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This paper introduces the Fish 3D Locomotion app (F3LA), a Python‐based, Graphical User Interface (GUI)‐equipped tool designed to automate behavioral endpoint extraction in zebrafish locomotion assays. Building on our previous work, which utilized a specialized aquatic tank with a mirror and a single camera for fish movement tracking in three dimensions, F3LA significantly enhances data processing efficiency. Its accuracy was tested by reanalyzing and comprehensively comparing the calculated data with the previously published data from prior publications. From the comparison results, 90% of endpoints showed a similar statistical difference result. These minor differences were due to the different starting points for the dataset and updated calculation formulas that are implemented in F3LA. In addition, shoaling area or shoaling volume calculations are also included in F3LA as a new feature that can serve as sensitive indicators of social cohesion, group dynamics, or stress responses, offering insights into neuropsychological conditions or the effects of pharmacological interventions. Furthermore, F3LA offers a marked improvement over manual operations, being at least five times faster, while maintaining consistent accuracy as it reduces human‐induced errors, ensuring a higher degree of reliability in the results. Finally, the potency of F3LA was tested to evaluate the toxicities of 14 rare earth elements (REEs) to the adult zebrafish behaviors. Based on the results, our findings suggested that each tested REE altered fish behaviors in different patterns and magnitudes to each other. However, among the tested light rare earth elements (LREEs), neodymium was demonstrated to cause more relatively severe behavior alterations than other LREEs, indicated by the statistically higher value of entropy (0.2695 ± 0.04977 (mean with a standard deviation)) than the control group (0.2352 ± 0.05896). Meanwhile, in terms of heavy rare earth elements (HREEs), erbium seemed to lead to more distinct behavior toxicities than other HREEs, which was shown by the statistically lower level of fractal dimension (2.022 ± 0.3412) than the untreated group (2.255 ± 0.1661). Taken together, F3LA's development marks a significant advance in high‐throughput toxicological and pharmacological assessments in zebrafish, leveraging three‐dimensional locomotion data for a more comprehensive analysis of fish behavior performance, providing a significant contribution to research in various fields. [ABSTRACT FROM AUTHOR]

Robotic Process Automation (RPA) is an emerging software technology for automating business processes. RPA uses software robots to perform repetitive and error‐prone tasks previously done by human actors quickly and accurately. These robots mimic humans by interacting with existing software applications through user interfaces (UI). The goal of RPA is to relieve employees from repetitive and tedious tasks to increase productivity and to provide better service quality. Yet, despite all the RPA benefits, most organizations fail to adopt RPA. One of the main reasons for the lack of adoption is that organizations are unable to effectively identify the processes that are suitable for RPA. This paper proposes a new method, called Rule‐based robotic process analysis (RRPA), that assists process automation practitioners to classify business processes according to their suitability for RPA. The RRPA method computes a suitability score for RPA using a combination of two RPA goals: (i) the RPA feasibility, which assesses the extent to which the process or the activity lends itself to automation with RPA and (ii) the RPA relevance, which assesses whether the RPA automation is worthwhile. We tested the RRPA method on a set of 13 processes. The results showed that the method is effective at 82.05% and efficient at 76.19%. [ABSTRACT FROM AUTHOR]

The development of systems offers a particular challenge for the interoperability of different tools used by collaborating developers like requirements management, design, or simulation tools. The difficult and time‐consuming process to integrate and exchange data between different systems can lead to data inconsistencies and reduced efficiency in the development process. The integration standard Open Services for Lifecycle Collaboration (OSLC) targets the integration of engineering software applications. Its approach supports loose tool coupling, in which each application autonomously manages its own product data, while providing RESTful web services through which other applications can interact. This paper aims to analyze the suitability of OSLC as an overarching integration mechanism for the complete set of engineering artifacts created during system development. This paper presents use cases for the application of OSLC at the company MAHLE. For these use cases, the employed OSLC based toolchain is assessed. The analysis in this paper confirms that OSLC's capabilities allow users to support traceability and can support the exchange and integrate data according to the defined requirements, but it is not sufficient for sophisticated data processing functionalities, such as safety analysis or simulation. The OSLC integration does correspondingly compare favorably to integration technologies already in use regarding traceability, while transformation of data in domain specific tools is needed to achieve deeper levels of integration. [ABSTRACT FROM AUTHOR]

The HYDRUS codes have become standard tools for addressing many soil, agricultural, environmental, and hydrological problems requiring the evaluation of various subsurface physical, chemical, and biological processes. There are now many thousands of HYDRUS users worldwide, with thousands of applications of the HYDRUS models appearing in the peer‐reviewed literature. In this manuscript, we provide an overview of the capabilities of the most recent Version 5 of HYDRUS, focusing primarily on features implemented since 2016. We briefly describe the standard HYDRUS model and its standard and nonstandard specialized add‐on modules that significantly expand the capabilities of the software packages. The standard add‐on modules include HPx, UNSATCHEM, Wetland, Furrow, PFAS, COSMIC, DPU, SLOPE Cube, and Particle Tracking. Recent developments of the HYDRUS Package for MODFLOW are also described, along with additional capabilities incorporated into the graphical user interface supporting HYDRUS. Also discussed are new or improved options to simulate the fate and transport of environmental isotopes, multi‐cropping systems, compensated root water uptake, and hydraulic redistribution within the rootzone, which will be implemented in upcoming add‐on modules. Another objective is to review selected applications of the HYDRUS models, such as evaluations of various irrigation, low‐impact development (LID), and managed aquifer recharge (MAR) schemes. Core Ideas: An overview of the capabilities of the most recent Version 5 of HYDRUS.The description of the standard and nonstandard specialized HYDRUS add‐on modules.A review of selected popular applications of the HYDRUS models.Description of new or improved upcoming HYDRUS add‐on modules. [ABSTRACT FROM AUTHOR]

Biopharmaceutical manufacturing entails a series of highly regulated steps. The manufacturing of safe and efficacious drug product (DP) requires testing of critical quality attributes (CQAs) against specification limits. DP potency concentration, which measures the dosage strength of a particular DP, is a CQA of great interest. In order to minimize the DP potency out‐of‐specification (OOS) risk, sterile fill finish (SFF) process adjustments may be needed. Varying the potency targets can be one such process adjustment. To facilitate such evaluation, data acquisition and statistical calculations are required. Regularly conducting the OOS risk assessment manually using commercial statistical software can be tedious, error‐prone, and impractical, especially when several alternate potency targets are under consideration. In this work, the development of a novel framework for OOS risk assessment and deployment of cloud‐based statistical software application to facilitate the risk assessment are presented. This application is intended to streamline the assessment of alternate potency targets for DP in biologics manufacturing. The major aspects of this potency targeting application development are presented in detail. Specifically, data sources, pipeline, application architecture, back‐end and front‐end development as well as application verification are discussed. Finally, several use cases are presented to highlight the application's utility in biologics manufacturing. [ABSTRACT FROM AUTHOR]

This study includes the development of a farm advisory framework known as the "AquaProFAN framework," which is concerned with the study of various requirements by the aquafarmers and stakeholder community in fisheries. AquaProFAN (Aqua Professional Farm Advisory Network) advisory committee provided careful consideration to the aquafarmers' inquiries and proper clarification with many innovative ideas, and the feasibility study on chatbot implementation was also performed. The end product, called AquaGent, is an AI‐based chatbot designed for shrimp aquafarmers and support services. It was developed and deployed in social media platforms like Facebook Messenger and Telegram for research and dissemination purposes. The effectiveness of the chatbot was analysed and the findings indicated that: (i) informational requests are more satisfactory than emotional requests, (ii) the performance of chatbot is comparatively better than other software applications concerning informational requests, (iii) participants perceive 'AquaGent' chatbot to be more user friendly and time saving. It can be concluded that the implementation of this state‐of‐art technology in aquaculture sector will improve stakeholders' understanding for future efficient and profitable production. [ABSTRACT FROM AUTHOR]

Introduction: Precise electrocardiographic localization of accessory pathways (AP) can be challenging. Seminal AP localization studies were limited by complexity of algorithms and sample size. We aimed to create a nonalgorithmic method for AP localization based on color‐coded maps of AP distribution generated by a web‐based application. Methods: APs were categorized into 19 regions/types based on invasive electrophysiologic mapping. Preexcited QRS complexes were categorized into 6 types based on polarity and notch/slur. For each QRS type in each lead the distribution of APs was visualized on a gradient map. The principle of common set was used to combine the single lead maps to create the distribution map for AP with any combination of QRS types in several leads. For the validation phase, a separate cohort of APs was obtained. Results: A total of 800 patients with overt APs were studied. The application used the exploratory data set of 553 consecutive APs and the corresponding QRS complexes to generate AP localization maps for any possible combination of QRS types in 12 leads. Optimized approach (on average 3 steps) for evaluation of preexcited electrcardiogram was developed. The area of maximum probability of AP localization was pinpointed by providing the QRS type for the subsequent leads. The exploratory data set was validated with the separate cohort of APs (n = 256); p =.23 for difference in AP distribution. Conclusions: In the largest data set of APs to‐date, a novel probabilistic and semi‐automatic approach to electrocardiographic localization of APs was highly predictive for anatomic localization. [ABSTRACT FROM AUTHOR]

Multidrug-resistant organism infections are a serious health problem globally, and can result in patient mortality and morbidity. In this descriptive study, we produced the first web application for transmission prevention specific to the situation based on nursing experience, knowledge, and practice guidelines and to evaluate web application satisfaction among Thai nurses. The sample comprised 282 Thai registered nurses experienced in caring for patients with multidrug-resistant organisms in a tertiary hospital. A demographic form and knowledge test were completed anonymously online. Data were analyzed using descriptive statistics. The application emphasized crucial topics for which participants had low preliminary knowledge and included tutorial sessions, pictures, video clips, drills, and a post-test. The application was piloted with a random sample of 30 nurses, and an instrument tested their satisfaction with this. Results revealed that preliminary knowledge scores for preventing transmission were moderate, and participants were highly satisfied with the application. Findings suggest the application is suitable for Thai nurses and could be applied to nursing practice elsewhere. However, further testing is recommended before implementing it into nursing practice. [ABSTRACT FROM AUTHOR]

The expansive scientific software ecosystem, characterized by millions of titles across various platforms and formats, poses significant challenges in maintaining reproducibility and provenance in scientific research. The diversity of independently developed applications, evolving versions and heterogeneous components highlights the need for rigorous methodologies to navigate these complexities. In response to these challenges, the SBGrid team builds, installs and configures over 530 specialized software applications for use in the on‐premises and cloud‐based computing environments of SBGrid Consortium members. To address the intricacies of supporting this diverse application collection, the team has developed the Capsule Software Execution Environment, generally referred to as Capsules. Capsules rely on a collection of programmatically generated bash scripts that work together to isolate the runtime environment of one application from all other applications, thereby providing a transparent cross‐platform solution without requiring specialized tools or elevated account privileges for researchers. Capsules facilitate modular, secure software distribution while maintaining a centralized, conflict‐free environment. The SBGrid platform, which combines Capsules with the SBGrid collection of structural biology applications, aligns with FAIR goals by enhancing the findability, accessibility, interoperability and reusability of scientific software, ensuring seamless functionality across diverse computing environments. Its adaptability enables application beyond structural biology into other scientific fields. [ABSTRACT FROM AUTHOR]

Introduction: Liver cancer presents a growing global health concern, necessitating advanced approaches for intervention. This review investigates the use and effectiveness of software navigation in interventional radiology for liver tumour procedures. Methods: In accordance with Preferred Reporting Items for Systematic reviews and Meta‐Analyses extension for Scoping Reviews (PRISMA‐ScR) guidelines, a scoping review was conducted of the literature published between 2013 and 2023 sourcing articles through MEDLINE, Scopus, CINAHL and Embase. Eligible studies focused on liver cancer, utilised cone‐beam computed tomography (CBCT), and employed software for intervention. Twenty‐one articles were deemed eligible for data extraction and analysis. Results: Categorised by type, software applications yielded diverse benefits. Feeder detection software significantly enhanced vessel identification, reducing non‐target embolisation by up to 43%. Motion correction software demonstrated a 20% enhancement in image quality, effectively mitigating breathing‐induced motion artefacts. Liver perfusion software facilitated efficient tumour targeting while simultaneously reducing the occurrence of side effects. Needle guide software enabled precise radiofrequency ablation needle placement. Additionally, these software applications provided detailed anatomical simulations. Overall, software integration resulted in shorter procedures, reduced radiation exposure and decreased contrast media usage. Conclusion: This scoping review highlights the innovative yet relatively underexplored role of software navigation for liver tumour procedures. The integration of software applications not only enhances procedural efficiency but also bolsters operator confidence, and contributes to improved patient outcomes. Despite the current lack of uniformity and standardisation, these software‐driven advancements hold significant promise for transforming liver tumour interventions. To realise these benefits, further research is needed to explore the clinical impact and optimal utilisation of software navigation tools in interventional radiology. [ABSTRACT FROM AUTHOR]

The paper presents a research on estimating the positioning accuracy of autonomous industrial vehicles, using an original sensor fusion combination, in specific polymer production factories environments. Mechanical and electrical subsystems designs are presented, together with the software application and testing results. Conclusions are drawn, serving for future positioning system design. [ABSTRACT FROM AUTHOR]

Background: Alcohol use disorder (AUD) is a highly impairing condition with important public health impacts. Despite the availability of treatment options for AUD, research shows that few people receive treatment, and even fewer can maintain abstinence/low‐drinking levels. This study investigated the role of personality traits in past‐year alcohol use among individuals with severe AUD who ever attended Alcoholics Anonymous (AA), a widespread and easily accessible self‐help group for alcohol problems. Methods: Univariable and multivariable regressions were performed separately in females and males with alcohol consumption as an outcome. Socioeconomic factors, genetic liability, and psychopathology were included as covariates in the analyses. Results: Results from the multivariable model indicated that in females who attended AA, greater alcohol use was related to both positive and negative urgency and low sensation seeking, while in males, greater alcohol use was related to positive urgency. Results also showed that, in both sexes, younger age and lower educational levels were associated with greater alcohol use. Moreover, single males and individuals with lower AUD severity were at higher risk of using alcohol in the past year. Conclusions: These findings highlight sex‐specific correlates of drinking in individuals with AUD who engaged in self‐help groups. These findings may help to improve treatment options, as personality encompasses modifiable traits that can be targeted in psychological interventions. [ABSTRACT FROM AUTHOR]

Web search is a crucial technology for the digital economy. Dominated by a few gatekeepers focused on commercial success, however, web publishers have to optimize their content for these gatekeepers, resulting in a closed ecosystem of search engines as well as the risk of publishers sacrificing quality. To encourage an open search ecosystem and offer users genuine choice among alternative search engines, we propose the development of an Open Web Index (OWI). We outline six core principles for developing and maintaining an open index, based on open data principles, legal compliance, and collaborative technology development. The combination of an open index with what we call declarative search engines will facilitate the development of vertical search engines and innovative web data products (including, e.g., large language models), enabling a fair and open information space. This framework underpins the EU‐funded project OpenWebSearch.EU, marking the first step towards realizing an Open Web Index. [ABSTRACT FROM AUTHOR]

Security is an essential attribute of high‐quality software. However, effectively incorporating security practices into different phases of the software development life cycle (SDLC) remains challenging. Owing to less mature secure testing processes, organizations are prone to ineffective testing practices for defect detection, including severe security‐related failures. Thus, in this study, we present a maturity model for secure software testing (MMSST) to assist software development organizations in improving the secure testing of software applications. We conducted a multivocal literature review and identified 68 primary studies from the formal and gray literature. Then, based on the available evidence, 27 process areas were identified to develop the proposed MMSST. The MMSST includes five main categories: governance, contrive and design, execution, deployment and configuration, and mature. The MMSST was subsequently evaluated using case studies related to practical environments. Results demonstrate that the proposed MMSST is useful for estimating the maturity level of an organization with respect to the secure testing phase of the SDLC. The participants of the case studies also agreed that the proposed MMSST is useful in terms of structure, user satisfaction, and ease of use. We believe that the proposed MMSST can help organizations evaluate and improve software security testing practices. In addition, the proposed MMSST is expected to provide researchers and industry practitioners with an effective foundation for developing new secure testing approaches and tools. [ABSTRACT FROM AUTHOR]

This study was conducted to assess the disparities in camel activities such as eating, drinking, sitting, standing, and sleeping between primiparous and multiparous females before parturition using computer vision. Also, any extraordinary behaviours during the final 2 h before parturition and the necessary manual interventions were meticulously recorded. Five primiparous (age: 4.5–7 years) and 7 multiparous (age: 8–14 years; parity: 2.1 ± 1.5) dromedary camels, were included in this study. Pre‐partum females were housed double in a parturition pen provided with two Reolink RLC‐810A cameras and the data were collected and recorded for each female. Two primiparous and 1 multiparous female required assistance in pulling the calf from both forelimbs to complete their parturition (27.3%). The drinking and sleeping activities were similar in primiparous and multiparous females during the recorded 32 h leading up to calving. Only eating activity exhibited a longer period in primiparous females compared to multiparous females specifically during the 12‐h before calving. Sitting activity was longer, and standing activity was shorter in multiparous than in primiparous females during the 24, 12, and 6 h before calving. All parturient camels, whether primiparous or multiparous, exhibited signs of distress. Some extraordinary behaviours were observed, such as two multiparous females attempting to deter their primiparous counterparts from eating. Additionally, three females displayed a distinctive standing position on their knees while their hind limbs were in a complete standing position for 3–5 min before transitioning to sitting or standing positions. Furthermore, one primiparous female stood while the head and forelimbs of the calf partially protruded from her vulva. In conclusion, the application of computer vision and deep learning technology proves valuable for observing prepartum camels under farm conditions, potentially reducing economic losses stemming from delayed human intervention in dystocia cases. [ABSTRACT FROM AUTHOR]

We present a new virtual laboratory developed with COMSOL multiphysics for the simulation of an acoustic levitator, as well as a three‐dimensional (3D) printed experimental setup. Our software application simulates the acoustic pressure field and its interaction with a set of particles. Students can interact with the system having the possibility to change the frequency and distance parameters between transducers in real time. We have also developed and shared for free use the 3D printing design files for the construction of the necessary components for the acoustic levitator, as well as the instructions for its experimental implementation. The experimental results are contrasted, along with those from the virtual laboratory, providing students with useful tools to understand and interpret the acoustic phenomenon in question. [ABSTRACT FROM AUTHOR]

With technological developments, the resolution of the display systems is increasing, causing image data to increase. Several technologies are aiding in optimizing these data during transmission and storage while maintaining quality. Still, the internal data transmission for accessing the memory sub‐system during reading and writing cycles consumes significant power while requiring large memory for storage, which is inefficient, especially for portable displays. Hence, this work investigates the feasibility of reducing data through approximation for images in different formats and resolutions for human and computer vision based applications. Different image quality assessment metrics are utilized for performance evaluations with optimum image quality assessment selection according to application requirements. In addition, the feasibility analysis is conducted for three different applications as examples of computer vision. The experimental analysis highlights theoretical and industrial importance by showing that image data can be reduced from 25.0% to 62.5%, while satisfying requirements for HVS‐based and computer vision‐based applications. [ABSTRACT FROM AUTHOR]

Rigid solid body dynamics is a key element of the undergraduate mechanical engineering curriculum. In a context of reverse engineering and/or sustainable development, being able to analyze the mechanical and material properties of a system without damaging it is a required skill. In this work, two systems based on wheels rolling over horizontal paths without sliding are studied: an unbalanced hollow cylinder and a wheel with displaced mass assembly. Four generations of last year's bachelor's students in mechanical engineering, representing a hundred people a year, followed a total of 12 h of practical sessions working on such systems. Without focusing on the programming part, this paper aims at showing how computer tools can help and improve a rigid solid body dynamics course. The objectives were to develop, apply, and analyze this teaching sequence, allowing students to (i) perform and characterize experimental measurements, (ii) establish systems motion equations, and (iii) think about dynamics results through cross‐talks between different techniques such as geometrical and analytical methods as well as computer‐assisted design tools. Different analysis methods of these systems could be discussed in the context of the classes, successfully bringing pertinent reflections to the students. The possibility of transferring such discussions to other contexts proved to be wide, thanks to computer science, dynamics software, other analysis methods and applications. [ABSTRACT FROM AUTHOR]

The rapid expansion of smart devices leads to the increasing demand for vulnerability detection in the cyber security field. Writing secure source codes is crucial to protect applications and software. Recent vulnerability detection methods are mainly using machine learning and deep learning. However, there are still some challenges, how to learn accurate source code semantic embedding at the function level, how to effectively perform vulnerability detection using the learned semantic embedding of source code and how to solve the overfitting problem of learning‐based models. In this paper, we consider codes as various graphs with node features and propose a tensor‐based gated graph neural network called TensorGNN to produce code embedding for function‐level vulnerability detection. First, we propose a high‐dimensional tensor for combining different code graph representations. Second, inspired by the work of tensor technology, we propose the TensorGNN model to produce accurate code representations using the graph tensor. We evaluate our model on 7 C and C++ large open‐source code corpus (e.g. SARD&NVD, Debian, SATE IV, FFmpeg, libpng&LibTiff, Wireshark and Github datasets), which contains 13 types of vulnerabilities. Our TensorGNN model improves on existing state‐of‐the‐art works by 10%–30% on average in terms of vulnerability detection accuracy and F1, while our TensorGNN model needs less training time and model parameters. Specifically, compared with other existing works, our model reduces 25–47 times of the number of parameters and decreases 3–10 times of training time. Results of evaluations show that TensorGNN has better performance while using fewer training parameters and less training time. [ABSTRACT FROM AUTHOR]

The one‐stage object detector has been widely applied in many computer vision applications due to its high detection efficiency and simple framework. However, one‐stage detectors heavily rely on Non‐maximum Suppression to remove the duplicated predictions for the same objects, and the detectors produce detection confidence to measure the quality of those predictions. The localisation quality is an important factor to evaluate the predicted bounding boxes, but its role has not been fully utilised in previous works. To alleviate the problem, the Quality Prediction Block (QPB), a lightweight sub‐network, is designed by the authors, which strengthens the effect of localisation quality evaluation on detection confidence by leveraging the features of predicted bounding boxes. The QPB is simple in structure and applies to different forms of detection confidence. Extensive experiments are conducted on the public benchmarks, MS COCO, PASCAL VOC and Berkeley DeepDrive. The results demonstrate the effectiveness of our method in the detectors with various forms of detection confidence. The proposed approach also achieves better performance in the stronger one‐stage detectors. [ABSTRACT FROM AUTHOR]

A systematic review is a type of literature review that aims to collect and analyse all available evidence from the literature on a particular topic. The process of screening and identifying eligible articles from the vast amounts of literature is a time‐consuming task. Specialised software has been developed to aid in the screening process and save significant time and labour. However, the most suitable software tools that are available often come with a cost or only offer either a limited or a trial version for free. In this paper, we report the release of a new software application, Catchii, which contains all the important features of a systematic review screening application while being completely free. It supports a user at different stages of screening, from detecting duplicates to creating the final flowchart for a publication. Catchii is designed to provide a good user experience and streamline the screening process through its clean and user‐friendly interface on both computers and mobile devices. All in all, Catchii is a valuable addition to the current selection of systematic review screening applications. It enables researchers without financial resources to access features found in the best paid tools, while also diminishing costs for those who have previously relied on paid applications. Catchii is available at https://catchii.org. [ABSTRACT FROM AUTHOR]

Summary: We conducted a prospective observational service evaluation across the United Kingdom on the use of total intravenous anaesthesia (TIVA) for obstetric surgery between November 2022 and June 2023. The primary aim was to describe the incidence of TIVA for obstetric surgery within participating units, with secondary aims to describe maternal and neonatal postoperative recovery indicators. Of 184 maternity units in the United Kingdom, 30 (16%) contributed data to the service evaluation. There were 104 patients who underwent caesarean delivery under TIVA and 19 patients had TIVA for other reasons. Infusions of propofol and remifentanil were used in 100% and 84% of cases, respectively. Fifty‐nine out of 103 live neonates (57%) required some form of respiratory support. Of the neonates with recorded data, 73% and 17% had Apgar scores < 7 at 1 and 5 min respectively. No neonates were recorded to have Apgar scores < 7 at 10 min. Further prospective research is required to investigate the impact of obstetric TIVA on maternal and neonatal outcomes and inform best practice recommendations. [ABSTRACT FROM AUTHOR]

GLAM organizations have been digitizing their collections and making them available for the public for several decades. Recent methods for publishing digital collections such as "GLAM Labs" and "Collections as Data" provide guidelines for the application of computational methods to reuse the contents of cultural heritage institutions in innovative and creative ways. Jupyter Notebooks have become a powerful tool to foster use of these collections by digital humanities researchers. Based on previous approaches for quality assessment, which have been adapted for cultural heritage collections, this paper proposes a methodology for assessing the quality of projects based on Jupyter Notebooks published by relevant GLAM institutions. A list of projects based on Jupyter Notebooks using cultural heritage data has been evaluated. Common features and best practices have been identified. A detailed analysis, that can be useful for organizations interested in creating their own Jupyter Notebooks projects, has been provided. Open issues requiring further work and additional avenues for exploration are outlined. [ABSTRACT FROM AUTHOR]

Rain removal is very important for many applications in computer vision, and it is a challenging problem due to its ill‐posed nature, especially for single‐image deraining. In order to remove rain streaks more thoroughly, as well as to retain more details, a progressive dilation dense residual fusion network is proposed. The entire network is designed in a cascade manner with multiple fusion blocks. The fusion block consists of a dilation dense residual block (DDRB) and a dense residual feature fusion block (DRFFB), where DDRB is created for feature extraction and DRFFB is mainly designed for feature fusion operation. Meanwhile, detail compensation memory mechanism (DCMM) is leveraged between each of two cascade modules to retain more background details. Compared with previous state‐of‐the‐art methods, extensive experiments show that the proposed method can achieve better results, in terms of rain streaks removal and background details preservation. Furthermore, the authors' network also shows its superiority for image noise removal. [ABSTRACT FROM AUTHOR]

Objective: To assess prevalence of elevated blood pressure readings, rates of established hypertension diagnosis, and blood pressure control medication prescription rates in a cohort of older people experiencing unsheltered homelessness presenting to a Street Medicine clinic in Miami‐Dade County, Florida. In addition, we will compare outcomes found in the study cohort to that of the general population. Methods: Demographic information, clinical history, blood pressure control medication prescription, and blood pressure measurements were taken by a Street Medicine team of medical providers. The team routinely provides medical evaluations and care for people experiencing unsheltered homelessness who reside in rough sleeper tent encampments located on the street. Clinical information and vitals were recorded in REDCap. De‐identified data from patients 65 years and above were downloaded and compared to a general population data set—the Centers for Disease Control National Health and Nutrition Examination Survey (CDC NHANES) 2017–2020 Pre‐pandemic cohort. Data analysis was performed using R Studio version 4.3.2. Results: Blood pressure was reported in 120 distinct interactions with older people experiencing homelessness. Compared to the age‐matched NHANES data, older people experiencing unsheltered homelessness were at significantly increased relative risk for elevated blood pressure within the range of Stage 1 Hypertension (RR: 3.914, 95% CI: 2.560–5.892, P < 0.001), and within range of Stage 2 Hypertension (RR: 5.550, 95% CI: 4.272–7.210, P < 0.001). According to NHANES, 49.6% of adults over 60 with diagnosed hypertension receive treatment. Of study participants, 69% of those with elevated blood pressure had previously received a diagnosis of hypertension and 15.9% on medication to control blood pressure. Conclusion: Our cohort of older people experiencing unsheltered homelessness had higher rates of elevated blood pressure and reduced rates of hypertension diagnosis and treatment as compared to the general population. Older people experiencing unsheltered homelessness are a growing population, and future research should seek to evaluate and understand older adult care vulnerabilities, including chronic disease management, to improve health outcomes for those who are aging, hypertensive, and unhoused. [ABSTRACT FROM AUTHOR]

In thinking back on Richard Lerner's impact on our lab's trajectory at Scripps Research, we see his fingerprints on all the efforts we have undertaken over the last 40 years. Immunology and virology have been a continuing driving focus in our software development and application within the Molecular Graphics Lab (now the Center for Computational Structural Biology – CCSB), spurred on by the marriage of chemistry with biology that Richard enabled at Scripps. Many of our earliest and continuing computational docking targets have been focused on HIV with collaborations with Chi‐Huey Wong and Barry Sharpless. Along with subsequent computational work with Jeff Kelly, Reza Ghadiri, Udi Keinan and Ben Cravatt we have been able to sustain continuous efforts in developing and applying docking and other computational technologies to structural chemistry problems. In this remembrance, we give our reflections of Richard Lerner's character, vision, and his inspiration in our scientific lives and in the environment that he created at Scripps Research. [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]

Inputs and Outputs: The Strike‐a‐Match Function, written in JavaScript version ES6+, accepts the input of two datasets (one dataset defining eligibility criteria for research studies or clinical decision support, and one dataset defining characteristics for an individual patient). It returns an output signaling whether the patient characteristics are a match for the eligibility criteria. Purpose: Ultimately, such a system will play a "matchmaker" role in facilitating point‐of‐care recognition of patient‐specific clinical decision support. Specifications: The eligibility criteria are defined in HL7 FHIR (version R5) EvidenceVariable Resource JSON structure. The patient characteristics are provided in an FHIR Bundle Resource JSON including one Patient Resource and one or more Observation and Condition Resources which could be obtained from the patient's electronic health record. Application: The Strike‐a‐Match Function determines whether or not the patient is a match to the eligibility criteria and an Eligibility Criteria Matching Software Demonstration interface provides a human‐readable display of matching results by criteria for the clinician or patient to consider. This is the first software application, serving as proof of principle, that compares patient characteristics and eligibility criteria with all data exchanged using HL7 FHIR JSON. An Eligibility Criteria Matching Software Library at https://fevir.net/110192 provides a method for sharing functions using the same information model. [ABSTRACT FROM AUTHOR]

Context: GitHub is the world's most prominent host of source code, with more than 327M repositories. However, most of these repositories are not labelled or inadequately, making it harder for users to find relevant projects. Various proposals for software application domain classification over the past years have been proposed. However, these several of those approaches suffer from multiple issues, called antipatterns of software classification, that reduce their usability. Objective: In this paper, we propose a new taxonomy in the GitHub ecosystem, called GitRanking, starting from a well‐structured data set, composed of curated repositories annotated with topics. The main objective is to create a baseline methodology for software classification that is expandable, hierarchical, grounded in a knowledge base, and free of antipatterns. Method: We collected 121K topics from GitHub and used GitRanking to create a taxonomy of 301 ranked application domains. GitRanking (1) uses active sampling to ensure a minimal number of annotations to create the ranking; and (2) links each topic to Wikidata, reducing ambiguities and improving the reusability of the taxonomy. Furthermore, we adopt the conceived taxonomy in a classification task by considering a state‐of‐the‐art classifier. Results: Our results show that GitRanking can effectively rank terms in a hierarchy according to how general or specific their meaning is. Furthermore, we show that GitRanking is a dynamically extensible method: it can currently accept further terms to be ranked, and with a minimum number of annotations (≈15$$ \approx 15 $$). Concerning the classification task, we show that the model achieves an F1‐score of 34%, with a precision of 54%. Conclusion: This paper is the first collective attempt at building a ground‐up taxonomy of software domains. Our vision is that our taxonomy, and its extensibility, can be used to better and more precisely label software projects. [ABSTRACT FROM AUTHOR]

The article evaluates a statewide initiative in rural emergency departments (EDs) aimed at addressing the increasing presentation of children with mental health concerns and subsequent ED boarding. The initiative involves providing youth activity kits and self-care binders to ED staff caring for children boarding with primary mental health issues, with the assessment focusing on utilization and acceptability through a survey of clinical quality leaders in participating EDs (92% response rate).

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 promise of transforming digital technologies into treatments is what drives the development of digital therapeutics (DTx), generally known as software applications embedded within accessible technologies—such as smartphones—to treat, manage, or prevent a pathological condition. Whereas DTx solutions that successfully demonstrate effectiveness and safety could drastically improve the life of patients in multiple therapeutic areas, there is a general consensus that generating therapeutic evidence for DTx presents challenges and open questions. We believe there are three main areas where the application of clinical pharmacology principles from the drug development field could benefit DTx development: the characterization of the mechanism of action, the optimization of the intervention, and, finally, its dosing. We reviewed DTx studies to explore how the field is approaching these topics and to better characterize the challenges associated with them. This leads us to emphasize the role that the application of clinical pharmacology principles could play in the development of DTx and to advocate for a development approach that merges such principles from development of traditional therapeutics with important considerations from the highly attractive and fast‐paced world of digital solutions. [ABSTRACT FROM AUTHOR]

Virtual patients (VPs) are widely used within quantitative systems pharmacology (QSP) modeling to explore the impact of variability and uncertainty on clinical responses. In one method of generating VPs, parameters are sampled randomly from a distribution, and possible VPs are accepted or rejected based on constraints on model output behavior. This approach works but can be inefficient (i.e., the vast majority of model runs typically do not result in valid VPs). Machine learning surrogate models offer an opportunity to improve the efficiency of VP creation significantly. In this approach, surrogate models are trained using the full QSP model and subsequently used to rapidly pre‐screen for parameter combinations that result in feasible VPs. The overwhelming majority of parameter combinations pre‐vetted using the surrogate models result in valid VPs when tested in the original QSP model. This tutorial presents this novel workflow and demonstrates how a surrogate model software application can be used to select and optimize the surrogate models in a case study. We then discuss the relative efficiency of the methods and scalability of the proposed method. [ABSTRACT FROM AUTHOR]

PBPK applications published in the literature support a greater adoption of non‐open source‐code (NOSC) software as opposed to open source‐code (OSC) alternatives. However, a significant number of PBPK modelers are still using OSC software, understanding the rationale for the use of this modality is important and may help those embarking on PBPK modeling. No previous analysis of PBPK modeling trends has included the rationale of the modeler. An in‐depth analysis of PBPK applications of OSC software is warranted to determine the true impact of OSC software on the rise of PBPK. Publications focusing on PBPK modeling applications, which used OSC software, were identified by systematically searching the scientific literature for original articles. A total of 171 articles were extracted from the narrowed subset. The rise in the use of OSC software for PBPK applications was greater than the general discipline of pharmacokinetics (9 vs. 4), but less than the overall growth of the PBPK area (9 vs. 43). Our report demonstrates conclusively that the surge in PBPK usage is primarily attributable to the availability and implementations of NOSC software. Modelers preferred not to share the reasons for their selection of certain modeling software and no 'explicit' rationale was given to support the use of OSC analysed by this study. As the preference for NOSC versus OSC software tools in the PBPK area continues to be divided, initiatives to add the rationale in using one form over another to every future PBPK modeling report will be a welcomed and informative addition. [ABSTRACT FROM AUTHOR]

Introduction: Pregnant women are vulnerable to severe acute respiratory syndrome coronavirus (SARS‐CoV‐2) infection. Neutralizing antibodies against the SARS‐CoV‐2 spike (S) protein protect from severe disease. This study analyzes the antibody titers to SARS‐CoV‐2 S protein in pregnant women and their newborns at delivery, and six months later. Methods: We conducted a prospective study on pregnant women with confirmed SARS‐CoV‐2 infection and newborns. Antibody (IgG, IgM, and IgA) titers were determined using immunoassays in serum and milk samples. An angiotensin‐converting enzyme 2 (ACE2) receptor‐binding inhibition assay to the S protein was performed on the same serum and milk samples. Results: At birth, antibodies to SARS‐CoV‐2 spike protein were detected in 81.9% of mothers' sera, 78.9% of cord blood samples, and 63.2% of milk samples. Symptomatic women had higher antibody titers (IgG, IgM, and IgA) than the asymptomatic ones (P < 0.05). At six months postpartum, IgG levels decreased drastically in children's serum (P < 0.001) but remained high in mothers' serum. Antibody titers correlated positively with its capacity to inhibit the ACE2–spike protein interaction at baseline in maternal sera (R2 = 0.203; P < 0.001), cord sera (R2 = 0.378; P < 0.001), and milk (R2 = 0.564; P < 0.001), and at six months in maternal sera (R2 = 0.600; P < 0.001). Conclusions: High antibody levels against SARS‐CoV‐2 spike protein were found in most pregnant women. Due to the efficient transfer of IgG to cord blood and high IgA titers in breast milk, neonates may be passively immunized to SARS‐CoV‐2 infection. Our findings could guide newborn management and maternal vaccination policies. [ABSTRACT FROM AUTHOR]

Researchers recommend that parents look for five benchmarks as indicators of quality educational apps (ie, scaffolding, curriculum, development team, feedback, learning theory), yet results show that parents undervalue some of these benchmarks. The current study examined if a short video‐based intervention would enhance parents' value‐judgements of apps featuring the five educational benchmarks. In original and modified app experiments (n = 100; n = 101), parents of children 4–11 years old were randomly assigned to watch either a 9‐minute video that detailed how the five benchmarks augment learning, or a 2‐minute control video. Parents evaluated 10 simulated apps containing either benchmarks or buzzwords. The original app experiment shows that a brief intervention can help parents identify quality educational apps via the benchmarks, but the modified app experiment suggests it only works if developers are using specific keywords in app descriptions. Helping parents select quality educational apps is more complicated than simply telling them what to look for. Practitioner notesWhat is already known about this topic Parents have a main role in selecting apps and deciding on how often children use them; however, they have difficulty evaluating an app's educational potential in a market mixed with high‐ and low‐quality products that lacks a standard for including educational apps on the App Store.There are five research‐based benchmarks that are indicators of quality educational apps. These include apps created by an interdisciplinary development team, having a guiding curriculum with a clear purpose, including scaffolding and feedback, and being based on a learning theory. However, parents are not valuing all of these educational benchmarks equally.Educational videos disseminated via YouTube have become an established medium to enhance people's knowledge.Mayer's cognitive theory of multimedia learning, which suggests that people learn better when there is both auditory and visual information given together, is a framework used to design educational videos.What this paper adds This study leveraged a useful, accessible medium (ie, educational YouTube videos) to make research on educational apps accessible enough such that it could influence parents' app selection.Parents of children aged 4–11 years‐old viewed either an educational intervention‐ or control‐video and assessed educational apps through measures that replicate how consumers evaluate apps on the App Store (ie, their willingness to download the app, how much they would pay, their rating, and ranking).Original and modified app experiments demonstrate that a brief, educational video designed using key features from Mayer's multimedia theory can improve parents' app selection.In the original app experiment, parents in the intervention group are valuing the guiding curriculum and development team benchmarks over others, which may be due to the structure of the intervention video (ie, worked‐examples immediately after pre‐training of benchmarks).In the modified app experiment, parents in the intervention group did not differ from the control group in their evaluations of the different benchmarks apart from rating the app with learning theory higher and ranking the guiding curriculum benchmark lower. The higher rating of learning theory may be a result of the language change in the simulated app to include more user‐friendly terms. The unexpected ranking result may be due to a limitation with the measure.Building on prior research on the educational benchmarks, these experiments show that parents are valuing them over buzzwords; however, even when shown an educational video, they are not valuing them all equally.Implications for practice and/or policy An educational video based on the five educational benchmarks could be used as a tool to easily disseminate knowledge to enhance parents' educational app selection.The experiments shed light on the complexity of knowledge dissemination to the public. While there is evidence for the use of research‐based educational videos to disseminate knowledge to parents when selecting educational apps, the App Store descriptions should include accessible language that makes the research‐based benchmarks easy to select.This study also provides suggestions for improving the development of educational videos. [ABSTRACT FROM AUTHOR]

The Laplace Beltrami operator is one of the essential tools in geometric processing. It allows us to solve numerous partial differential equations on discrete surface meshes, which is a fundamental building block in many computer graphics applications. Discrete Laplacians are typically limited to standard elements like triangles or quadrilaterals, which severely constrains the tessellation of the mesh. But in recent years, several approaches were able to generalize the Laplace Beltrami and its closely related gradient and divergence operators to more general meshes. This allows artists and engineers to work with a wider range of elements which are sometimes required and beneficial in their field. This paper discusses the different constructions of these three ubiquitous differential operators on arbitrary polygons and analyzes their individual advantages and properties in common computer graphics applications. [ABSTRACT FROM AUTHOR]

Video data received for analysis often come in a variety of file formats and compression schemes. These data are often transcoded to a consistent file format for forensic examination and/or ingesting into a video analytic system. The file format often requested is an MP4 file format. The MP4 file format is a very common and a universally accepted file format. The practical application of this transcoding process, across the analytical community, has generated differences in video quality. This study sought to explore possible origins of the differences and assist the practitioner by defining minimum recommendations to ensure that quality of the video data is maintained through the transcoding process. This study sought to generate real world data by asking participants to transcode provided video files to an MP4 file format using programs they would typically utilize to perform this task. The transcoded results were evaluated based on measurable metrics of quality. As the results were analyzed, determining why these differences might have occurred became less about a particular software application and more about the settings employed by the practitioner or of the capabilities of the program. This study supports the need for any video examiner who is transcoding video data to be cognizant of the settings utilized by the programs employed for transcoding video data, as loss of video quality can affect analytics as well as further analysis. [ABSTRACT FROM AUTHOR]

Different quality grades of tea tend to have a high degree of similarity in appearance. Traditional image‐based identification methods have limited effects, while complex deep learning architectures require much data and long‐term training. In this paper, two tea quality identification methods based on deep convolutional neural networks and transfer learning are proposed. Different types and quality of tea images are collected by a self‐designed computer vision system to form a data set, which is small‐scale and of high inter‐ and intraclass similarity. The first method uses three simplified convolutional neural network (CNN) models with different image input sizes to identify the quality of tea. The second method performs transfer learning to identify the tea quality by fine‐tuning the mature AlexNet and ResNet50 architecture. Classification performance and model complexity are measured and compared. The related application software is also developed. The results show that the performance of the CNN models and the transfer learning models are close, and both can achieve high identification accuracy. However, the complexity of the CNN models is two to three orders of magnitude lower than that of the transfer learning models. The study shows that deep CNNs and transfer learning have great potential to be rapid and effective methods for automated tea quality identification tasks with high inter‐ and intrasimilarity. [ABSTRACT FROM AUTHOR]

One of the main factors leading to fatalities in construction sites is the inefficiency of safety training programs. This article presents an immersive and interactive virtual reality (VR) model for safety training, which is an advanced and more comprehensive version of previously developed VR models in the literature. The novelty of this research is present in the proposed general safety training model that is fully immersive and interactive, that is built based on the concepts of experiential learning; where users learn from their mistakes rather than being passive learners in a virtual environment. The model, which was developed using the Unity® platform and C#, contains 12 scenario‐based hazards with programmed interactions and responses to the actions of the trainees. The developed model was tested for two aspects: (1) the ability to achieve learning outcomes and supersede traditional training, and (2) user experience and usability. Using an experimental setting and statistical tests, the developed model has shown statistical significance when it comes to its efficiency in enhancing hazard identification and mitigation skills as opposed to traditional training. The model also performed well in terms of usability and user experience, and important lessons were extracted for future VR development in construction education applications. This research strengthens the utility of VR as an effective tool for experiential learning; which enables future research in exploring how computer applications can improve experiential learning even further. [ABSTRACT FROM AUTHOR]

Composite column design in accordance with EN 1994‐1‐1 can be computed by the general method or by simplified methods. For the general method, EN 1994‐1‐1 refers to a comprehensive FE‐Analysis. However, the recent Eurocode 4 does not provide sufficient guidance for the application of the general method and there is not a harmony in the literature on how to do it. Additional information may be found as non‐contradictory complementary information (NCI) in National Annexes (NA). This paper points out the procedure for the general method and refers to the changes and additional information provided by the draft of prEN 1994‐1‐1:2021. Furthermore, the modelling and computation by FE‐Analysis for several software applications are presented by implementing specified initial bow imperfections and predefined residual stresses for the steel section. The results obtained with the general method's approach are compared with that calculated by simplified method by the European buckling curves. In addition, the impact of different stress‐strain curves for concrete and strain limits introduced by Codes are investigated. [ABSTRACT FROM AUTHOR]

The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically‐based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P‐PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P‐PBPK modeling. We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients. [ABSTRACT FROM AUTHOR]

Abtract: In this paper, a new cybernetic control technology that can be used in complex software systems will be introduced. In this approach, the software systems are governed by cybernetic control objects and the class libraries defining the types of these cybernetic control objects are produced by special meta‐programming platforms. In this approach, the requirements of the software to be developed are received from the programmer by meta‐programming systems before coding. Actually, the cybernetic control objects have standard design and properties and the programmers only determine the quantities and the locations of these properties before library production process. Then, the meta‐programming platforms build project‐specific class libraries based on previously determined code templates. By this way, the cybernetic control objects are constructed with optimal memory and they can receive feedback about ongoing operations on the process. With the help of the feedback coming from the process, the control objects steer the process in the line of the programmer directives. By this way, the control of the programmer on the software increases significantly. In addition, in this paper, a typical application of this approach to the multithread programming will be introduced. [ABSTRACT FROM AUTHOR]

Purpose: To develop an automated image recognition software for the objective quantification of choroidal vascularity index (CVI) and choroidal thickness (CT) at different choroidal locations on images obtained from enhanced depth imaging optical coherence tomography (EDI‐OCT), and to validate its reliability and investigate the difference and correlation between measurements made by manual and software. Methods: A total of 390 EDI‐OCT scans, captured from 130 eligible emmetropic or myopic subjects, were categorized into four grades in terms of their accessibility to identify the choroidal‐scleral interface (CSI) and were further assessed for CT and CVI at five locations (subfoveal, nasal, temporal, superior and inferior) by the newly developed Choroidal Vascularity Index Software (CVIS) and three ophthalmologists. Choroidal parameters acquired from CVIS were evaluated for its reliability and correlation with ocular factors, in comparison to manual measurements. Distribution of difference and correlation coefficient between CVIS and manual measurements were also analysed. Results: Choroidal Vascularity Index Software (CVIS) demonstrated excellent intra‐session reliability for CT (ICC: 0.992) and CVI (ICC: 0.978) measurements, compared to the relatively lower intra‐ and inter‐observer reliability of manual measurements. Choroidal Vascularity Index Software (CVIS) and manual assessments had the highest correlation at nasal choroid (CT: r = 0.829, p < 0.001; CVI: r = 0.665, p < 0.001). Choroidal parameters identified with CVIS showed stronger correlations with axial length than manual measurements. Conclusion: This automated software, CVIS, exhibited excellent reliability compared to manual measurements, which are subject to image quality and clinical experience. With its validated clinical relevance, CVIS holds promise to serve as a flexible and robust tool in future vitreoretinal and chorioretinal studies. [ABSTRACT FROM AUTHOR]

Educational apps can be considered a dominant medium for providing educational content to children. Parents are major stakeholders and mediators in the selection of apps (Dias & Brito, 2021). It is critical to know how they choose apps for their children and understand what indicates a quality educational app, as well‐designed apps can support and enhance children's learning process. An online study with parents was conducted to identify parents' most dominant needs while selecting apps for their children. Parents' app selection behaviour was investigated leveraging Uses and Gratifications theory. Parents viewed 10 mock math apps that replicated the App Store presentation format. Five apps included educational benchmarks (eg, feedback) and five contained educational buzzwords (eg, interactive). Immediately following each app, parents provided value judgements of the app by stating whether they would download the app or not, rating it on a 5‐point‐scale, stating how much they would be willing to pay, and explaining why they chose to download the app or not. Results from paired‐samples t‐tests, and repeated‐measures ANOVAs indicated that parents value educational benchmarks over buzzwords suggesting that parents are primarily seeking apps that meet their children's educational needs. Parents' app needs seem to align with some of the research on what makes a good educational app. Practitioner notesWhat is already known about this topicTouch screen devices can enhance learning outcomes for children, if well designed educational applications are used (Camilleri & Camilleri, 2019; Cohen et al., 2011).Five educational benchmarks have been identified as indicators of app quality that parents can use to distinguish well designed apps (Dubé et al., 2020); having a development team that involves educators, possessing a guiding curriculum (Vaala et al., 2015), being based on a learning theory (Kebritchi & Hirumi, 2008), containing scaffolded learning, and providing feedback (Callaghan & Reich, 2018; Cayton‐Hodges et al., 2015).Uses and Gratifications theory suggests that people use the media to satisfy their psychological needs and to achieve their personal goals (Katz et al., 1973).What this paper addsThe study used Uses and Gratifications theory to identify parents' most dominant needs while selecting apps for their children. With the assumption that parents select apps based on their anticipated gratifications or parental need fulfilment (Broekman et al., 2016, 2018).Different features of the apps are presented in the forms of images and text descriptions in the App Store. The study investigated which features parents value when selecting apps from the App Store by including educational benchmarks and buzzwords in the images and text descriptions of the apps.Parents valued educational benchmarks over buzzwords. Thus, parents' app needs seem to align with the research‐based signifiers of app quality.Parents valued apps that feature development team, scaffolding, and guiding curriculums more than those with central learning theories and feedback.Development team had the highest download frequency and rating while learning theory had the lowest download frequency and rating.Parents were willing to pay more for the development team app and the least for ones containing feedback.The learning theory app was ranked the highest while the development team app received the lowest ranking from parents.Implications for practice and/or policyIncluding research‐based educational benchmarks in the apps and their app store descriptions promotes a research‐based framework for developing and identifying quality apps.Research‐based educational benchmarks could be used to determine a set of evidence‐based guidelines to assist app developers in the process of developing and presenting apps. [ABSTRACT FROM AUTHOR]

Lattice structures are known for their superior performance in weight reduction, stiffness, and increased manufacturability, but when materials need to be adaptive, multifunctional, and with tunable properties, functionally graded lattice structures (FGLS) play a crucial role in innovative solutions. Recent digital manufacturing technologies offer ideal conditions for creating lattice structures with high geometrical complexity and functional gradients. However, the design and development of these inherently complex structures often require the use of specialized methods and software tools. As researchers venture from diverse areas into the research of FGLS in search of novel applications, it is important to choose adequate design tools. Herein, an overview of methods and software for the design of FGLS is presented, identifying geometrical parameters of common lattice topologies and ways to manipulate them to create functional gradients. Fifty software applications or methods are listed, dedicated to the design of single material lattices produced by additive manufacturing processes. Typical applications of the reviewed software are identified, and FGLS design methods are compared. Generative Design seems more suited as an explorative process, Topology Optimization is an established efficiency‐focused design process, and Machine Learning is considered a promising data‐driven approach for the design of innovative FGLS. [ABSTRACT FROM AUTHOR]

The number of malicious software applications, or malware programs, increases every year. Their development becomes more sophisticated as new techniques are used to bypass program scanning software applications, such as antiviruses. Thereby, deep learning‐based methods emerge as a new promising way to identify these threats. Our main purpose and contribution in this work is proposing and implementing a successful approach to tackle both binary and multiclass malware classification problems. We used unsupervised word embedding algorithms for representing software applications to be analyzed and long‐short term memory for classifying the software applications. For evaluating our pipeline, we introduce a new dataset for binary and multiclass malware classification because we could not find large datasets containing sufficient samples of cleanware and the various malware types for multiclass classification that could be used to evaluate classification models. Our experimental results reached an accuracy of 88.94% for binary classification and 75.13% for multiclass classification. These results suggest that the proposed dataset is challenging, and using it can help in the training of better malware classifiers, improving security. [ABSTRACT FROM AUTHOR]

We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim. The code is open‐source, object‐oriented, and built upon the standard scientific Python stack, allowing users to take advantage of a large collection of existing and emerging techniques. We describe the code's philosophy, structure, and base functionalities and apply it to three paleoclimate problems: (a) orbital‐scale climate variability in a deep‐sea core, illustrating spectral, wavelet, and coherency analysis in the presence of age uncertainties; (b) correlating a high‐resolution speleothem to a climate field, illustrating correlation analysis in the presence of various statistical pitfalls (including age uncertainties); (c) model‐data confrontations in the frequency domain, illustrating the characterization of scaling behavior. We show how the package may be used for transparent and reproducible analysis of paleoclimate and paleoceanographic datasets, supporting Findable, Accessible, Interoperable, and Reusable software and an open science ethos. The package is supported by an extensive documentation and a growing library of tutorials shared publicly as videos and cloud‐executable Jupyter notebooks, to encourage adoption by new users. Plain Language Summary: This article describes a software application called Pyleoclim meant to help scientists analyze datasets of ordered observations, particularly applicable to the study of past climates, environments, and ecology. Pyleoclim is meant to be used by domain scientists as well as students interested in learning more about Earth's climate through examples provided in the documentation and online tutorials. Pyleoclim is intended to help scientists save time with their analyses, documenting the steps for better transparency, and as such, allows other scientists to reproduce results from previous studies. Key Points: Pyleoclim makes timeseries analysis tools accessible to practicing scientists, via a user‐friendly Python packageThree Jupyter Notebooks illustrate how Pyleoclim facilitates common and advanced tasksPyleoclim can enhance reproducibility and rigor of paleogeoscientific workflows involving timeseries [ABSTRACT FROM AUTHOR]

Layered (2D) artificial (or synthetic) antiferromagnets are fabricated by atom deposition techniques and possess very thin, nanometer‐scale, magnetically ordered layers separated by a very thin nonmagnetic layer that antiferromagnetically couples the magnetic layers. Artificial antiferromagnets were crucial in the discovery of the giant magnetic effect (GMR), which had an incredible impact on the evolution of computer memory and its applications, and nucleated the dawn of spintronics (magnetoelectrics). The fundamental structural motif has been more recently achieved by using synthetic chemical methods that led to insulating artificial antiferromagnets. Examples of magnetically ordered layers that are antiferromagnetic coupled to form artificial antiferromagnets have been extended to isolated ions (0D) as well as extended chain (1D) and extended network 3D structures, and new phenomena and applications are anticipated as insulating antiferromagnets are more effective at propagating spin currents with respect to dielectric materials. [ABSTRACT FROM AUTHOR]

In the present paper, we assess whether website rating systems are useful for selecting educational apps for preschool age children. We selected the 10 highest scoring and 10 lowest scoring apps for 2–4‐year‐olds from two widely used websites (Good App Guide; Common Sense Media). Apps rated highly by the two websites had a higher educational potential as assessed by a validated questionnaire for evaluating the educational potential of apps and were more likely to include a learning goal and feedback compared to low scoring apps. However, high scoring apps scored on average just 9/20 for indicators of educational potential, and both high and low scoring apps had poor language quality as determined by psycholinguistic and construction type analyses. We argue that website rating systems should also include quality of feedback, adjustable content, social interactions, storyline and a more fine‐grained analysis of language in their assessments. Practitioner notesWhat is already known about this topic Appropriately designed apps for preschool age children have the potential to teach early school readiness skills.Selecting high quality educational apps for preschool age children is challenging.The children's app marketplace is currently unregulated.What this paper adds We assess whether two leading app rating websites are useful for selecting educational apps for preschool age children.Children's apps rated highly by two app website rating systems had a higher educational potential than low rated apps as measured by a research informed app evaluation tool.In‐depth analysis of the language in apps shows that highly rated children's apps on app rating websites may not enrich a child's early language environment.Implications for practice and/or policy Children's app rating website assessments should include potential for feedback, language, adjustable content, storyline and social interactions.Policy should be implemented for app ratings in the app stores or on website app rating systems. [ABSTRACT FROM AUTHOR]