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The increasing popularity of mHealth presents an opportunity for collecting rich datasets using mobile phone applications (apps). Our health-monitoring mobile application uses motion detection to track an individual's physical activity and location. The data collected are used to improve health outcomes, such as reducing the risk of chronic diseases and promoting healthier lifestyles through analyzing physical activity patterns. Using smartphone motion detection sensors and GPS receivers, we implemented an energy-efficient tracking algorithm that captures user locations whenever they are in motion. To ensure security and efficiency in data collection and storage, encryption algorithms are used with serverless and scalable cloud storage design. The database schema is designed around Mobile Advertising ID (MAID) as a unique identifier for each device, allowing for accurate tracking and high data quality. Our application uses Google's Activity Recognition Application Programming Interface (API) on Android OS or geofencing and motion sensors on iOS to track most smartphones available. In addition, our app leverages blockchain and traditional payments to streamline the compensations and has an intuitive user interface to encourage participation in research. The mobile tracking app was tested for 20 days on an iPhone 14 Pro Max, finding that it accurately captured location during movement and promptly resumed tracking after inactivity periods, while consuming a low percentage of battery life while running in the background. [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]

There are not currently any univariate outlier detection algorithms that transform and model arbitrarily shaped distributions to remove univariate outliers. Some algorithms model skew, even fewer model kurtosis, and none of them model bimodality and monotonicity. To overcome these challenges, we have implemented an algorithm for Skew and Tail-heaviness Adjusted Removal of Outliers (STAR_outliers) that robustly removes univariate outliers from distributions with many different shape profiles, including extreme skew, extreme kurtosis, bimodality, and monotonicity. We show that STAR_outliers removes simulated outliers with greater recall and precision than several general algorithms, and it also models the outlier bounds of real data distributions with greater accuracy. Background Reliably removing univariate outliers from arbitrarily shaped distributions is a difficult task. Incorrectly assuming unimodality or overestimating tail heaviness fails to remove outliers, while underestimating tail heaviness incorrectly removes regular data from the tails. Skew often produces one heavy tail and one light tail, and we show that several sophisticated outlier removal algorithms often fail to remove outliers from the light tail. Multivariate outlier detection algorithms have recently become popular, but having tested PyOD's multivariate outlier removal algorithms, we found them to be inadequate for univariate outlier removal. They usually do not allow for univariate input, and they do not fit their distributions of outliership scores with a model on which an outlier threshold can be accurately established. Thus, there is a need for a flexible outlier removal algorithm that can model arbitrarily shaped univariate distributions. Results In order to effectively model arbitrarily shaped univariate distributions, we have combined several well-established algorithms into a new algorithm called STAR_outliers. STAR_outliers removes more simulated true outliers and fewer non-outliers than several other univariate algorithms. These include several normality-assuming outlier removal methods, PyOD's isolation forest (IF) outlier removal algorithm (ACM Transactions on Knowledge Discovery from Data (TKDD) 6:3, 2012) with default settings, and an IQR based algorithm by Verardi and Vermandele that removes outliers while accounting for skew and kurtosis (Verardi and Vermandele, Journal de la Société Française de Statistique 157:90–114, 2016). Since the IF algorithm's default model poorly fit the outliership scores, we also compared the isolation forest algorithm with a model that entails removing as many datapoints as STAR_outliers does in order of decreasing outliership scores. We also compared these algorithms on the publicly available 2018 National Health and Nutrition Examination Survey (NHANES) data by setting the outlier threshold to keep values falling within the main 99.3 percent of the fitted model's domain. We show that our STAR_outliers algorithm removes significantly closer to 0.7 percent of values from these features than other outlier removal methods on average. Conclusions STAR_outliers is an easily implemented python package for removing outliers that outperforms multiple commonly used methods of univariate outlier removal. [ABSTRACT FROM AUTHOR]

Verif is an open-source tool for verifying weather predictions against a ground truth. It is suitable for a range of applications and designed for iterative product development involving fine-tuning of algorithms, comparing methods, and addressing scientific issues with the product. The tool generates verification plots based on user-supplied input files containing predictions and observations for multiple point-locations, forecast lead times, and forecast initialization times. It supports over 90 verification metrics and diagrams and can evaluate deterministic and probabilistic predictions. An extensive set of command-line flags control how the input data are aggregated, filtered, stratified, and visualized. The broad range of metrics and data manipulation options allows the user to gain insight from both summary scores and detailed time series of individual weather events. Verif is suitable for many applications, including assessing numerical weather prediction models, climate models, reanalyses, machine learning models, and even the fidelity of emerging observational sources. The tool has matured through long-term development at the Norwegian Meteorological Institute and the University of British Columbia. Verif comes with an extensive wiki page and example input files covering a wide range of prediction applications, allowing students and researchers interested in verification to get hands-on experience with real-life datasets. This article describes the functionality of Verif version 1.3 and shows how the tool can be used for effective product development. [ABSTRACT FROM AUTHOR]

Exploitation of the ever-increasing volume of observational data has become a major challenge for real-world evidence (RWE). Causal inference can be viewed as emulations of clinical trials (ECTs) from real-world data (RWD). This requires in-depth knowledge of data management and modern statistical models, which evolve considerably. We have developed Plug-Stat® to facilitate these analyses. Plug-Stat® is a user-friendly graphical interface of R software implemented with JavaScript and VB.net. The implementation of Plug-Stat® for a specific database consists of two main tasks. The first concerns the automatic importation of data to link the software with the data and to avoid the repetition of data management activities for each study. The second is to define the outcomes and the associated possible confounders. To perform an ECT, we proposed the use of inverse probability weighting, flexible parametric estimation of the propensity score model with B-splines, and robust estimation of the variance. The statistical modeling steps are automatized to direct the user toward the correct methodology without data management. We illustrated the usefulness of Plug-Stat® with several recently published ECTs. In this paper, we presented the outcome comparison of preemptive deceased-donor kidney transplantations versus transplantations after dialysis. The interactive interfaces assist the user in conducting causal research based on ECT, and tutorials are available, offering self-training opportunities. Plug-Stat® reduces the time and, consequently, the cost necessary for different studies from the same cohort. [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]

Purpose This study aimed to compare the volume and normative percentiles of brain volumetry in the Korean population using quantitative brain volumetric MRI analysis tools NeuroQuantⓇ (NQ) and DeepBrainⓇ (DB), and to evaluate whether the differences in the normative percentiles of brain volumetry between the two tools is related to cranial shape. Materials and Methods In this retrospective study, we analyzed the brain volume reports obtained from NQ and DB in 163 participants without gross structural brain abnormalities. We measured threedimensional diameters to evaluate the cranial shape on T1-weighted images. Statistical analyses were performed using intra-class correlation coefficients and linear correlations. Results The mean normative percentiles of the thalamus (90.8 vs. 63.3 percentile), putamen (90.0 vs. 60.0 percentile), and parietal lobe (80.1 vs. 74.1 percentile) were larger in the NQ group than in the DB group, whereas that of the occipital lobe (18.4 vs. 68.5 percentile) was smaller in the NQ group than in the DB group. We found a significant correlation between the mean normative percentiles obtained from the NQ and cranial shape: the mean normative percentile of the occipital lobe increased with the anteroposterior diameter and decreased with the craniocaudal diameter. Conclusion The mean normative percentiles obtained from NQ and DB differed significantly for many brain regions, and these differences may be related to cranial shape. [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]

Today, land and ocean observations are crucial for monitoring climate change. The method of GNSS reflectometry is an opportunistic way to provide low-cost observations of many geophysical parameters. However, although this method has been the subject of numerous research studies, work is still in progress to improve its possibilities and fields of application. This paper focuses on GNSS reflectometry using carrier phase measurements for water altimetry measurements. The difficulties in implementing such a method lie in the need to collect a coherent signal and to solve the integer ambiguity value. In this context, the implementation of innovative signal processing is described, including the correlation of the reflected signals in dedicated software and the prolongation of the coherent integration time to enhance signal coherency. These processes were applied to data collected over Carcans-Hourtin Lake in France to compute the height of the reflection surface which was then compared to in situ GNSS buoy height measurements. The results show that at 300 ft (91.44 m), the differences between the lake heights measured with the buoy and with the reflectometry data can reach less than 1 cm for the L1, E1 and E5 GNSS signals. In addition, the slope of the geoid estimated with the reflectometry data is very consistent with that of the RAF20 geoid model, with a difference of up to less than 2 mm/km. [ABSTRACT FROM AUTHOR]

[Display omitted] • Complete method for SPVWPS deployment; site selection & sizing. • Comprehensive user-friendly tool for SPVWPS deployment. • Case study for the SPVWPS deployment in a remote and complex terrain. • Tool's FAHP-based ranking functionality for any MCDM problem. • Optimized energy and water resource utilization with the software tool. Water resources are essential for human survival, environmental stability, sustainable development, and economic growth. However, the lack of access to clean water poses a significant challenge to people's well-being. Solar photovoltaic-powered water pumping systems offer a sustainable solution to this problem. Despite their implementation in various locations, there is currently no established methodology for optimal site selection and sizing. To address this gap, this study thoroughly investigates and analyzes the design and deployment steps of a solar PV water pumping system, including site selection and sizing of the components. A graphical user interface is developed based on fundamental equations to assist users in appropriately sizing the system for the most suitable site, aiming to minimize costs. The tool is rigorously tested and validated through a case study focusing on economically disadvantaged communities in remote areas with complex terrains. The results align with ground data, providing valuable insights into system design and deployment. This study serves as a comprehensive guide for designing solar PV water pumping systems, applicable worldwide with relevant data inputs. It contributes to the planning and implementation of sustainable solutions, addressing water access challenges through a scientific approach. [ABSTRACT FROM AUTHOR]

Warcraft Evolves by identifying and adapting the technical and functional affordances of technologies to exploit vulnerabilities in adversaries’ defenses and defend against their attacks. Nowhere is this arms race more apparent than cybersecurity wherein zero-day vulnerabilities are identified and exploited at an ever-growing rate. Cybersecurity, however, is not limited to hardware and software. Cyberoperations require an understanding of the larger sociotechnical system that includes individual users and groups, for example, governmental, industry, and nongovernmental organizations. Indeed, the failure to identify the technical and functional affordances that allow for zero-day vulnerabilities illustrates the ambiguous and ill-defined nature of “cyberspace.” [ABSTRACT FROM AUTHOR]

BACKGROUND: With the development of modern technology, the use of software-based applications in the field of health has become increasingly widespread. For this reason, computer-assisted personal registration forms have been developed using software programs. OBJECTIVE: The aim of this study was to compare surface contamination during the filling of orthodontic anamnesis-consent forms, traditionally on paper and digitally on a tablet equipped with a software application, measured in confined spaces using the 3M Clean-Trace Luminometer device. METHODS: In order for the participants to complete the orthodontic anamnesis-consent forms, two separate identical cabins with standard flat surfaces were prepared. In the first cabin, the participants conventionally completed these forms on paper (conventional group), while in the second cabin, the other group used a tablet equipped with a software program for this purpose (digital group). After the form completion process, surface pollution of the predetermined areas was measured in both cabins using a 3M Clean-Trace Luminometer device. RESULTS: Surface contamination was found to be statistically significantly higher in all measurement areas in the conventional group than in the digital group. Despite a statistically significant difference between the two groups in relation to the measurements performed using the pens (conventional or electronic), this was not as strong as those found for the remaining surfaces. CONCLUSION: The completion of orthodontic anamnesis-consent forms over tablets significantly reduced surface contamination in the close environment. This study reflects the importance of digitization – which has become beneficial in many fields – in reducing the spread of infections. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the new features of the finite element library deal.II, version 9.5. [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]

As a result of constant competitive pressure, companies are forced to constantly look for ways to produce more efficiently. To increase production efficiency and competitiveness, the actual situation needs to be analyzed and measures proposed. However, proposals, when put into practice, do not always result in improvements, due to various errors and omissions in their design. A helpful tool to minimize failures is to apply computer simulations, in which the proposed solutions are being tested and a proven solution implemented into practice afterwards. This is especially important when a proposed solution requires increased investment costs and time. This paper deals with streamlining technological processes on an assembly line of a turbocharger with an electrically controlled actuator, by automating a section of the assembly line (reduced number of operators and defective products), based on analysis and identified deficiencies. The Tecnomatix Plant Simulation software was chosen to analyze the assembly line's condition, as well as to simulate proposed measures' impact on the line's improvement. The design brings increased efficiency of a turbocharger assembly process and a reduced number of workers. According to the simulation results, when proposed improvements are applied, the annual production of the assembly line increases from 89,575 pieces to 98,139 pieces, which is 8,564 pieces more, i.e., an increase of 9.56%, while reducing the number of workers from four to three. [ABSTRACT FROM AUTHOR]

Abstract Purpose Method Results Conclusion \nIMPLICATIONS FOR REHABILITATION Supported employment is a promising vocational rehabilitation intervention for improving disability employment. Its implementation, however, is not without challenges. Lack of funding and the heavy caseload of job coaches significantly constrain its impacts. A mobile software, avail® by CentralReach, was created based on the individual placement and support model for assisting individuals with disabilities to perform their job tasks. The purpose of this pilot study was to explore the feasibility and preliminary efficacy of avail.A total of 17 participants with disabilities were recruited in a Midwestern state from the United States to try avail for a period of time ranging from 40 to 348 days. Participants’ experiences, including perceived usability, acceptance, and satisfaction, were collected to determine the feasibility of avail. In addition, a pre- and post-intervention analysis was conducted to identify its effects on users’ job satisfaction, self-efficacy, and self-determination.Participants of this study expressed positive user experience for avail. Specifically, they felt that avail was helpful for their job performance. The results also showed a statistically significant result for improving participants’ self-determination.avail is a feasible and potentially promising application for assisting workers with disabilities in their job performance. Directly available on mobile devices, avail has several advantages, such as real-time support and good portability. Suggestions and future directions were discussed for further software development. A job coach is needed in the individual placement and support model (IPS) to provide on-site job support for individuals with disabilities. However, job coaches were typically overwhelmed by the heavy caseloads. A job coach application such as the avail was created, and this study was to test its feasibility and preliminary efficacy. The study showed that avail was appropriate for individuals with disabilities to use at work, and they generally enjoyed using the application. The preliminary efficacy showed that avail improved their job performances and overall self-determination. A job coach is needed in the individual placement and support model (IPS) to provide on-site job support for individuals with disabilities. However, job coaches were typically overwhelmed by the heavy caseloads.A job coach application such as the avail was created, and this study was to test its feasibility and preliminary efficacy.The study showed that avail was appropriate for individuals with disabilities to use at work, and they generally enjoyed using the application.The preliminary efficacy showed that avail improved their job performances and overall self-determination. [ABSTRACT FROM AUTHOR]

As the world's population continues to grow and the demand for energy increases, there is an urgent need for sustainable and efficient energy systems. Renewable energy sources, such as wind and solar power, have the potential to play a significant role in meeting this demand, but their intermittency can make integration into existing energy systems a challenge. Moreover, the development of sustainable energy systems has become even more critical in recent years, due to a confluence of events, including the decline in fuel prices, geopolitical conflicts, and the recent COVID-19 pandemic. The decrease in fuel prices has led to a decline in investment in renewable energy and has slowed the transition to sustainable energy systems. Additionally, geopolitical conflicts and pandemics have highlighted the need for resilient and self-sufficient energy systems that can operate independently of external factors. Also, energy storage technologies play a critical role in achieving this goal by providing reliable backup power and enabling microgrids to operate independently of the larger power grid. As such, developing efficient and effective energy storage technologies is essential for creating sustainable energy systems that can meet the demands of modern society while mitigating the impact of external factors. In this regard, this work provides an overview of microgrids' latest energy storage technologies, including their applications, types, integration strategies, optimization algorithms, software, and uncertainty analysis. Energy storage technologies have a wide range of applications in microgrids, including providing backup power and balancing the supply and demand of energy. Different energy storage techniques have been discussed, including batteries, flywheels, supercapacitors, pumped hydro energy storage, and others. Moreover, integration strategies of energy storage in microgrids, models, assessment indices, and optimization algorithms used in the design of energy storage systems are presented in detail. The capabilities of software used in energy storage sizing are explored. Further, uncertainty analysis in modeling energy storage devices is presented and discussed. This state-of-the-art technology has been prepared to demonstrate the effectiveness of energy storage technologies in microgrids, providing valuable insights for future developments in the field. [ABSTRACT FROM AUTHOR]

In molecular dynamics simulations of membrane systems, it is very important to evaluate the interactions between membrane bilayers and other molecules like small compounds, peptides, or proteins. When these interactions lead to local deformations in the membrane, it is essential to fully understand and accurately characterize them, since these deformations can impact the calculation of membrane properties. Here, we introduce MembIT, a simple standalone tool that calculates several membrane properties that are very useful to gauge system equilibration and quality control in molecular dynamics simulations. It has implemented a distinction between local and bulk lipids, which corrects the local deformations, that are often overlooked by other tools. We show examples of MembIT calculations of membrane insertion and deformation values in systems containing POPC and a small drug (sunitinib), a transmembrane peptide (pHLIP), and a transmembrane protein (ADP/ATP carrier). We hope that this tool will be adopted by the scientific community and that the analyses that it provides become good practices in MD simulations of membrane systems. We present a simple standalone tool (MembIT) that calculates several membrane properties from MD simulations. It is useful for studying the membrane thickness, insertion, and deformation induced by different solutes. We showcased its application on three different systems containing sunitinib, pHLIP, or the ADP/ATP carrier in a POPC bilayer. [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]

The appearance of genetic variants impacts vaccination efficiency and therapeutic options, generating a need to map and relate mutations observed in the proteome and the genome. We develop an user-friendly web service software (Viral Instant Mutation Viewer or VIMVer) which allows a direct identification of mutations in the genome and its counterpart in the viral proteome. Since its emergence in 2019, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for the COVID-19 pandemic, has generated an overwhelming amount of data while becoming one of the most studied viruses of the Nidovirales order. We originally developed this tool during the COVID pandemic; thus, for any SARS-CoV-2 nucleotide sequence, the web service gives a fast identification, mapping, and display of new mutations simultaneously at the nucleotide and amino acid level in comparison to a reference sequence (Wuhan-1). Furthermore, the lineage or the relative position to the known lineage of the variant of interest is available on the link to Phylogenetic Assignment of Named Global Outbreak LINeages (PANGOLIN COVID-19). The workflow presented here is available online. The source code is released under public license and can be easily adapted for further development to other viruses. [ABSTRACT FROM AUTHOR]

Developments in retinal imaging technologies have enabled the quantitative evaluation of the retinal vasculature. Changes in retinal calibre and/or geometry have been reported in systemic vascular diseases, including diabetes mellitus (DM), cardiovascular disease (CVD), and more recently in neurodegenerative diseases, such as dementia. Several retinal vessel analysis softwares exist, some being disease-specific, others for a broader context. In the research setting, retinal vasculature analysis using semi-automated software has identified associations between retinal vessel calibre and geometry and the presence of or risk of DM and its chronic complications, and of CVD and dementia, including in the general population. In this article, we review and compare the most widely used semi-automated retinal vessel analysis softwares and their associations with ocular imaging findings in common systemic diseases, including DM and its chronic complications, CVD, and dementia. We also provide original data comparing retinal calibre grading in people with Type 1 DM using two softwares, with good concordance. [ABSTRACT FROM AUTHOR]

Objectives: To provide radiologists and physicists with methodological tools to improve patient management after vascular fluoroscopically guided intervention (FGI) by providing optimized thresholds (OT) values that could be used as a surrogate to the thresholds classically proposed by the National Council on Radiation Protection (NCRP) or could be useful to adapt their own substantial radiation dose levels (SRDL) values. Methods: PSD of 2000–4000 mGy after FGI were calculated for 258 patients with dedicated software. Overall, the kerma and KAP 3D-ROC curves were used to assess the sensitivity (SEN) and specificity (SPE) of NCRP thresholds and OT for each PSD. Kiviat diagram and density curves were plotted for the best SEN/SPE pair of 3D-ROC curves and compared to the NCRP thresholds. Results: OT for both kerma and KAP generating the best SEN/SPE couple for PSD of 2000–4000 mGy were obtained. The SEN/SPE couple of each OT was always better than that obtained using NCRP ones. The best OT among all those calculated providing the highest SEN/SPE values for kerma (3020.5 mGy) and KAP (741.02 Gy.cm2) were obtained when PSD was equal to 3300 mGy. Conclusions: We have calculated OT in terms of kerma and KAP based on 3D-ROC curves analysis and peak skin dose calculations that can be obtained to better predict high skin dose. The use of OT that predicted PSD greater than 3000 mGy is likely to improve patient follow-up. The methodology developed in this work could be adapted to other institutions in order to better define their own SRDL. Key Points: • Optimized dose thresholds in terms of kerma and KAP based on 3D-ROC curves analysis and peak skin dose calculations between 2000 and 4000 mGy can be obtained to better predict high skin dose. • Patients receiving a peak skin dose between 2000 and 4000 mGy have their follow-up enhanced by using the optimized thresholds instead of the NCRP thresholds. • The best-optimized thresholds, corresponding to 3020.5 mGy and 741.02 Gy.cm2 for kerma and KAP respectively can be used instead of NRCP ones to trigger patient follow-up after fluoroscopically guided vascular interventions. [ABSTRACT FROM AUTHOR]

Route optimization, which is a result of the advancement of technology today, makes companies profitable within months. The aim of this study is to explain the relation between route optimization software and the customer satisfaction. Route optimization softwares become widely used by the companies and this study touches briefly on the subject of the relation between route optimization software and customer satisfaction level. While explain this relation, the study described route optimization software, how it works and its execution areas. Hereafter, the article start to explain customer satisfaction and route optimization software’s effects on customer satisfaction and conclude the study. In the drafting and writing process of this article, the topic is detaily searched and analyzed. [ABSTRACT FROM AUTHOR]

Due to the COVID-19, educational institutions fully or partially shifted to online teaching. Hardware-based laboratories presented a major challenge given the online learning environment. Online running of hardware-based laboratory classes using software does not provide students. Online teaching reduces the interaction level between students and demonstrators. As a result, students' performance and satisfaction were reduced. To address these challenges, this article presents a novel mixed mode delivery approach for undergraduate engineering students. This approach is based on pairing remotely and on-campus students. This article uses a case study to describe the implementation of the proposed approach for a large first-year electronics circuit theory class. Compared to students' laboratory performance before COVID-19 pandemic (on-campus only laboratories), online students' laboratory experience was not affected. Their lab performance found to be at 89.64%. Online students gained experience in troubleshooting by their involvement, while on-campus students are connecting the hardware and obtaining measurement results. [ABSTRACT FROM AUTHOR]

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]

This article presents the development of a model for deploying software processes within the context of free and open-source software FLOSS communities, characterized by the voluntary participation of people geographically distributed in different places and with diverse profiles and interests in a software development project. The Delphi method validated the model, in which 15 people interested in FLOSS communities participated. It was found that the model promotes communication and motivation of the participants in more than 80% and favors the participation of new community members, according to the answers given by the participants. The communication and motivation skills of the members of a FLOSS community are fundamental for the proper development of free software construction projects. [ABSTRACT FROM AUTHOR]

Accelerated failure time (AFT) models are used widely in medical research, though to a much lesser extent than proportional hazards models. In an AFT model, the effect of covariates act to accelerate or decelerate the time to event of interest, that is, shorten or extend the time to event. Commonly used parametric AFT models are limited in the underlying shapes that they can capture. In this article, we propose a general parametric AFT model, and in particular concentrate on using restricted cubic splines to model the baseline to provide substantial flexibility. We then extend the model to accommodate time-dependent acceleration factors. Delayed entry is also allowed, and hence, time-dependent covariates. We evaluate the proposed model through simulation, showing substantial improvements compared to standard parametric AFT models. We also show analytically and through simulations that the AFT models are collapsible, suggesting that this model class will be well suited to causal inference. We illustrate the methods with a data set of patients with breast cancer. Finally, we provide highly efficient, user-friendly Stata, and R software packages. [ABSTRACT FROM AUTHOR]

Coastal aquaculture is an important economic activity in India dominated majorly by shrimp culture, which involves a range of interconnected processes that are challenging to analyse and optimise without a systematic approach. System dynamics modelling is a useful tool for understanding and predicting the behavior of complex coastal aquaculture systems. here, we review the status of dynamic simulation modelling works undertaken in aquaculture, which can provide directives for various researchers working on developing simulation models for shrimp aquaculture. There is a need to assess the impact of dynamic forces on the animals during the culture period which could be addressed through these models. System dynamic models assist decision-makers to augment potential measures for aquaculture-related problems under different possible scenarios. System dynamic models developed in aquaculture were related to feeding, water quality parameters, nitrogen dynamics, growth, etc. The strengths and limitations of software packages used in developing the simulation models are discussed. Considering the economic potential of shrimp aquaculture, it is important to develop an integrated dynamic model for predicting all the sub-processes of shrimp aquaculture. [ABSTRACT FROM AUTHOR]

Background: Patients’ education is a vital strategy for understanding a disease by patients and proper management of the condition. Physicians and academicians frequently make customized education materials for their patients. An artificial intelligence (AI)‑based writer can help them write an article. Chat Generative Pre‑Trained Transformer (ChatGPT) is a conversational language model developed by OpenAI (openai.com). The model can generate human‑like responses. Objective: We aimed to evaluate the generated text from ChatGPT for its suitability in patients’ education. Materials and Methods: We asked the ChatGPT to list common dermatological diseases. It provided a list of 14 diseases. We used the disease names to converse with the application with disease‑specific input (e.g., write a patient education guide on acne). The text was copied for checking the number of words, readability, and text similarity by software. The text's accuracy was checked by a dermatologist following the structure of observed learning outcomes (SOLO) taxonomy. For the readability ease score, we compared the observed value with a score of 30. For the similarity index, we compared the observed value with 15% and tested it with a one‑sample t‑test. Results: The ChatGPT generated a paragraph of text of 377.43 ± 60.85 words for a patient education guide on skin diseases. The average text reading ease score was 46.94 ± 8.23 (P < 0.0001), and it indicates that this level of text can easily be understood by a high‑school student to a newly joined college student. The text similarity index was higher (27.07 ± 11.46%, P = 0.002) than the expected limit of 15%. The text had a “relational” level of accuracy according to the SOLO taxonomy. Conclusion: In its current form, ChatGPT can generate a paragraph of text for patients’ educational purposes that can be easily understood. However, the similarity index is high. Hence, doctors should be cautious when using the text generated by ChatGPT and must check for text similarity before using it. [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]

The International Society of Blood Transfusion (ISBT) 128 is an internationally endorsed, electronically readable labeling standard that provides a convenient and accurate means of identification, traceability, publication, and storage of information for blood and blood products. The authors' center recently registered with the International Council for Commonality in Blood Banking Automation (ICCBBA) and progressed to ISBT 128 labeling standard. This manuscript was written with the objective of sharing the authors' experience with respect to the implementation of ISBT 128 standards for whole blood donations and integration of ISBT 128 standards with Indian licensing regulations. The authors explore the process of implementation of ISBT 128 standards through a step-by-step journey that included facility registration with International Council for Commonality in Blood Banking Automation (ICCBBA), allotment of facility identification number, development of four-quadrant label for blood components, and integration of local regulatory requirements in the final "composite" label. Acknowledging the lack of any published report from India on ISBT 128 standards implementation, the authors wish to attempt help their peers in understanding and implementation of this global standard at their respective facilities. [ABSTRACT FROM AUTHOR]

Although there exist various reliability assessment models, many of these models did not consider the temporal incorrectness, incompatibilities and dependencies between hardware and software. Also, many models did not consider the hardware changes, software changes and hardware changes leading to software changes resulting in system failure. Thus, an approach that considers various aspects like pure software failures, pure hardware failures, software change, hardware change, hardware change leading to software change and incompatibility issues between hardware and software components (in the presence of temporal incorrectness) leading to the failure of non-repairable time-critical heterogeneous software systems has been developed. This approach considers the operation of the hardware–software system, both in normal (non-degraded) and degraded modes. The proposed approach was applied to a time-critical stepper motor system, results were obtained and a case study was performed. The effectiveness of the proposed approach has been analyzed by comparing the results obtained from the proposed approach with the results obtained from the other existing approaches. [ABSTRACT FROM AUTHOR]

Simple Summary: Next-generation sequencing (NGS) is a cutting-edge technology that enables rapid, high-throughput sequencing of DNA and RNA. Researchers and clinicians can identify genetic mutations, gene fusions, and other alterations that may drive cancer growth. This is particularly important in precision oncology as it is applied in the context of Molecular Tumor Boards (MTBs). The latter are multidisciplinary teams of experts who use NGS and bioinformatics tools to analyze patients' genetic profiles and develop personalized treatment recommendations for cancer patients. Thus, a crucial process for MTB decision-making is the analysis, compilation, and presentation of high-dimensional sequencing data, which are used for both preparation of and case presentation to all stakeholders. MIRACUM-Pipe precisely addresses these requirements and offers an easy-to-use, one-prompt standardized solution to analyze NGS data, including quality control, variant calling, copy number estimation, annotation, visualization, and report generation. (1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge of both bioinformatics and oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses and annotation of NGS data including quality control, alignment, variant calling, copy number variation estimation, evaluation of complex biomarkers, and RNA fusion detection. (3) Results: MIRACUM-Pipe offers an easy-to-use, one-prompt standardized solution to analyze NGS data, including quality control, variant calling, copy number estimation, annotation, visualization, and report generation. (4) Conclusions: MIRACUM-Pipe, a versatile pipeline for NGS, can be customized according to bioinformatics and clinical needs and to support clinical decision-making with visual processing and interactive reporting. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the clinical implications and prognostic value of artificial intelligence (AI)-based results for chest radiographs (CXR) in coronavirus disease 2019 (COVID-19) patients. Patients who were admitted due to COVID-19 from September 2021 to March 2022 were retrospectively included. A commercial AI-based software was used to assess CXR data for consolidation and pleural effusion scores. Clinical data, including laboratory results, were analyzed for possible prognostic factors. Total O2 supply period, the last SpO2 result, and deterioration were evaluated as prognostic indicators of treatment outcome. Generalized linear mixed model and regression tests were used to examine the prognostic value of CXR results. Among a total of 228 patients (mean 59.9 ± 18.8 years old), consolidation scores had a significant association with erythrocyte sedimentation rate and C-reactive protein changes, and initial consolidation scores were associated with the last SpO2 result (estimate −0.018, p = 0.024). All consolidation scores during admission showed significant association with the total O2 supply period and the last SpO2 result. Early changing degree of consolidation score showed an association with deterioration (odds ratio 1.017, 95% confidence interval 1.005–1.03). In conclusion, AI-based CXR results for consolidation have potential prognostic value for predicting treatment outcomes in COVID-19 patients. [ABSTRACT FROM AUTHOR]

Background: Reaction networks are widely used as mechanistic models in systems biology to reveal principles of biological systems. Reactions are governed by kinetic laws that describe reaction rates. Selecting the appropriate kinetic laws is difficult for many modelers. There exist tools that attempt to find the correct kinetic laws based on annotations. Here, I developed annotation-independent technologies that assist modelers by focusing on finding kinetic laws commonly used for similar reactions. Results: Recommending kinetic laws and other analyses of reaction networks can be viewed as a classification problem. Existing approaches to determining similar reactions rely heavily on having good annotations, a condition that is often unsatisfied in model repositories such as BioModels. I developed an annotation-independent approach to find similar reactions via reaction classifications. I proposed a two-dimensional kinetics classification scheme (2DK) that analyzed reactions along the dimensions of kinetics type (K type) and reaction type (R type). I identified approximately ten mutually exclusive K types, including zeroth order, mass action, Michaelis–Menten, Hill kinetics, and others. R types were organized by the number of distinct reactants and the number of distinct products in reactions. I constructed a tool, SBMLKinetics, that inputted a collection of SBML models and then calculated reaction classifications as the probability of each 2DK class. The effectiveness of 2DK was evaluated on BioModels, and the scheme classified over 95% of the reactions. Conclusions: 2DK had many applications. It provided a data-driven annotation-independent approach to recommending kinetic laws by using type common for the kind of models in combination with the R type of the reactions. Alternatively, 2DK could also be used to alert users that a kinetic law was unusual for the K type and R type. Last, 2DK provided a way to analyze groups of models to compare their kinetic laws. I applied 2DK to BioModels to compare the kinetics of signaling networks with the kinetics of metabolic networks and found significant differences in K type distributions. [ABSTRACT FROM AUTHOR]

Bacterial genomes exhibit widespread horizontal gene transfer, resulting in highly variable genome content that complicates the inference of genetic interactions. In this study, we develop a method for detecting coevolving genes from large datasets of bacterial genomes based on pairwise comparisons of closely related individuals, analogous to a pedigree study in eukaryotic populations. We apply our method to pairs of genes from the Staphylococcus aureus accessory genome of over 75,000 annotated gene families using a database of over 40,000 whole genomes. We find many pairs of genes that appear to be gained or lost in a coordinated manner, as well as pairs where the gain of one gene is associated with the loss of the other. These pairs form networks of rapidly coevolving genes, primarily consisting of genes involved in virulence, mechanisms of horizontal gene transfer, and antibiotic resistance, particularly the SCCmec complex. While we focus on gene gain and loss, our method can also detect genes that tend to acquire substitutions in tandem, or genotype-phenotype or phenotype-phenotype coevolution. Finally, we present the R package DeCoTUR that allows for the computation of our method. [ABSTRACT FROM AUTHOR]

Background: Stochastic optical reconstruction microscopy (STORM), a super-resolution microscopy technique based on single-molecule localizations, has become popular to characterize sub-diffraction limit targets. However, due to lengthy image acquisition, STORM recordings are prone to sample drift. Existing cross-correlation or fiducial marker-based algorithms allow correcting the drift within each channel, but misalignment between channels remains due to interchannel drift accumulating during sequential channel acquisition. This is a major drawback in multi-color STORM, a technique of utmost importance for the characterization of various biological interactions. Results: We developed RegiSTORM, a software for reducing channel misalignment by accurately registering STORM channels utilizing fiducial markers in the sample. RegiSTORM identifies fiducials from the STORM localization data based on their non-blinking nature and uses them as landmarks for channel registration. We first demonstrated accurate registration on recordings of fiducials only, as evidenced by significantly reduced target registration error with all the tested channel combinations. Next, we validated the performance in a more practically relevant setup on cells multi-stained for tubulin. Finally, we showed that RegiSTORM successfully registers two-color STORM recordings of cargo-loaded lipid nanoparticles without fiducials, demonstrating the broader applicability of this software. Conclusions: The developed RegiSTORM software was demonstrated to be able to accurately register multiple STORM channels and is freely available as open-source (MIT license) at and (archived), and runs as a standalone executable (Windows) or via Python (Mac OS, Linux). [ABSTRACT FROM AUTHOR]

The role of restaurants, canteens, other forms of eatery and food service outlets are becoming very big part of most economies at different levels. However improvement in customer experience while making orders plays a very critical role in having a smooth and efficient menu ordering process. This article presents a novel hybrid approach that tackles the challenges associated with menu ordering especially in the post-covid era; both from software and hardware perspectives. First, a web-application - powered by ReactJS and GraphQL, which enables order request anywhere at any time was developed. In addition, is the implementation of hardware with mobility feature on trips to the restaurant using two Arduino microcontrollers (transmitter and receiver). The result allows the user to browse through a catalogue, check-in and out on a Thin-Film-Transistor (TFT) liquid-crystal display (LCD) and deliver a seamless experience to the customer. [ABSTRACT FROM AUTHOR]

The development of the system document models in the field of MR-PYRO was done taking into account the adaptation of the application requirements of this management system, to the organizational and work process particularities specific to the pyrotechnic field, but also with the requirements of the legislation in force in the field of occupational health and safety, namely Law 319/2006 on safety and health at work and the methodological rules for its application, as well as specific legislation (Law 126/1995 on the regime of explosive materials and the Technical Norms of application with subsequent amendments and additions). The scientific article offers an original perspective of solving the problem in the field of management system of pyrotechnic articles (MR-PYRO). The MR-PYRO.EXE 01 software application ensures the operational and procedural development of the MSSM system documents based on the analysis and evaluation of the particular way of occurrence of all aspects of occupational safety and health managed at the level of economic operators working in the field of pyrotechnic articles. [ABSTRACT FROM AUTHOR]

The article proposes a generalized algorithm for evaluating the shielding effectiveness (SE) of electronic equipment enclosures. The algorithm is based on a number of analytical models that use equivalent circuits to obtain SE values. The article begins with a brief review and interpretation of the mathematical formulation used in the algorithm. Then, we describe the proposed algorithm using flowcharts, and we perform its validation. The validation results show that the proposed algorithm has acceptable accuracy and gives SE values comparable to numerical methods or measurements, with much less time costs. The last part of the article presents the software developed to evaluate SE based on analytical models. [ABSTRACT FROM AUTHOR]

One developing approach for robotic control is the use of networks of dynamic neurons connected with conductance-based synapses, also known as Synthetic Nervous Systems (SNS). These networks are often developed using cyclic topologies and heterogeneous mixtures of spiking and non-spiking neurons, which is a difficult proposition for existing neural simulation software. Most solutions apply to either one of two extremes, the detailed multi-compartment neural models in small networks, and the large-scale networks of greatly simplified neural models. In this work, we present our open-source Python package SNS-Toolbox, which is capable of simulating hundreds to thousands of spiking and non-spiking neurons in real-time or faster on consumer-grade computer hardware. We describe the neural and synaptic models supported by SNS-Toolbox, and provide performance on multiple software and hardware backends, including GPUs and embedded computing platforms. We also showcase two examples using the software, one for controlling a simulated limb with muscles in the physics simulator Mujoco, and another for a mobile robot using ROS. We hope that the availability of this software will reduce the barrier to entry when designing SNS networks, and will increase the prevalence of SNS networks in the field of robotic control. [ABSTRACT FROM AUTHOR]

Background: The outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in the global COVID-19 pandemic. The urgency for an effective SARS-CoV-2 vaccine has led to the development of the first series of vaccines at unprecedented speed. The discovery of SARS-CoV-2 spike-glycoprotein mutants, however, and consequentially the potential to escape vaccine-induced protection and increased infectivity, demonstrates the persisting importance of monitoring SARS-CoV-2 mutations to enable early detection and tracking of genomic variants of concern. Results: We developed the CoVigator tool with three components: (1) a knowledge base that collects new SARS-CoV-2 genomic data, processes it and stores its results; (2) a comprehensive variant calling pipeline; (3) an interactive dashboard highlighting the most relevant findings. The knowledge base routinely downloads and processes virus genome assemblies or raw sequencing data from the COVID-19 Data Portal (C19DP) and the European Nucleotide Archive (ENA), respectively. The results of variant calling are visualized through the dashboard in the form of tables and customizable graphs, making it a versatile tool for tracking SARS-CoV-2 variants. We put a special emphasis on the identification of intrahost mutations and make available to the community what is, to the best of our knowledge, the largest dataset on SARS-CoV-2 intrahost mutations. In the spirit of open data, all CoVigator results are available for download. The CoVigator dashboard is accessible via covigator.tron-mainz.de. Conclusions: With increasing demand worldwide in genome surveillance for tracking the spread of SARS-CoV-2, CoVigator will be a valuable resource of an up-to-date list of mutations, which can be incorporated into global efforts. [ABSTRACT FROM AUTHOR]

This paper presents the development of a dynamic positioning in ice validation platform (DPIVP) which is part of a larger research project aimed at developing dynamic positioning (DP) system technologies for ice-rich environments. One outcome is simulation software to aid research in this area. The DPIVP software was designed to realistically simulate the dynamics of ice-structure interactions for real-time applications and to validate components common to DP in ice simulations. The software consists of many components which the DPIVP ties together as a unified system. All components have well-defined interfaces. Many of them are also distributed, allowing execution on separate computers and/or CPUs which helps ensure real-time operation. These two characteristics also decreases coupling and encourages a more modular design with the benefit of easily substituting alternative component implementations without reprogramming the DPIVP. Alternate implementations are useful for conducting research in specific DP in ice areas without substantially changing the system, such as alternative ice force models, DP control algorithms, vessel models, 3D and 2D visualization, environment models, and data acquisition systems. The integrated system was tested and evaluated using unit testing, integration testing, and system testing. The completed system was also validated using test cases that match physical model tests; the results compared favorably. Although the software has some limitations, for example, validated ice-force models being limited to two vessels, and thus lacks the generality we wish, the end result is a working prototype that satisfies the research requirements and provides an architecture and framework for future development. [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]

Drug combinations are increasingly studied in the field of anticancer agents. Mathematical models, such as Loewe, Bliss, and HSA, are used to interpret drug combinations, while informatics tools help cancer researchers identify the most effective combinations. However, the different algorithms each software uses lead to results that do not always correlate. This study compared the performance of Combenefit (Ver. 2.021) and SynergyFinder (Ver. 3.6) in analyzing drug synergy by studying combinations involving non-steroidal analgesics (celecoxib and indomethacin) and antitumor drugs (carboplatin, gemcitabine, and vinorelbine) on two canine mammary tumor cell lines. The drugs were characterized, their optimal concentration–response ranges were determined, and nine concentrations of each drug were used to make combination matrices. Viability data were analyzed under the HSA, Loewe, and Bliss models. Celecoxib-based combinations showed the most consistent synergistic effect among software and reference models. Combination heatmaps revealed that Combenefit gave stronger synergy signals, while SynergyFinder produced better concentration–response fitting. When the average values of the combination matrices were compared, some combinations shifted from synergistic to antagonistic due to differences in the curve fitting. We also used a simulated dataset to normalize each software's synergy scores, finding that Combenefit tends to increase the distance between synergistic and antagonistic combinations. We conclude that concentration–response data fitting biases the direction of the combination (synergistic or antagonistic). In contrast, the scoring from each software increases the differences among synergistic or antagonistic combinations in Combenefit when compared to SynergyFinder. We strongly recommend using multiple reference models and reporting complete data analysis for synergy claiming in combination studies. [ABSTRACT FROM AUTHOR]

Introduction: Metabolomics analysis based on liquid chromatography-mass spectrometry (LC-MS) has been a prevalent method in the metabolic field. However, accurately quantifying all the metabolites in large metabolomics sample cohorts is challenging. The analysis efficiency is restricted by the abilities of software in many labs, and the lack of spectra for some metabolites also hinders metabolite identification. Objectives: Develop software that performs semi-targeted metabolomics analysis with an optimized workflow to improve quantification accuracy. The software also supports web-based technologies and increases laboratory analysis efficiency. A spectral curation function is provided to promote the prosperity of homemade MS/MS spectral libraries in the metabolomics community. Methods: MetaPro is developed based on an industrial-grade web framework and a computation-oriented MS data format to improve analysis efficiency. Algorithms from mainstream metabolomics software are integrated and optimized for more accurate quantification results. A semi-targeted analysis workflow is designed based on the concept of combining artificial judgment and algorithm inference. Results: MetaPro supports semi-targeted analysis workflow and functions for fast QC inspection and self-made spectral library curation with easy-to-use interfaces. With curated authentic or high-quality spectra, it can improve identification accuracy using different peak identification strategies. It demonstrates practical value in analyzing large amounts of metabolomics samples. Conclusion: We offer MetaPro as a web-based application characterized by fast batch QC inspection and credible spectral curation towards high-throughput metabolomics data. It aims to resolve the analysis difficulty in semi-targeted metabolomics. [ABSTRACT FROM AUTHOR]

An existing approximately neutral surface, the ω surface, minimizes the neutrality error and hence also exhibits very small fictitious dianeutral diffusivity Df that arises when lateral diffusion is applied along the surface, in nonneutral directions. However, there is also a spurious dianeutral advection that arises when lateral advection is applied nonneutrally along the surface; equivalently, lateral advection applied along the neutral tangent planes creates a vertical velocity esp through the ω surface. Mathematically, esp = u ⋅ s, where u is the lateral velocity and s is the slope error of the surface. We find that esp produces a leading-order term in the evolution equations of temperature and salinity, being similar in magnitude to the influence of cabbeling and thermobaricity. We introduce a new method to form an approximately neutral surface, called an ωu·s surface, that minimizes esp by adjusting its depth so that the slope error is nearly perpendicular to the lateral velocity. The esp on a surface cannot be reduced to zero when closed streamlines contain nonzero neutral helicity. While esp on the ωu·s surface is over 100 times smaller than that on the ω surface, the fictitious dianeutral diffusivity on the ωu·s surface is larger, nearly equal to the canonical 10−5 m2 s−1 background diffusivity. Thus, we also develop a method to minimize a combination of esp and Df, yielding the ω u · s + s 2 surface, which is recommended for inverse models since it has low Df and it significantly decreases esp through the surface, which otherwise would be a leading term that cannot be ignored in the conservation equations. [ABSTRACT FROM AUTHOR]

Technology is used to keep track of things and timing and make the best decision on the information available. Project Management (PM) has to offer through its various software and technical tools. PM software has always been compared to the traditional ways of libraries. If a library has always been compared to its traditional ways of doing projects, PM brings systematic strategies to the planned project of libraries from beginning to end. The main objective of this research is to find a systematic literature review on the software of PM, the -advantages of using PM in libraries, and the challenges faced by the libraries using PM. This research used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to illustrate the systematic literature review. The terms "Project Management" and ("library" OR "libraries") were applied to the advanced research of the five databases: Ebscohost, Emerald, Scopus, WOS, and ScienceDirect were selected databases to ensure relevant studies were captured. The main finding from the research is that using Project Management software in libraries has many advantages, such as clarity of planning and a good understanding of technical tools and software, despite many challenges. It provides end-to-end planning and can be adapted to frequent changes to increase productivity and success. In addition, unlike other studies, this study indicates the missing gap in the literature, and it is hoped that it will guide the researchers. [ABSTRACT FROM AUTHOR]