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Previous research has shown a strong link between our sense of smell and emotion. More recently, the importance we attach to olfaction has been found to relate to our susceptibility to 'catch' the emotions of others. We explore this further by examining the relation between a newly developed measure of olfaction (social odour scale, SOS), which measures awareness of social odours, and emotional contagion susceptibility in female participants. The study therefore aimed to test the strength of this relationship and also help validate the English language version of the SOS. Female (n = 148) participants completed an online study that measured odour awareness [SOS; important of odour questionnaire, IOQ] and emotional contagion (EC). We found that the English version of the SOS yielded high reliability and supported the previous factor structure of the scale; additionally, we demonstrated a strong association between the SOS and IOQ which provides criterion validity for its usage. The study also revealed that whilst both the SOS and IOQ were positively associated with EC, the SOS was the more accurate predictor. These findings provide further validation for the use of the SOS and suggest that our subjective awareness of olfaction, especially concerning 'social odours' is an accurate predictor of emotional contagion. [ABSTRACT FROM AUTHOR]

The article focuses on predicting rolling force (RF) in the hot rolling process by incorporating nano-lubrication conditions through strategies available in finite element method (FEM) software. Additional work includes RF prediction by artificial neural network (ANN) modelling. The experimental RF were collected from an experimental rolling mill (ERM) for hot rolling IS 2062 E250 steel. The simulations were performed using SIMUFACT and the results were validated by experimental data. The prediction was made accurately by adjusting the lubrication panel available in the software. Then, FEM and ANN were performed to predict RF at various combinations of process parameters. FEA simulated hot rolling of IS 2062 E250 with varying process parameters. It incorporates changing 5 process parameters for FEA as roll speed, reduction%, nano-lubrication condition, billet size (thickness), and rolling temperature. Then, the accumulation of data for further application in ANN modelling. The validation of FEM software was successful with an error of less than 5%. According to the validation, the lubrication corresponding to the nano-lubrication setup was fixed in the software. The mesh was optimised and detected the least RF deviation at 1.8 mm mesh. The ANN was performed from the simulation data. The ANN performed better for a single hidden layer model for 8 neurons. The training, validating, and testing of the model resulted in an R-square value of 0.991, 0.987, and 0.994, respectively. The root mean square error (RMSE) value obtained was 0.985. Therefore, the ANN model developed was performing better. The article uses the combined strategy of FEM and ANN, with available lubrication panels in FEM software for accurate RF predictions. [ABSTRACT FROM AUTHOR]

In the local building industry of Pakistan, pre-engineered steel building manufacturers mainly employ their own self-developed software and Excel sheets. These systems are based on empirical formulas mentioned in the AISI manual. Under this scenario, a need was found to validate AISI flow charts using commercial software like CUFSM 5.04 and ABAQUS R2019x. This study presents a validation of the CUFSM software and the American Iron and Steel Institute (AISI) Direct Strength Method (DSM) results of channel section flexural members using the non-linear finite element method employing ABAQUS. In this study, eight standard cold-formed channel-section (C-section) steel members were modeled and analyzed using ABAQUS to simulate realistic behavior under four-point loading conditions. The non-linear finite element models incorporated material and geometric non-linearities to capture the actual response of the steel elements. The results obtained from ABAQUS were compared with those predicted by the CUFSM and DSM, focusing on critical parameters such as nominal strength, buckling modes, and deformation patterns. During this study, it was observed that out of the selected sections, the AISI charts predict conservative and even unsafe flexural capacities in some of the cases concerning other methods, with a maximum difference of 14.03%. The differences obtained using DSM and ABAQUS when compared with the results of the AISI charts varies on both the plus and minus sides. This study will not only affect the industry in terms of innovative designs for efficient structures but also the community in regards to low-budget construction. [ABSTRACT FROM AUTHOR]

This study involves the investigation of the effect of the replacement of B2O3 with La2O3 on the properties of the multi-component lead Borovanadate glass. Five samples were prepared using the fast-quenching method according to the chemical formula (43-x) mole % B2O3 - x mole % La2O3- 10 mol % V2O5-12.5 mol % CaO-12.5 mol % Li2O -22 mol %PbO, where x = 0, 1, 2, 3, and 5 mol %. The amorphous character of the synthesized samples was confirmed via Fourier transform infrared and X-ray diffraction. XRD patterns suggest a lack of long-range organized crystalline structure, but FTIR reveals various structural unit blocks. On the other side, the increment of La2O3 content caused a proportional increase in the glasses' bulk density and molar volume. UV analysis revealed that the sample with 5 mol % La2O3 had superior absorption properties compared to the other samples. All the samples were found to be effective in transmitting light within the energy range of 3.43–4.07 eV, with the La2O3-free sample demonstrating the highest level of light transmission among all the samples. The radiation shielding characteristics of the synthesized glasses were analyzed. The theoretical predictions for the mass attenuation coefficients using WinXCom agreed well with the measured values, providing validation for both the software and the experimental techniques used. This investigation found that La2O3 concentration influenced the linear attenuation coefficient (LAC) at a defined energy level, with higher La2O3 resulting in higher LAC values. The study also showed that lower energy levels had better linear attenuation compared to higher ones. [ABSTRACT FROM AUTHOR]

A ventilator central monitoring system (VCMS) that can efficiently respond to and treat patients' respiratory issues in intensive care units (ICUs) is critical. Using Internet of Things (IoT) technology without loss or delay in patient monitoring data, clinical staff can overcome spatial constraints in patient respiratory management by integrated monitoring of multiple ventilators and providing real-time information through remote mobile applications. This study aimed to establish a VCMS and assess its effectiveness in an ICU setting. A VCMS comprises central monitoring and mobile applications, with significant real-time information from multiple patient monitors and ventilator devices stored and managed through the VCMS server, establishing an integrated monitoring environment on a web-based platform. The developed VCMS was analyzed in terms of real-time display and data transmission. Twenty-one respiratory physicians and staff members participated in usability and satisfaction surveys on the developed VCMS. The data transfer capacity derived an error of approximately 10 − 7 , and the difference in data transmission capacity was approximately 1.99 × 10 − 7 ± 9.97 × 10 − 6 with a 95% confidence interval of − 1.16 × 10 − 7 to 5.13 × 10 − 7 among 18 ventilators and patient monitors. The proposed VCMS could transmit data from various devices without loss of information within the ICU. The medical software validation, consisting of 37 tasks and 9 scenarios, showed a task completion rate of approximately 92%, with a 95% confidence interval of 88.81–90.43. The satisfaction survey consisted of 23 items and showed results of approximately 4.66 points out of 5. These results demonstrated that the VCMS can be readily used by clinical ICU staff, confirming its clinical utility and applicability. The proposed VCMS can help clinical staff quickly respond to the alarm of abnormal events and diagnose and treat based on longitudinal patient data. The mobile applications overcame space constraints, such as isolation to prevent respiratory infection transmission of clinical staff for continuous monitoring of respiratory patients and enabled rapid consultation, ensuring consistent care. [ABSTRACT FROM AUTHOR]

This study explores the influence of Co2+ and Cr3+ doping on the microstructure and electrical properties of Ba-hexagonal ferrite synthesized using the sol-gel method. X-ray diffraction (XRD) confirmed the formation of the anticipated hexagonal M-type crystal structure. Field emission scanning electron microscopy (FESEM) revealed the evolution of grain morphology with increasing doping levels, showcasing the formation of needle-like grains. Electrical characterization using an impedance analyzer investigated dielectric, impedance, electric modulus, and conductivity properties at room temperature. The analysis of the dielectric spectra indicated a decrease in dielectric constant and an increase in loss tangent with increasing dopant concentration. The electric modulus spectra provided evidence for non-Debye relaxation behavior, further supported by observations of relaxation processes at varying frequencies in the conductivity spectra. Additionally, an increase in doping led to a decrease in both relaxation time and AC conductivity. Electrochemical impedance spectroscopy (EIS) measurements yielded complex impedance curves. These curves exhibited good agreement with the values obtained through software-based simulations of grain and grain boundary characteristics. Furthermore, the distribution of grains and grain boundaries observed in FESEM micrographs aligned with the patterns predicted by the EIS software. [ABSTRACT FROM AUTHOR]

Abstract Background Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR). Methods Individuals were selected from the “Lifelines” cohort who had undergone low-dose chest CT. Nodules in individuals without emphysema were matched to similar-sized nodules in individuals with at least moderate emphysema. AI results for nodular findings of 30–100 mm3 and 101–300 mm3 were compared to those of HR; two expert radiologists blindly reviewed discrepancies. Sensitivity and false positives (FPs)/scan were compared for emphysema and non-emphysema groups. Results Thirty-nine participants with and 82 without emphysema were included (n = 121, aged 61 ± 8 years (mean ± standard deviation), 58/121 males (47.9%)). AI and HR detected 196 and 206 nodular findings, respectively, yielding 109 concordant nodules and 184 discrepancies, including 118 true nodules. For AI, sensitivity was 0.68 (95% confidence interval 0.57–0.77) in emphysema versus 0.71 (0.62–0.78) in non-emphysema, with FPs/scan 0.51 and 0.22, respectively (p = 0.028). For HR, sensitivity was 0.76 (0.65–0.84) and 0.80 (0.72–0.86), with FPs/scan of 0.15 and 0.27 (p = 0.230). Overall sensitivity was slightly higher for HR than for AI, but this difference disappeared after the exclusion of benign lymph nodes. FPs/scan were higher for AI in emphysema than in non-emphysema (p = 0.028), while FPs/scan for HR were higher than AI for 30–100 mm3 nodules in non-emphysema (p = 0.009). Conclusions AI resulted in more FPs/scan in emphysema compared to non-emphysema, a difference not observed for HR. Relevance statement In the creation of a benchmark dataset to validate AI software for lung nodule detection, the inclusion of emphysema cases is important due to the additional number of FPs. Key points • The sensitivity of nodule detection by AI was similar in emphysema and non-emphysema. • AI had more FPs/scan in emphysema compared to non-emphysema. • Sensitivity and FPs/scan by the human reader were comparable for emphysema and non-emphysema. • Emphysema and non-emphysema representation in benchmark dataset is important for validating AI. Graphical Abstract

Background: Real-time quantitative PCR (RT-qPCR) is one of the most widely used gene expression analyses for validating RNA-seq data. This technique requires reference genes that are stable and highly expressed, at least across the different biological conditions present in the transcriptome. Reference and variable candidate gene selection is often neglected, leading to misinterpretation of the results. Results: We developed a software named "Gene Selector for Validation" (GSV), which identifies the best reference and variable candidate genes for validation within a quantitative transcriptome. This tool also filters the candidate genes concerning the RT-qPCR assay detection limit. GSV was compared with other software using synthetic datasets and performed better, removing stable low-expression genes from the reference candidate list and creating the variable-expression validation list. GSV software was used on a real case, an Aedes aegypti transcriptome. The top GSV reference candidate genes were selected for RT-qPCR analysis, confirming that eiF1A and eiF3j were the most stable genes tested. The tool also confirmed that traditional mosquito reference genes were less stable in the analyzed samples, highlighting the possibility of inappropriate choices. A meta-transcriptome dataset with more than ninety thousand genes was also processed successfully. Conclusion: The GSV tool is a time and cost-effective tool that can be used to select reference and validation candidate genes from the biological conditions present in transcriptomic data. [ABSTRACT FROM AUTHOR]

Computer System Validation (CSV) is a critical aspect of ensuring that any software or system used in regulated environments, such as pharmaceuticals, healthcare, and biotechnology, meets its intended purpose and operates consistently within specified parameters. The UV spectroscopy instrument, specifically the CARRY UV software, is a pivotal tool in analytical laboratories for measuring the absorbance and transmission of ultraviolet and visible light by a sample. Validating this software using the V-Model ensures its reliability, accuracy, and compliance with regulatory standards. The V-Model, or Validation Model, is a systematic approach widely used in software development and validation. It emphasizes verification and validation activities corresponding to each stage of the software development lifecycle. Key aspects include accuracy in measurement, data integrity, user access controls, and audit trails. This stage involves outlining the software's capabilities, such as wavelength range, data processing algorithms, user interface design, and integration with laboratory information management systems (LIMS). The design specifications phase involves creating a blueprint for the software's architecture. This includes the design of databases, software modules, and user interfaces. For CARRY UV software, it is crucial to ensure that the design supports robust data handling, secure user access, and accurate data processing. For the CARRY UV software, developers must focus on implementing algorithms for accurate spectral data analysis and ensuring the software's compatibility with various hardware configurations. Integration testing involves combining individual modules and testing them as a group. System testing validates the complete and integrated software to ensure it meets the specified requirements. For the CARRY UV software, this involves testing the entire workflow from sample measurement to data analysis and reporting. It ensures the software performs reliably under different conditions and usage scenarios Users test the CARRY UV software in a real-world environment to ensure it performs as expected. This phase includes installation qualification (IQ), operational qualification (OQ), and performance qualification (PQ) to ensure the CARRY UV software is installed correctly, operates according to specifications, and performs consistently in the production environment. Throughout the validation process, meticulous documentation is maintained. This includes validation plans, test scripts, test results, and validation reports. Documentation is essential for demonstrating compliance with regulatory requirements, such as those set by the FDA, EMA, or other relevant authorities. Validating the CARRY UV software using the V Model ensures a structured and thorough approach to verifying and validating the software's functionality, performance, and compliance. This methodical process helps identify and mitigate risks early, ensuring the software's reliability and integrity in critical analytical applications. Through rigorous testing and documentation, the V Model supports the delivery of a robust and compliant UV spectroscopy instrument software, ultimately enhancing laboratory efficiency and accuracy. [ABSTRACT FROM AUTHOR]

The use of SiO2 ceramic materials is increasingly prevalent in both industrial and artisanal craftsmanship. These materials exhibit excellent mechanical properties, making them challenging to process, especially after firing. The paper explores the application of CO2 lasers for engraving ceramic materials, addressing challenges in traditional processing methods and offering insights into optimizing laser parameters for enhanced engraving performance. Through simulations using COMSOL Multiphysics software and experimental validations, the thermal interaction between CO2 lasers and SiO2 ceramic substrates is thoroughly investigated. Parameters such as power, scanning speed, pulse width, and repetition frequency are examined to understand their influence on engraving depth, resolution, and surface quality. The research compares continuous wave (CW) and pulsed modes, highlighting their advantages and limitations. The most suitable set of technological parameters is selected for experimentations on unfired and fired ceramic samples. The results demonstrate the effectiveness of CO2 lasers in engraving ceramics and their potential for various industrial applications. This research provides comprehensive insights into applying CO2 laser technology to ceramic materials. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop software for reading and managing sunshine duration recorded by Campbell–Stokes heliographs. The software employs digital image processing techniques, such as mean filtering, thresholding, and opening, to interpret digitized images of record cards containing sunshine duration measurements. The software's validation was conducted by comparing global solar irradiation measurements with estimates of global solar irradiation generated from sunshine duration obtained automatically by the software and manually by a meteorological observer. Estimates generated by the automated method showed better performance (mean bias error: 0.084, relative mean bias error: 0.500, root mean square error: 2.045, relative root mean square error: 12.109, and correlation coefficient: 0.954). Additionally, the automated method was significantly faster, taking an average of 41.825 s less than the manual method to perform the readings. This suggests that the software can be used to automate, standardize, and speed up reading sunshine duration data. Furthermore, the use of the software enabled the creation of a daily sunshine duration database, common in meteorological stations, and an hourly database, which is a novelty due to the complexity of the manual reading method. [ABSTRACT FROM AUTHOR]

This investigation delves into the analytic optical exploration of the Biswas–Milovic equation featuring both parabolic and power law nonlinearity. It provides valuable insights into the distinctive characteristics of optical soliton solutions, enhancing our comprehension of soliton dynamics in diverse optical systems. Employing the potent Sardar-subequation analytical method, we construct a variety of wave structures, revealing a spectrum of optical soliton solutions that span trigonometric and hyperbolic functions. Thorough validation with Mathematica software ensures precision and dynamic visual representations depict soliton solutions that exhibit diverse patterns. These patterns include bright solitons, dark solitons, singular solitons, king solutions, bell-shaped patterns, as well as parabolic-shaped and hyperbolic-shaped patterns. These solutions hold significance in the realms of optical fiber and wave dynamics within various optical systems. Our approach above demonstrates versatility and applicability in solving a wide range of mathematical and physical problems, indicating its usefulness in generating such optical solutions. [ABSTRACT FROM AUTHOR]

To validate safety-related automotive software systems, experimental tests are conducted at different stages of the V-model, which are referred as "X-in-the-loop (XIL) methods". However, these methods have significant drawbacks in terms of cost, time, effort and effectiveness. In this study, based on hardware-in-the-loop (HIL) simulation and real-time fault injection (FI), a novel testing framework has been developed to validate system performance under critical abnormal situations during the development process. The developed framework provides an approach for the real-time analysis of system behavior under single and simultaneous sensor/actuator-related faults during virtual test drives without modeling effort for fault mode simulations. Unlike traditional methods, the faults are injected programmatically and the system architecture is ensured without modification to meet the real-time constraints. Moreover, a virtual environment is modeled with various environmental conditions, such as weather, traffic and roads. The validation results demonstrate the effectiveness of the proposed framework in a variety of driving scenarios. The evaluation results demonstrate that the system behavior via HIL simulation has a high accuracy compared to the non-real-time simulation method with an average relative error of 2.52. The comparative study with the state-of-the-art methods indicates that the proposed approach exhibits superior accuracy and capability. This, in turn, provides a safe, reliable and realistic environment for the real-time validation of complex automotive systems at a low cost, with minimal time and effort. [ABSTRACT FROM AUTHOR]

Simple Summary: Simple Summary: The global demand for livestock products is increasing, and to meet this demand there is a need for more research efforts to increase livestock production. Despite varieties of simulation models developed and used in the beef production sector, an overview of available research is lacking. A systematic literature review was conducted to provide an overview of available beef production simulation modelling research and to describe simulation approaches used for livestock management. A growing research interest in simulating beef production systems was noted, with the main characteristics of the studies being biophysical and bioeconomic study types, deterministic and dynamic simulation approaches, whole-farm scenarios, and a focus area of productivity and economy. We recognized the need for improving the availability of information related to model validation techniques and type of software or programming languages used, which could facilitate the further research extension and/or adoption of simulation modelling studies in livestock management. Simulation models are used in various areas of agriculture to better understand the system and assist in decision making. In the beef production sector, a variety of simulation research focusing on various dimensions of the system is available. However, an overview of the available research is lacking. Therefore, a systematic review was conducted to provide an overview of simulation studies of beef production and create an understanding of the simulation approaches used. Scopus, Web of Science, and ProQuest Central research databases were used to search the relevant articles, with the last search conducted in June 2023. Studies that developed or used simulation strategies and used beef cattle as a primary focus of the study were included. The 105 studies included in this review were examined thoroughly to record the authors, year of publication, country of study, type of study, focus area of the study, simulated scenarios, validation methods, and software programs used. There has been growing research interest in simulating beef production systems worldwide, with most studies conducted in North America and Europe. Among these studies, the majority (84.76%, n = 89) are biophysical or bioeconomic study types and use deterministic approaches (n = 42). Additionally, most studies have a whole-farm scope (38.09%, n = 40) and focus on productivity (51.43%, n = 54). Since only less than half of the studies mentioned the validation techniques and software programs used, there is a need to improve the availability of this information to ensure that the models are adopted effectively in decision making. [ABSTRACT FROM AUTHOR]

Computer methods in biomechanics are computer methods for solving biomechanics problems. Rula, Reba, Niosh, Owas is a method of analyzing work risks due to incorrect posture. Each method uses a worksheet on one posture to analyze risk. For dynamic work, a computer method is needed that can quickly calculate every change in posture. Virtual reality and Kinect as dynamic work analysis methods cannot be carried out preventively. Preventive measures are needed to prevent workers from risks resulting from work. For this reason, computer simulation methods are needed to create work stations and work processes so that they can be carried out preventively. The s-task simulation builder (S-TSB) framework provides a dynamic work analysis solution using simulation. The three processes carried out include surveying, creating simulations and processing posture data. Software validation was tested using the black box analysis method and the results were as expected. The dynamic working model is tested showing results in the form of graphs so it is easy to compare each change. The use of simulation also saves design costs because optimization can simply be done by changing the simulated work station data and/or work process. [ABSTRACT FROM AUTHOR]

Cooperative software validation aims at having verification and/or testing tools cooperate on the task of correctness checking. Cooperation involves the exchange of information about currently achieved results in the form of (verification) artifacts. These artifacts are typically specialized to the type of analysis performed by the tool, e.g., bounded model checking, abstract interpretation or symbolic execution, and hence require the definition of a new artifact for every new cooperation to be built. In this article, we introduce a unified artifact (called Generalized Information Exchange Automaton, short GIA) supporting the cooperation of over-approximating with under-approximating analyses. It provides information gathered by an analysis to its partner in a cooperation, independent of the type of analysis and usage context within software validation. We provide a formal definition of this artifact in the form of an automaton together with two operators on GIAs. The first operation reduces a program by excluding these parts, where the information that they are already processed is encoded in the GIA. The second operation combines partial results from two GIAs into a single on. We show that computed analysis results are never lost when connecting tools via these operations. To experimentally demonstrate the feasibility, we have implemented two such cooperation: one for verification and one for testing. The obtained results show the feasibility of our novel artifact in different contexts of cooperative software validation, in particular how the new artifact is able to overcome some drawbacks of existing artifacts. [ABSTRACT FROM AUTHOR]

Software process simulation models (SPSMs) that are based on descriptive process models offer the executability that can demonstrate dynamic changes of software processes over time. Verification and validation (V&V) is critical in SPSMs for guaranteeing the quality and reliability of models. V&V of dynamic software process models is more complex and challenging than for static software process models. This work systematically summarizes and maps V&V studies in SPSM to provide guidelines for future research and practice. Specifically, this study aims at identifying the focus of research on V&V, the methods used for V&V, and how to implement V&V of SPSMs in software engineering research. We conducted a systematic mapping study on studies of SPSMs that report on their V&V activities. Under the guidance of a V&V meta‐model for SPSMs, we study four research questions about V&V process. We identified 107 primary studies from a pool of 313 papers on SPSMs until 2021. There are two main results of our study. The first one presents the relationship between quality aspects of SPSMs and the V&V methods to assure them. The second result reveals the relationships among the modeling process, three modeling steps, five quality aspects, and 10 V&V methods. Generally, researchers do not pay sufficient attention to V&V, as 65.8% ((313−107)/313) failed to mention or elaborate on their V&V process. We systematically summarize and map the state‐of‐the‐art V&V research in software process modeling field to support modelers' practice and improve their V&V process. [ABSTRACT FROM AUTHOR]

Globally, the quantity of road accidents is steadily decreasing annually. Even if the epidemic has recently had an effect, this number is still quite high. Therefore, every attempt should be made to reduce this number. The purpose of this article is to forecast the number of accidents that will transpire on various kinds of roads in Poland. For this purpose, monthly data on the total number of traffic accidents in Poland broken down by type of road were examined. Based on police data, a forecast was created for the years 2022--2040. A few neural network models were used to predict the frequency of accidents in Poland. The results show that we should keep expecting a high degree of stability in terms of the quantity of traffic accidents. On the one hand, the construction of new highways and the increase in the number of cars on Polish roads have an effect on this. The number of random samples utilized in the processes of learning, testing, and validation affects the results. In the case of 70-15-15, the average projected number of accidents for 2022-2024 should be: motorway - 827, expressway - 1136, 2 one-way carriageway - 5451, single carriageway -3067 and 1 carriageway 2 directions - 28048, respectively. For 80-10-10, these values should be respectively: motorway - 1057, expressway - 1141, 2 one-way carriageway - 5486, single carriageway -2745 and 1 carriageway 2 directions - 28039. As you can see, the values are similar. [ABSTRACT FROM AUTHOR]

Urban greenery is a strategy to improve the thermal environment in urban areas affected by heat islands and global warming. These phenomena can harm the citizens' quality of life. Researchers have investigated the thermal benefits of urban vegetation, but only a few have explored its complexities across diverse urban scales. Understanding these variations is critical for precise analysis, customized solutions, efficient resource allocation, and enhancing urban living quality while promoting sustainability and climate resilience. This paper reviews 250 scientific articles about the relationship between greenspace and the urban thermal environment published between 2010 and 2023 through urban scales. It summarizes the parameters and findings of greenery's contribution to cooling the urban environment. The data reveal that most studies concentrated on the block scale, public open spaces, neighborhoods, parks, grouped vegetation, mixed arrangements, high vegetation, spatial parameters, and the use of air temperature data to report their findings. The cooling-effect evidence shows that the block scale has an average mitigation range of 0.7–2.7 °C, the neighborhood scale of 1.1–2.9 °C, and the city scale of 0.5–2.2 °C. Furthermore, it is critical to define reliable research methods and perform thorough software validation to assess model performance and establish guidelines for urban-landscape design accurately. [ABSTRACT FROM AUTHOR]

In recent years, open-source software (OSS) has attracted increasing attention due to its easy accessibility via cloud repositories, voluntary community, no vendor lock-in, and low total cost of ownership. In turn, specifying and evaluating OSS quality has become a significant challenge for OSS adoption in organizations that are inclined to use them. Although many OSS quality models have been proposed in the literature, the dynamic and diverse nature of OSS has caused these models to be heterogeneous in terms of structure and content. This has adversely affected the standardization of evaluations and led to the evaluation results obtained from different OSS quality models for the same purpose being incomparable and sometimes unreliable. Therefore, in this study, a meta-model for OSS quality (OSS-QMM), which employs a unified structure from existing quality models and enables the derivation of homogeneous models, has been proposed. For this purpose, a systematic and laborious effort has been spent via a step-based meta-model creation process including review-and-revise iterations. In order to validate the OSS-QMM, case study and expert opinion methods have been applied to answer three research questions (RQs) targeted to investigate practical applicability, results comparability, and effectiveness of using the meta-model. Multiple and embedded case study designs have been employed for evaluating three real ERP systems, and 20 subject matter experts have been interviewed during the validation process. The results of multi-faceted empirical studies have indicated that the OSS-QMM has addressed solving problems in OSS quality evaluation and its adoption with high degrees of confidence. [ABSTRACT FROM AUTHOR]

Background: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR). Methods: Individuals were selected from the "Lifelines" cohort who had undergone low-dose chest CT. Nodules in individuals without emphysema were matched to similar-sized nodules in individuals with at least moderate emphysema. AI results for nodular findings of 30–100 mm3 and 101–300 mm3 were compared to those of HR; two expert radiologists blindly reviewed discrepancies. Sensitivity and false positives (FPs)/scan were compared for emphysema and non-emphysema groups. Results: Thirty-nine participants with and 82 without emphysema were included (n = 121, aged 61 ± 8 years (mean ± standard deviation), 58/121 males (47.9%)). AI and HR detected 196 and 206 nodular findings, respectively, yielding 109 concordant nodules and 184 discrepancies, including 118 true nodules. For AI, sensitivity was 0.68 (95% confidence interval 0.57–0.77) in emphysema versus 0.71 (0.62–0.78) in non-emphysema, with FPs/scan 0.51 and 0.22, respectively (p = 0.028). For HR, sensitivity was 0.76 (0.65–0.84) and 0.80 (0.72–0.86), with FPs/scan of 0.15 and 0.27 (p = 0.230). Overall sensitivity was slightly higher for HR than for AI, but this difference disappeared after the exclusion of benign lymph nodes. FPs/scan were higher for AI in emphysema than in non-emphysema (p = 0.028), while FPs/scan for HR were higher than AI for 30–100 mm3 nodules in non-emphysema (p = 0.009). Conclusions: AI resulted in more FPs/scan in emphysema compared to non-emphysema, a difference not observed for HR. Relevance statement: In the creation of a benchmark dataset to validate AI software for lung nodule detection, the inclusion of emphysema cases is important due to the additional number of FPs. Key points: • The sensitivity of nodule detection by AI was similar in emphysema and non-emphysema. • AI had more FPs/scan in emphysema compared to non-emphysema. • Sensitivity and FPs/scan by the human reader were comparable for emphysema and non-emphysema. • Emphysema and non-emphysema representation in benchmark dataset is important for validating AI. [ABSTRACT FROM AUTHOR]

Digital reconstruction has been instrumental in deciphering how in vitro neuron architecture shapes information flow. Emerging approaches reconstruct neural systems as networks with the aim of understanding their organization through graph theory. Computational tools dedicated to this objective build models of nodes and edges based on key cellular features such as somata, axons, and dendrites. Fully automatic implementations of these tools are readily available, but they may also be purpose-built from specialized algorithms in the form of multi-step pipelines. Here we review software tools informing the construction of network models, spanning from noise reduction and segmentation to full network reconstruction. The scope and core specifications of each tool are explicitly defined to assist bench scientists in selecting the most suitable option for their microscopy dataset. Existing tools provide a foundation for complete network reconstruction, however more progress is needed in establishing morphological bases for directed/weighted connectivity and in software validation. A review of computational tools for mapping networks from in vitro neuron morphology, facilitating topological analysis of cell organization. [ABSTRACT FROM AUTHOR]

The operation of marine vessels with high efficiency provides a great contribution within the scope of the International Maritime Organization and the sustainable development goals. In terms of the propulsion system, selecting the appropriate propeller is critical to effectively use the engine power installed in marine vessels because the biggest energy losses during transmission occur on the propeller and ship hull. Increasing propeller efficiencies above a certain level is quite a challenge by simply changing the number of blades, pitch, or propeller type. Therefore, various energy-saving device applications, such as propeller boss cap fins (PBCFs), are performed on the ship propeller. The effects of National Advisory Committee for Aeronautics 4415 profile PBCFs which have a different position and pitch angle integrated into the E698 model propeller have been investigated to describe efficiency, vortex, and pressure distributions based on the KRISO very large crude carrier 2 designed hull in this study. The E698 model propeller has been created by the 3D software and the validation has been performed by the computational fluid dynamic solver software based on the reference values of the propeller. The effect of four PBCF applications which have different pitches and positions on the model propeller has been revealed in terms of the efficiency, pressure distributions, and vortexes. Although P45-R45 and P45-R90 PBCF applications are quite close to the E698 propeller in terms of efficiency, no significant efficiency increase has been observed. In addition, the efficiency has decreased considerably in P90-R45 and P90-R90 applications. PBCFs application with P45-R90 has provided superiority to the base model in terms of pressure distributions and vortex formation. However, any improvement has not been achieved in the remaining three designs. Therefore, PBCF applications should be applied quite elaborately based on propeller types. [ABSTRACT FROM AUTHOR]

Partial shading within arrays diminishes power output, induces hotspots, and compromises module integrity, thereby impacting system performance. The presence of bypass diodes further exacerbates these issues by introducing non‐convexities in power curves, leading to additional power losses. To solve this problem, a new reconfiguration technique named Fibonacci Random Number Generator is proposed in this work which minimizes the effects of shading on the panels. The proposed methodology swiftly reduces current discrepancies between PV array rows by reshuffles the panels in an array to disperse the shade better using a mathematical formula resulting in increased power output and smoother power curves during partial shading events. The effectiveness of the proposed method is measured in terms of GMPP, row current calculations, power loss (PL), mismatch losses (ML), execution ratio (ER), fill factor (FF), and capacity factor (CF) for four distinctive shading conditions. Validation of results in software and hardware platforms showcase the applicability of proposed approach in real‐time environments. Results indicate significant average power improvements of 25.49%, 15.47%, and 9.29% compared to existing popular reconfigurations like Skyscraper, Ken‐Ken, and Chaotic baker map. The proposed method stands out as a potent tool for optimizing PV arrays within real‐world systems grappling with partial shading issues. [ABSTRACT FROM AUTHOR]

The article discusses the use of traction-assisted endoscopic submucosal dissection (ESD) for managing complex colonic lesions in patients with diverticulosis. ESD is a minimally invasive technique that allows for en bloc resection of premalignant lesions in the sigmoid colon, despite technical challenges and increased risk of perforation. The case study presented in the article demonstrates the efficacy of ESD in treating colorectal lesions, emphasizing the importance of comprehensive lesion removal and the use of innovative tools like the DiLumen single balloon platform. The authors highlight the successful resection of a tubular adenoma in a 74-year-old patient, showcasing the potential of ESD in minimizing the need for invasive surgery and ensuring optimal patient outcomes. [Extracted from the article]

Many object‐oriented metrics have been proposed in the literature to measure various structural properties of object‐oriented software. Furthermore, many centrality measures have been introduced to identify central nodes in large networks. However, few studies have used them to measure dependencies in software systems. In fact, centrality measures, as opposed to most traditional object‐oriented metrics that mainly focus on intrinsic properties of classes, can be used to better model the control flow and to identify the most important classes in a software system. This paper aims (1) to investigate the relationships between object‐oriented metrics and centrality measures and (2) to explore the ability of their combination to support fault‐proneness prediction from different perspectives (fault‐prone classes, fault severity, and number of faults). Many studies in the literature have addressed the prediction of fault‐prone classes, from different perspectives, using object‐oriented metrics. The main motivation here is in fact to investigate if the information captured by centrality measures is related to fault proneness and complementary to the information captured by object‐oriented metrics and to investigate if the combination of object‐oriented metrics and centrality measures improves the performance of fault‐proneness prediction significantly. We used size, complexity, and coupling object‐oriented metrics in addition to various centrality measures. We collected data from 20 different versions of five open‐source Java software systems. We first studied the relationships between selected metrics and their relationships to fault proneness. Then, we built different models to predict fault‐prone classes using several machine learning algorithms. In addition, we built models to predict if a class contains a high severity fault, and the number of faults in a class. Results indicate that using centrality measures in combination with object‐oriented metrics improves the prediction of fault‐prone classes as well as the prediction of the number of faults in a class. However, the combination has no significant impact, according to the data we collected, on the quality of the prediction of fault severity. Moreover, using centrality measures in combination with object‐oriented metrics also improves the prediction performance of fault proneness and the number of faults in both cross‐version and cross‐system validation. [ABSTRACT FROM AUTHOR]

The pervasive presence of IoT sensing devices combined with advances in cloud-based services has made historical- and forecast weather data services widely available for use in smart software systems. The contribution of this paper is the design, performance evaluation, and validation of a software implementation of model-based dynamic fire risk prediction for wooden homes using local weather data. A key feature of the implementation is that the software architecture has been designed to support the use of different underlying cloud-based weather data services, and the integration as a service in third-party smart systems embedding fire risk predictions. The performed evaluation shows that the implementation is efficient, as weather data can be retrieved, preprocessed and fire risk predictions computed within seconds using only in the order of Kb's of memory; and accurate considering our sets of data, as the fire risks computed by the implementation have been validated against a set of in-situ measurements. [ABSTRACT FROM AUTHOR]

Hydrocortisone is a glucocorticoid-type hormone produced naturally by the organism, such that it maintains the body functional during physical or mental stress episodes. The present work focuses on the UV-Vis spectrophotometric assessment of the chemical stability of hydrocortisone in an aqueous medium during the time of analysis, determination of its acidity constants through a robust methodology that involves the usage of SQUAD software and validation of an analytical method to determine hydrocortisone by means of UV-Vis spectrophotometry, in pharmaceuticals. The acidity constant was determined as pKa 11.45 ± 0.02 (298 K), and the molar absorptivity coefficients and the molar absorptivity coefficients of the species involved in this acidity equilibrium were also determined as a function of the wavelength. The analytical method developed attained detection and quantification limits of 386 ± 3 and 1280 ± 10 nM, respectively, whereas the validation allows reliable quantification of hydrocortisone in pharmaceuticals. [ABSTRACT FROM AUTHOR]

Before the COVID-19 pandemic, ventilation in buildings was not always given its due importance. The World Health Organization has highlighted the important role of air exchange with the outdoors in improving the air quality in buildings; buildings should, therefore, be equipped with mechanical ventilation or adequate air conditioning systems. This paper aims to investigate different retrofit solutions for air conditioning, evaluating them in terms of energy consumption and cost and the impact of increased outdoor air exchange rates on countering the propagation of COVID-19; the latter is the main novelty of the paper. As a case study, we take an existing office building located in Central Italy that was previously not equipped with a mechanical ventilation system (a system with primary air was introduced during the study). The energy analysis was conducted using dynamic simulation software after validation through energy bills; energy and economic analyses were conducted considering different external-air exchange rates. An optimal number of outdoor air changes was found to mitigate the risk of COVID-19 infection, a finding in line with the international literature. The increase in air changes with outdoor air leads to a rise in energy consumption and costs. These values were evaluated for different air conditioning systems and operational schedules. These drawbacks can be made less significant by combining interventions in the system with energy-efficiency measures applied to the building envelope. [ABSTRACT FROM AUTHOR]

Background: To describe the implementation of a registry system for patients with thyroid eye disease (TED) in Iran to obtain more information about its nature, prevalence, and annual incidence, as well as extend insight into the etiology, pathogenesis, and eventually make an accurate prognosis of different medical or surgical treatment methods. Methods: After receiving approval from the Disease Registry Committee of Iran University of Medical Sciences (IUMS) in 2019 and the Ministry of Health and Medical Education (MOHME) in 2020, the protocol was introduced in three consecutive phases at regional, provincial and national levels. The establishment of a registry committee in Rassoul Akram Hospital, one of the medical centers affiliated to IUMS, was the first step to organizing the registry project's main core. The steering committee included six subgroups of required subject fields. The members are experts in developing a guideline, providing a new dataset, drawing an outline for the next steps, and structuring user-friendly software through several panel discussion meetings. The data is collected from clinical and para-clinical/imaging findings, laboratory evaluations, and their selected treatment strategy, retrospectively and prospectively. Results: The purpose is to broaden our knowledge about the profile of TED; accordingly, data related to patients' demographics, thyroid gland disease (status, duration, treatments, and function tests), general medical and ocular history, along with visual/ocular exams resulting TED status are collected and recorded in a 2- language software. The web-based software system is accessible at https://orc.iums.ac.ir. To maintain data security, prioritized user access was defined for different members. Furthermore, diverse methods, such as employing trained staff and utilizing software validation rules, were implemented to control data quality in every step of data collection, entry, and registration. Medical records of retrospective subjects were also evaluated and entered after accuracy verification. Conclusion: Iran's TED registry provides practitioners with comprehensive data on natural history and phenotype variations in clinical features and outcomes. It facilitates patient recruitment and, consequently, earlier diagnosis on a large scale which helps improve treatment and quality of life for patients. [ABSTRACT FROM AUTHOR]

Heuristic evaluation provides usability auditors with a structured flow of activities that enables them to obtain reliable, comparable and cost-effective usability evaluation results. Tools supporting heuristic evaluation are scarce in literature. Usevalia is an Internet-based tool that manages usability audits on the basis of heuristic evaluation. This article presents the main features of Usevalia, together with a validation of the software by following the Technology Acceptance Model, which verified the users' perceptions of Usevalia as regards usefulness, ease of use, attitude and intention to use. A total of 22 students enrolled on a human–computer interaction course were involved in the validation. According to the results of the survey conducted with them, the proposed tool is easy to use (MD = 4.00 out of 5) and useful for conducting usability audits based on heuristic evaluation (MD = 4.00 out of 5). An expert-based validation was also carried out in order to thoroughly compare Usevalia's features with those of a spreadsheet-based tool that performs usability audits in the traditional manner. This comparative analysis made it possible to conclude that the Usevalia tool has a higher perceived usefulness (M = 4.43) and perceived ease of use (M = 4.13) than a traditional audit tool, such as the Usability Datalogger spreadsheet (M = 2.43 and M = 3.03, respectively). [ABSTRACT FROM AUTHOR]

Object Constraint Language (OCL) is one kind of lightweight formal specification, which is widely used for software verification and validation in NASA and Object Management Group projects. Although OCL provides a simple expressive syntax, it is hard for the developers to write correctly due to lacking knowledge of the mathematical foundations of the first‐order logic, which is approximately half accurate at the first stage of development. A deep neural network named DeepOCL is proposed, which takes the unrestricted natural language as inputs and automatically outputs the best‐scored OCL candidates without requiring a domain conceptual model that is compulsively required in existing rule‐based generation approaches. To demonstrate the validity of our proposed approach, ablation experiments were conducted on a new sentence‐aligned dataset named OCLPairs. The experiments show that the proposed DeepOCL can achieve state of the art for OCL statement generation, scored 74.30 on BLEU, and greatly outperformed experienced developers by 35.19%. The proposed approach is the first deep learning approach to generate the OCL expression from the natural language. It can be further developed as a CASE tool for the software industry. [ABSTRACT FROM AUTHOR]

Objective: To systematically evaluate the ability of the CINA® LVO software to detect large vessel occlusions eligible for mechanical thrombectomy on CTA using conventional neuroradiological assessment as gold standard. Methods: Retrospectively, two hundred consecutive patients referred for a brain CTA and two hundred patients that had been subject for endovascular thrombectomy, with an accessible preceding CTA, were assessed for large vessel occlusions (LVO) using the CINA® LVO software. The patients were sub-grouped by occlusion site. The original radiology report was used as ground truth and cases with disagreement were reassessed. Two-by-two tables were created and measures for LVO detection were calculated. Results: A total of four-hundred patients were included; 221 LVOs were present in 215 patients (54 %). The overall specificity was high for LVOs in the anterior circulation (93 %). The overall sensitivity for LVOs in the anterior circulation was 54 % with the highest sensitivity for the M1 segment of the middle cerebral artery (87 %) and T-type internal carotid occlusions (84 %). The sensitivity was low for occlusions in the M2 segment of the middle cerebral artery (13 % and 0 % for proximal and distal M2 occlusions respectively) and in posterior circulation occlusions (0 %, not included in the intended use of the software). Conclusions: LVO detection sensitivity for the CINA® LVO software differs largely depending on the location of the occlusion, with low sensitivity for detection of some LVOs potentially eligible for mechanical thrombectomy. Further development of the software to increase sensitivity to all LVO locations would increase the clinical usefulness.

This article discusses a case of allergic cheilitis caused by stannous fluoride-containing toothpaste, which is the first reported case in Italy. The patient experienced lip swelling, blisters, itching, and redness, which improved with corticosteroids and antihistamines but returned when treatment was stopped. Patch tests confirmed a positive reaction to stannous oxalate, and the toothpaste used by the patient was found to contain stannous fluoride. After switching to a toothpaste without stannous fluoride, the symptoms resolved. The article also provides a mini-review of previously published cases of allergic contact cheilitis caused by stannous-containing toothpaste. [Extracted from the article]

Recently, a data-driven approach has been widely used at various stages of the system development lifecycle thanks to its ability to extract knowledge from historical data. However, despite its superiority over other conventional approaches, e.g., approaches that are model-based and signal-based, the availability of representative datasets poses a major challenge. Therefore, for various engineering applications, new solutions to generate representative faulty data that reflect the real world operating conditions should be explored. In this study, a novel approach based on a hardware-in-the-loop (HIL) simulation and automated real-time fault injection (FI) method is proposed to generate, analyse and collect data samples in the presence of single and concurrent faults. The generated dataset is employed for the development of machine learning (ML)-assisted test strategies during the system verification and validation phases of the V-cycle development model. The developed framework can generate not only time series data but also a textual data including fault logs in an automated manner. As a case study, a high-fidelity simulation model of a gasoline engine system with a dynamic entire vehicle model is utilised to demonstrate the capabilities and benefits of the proposed framework. The results reveal the applicability of the proposed framework in simulating and capturing the system behaviour in the presence of faults occurring within the system's components. Furthermore, the effectiveness of the proposed framework in analysing system behaviour and acquiring data during the validation phase of real-time systems under realistic operating conditions has been demonstrated. [ABSTRACT FROM AUTHOR]

Introduction and hypothesis: Transperineal ultrasound (TPUS) is an effective tool for evaluating the integrity of the levator ani muscle (LAM). Several operating steps are required to obtain the standard multi-slice image of the LAM, which is experience dependent and time consuming. This study was aimed at evaluating the feasibility and reproducibility of the built-in software, Smart-pelvic™, in reconstructing standard tomographic images of LAM from 3D/4D TPUS volumes. Methods: This study was conducted at a tertiary teaching hospital, enrolling women who underwent TPUS. Tomographic images of the LAM were automatically reconstructed by Smart-pelvicTM and rated by two experienced observers as standard or nonstandard. The anteroposterior diameter (APD) of the levator hiatus was also measured on the mid-sagittal plane of the automatically and manually reconstructed images. The APD measurements of each approach were compared using Bland–Altman plots, and interclass correlation coefficient (ICC) was used to evaluate intra- and inter-observer reproducibility. Meanwhile, the time taken for the reconstruction process of both methods was also recorded. Results: The ultrasound volume of a total of 104 patients were included in this study. Using Smart-pelvicTM, the overall success rate of the tomographic image reconstruction was 98%. Regarding measurements of APD, the ICC between the automatic and manual reconstruction methods was 0.99 (0.98, 0.99). The average time taken for reconstruction per case was 2.65 ± 0.52 s and 22.08 ± 3.45 s, respectively. Conclusions: Using Smart-pelvicTM to reconstruct tomographic images of LAM is feasible, and it can promote TPUS by reducing operator dependence and improving examination efficiency in a clinical setting. [ABSTRACT FROM AUTHOR]

The combine harvester, a versatile machine for harvesting various crops, has evolved to address specific challenges. In India, wheel-type harvesters were once common but struggled in muddy conditions, leading to the rise of track-type harvesters with better traction and maneuverability. However, these new machines faced breakdowns on uneven terrain, disrupting harvest schedules and causing financial losses. To tackle this, a solution was proposed: an adjustable chassis for track-type harvesters. This innovative design aimed to lift and level the chassis, enhancing stability and performance. Four hydraulic cylinders were installed between the chassis frame and walking device to achieve this. Mathematical models were developed to guide the mechanism's design, ensuring optimal height and transverse tilt adjustments. Hydraulic components were carefully selected based on force calculations, with a MATLAB Simulink circuit designed for performance analysis. A virtual model of the adjustable chassis was created using CATIA software and imported into ADAMS simulation software to assess its attitude. Numerical validation in ANSYS software confirmed the design's safety and feasibility. The height adjustment range was 0-245 mm, and the transverse tilt adjustment range was 0 ± 15.2° for a piston extension length of 0-100 mm. During simulation, the maximum pressure exerted by the pump was 100 bar, with hydraulic cylinders exerting a maximum force of 43.2 kN over 40 s. ADAMS simulation revealed maximum height adjustment and transverse tilt of 243 mm and 15.2°, respectively, under specific driving parameters. The designed lifting chassis exhibited a maximum displacement of 2.7 mm and a maximum stress of 394 MPa, with a safety factor of 1.94, indicating suitability for real-world applications. This solution promises to improve the efficiency and reliability of track-type combine harvesters, mitigating breakdowns and optimizing harvest operations. [ABSTRACT FROM AUTHOR]

Significantly shorter software development and deployment cycles have been made possible by the adoption of continuous software engineering techniques in business operations, such as DevOps (Development and Operations). Data scientists and operations teams have recently become more and more interested in a practice known as MLO (Machine Learning Operations). However, MLO adoption in practice is still in its early stages, and there aren't many established best practices for integrating it into current software development methods. In order to give a frame that outlines the way necessary in espousing MLO and the stages through which business capes process as they come riper and sophisticated, we achieve a methodical literature study as well as a slate review of literature in this composition. We test this approach in three example businesses and demonstrate how they were able to embrace and incorporate MLO into their massive software development businesses. This study offers three contributions. To give an overview of the state of the art in MLO, we first examine recent publications. Based on this analysis, we create an MLO framework that outlines the steps taken in the ongoing creation of machine learning models. Second, we define the several stages that businesses go through as they develop their MLO practices in a maturity model. Third, we map the firms to the maturity model phases and test our methodology using three embedded systems case companies. The main objective is to create an MLO framework. [ABSTRACT FROM AUTHOR]

Research in science education has recognized the importance of pedagogical content knowledge (PCK) and its relationship to practical work. Although efforts have been made to characterize this relationship accurately, research in this field still needs to be completed. This article shows an instrument's design and validation process that aims to determine the perception of PCK elements and their incidence in the design, implementation, and evaluation of practical work in science teachers. The questionnaire was subjected to content validation by a panel of experts and a pilot study to evaluate its internal consistency through Cronbach's alpha. The construction and validation yielded an instrument of 30 items grouped into five categories: orientations toward science teaching, knowledge of the curriculum, knowledge of assessment, knowledge of students' understanding of science, and knowledge of instructional strategies. Reliability yielded a Cronbach's alpha value of 0.881, showing the development of a consistent and reliable instrument. [ABSTRACT FROM AUTHOR]

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Reports of Rhipicephalus microplus resistant populations worldwide have increased extensively, making it difficult to control this ectoparasite. The adult immersion test, commonly used to screen for acaricide resistance, produces the results only after 40 days of the tick collection because it needs the eggs to be laid and larvae to hatch. The present study aims to develop an automatic method, based on deep learning, to predict the hatching of R. microplus larva based on egg morphology. Initially, the time course of embryonic development of tick eggs was performed to discriminate between viable and non‐viable eggs. Secondly, using artificial intelligence deep learning techniques, a method was developed to classify and count the eggs. The larval hatching rate of three populations of R. microplus was evaluated for the software validation process. Groups of three and six images of eggs with 12 days of embryonic development were submitted to the software to predict the larval hatching percent automatically. The results obtained by the software were compared with the prediction results of the hatching percentage performed manually by the specialist and with the results of the hatching percentage of larvae obtained in the biological assay. The group with three images of each population submitted to the software for automatic prediction of the larval hatching percent presented mean values of 96.35% ± 3.33 (Piracanjuba population), 95.98% ± 3.5 (Desterro population) and 0.0% ± 0.0 (Barbalha population). For groups with six images, the values were 94.41% ± 3.84 (Piracanjuba population), 95.93% ± 2.36 (Desterro population) and 0.0% ± 0.0 (Barbalha population). Biological assays showed the following hatching percentage values: 98% ± 1.73 (Piracanjuba population); 96% ± 2.1 (Desterro population); and 0.14% ± 0.25 (Barbalha population). There was no statistical difference between the evaluated methods. The automatic method for predicting the hatching percentage of R. microplus larvae was validated and proved to be effective, with considerable reduction in time to obtain results. [ABSTRACT FROM AUTHOR]

The evaluation of human exposure to electric and magnetic fields represents a subject of great scientific and public interest due to the biological effects of electromagnetic fields (EMFs) on the human body and the risks caused by them to living organisms. In this context, this article proposes a software program designed by the authors for the evaluation of human exposure to electric and magnetic fields at low frequencies (EMF software program), an application that can also be accessed from a mobile phone. The analytical model on which the EMF program is based is synthetically presented, and the application is then described. The first example implemented in the EMF program is taken from the existing literature on this subject, thus confirming the correctness and calculation precision of the program. Next, a case study is proposed for an overhead transmission line of 400 KV from the Cluj-Napoca area, Romania, for which the electric and magnetic fields are first measured experimentally and then using the EMF program. The validation of the EMF software program is performed by comparing the obtained results with those measured experimentally and with those obtained with a commercial software program. [ABSTRACT FROM AUTHOR]

Background: Spirometry services to diagnose and monitor lung disease in primary care were identified as a priority in the NHS Long Term Plan, and are restarting post-COVID-19 pandemic in England; however, evidence regarding best practice is limited. Aim: To explore perspectives on spirometry provision in primary care, and the potential for artificial intelligence (AI) decision support software to aid quality and interpretation. Design and setting: Semi-structured interviews with stakeholders in spirometry services across England. Method: Participants were recruited by snowball sampling. Interviews explored the pre- pandemic delivery of spirometry, restarting of services, and perceptions of the role of AI. Transcripts were analysed thematically. Results: In total, 28 participants (mean years' clinical experience = 21.6 [standard deviation 9.4, range 3–40]) were interviewed between April and June 2022. Participants included clinicians (n = 25) and commissioners (n = 3); eight held regional and/or national respiratory network advisory roles. Four themes were identified: 1) historical challenges in provision of spirometry services; 2) inequity in post- pandemic spirometry provision and challenges to restarting spirometry in primary care; 3) future delivery closer to patients' homes by appropriately trained staff; and 4) the potential for AI to have supportive roles in spirometry. Conclusion: Stakeholders highlighted historic challenges and the damaging effects of the pandemic contributing to inequity in provision of spirometry, which must be addressed. Overall, stakeholders were positive about the potential of AI to support clinicians in quality assessment and interpretation of spirometry. However, it was evident that validation of the software must be sufficiently robust for clinicians and healthcare commissioners to have trust in the process. [ABSTRACT FROM AUTHOR]

SAM-II is a computer program for seismic nonlinear static (pushover) analysis on new and existing unreinforced (URM), reinforced (RM) masonry and mixed masonry-reinforced concrete (RC) buildings, based on an equivalent frame (EF) modelling approach. The SAM program was originally proposed in the mid-1990s by Magenes and Della Fontana in Proceedings of the British Masonry Society, 1998) and Magenes (in Proceedings of the 12th World Conference in Earthquake Engineering, Auckland, 2000) and was initially conceived for the sole analysis of URM buildings. From the mid-2000s it was completely rewritten in a new code, named SAM-II, and substantially improved. The new program, in fact, also allows for the analysis of RM buildings and mixed RC-masonry structures, the management of semi-rigid floor/roof diaphragms, and the use of new shear strength criteria for masonry elements. The idealization criterion of the adopted EF model and the constitutive laws and strength criteria of the implemented structural elements are presented, focusing on the features of the program implemented in the last 15 years. Some cases of validation of the software, among the most relevant, are presented and discussed. The obtained results confirm that EF models such as SAM-II can be in many cases effective and reliable calculation tools for seismic pushover analyses of masonry buildings, provided the geometry of the building is sufficiently regular in plan and elevation to allow for the EF idealization to simulate its seismic behaviour. [ABSTRACT FROM AUTHOR]

Introduction: Tinnitus is one of the most common complaints, distressing about 15–24% of the adult population. Because of its pathophysiology heterogeneity, no curable treatment has been attained yet. Even though a neuromodulation management technique based on the tinnitus network model is currently being developed, it has not yet worked because the most involved brain areas still remain unpredictable from the patient's individual clinical and functional profile. A remarkable correlation between tinnitus network activity and the subjective measures of tinnitus like perceived loudness and annoyance and functional handicap is well established. Therefore, this study aimed to develop software for predicting the involved brain areas in the tinnitus network based on the subjective characteristics and clinical profile of patients using a supervised machine-learning method. Methods: The involved brain areas of 30 tinnitus patients ranging from 6 to 80 months in duration were recognized by using QEEG and sLORETA software. There was a correlation between subjective information and those areas of activities in all rhythms by which we wrote our software. Results: For verification and validation of the software, we compared and analyzed the results with SPSS data and the receiver operating characteristic (ROC) curves. Conclusions: The findings of this study confirmed the effectiveness of the software in predicting the brain activity in tinnitus subjects; however, some other important parameters can be added to the model to strengthen its reliability and feasibility in clinical use. [ABSTRACT FROM AUTHOR]

Numerous models exist for users to simulate land change to communicate with an audience concerning future land change. This article raises four fundamental questions to help model users decide whether to use any model: (1) Can the user understand the model? (2) Can the audience understand the model? (3) Can the user control the model? (4) Does the model address the goals of the specific application? This article applies these questions to the popular cellular automata–Markov (CA–Markov) model as IDRISI's CA–Markov module expresses. Sensitivity analysis examines 120 ways to set the module's parameters. Verification compares the module's behavior to the software's documentation. Results show that the cellular automata's allocation fails to follow the quantity of change that the Markov module computes. The module's behavior is likely to cause users to misinterpret the validation metrics and to miscommunicate with audiences. Thus, the answers to the four questions were not satisfactory for this article's case study. This article's framework helps users to judge a model's appropriateness for a specific application by combining sensitivity analysis with verification in a manner that helps to interpret validation. Users should answer the four questions as they decide whether to use any software's modules. [ABSTRACT FROM AUTHOR]

Objectives: To validate an ultrasound software that uses transperineal ultrasound to diagnose uterine prolapse (UP). Methods: Multicenter, observational and prospective study with 155 patients that had indications for surgical intervention for dysfunctional pelvic floor pathology. Each patient underwent an examination with Pozzi tenaculum forceps was performed in the operating room with the patient anesthetized, followed by surgical correction of stages II–IV UP. Transperineal ultrasound was used to assess the difference in the pubis–uterine fundus measurement. With a multivariate logistic regression binary model (with the measurement ultrasound at rest, the Valsalva maneuver and age) using nonautomated methods to predict UP. With the purpose of evaluating the model, a table with coordinates of the receiver operating characteristic (ROC) curve, after which sensitivity and specificity were assessed. Results: A total of 153 patients were included (73 with a diagnosis of surgical UP). It was obtained from the AUC (0.89) of the probabilities predicted by the model (95% confidence interval, 0.84–0.95; P <.0005). Based on the ROC curve for the model, obtaining a sensitivity of 91.8% and a specificity of 72.7%, values that were superior to those for the clinical exam for surgical UP (sensitivity: 80.8%; specificity: 71.3%). Conclusions: We validated software that uses transperineal ultrasound of the pelvic floor and patient age to generate a more reliable diagnosis of surgical UP than that obtained from clinical examinations. [ABSTRACT FROM AUTHOR]

The authors of this document respond to previous recommendations regarding the use of fully continuous models (FCMs) in forensic science in Germany. They explain that FCMs are not currently widely implemented due to the expectation that different experts using different models should yield similar results, which is not the case with FCMs. The authors emphasize the importance of calibrating FCM programs and suggest a cautious interpretation of likelihood ratios (LRs) below a certain threshold to avoid overstating the probative value of evidence. They also clarify that their recommendations are adapted to the German legal framework and provide support for their approach from calibration data. [Extracted from the article]