is smaller than 9%, suggesting that the open‐source system developed here is reliable in measuring jet diameters. [ABSTRACT FROM AUTHOR]

Nuclear magnetic resonance (NMR) spectral analysis of biofluids can be a time‐consuming process, requiring the expertise of a trained operator. With NMR becoming increasingly popular in the field of metabolomics, there is a growing need to change this paradigm and to automate the process. Here we introduce MagMet, an online web server, that automates the processing and quantification of 1D 1H NMR spectra from biofluids—specifically, human serum/plasma metabolites, including those associated with inborn errors of metabolism (IEM). MagMet uses a highly efficient data processing procedure that performs automatic Fourier Transformation, phase correction, baseline optimization, chemical shift referencing, water signal removal, and peak picking/peak alignment. MagMet then uses the peak positions, linewidth information, and J‐couplings from its own specially prepared standard metabolite reference spectral NMR library of 85 serum/plasma compounds to identify and quantify compounds from experimentally acquired NMR spectra of serum/plasma. MagMet employs linewidth adjustment for more consistent quantification of metabolites from higher field instruments and incorporates a highly efficient data processing procedure for more rapid and accurate detection and quantification of metabolites. This optimized algorithm allows the MagMet webserver to quickly detect and quantify 58 serum/plasma metabolites in 2.6 min per spectrum (when processing a dataset of 50–100 spectra). MagMet's performance was also assessed using spectra collected from defined mixtures (simulating other biofluids), with >100 previously measured plasma spectra, and from spiked serum/plasma samples simulating known IEMs. In all cases, MagMet performed with precision and accuracy matching the performance of human spectral profiling experts. MagMet is available at http://magmet.ca. [ABSTRACT FROM AUTHOR]

We report the development of a software program, called MagMet‐F, that automates the processing and quantification of 1D 1H NMR of human fecal extracts. To optimize the program, we identified 82 potential fecal metabolites using 1D 1H NMR of six human fecal extracts using manual profiling and a literature review of known fecal metabolites. We acquired pure versions of those metabolites and then acquired their 1D 1H NMR spectra at 700 MHz to generate a fecal metabolite spectral library for MagMet‐F. The fitting of these metabolites by MagMet‐F was iteratively optimized to replicate manual profiling. We validated MagMet‐F's automated profiling using a test set of six fecal extracts. It correctly identified 80% of the compounds and quantified those within <20% of the values determined by manual profiling using Chenomx. We also compared MagMet‐F's profiling performance to two other open‐access NMR profiling tools, Bayesil and Batman. MagMet‐F outperformed both. Bayesil repeatedly overestimated metabolite concentrations by 10% to 40% while Batman was unable to properly quantify any compounds and took 10–20× longer. We have implemented MagMet‐F as a freely accessible web server to enable automated, fast and convenient 1D 1H NMR spectral profiling of fecal samples. MagMet‐F is available at https://www.magmet.ca. [ABSTRACT FROM AUTHOR]

Fraud is a persistent and increasing problem in the telecom industry. Telcos work in isolation to prevent fraud. Sharing information is critical for detecting and preventing fraud. The primary constraint on sharing information is privacy preservation. Several techniques have been developed to share data while preserving privacy using privacy‐preserving record linkage (PPRL). Most of the PPRL techniques use a similarity measure like Jacquard similarity on homologous datasets, which are all prone to graph‐based attacks, rendering existing methods insecure. Many complex and slow techniques use the Bloom filter implementation, which can be compromised in a cryptanalysis attack. This paper proposes an attack‐proof PPRL method using existing infrastructure of a telco without a complex multistep protocol. First, a novel way of matching two non‐homologous datasets using attack‐proof digital signature schemes, like the Edwards‐curve digital signature algorithm is proposed. Here, Jaccard similarity can only be estimated using this method and not on the datasets directly. Second, two parties transact with a simple request–reply method. To validate the match accuracy, privacy preservation, and performance of this approach, it was tested on a large public dataset (North Carolina Voter Database). This method is secure against attacks and achieves 100% match accuracy with improved performance. [ABSTRACT FROM AUTHOR]

Epilepsy is a common non‐communicable, group of neurological disorders affecting more than 50 million individuals worldwide. Different approaches of basic, clinical, and translational research of the human brain have been explored to diagnose, treat, and manage the growing no. of cases of epilepsy. Various hospital information from video, images, signals, forms, and so forth, are retrieved and analysed to develop a consensus for such patients. Electroencephalography (EEG) tests are routinely used to diagnose the type of epilepsy in a clinical setting. Artificial Intelligence algorithms are assisting in the early detection and prediction of epileptic patterns observed in EEG signals. This paper reviews recent and emerging state‐of‐the‐art (SOTA) software and hardware approaches in data selection, signal processing, feature estimation, classification, detection methods, and evaluation metrics applied to open and private EEG datasets from 2014 to 2022. The work summarizes and compares reported works through subjective and objective parameters. Rise in hardware pipeline, start‐ups, and companies, deep learning methods in software pipeline and release of free EEG datasets have been observed from 2014 to 2022. SOTA advancements have shown immense potential and paved a path to successful real‐time detection, prediction, and management of epileptic seizures. [ABSTRACT FROM AUTHOR]

Background and Purpose: This study was dedicated to investigating the agreement of the calculated results of two CT perfusion (CTP) postprocessing software packages, including parameter maps and ischemic volume, focusing on the infarct core volume (ICV) and penumbra volume (PV). Methods: A retrospective collection of 235 patients with acute ischemic stroke who underwent CTP examination were enrolled. All images had been analyzed with two software pipelines, RAPID CTP and AccuCTP, and the comparative analysis was based on ICV and PV results calculated by both software packages. The agreement of parameter maps was evaluated by root mean square error and Bland‐Altman analysis. The ICV and PV agreement was evaluated by intraclass correlation coefficient (ICC) and Bland‐Altman analysis. The accuracy of ICV and PV based on multiple thresholds was also analyzed. Results: The ICV and PV of AccuCTP and RAPID CTP show excellent agreement. The relative differences of the parameter maps were all within 10% and the Bland‐Altman analysis also showed a strong agreement. From ordinary least squares fitting results, both ICV and PV had a remarkably high goodness of fit (ICV, R2= 0.975 [p<.001]; PV, R2= 0.964 [p<.001]). For the ICC analysis, both had high ICC scores (ICV ICC 0.984, 95% CI [confidence interval] 0.973‐0.989; PV ICC 0.955, 95% CI 0.947‐0.964). Furthermore, multi‐threshold analysis on the basis of ICV and PV also achieved reliable analytical accuracy. Conclusions: The image analysis results of AccuCTP are in excellent agreement with RAPID CTP and can be used as an alternative analysis tool to RAPID CTP software in stroke clinical practice. [ABSTRACT FROM AUTHOR]

Ancient environmental DNA (aeDNA) is a crucial source of information for past environmental reconstruction. However, the computational analysis of aeDNA involves the inherited challenges of ancient DNA (aDNA) and the typical difficulties of eDNA samples, such as taxonomic identification and abundance estimation of identified taxonomic groups. Current methods for aeDNA fall into those that only perform mapping followed by taxonomic identification and those that purport to do abundance estimation. The former leaves abundance estimates to users, while methods for the latter are not designed for large metagenomic datasets and are often imprecise and challenging to use.Here, we introduce euka, a tool designed for rapid and accurate characterisation of aeDNA samples. We use a taxonomy‐based pangenome graph of reference genomes for robustly assigning DNA sequences and use a maximum‐likelihood framework for abundance estimation. At the present time, our database is restricted to mitochondrial genomes of tetrapods and arthropods but can be expanded in future versions.We find euka to outperform current taxonomic profiling tools and their abundance estimates. Crucially, we show that regardless of the filtering threshold set by existing methods, euka demonstrates higher accuracy. Furthermore, our approach is robust to sparse data, which is idiosyncratic of aeDNA, detecting a taxon with an average of 50 reads aligning. We also show that euka is consistent with competing tools on empirical samples.euka's features are fine‐tuned to deal with the challenges of aeDNA, making it a simple‐to‐use, all‐in‐one tool. It is available on GitHub: https://github.com/grenaud/vgan. euka enables researchers to quickly assess and characterise their sample, thus allowing it to be used as a routine screening tool for aeDNA. [ABSTRACT FROM AUTHOR]

GRASP is a scientific software application designed for the graphical inspection, reduction and analysis of multidetector data produced by the small-angle neutron scattering (SANS) instruments at the Institut Laue-Langevin and other neutron sources around the world. The first developments of GRASP began more than 20 years ago and were written in MATLAB, allowing rapid development of scientific code, with much of the data handling, matrix manipulation, mathematical tools, user interface and graphical tools integrated at a high level in the underlying MATLAB platform. By their very nature, multidimensional data are often best appreciated in graphical form. GRASP deals with many of the diverse requirements for data reduction and analysis of SANS data using a general set of tools and reduction algorithms suited to 2D multidetector data. A further fundamental architectural inclusion is a third dimension of data manipulation, thereby easily allowing parametric analysis and cross referencing of series data such as composition, kinetic measurements, temperature, magnetic field, angle or time of flight, often considered as a single 'measurement'. This article serves as a reference document for users of the software, and outlines the architecture and strategy of the program. An overview of some of the features, capabilities, peripheral user modules and neutron scattering tools is presented. [ABSTRACT FROM AUTHOR]

Accurate knowledge of the speed at which water moves along a river is essential for understanding ecohydraulic processes and managing natural resources. Measuring flow velocity via remote sensing can be more efficient than conventional field methods, and powerful computational techniques for inferring velocity fields from videos or image time series have been developed. The development of dedicated software tools for particle image velocimetry (PIV) could facilitate greater use of these methods by the river community. This paper introduces a standalone app designed for this exact purpose: the Toolbox for River Velocimetry using Images from Aircraft, or TRiVIA. The program provides a complete workflow for producing spatially distributed velocity vectors from a video or sequence of images, all within an accessible graphical user interface. TRiVIA includes modules for extracting and resampling frames, stabilization and geo‐referencing images, defining a region of interest, enhancing images, performing PIV with an efficient ensemble correlation algorithm, visualizing results, assessing accuracy assessment, and exporting PIV output. We illustrate the software's capabilities using an example data set from a large river in Alaska. The initial release of the toolbox is now freely available. Augmenting TRiVIA to incorporate bathymetric information could enable discharge calculation functionality. [ABSTRACT FROM AUTHOR]

CellProfiler is a widely used software for creating reproducible, reusable image analysis workflows without needing to code. In addition to the >90 modules that make up the main CellProfiler program, CellProfiler has a plugins system that allows for the creation of new modules which integrate with other Python tools or tools that are packaged in software containers. The CellProfiler‐plugins repository contains a number of these CellProfiler modules, especially modules that are experimental and/or dependency‐heavy. Here, we present an upgraded CellProfiler‐plugins repository, an example of accessing containerised tools, improved documentation and added citation/reference tools to facilitate the use and contribution of the community. [ABSTRACT FROM AUTHOR]

Comparison of software applications for the construction of the special model subsoil In the context of Building Information Modeling (BIM), the subsurface is receiving increasing attention. The so‐called special model subsoil, which has to be constructed by a geotechnical ex‐pert, must contain not only the geometrical representation of the relevant soil layers, but also the associated data of the accompanying geotechnical report. In addition to the difficulty of more often than not insufficient specifications regarding information depth and structure by the client, limitations can arise from the software application used for modelling. This work provides a comparison of the construction process of the special model subsoil for a fictional test project using four different and well‐established software applications. The differences found regarding the effort required to obtain a working model, the modelling functionalities and the usefulness of the final special model subsoil as part of the parent BIM‐model are presented. Furthermore, more general aspects such as the level of software support, training materials and integration with other software applications are described and compared. The key differences in the geometrical modelling results are compared using cross‐sections. Based on the experienced gained by this comparison, areas are identified where current software applications are lacking and further development is required. [ABSTRACT FROM AUTHOR]

The question of whether the time has come to hang up the stethoscope is bound up in the promises of artificial intelligence (AI), promises that have so far proven difficult to deliver, perhaps because of the mismatch between the technical capability of AI and its use in real‐world clinical settings. This perspective argues that it is time to move away from discussing the generalised promise of disembodied AI and focus on specifics. We need to focus on how the computational method underlying AI, i.e. machine learning (ML), is embedded into tools, how those tools contribute to clinical tasks and decisions and to what extent they can be relied on. Accordingly, we pose four questions that must be asked to make the discussion real and to understand how ML tools contribute to health care: (1) What does the ML algorithm do? (2) How is output of the ML algorithm used in clinical tools? (3) What does the ML tool contribute to clinical tasks or decisions? (4) Can clinicians act or rely on the ML tool? Two exemplar ML tools are examined to show how these questions can be used to better understand the role of ML in supporting clinical tasks and decisions. Ultimately, ML is just a fancy method of automation. We show that it is useful in automating specific and narrowly defined clinical tasks but likely incapable of automating the full gamut of decisions and tasks performed by clinicians. [ABSTRACT FROM AUTHOR]

Mass spectrometry imaging (MSI) has become a widespread analytical technique to perform nonlabeled spatial molecular identification. The Achilles' heel of MSI is the annotation and identification of molecular species due to intrinsic limitations of the technique (lack of chromatographic separation and the difficulty to apply tandem MS). Successful strategies to perform annotation and identification combine extra analytical steps, like using orthogonal analytical techniques to identify compounds; with algorithms that integrate the spectral and spatial information. In this review, we discuss different experimental strategies and bioinformatics tools to annotate and identify compounds in MSI experiments. We target strategies and tools for small molecule applications, such as lipidomics and metabolomics. First, we explain how sample preparation and the acquisition process influences annotation and identification, from sample preservation to the use of orthogonal techniques. Then, we review twelve software tools for annotation and identification in MSI. Finally, we offer perspectives on two current needs of the MSI community: the adaptation of guidelines for communicating confidence levels in identifications; and the creation of a standard format to store and exchange annotations and identifications in MSI. [ABSTRACT FROM AUTHOR]

The controlled growth of surface‐modifying polymer films by electrodeposition often fails because of the lack of redox activity of these compounds. Here, electroactive complexants help to electrodeposit non‐electroactive polymers. Hence, we investigate the counterion‐induced electrodeposition of polyelectrolytes: three quaternized poly(N,N‐dialkylaminoethyl methacrylate)s (qPDAAEMA), in particular their methyl, ethyl, and isopropyl derivatives (i. e. qPDMAEMA, qPDEAEMA, and qPDPAEMA), provide transparent solutions in the presence of hexacyanoferrate(II) (ferrocyanide) at specific concentration windows of the KCl supporting electrolyte. Below a certain KCl concentration, insolubility dominates irrespective of the hexacyanoferrate valency, whilst above an upper threshold, full solubility is observed. Between these limits, oxidation reversibly electrodeposits polymer/hexacyanoferrate(III) (ferricyanide) complexes. Hydrodynamic voltammetry (and data analysis using in‐house software) provides access to the deposition efficiency (DE). qPDEAEMA with ethyl substituents shows highest DEs; larger or smaller substituents fall short because of a balance between "hydrophobicity" and charge separation, shifting the window toward smaller salt concentrations with increasing alkyl size. We always observe a DE maximum close to the minimum salt concentration, whilst electrochemical quartz crystal microbalance (EQCM) measurements indicate a change in film water content close to the maximum. These effects, being also discussed in terms of polymer conformation, can direct the future engineering of electroassisted coatings. [ABSTRACT FROM AUTHOR]

Dynamic light scattering (DLS) is routinely employed to assess the homogeneity and size‐distribution profile of samples containing microscopic particles in suspension or solubilized polymers. In this work, Raynals, user‐friendly software for the analysis of single‐angle DLS data that uses the Tikhonov–Phillips regularization, is introduced. Its performance is evaluated on simulated and experimental data generated by different DLS instruments for several proteins and gold nanoparticles. DLS data can easily be misinterpreted and the simulation tools available in Raynals allow the limitations of the measurement and its resolution to be understood. It was designed as a tool to address the quality control of biological samples during sample preparation and optimization and it helps in the detection of aggregates, showing the influence of large particles. Lastly, Raynals provides flexibility in the way that the data are presented, allows the export of publication‐quality figures, is free for academic use and can be accessed online on the eSPC data‐analysis platform at https://spc.embl‐hamburg.de/. [ABSTRACT FROM AUTHOR]

Premise: Transposable elements (TEs) make up more than half of the genomes of complex plant species and can modulate the expression of neighboring genes, producing significant variability of agronomically relevant traits. The availability of long‐read sequencing technologies allows the building of genome assemblies for plant species with large and complex genomes. Unfortunately, TE annotation currently represents a bottleneck in the annotation of genome assemblies. Methods and Results: We present a new functionality of the Next‐Generation Sequencing Experience Platform (NGSEP) to perform efficient homology‐based TE annotation. Sequences in a reference library are treated as long reads and mapped to an input genome assembly. A hierarchical annotation is then assigned by homology using the annotation of the reference library. We tested the performance of our algorithm on genome assemblies of different plant species, including Arabidopsis thaliana, Oryza sativa, Coffea humblotiana, and Triticum aestivum (bread wheat). Our algorithm outperforms traditional homology‐based annotation tools in speed by a factor of three to >20, reducing the annotation time of the T. aestivum genome from months to hours, and recovering up to 80% of TEs annotated with RepeatMasker with a precision of up to 0.95. Conclusions: NGSEP allows rapid analysis of TEs, especially in very large and TE‐rich plant genomes. [ABSTRACT FROM AUTHOR]

A new AWWA tool analyzes effective useful life for water treatment plant and pumping station assets, allowing utilities to make targeted, data‐driven, and timely rehabilitation or replacement decisions. [ABSTRACT FROM AUTHOR]

The availability of phylogenetic data has greatly expanded in recent years. As a result, a new era in phylogenetic analysis is dawning—one in which the methods we use to analyse and assess our data are the bottleneck to producing valuable phylogenetic hypotheses, rather than the need to acquire more data. This makes the ability to accurately appraise and evaluate new methods of phylogenetic analysis and phylogenetic artefact identification more important than ever. Incongruence in phylogenetic reconstructions based on different datasets may be due to two major sources: biological and methodological. Biological sources comprise processes like horizontal gene transfer, hybridization and incomplete lineage sorting, while methodological ones contain falsely assigned data or violations of the assumptions of the underlying model. While the former provides interesting insights into the evolutionary history of the investigated groups, the latter should be avoided or minimized as best as possible. However, errors introduced by methodology must first be excluded or minimized to be able to conclude that biological sources are the cause. Fortunately, a variety of useful tools exist to help detect such misassignments and model violations and to apply ameliorating measurements. Still, the number of methods and their theoretical underpinning can be overwhelming and opaque. Here, we present a practical and comprehensive review of recent developments in techniques to detect artefacts arising from model violations and poorly assigned data. The advantages and disadvantages of the different methods to detect such misleading signals in phylogenetic reconstructions are also discussed. As there is no one‐size‐fits‐all solution, this review can serve as a guide in choosing the most appropriate detection methods depending on both the actual dataset and the computational power available to the researcher. Ultimately, this informed selection will have a positive impact on the broader field, allowing us to better understand the evolutionary history of the group of interest. [ABSTRACT FROM AUTHOR]