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A stochastic network simulation is verified when its distribution of outputs is aligned with the ground truth, while tolerating deviations due to variability in real-world measurements and the randomness of a stochastic simulation. However, comparing distributions may yield false positives, as erroneous simulations may have the expected distribution yet present aberrations in low-level patterns. For instance, the number of sick individuals may present the right trend over time, but the wrong individuals were infected. We previously proposed an approach that transforms simulation traces into images verified by machine learning algorithms that account for low-level patterns. We demonstrated the viability of this approach when many simulation traces are compared with a large ground truth data set. However, ground truth data are often limited. For example, a publication may include few images of their simulation as illustrations; hence, teams that independently re-implement the model can only compare low-level patterns with few cases. In this paper, we examine whether our approach can be utilized with very small data sets (e.g., 5–10 images), as provided in publications. Depending on the network simulation model (e.g., rumor spread, cascading failure, and disease spread), we show that results obtained with little data can even surpass results obtained with moderate amounts of data at the cost of variability. Although a good accuracy is obtained in detecting several forms of errors, this paper is only a first step in the use of this technique for verification; hence, future works should assess the applicability of our approach to other types of network simulations. [ABSTRACT FROM AUTHOR]

Introduction To improve the feasibility of remote biochemical verification of smoking status, our team developed "COast," a mobile app integrated with REDCap that allows a research participant to complete self-report research assessments and provide a breath sample via the iCOQuit Smokerlyzer for the purposes of carbon monoxide (CO) testing. The aims of the present study were to examine (1) the validity of remote CO data capture using COast as compared to gold-standard approaches (salivary cotinine, stand-alone CO monitor) and (2) the feasibility of remote CO data capture using COast as applied to both daily and weekly CO collection schedules. Methods Participants (N  = 143, 59% Female), including recently quit (n  = 36) and current (n  = 107) smokers, completed a baseline video session to capture validity data, and then were randomized to daily or weekly CO monitoring for a period of 1 month. Results Balancing both sensitivity and specificity, optimal cut-points for defining abstinence using the COast system were <4 parts per million (ppm) with salivary cotinine as the referent (Sensitivity = 100%, Specificity = 92.8%) and <8 ppm with the stand-alone CO monitor as the referent (Sensitivity = 100%, Specificity = 88.9%). Compliance across groups with CO monitoring was high with average compliance of 74% for the daily group and 84% for the weekly group. Self-reported feasibility and acceptability of using the system were strong. Conclusions Pairing the iCOQuit with REDCap via the COast app was both valid and feasible among a sample of adults who smoke cigarettes enrolled remotely. This integration may help to improve the rigor of decentralized smoking cessation trials. Implications With increasing prevalence of decentralized trial designs, innovative methods are needed to remotely capture biomarkers. Methods that leverage existing widely available research data capture platforms may be particularly useful for promoting adoption. The COast app, which integrates a Bluetooth-enabled CO monitor with REDCap, is a fitting, valid, and feasible solution to remotely biochemically verify smoking status. [ABSTRACT FROM AUTHOR]

The development of safety-critical real-time embedded systems (RTESs) is a difficult task. Indeed, in addition to functional requirements, these systems must guarantee timing constraints. Model-driven engineering (MDE) promotes a rise in the level of abstraction during the development process of these systems. This is beneficial since it may help designers manage the increasing complexity of these systems. It may also accelerate the development process through model transformations and enable early verification of the timing properties. Schedulability analysis techniques aim to verify whether the tasks complete their executions within the time limit specified by the real-time application (i.e., the deadline). Unfortunately, software designers find this task difficult since it requires a deep understanding of real-time scheduling theory, as well as the use of dedicated tools (called analysis tools). In this paper, we propose real-time verification design patterns to promote early verification of timing properties in a model-based approach. These patterns aim to assist designers in the verification process. They encapsulate the knowledge of a real-time expert in scheduling theory. To facilitate and fasten the verification process, we propose to automate the generation of the analysis model. Thanks to the provided patterns, this generation phase includes an automatic consistency check of the design model. The consistency check step verifies the design's validity and completeness with respect to the applied pattern. To add further benefits to the proposed patterns, we describe a process that provides context for how these patterns can be applied. We apply and simulate the contribution to real-world case study. The obtained results show the viability of this research. [ABSTRACT FROM AUTHOR]

Detonation shock dynamics is a powerful method to model the behaviour of High Explosives (HE). However in order to use this method, the underlying relationship between the local radius of curvature and the detonation speed must be known. Previous work has developed methods to calculate this effect using simple, single-step Arrhenius and polytropic gas, models for the chemical reaction and the equation of state, respectively. In recent years, more complex models for both reaction rates and equations of state have been developed which show better agreement with experimental data than these simple models, especially when considering condensed phase explosives.. This work presents the governing equations for solving these problems in a way that is generalised to use arbitrary equations of state as well as reaction models which may have more than a single step and multiple product species. This implementation is verified against exact solutions, demonstrating that the equations were implemented properly. The verified algorithm is then validated against experimental data and high fidelity simulations, showing that it is able to make accurate predictions in a regime where the underlying assumptions of the governing equations are valid. This approach has many applications: from creating equivalent detonation shock dynamics models for existing reactive burn calibrations for HE; to developing new functional forms and calibrations of reactive burn models for condensed phase high explosives. [ABSTRACT FROM AUTHOR]

Airborne wind measurement is of great significance for understanding atmospheric motion and meteorological monitoring. In this paper, we present the development and verification of an airborne Doppler wind lidar (ADWL), featuring an approach proposed to integrate a real-time wind retrieval method with an intelligent processing method for automatic adaptive wind detection. Several verification experiments were conducted to evaluate the measurement effectiveness, including comparisons with a calibrated ground-based Doppler wind lidar (GDWL) and a sounding balloon. Compared with the sounding balloon, the ADWL demonstrated mean errors of 0.53 m/s for horizontal wind velocity and 4.60° for wind direction. The correlation coefficients consistently exceeded 0.98 in all linear analyses. Employed in multiple airborne wind detection events in North China at altitudes up to 6600 m, the ADWL provided effective wind field results with a vertical resolution of 50 m and a data rate of 2 Hz. The wind field results obtained during the detection events validate the ADWL's capabilities in diverse environments and underscore its potential for the comprehensive detection of meteorological information. [ABSTRACT FROM AUTHOR]

List intersection plays a pivotal role in various domains such as search engines, database systems, and social networks. Efficient indexes and query strategies can significantly enhance the efficiency of list intersection. Existing inverted index-based algorithms fail to utilize the length information of documents and require excessive list intersections, resulting in lower efficiency. To address this issue, in this paper, we propose the LDRpV (Length-based Document Reordering plus Verification) algorithm. LDRpV filters out documents that are unlikely to satisfy the intersection results by reordering documents based on their length, thereby reducing the number of candidates. Additionally, to minimize the number of list intersection operations, an intersection and verification strategy is designed, where only the first m lists are intersected, and the resulting candidate set is directly verified. This approach effectively improves the efficiency of list intersection. Experimental results on four real datasets demonstrate that LDRpV can achieve a maximum efficiency improvement of 46.69% compared to the most competitive counterparts. [ABSTRACT FROM AUTHOR]

[Display omitted] • Study evaluated potential of FEA to answer questions about device design iterations. • Comprehensive "end-to-end" orthopedic example of the ASME V&V 40-2018 standard. • Validation showed good agreement between the FEA model and experiment. • Study illustrated benefits of VVUQ for establishing credibility of FEA models. Computational modeling and simulation (CM&S) is a key tool in medical device design, development, and regulatory approval. For example, finite element analysis (FEA) is widely used to understand the mechanical integrity and durability of orthopaedic implants. The ASME V&V 40 standard and supporting FDA guidance provide a framework for establishing model credibility, enabling deeper reliance on CM&S throughout the total product lifecycle. Examples of how to apply the principles outlined in the ASME V&V 40 standard are important to facilitating greater adoption by the medical device community, but few published examples are available that demonstrate best practices. Therefore, this paper outlines an end-to-end (E2E) example of the ASME V&V 40 standard applied to an orthopaedic implant. The objective of this study was to illustrate how to establish the credibility of a computational model intended for use as part of regulatory evaluation. In particular, this study focused on whether a design change to a spinal pedicle screw construct (specifically , the addition of a cannulation to an existing non-cannulated pedicle screw) would compromise the rod-screw construct mechanical performance. This question of interest (?OI) was addressed by establishing model credibility requirements according to the ASME V&V 40 standard. Experimental testing to support model validation was performed using spinal rods and non-cannulated pedicle screw constructs made with medical grade titanium (Ti-6Al-4V ELI). FEA replicating the experimental tests was performed by three independent modelers and validated through comparisons of common mechanical properties such as stiffness and yield force. The validated model was then used to simulate F1717 compression-bending testing on the new cannulated pedicle screw design to answer the ?OI, without performing any additional experimental testing. This E2E example provides a realistic scenario for the application of the ASME V&V 40 standard to orthopedic medical device applications. [ABSTRACT FROM AUTHOR]

The Universal Thermal Climate Index (UTCI) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units of temperature and considers physiological aspects of the human body. It takes into account the effect of air temperature, humidity, wind, radiation, and clothes. It is increasingly used in many countries as a measure of thermal comfort for outdoor conditions, and its value is calculated as part of the operational meteorological forecast. At the same time, forecasts of outdoor UTCI tend to have a relatively large error caused by the error of meteorological forecasts. In Slovenia, there is a relatively dense network of meteorological stations. Crucially, at these stations, global solar radiation measurements are performed continuously, which makes estimating the actual value of the UTCI more accurate compared to the situation where no radiation measurements are available. We used seven years of measurements in hourly resolution from 42 stations to first verify the operational UTCI forecast for the first forecast day and, secondly, to try to improve the forecast via post-processing. We used two machine-learning methods, linear regression, and neural networks. Both methods have successfully reduced the error in the operational UTCI forecasts. Both methods reduced the daily mean error from about 2.6 ∘ C to almost zero, while the daily mean absolute error decreased from 5 ∘ C to 3 ∘ C for the neural network and 3.5 ∘ C for linear regression. Both methods, especially the neural network, also substantially reduced the dependence of the error on the time of the day. [ABSTRACT FROM AUTHOR]

Data stewards and analysts can promote transparent and trustworthy science and policy-making by facilitating assessments of the sensitivity of published results to alternate analysis choices. For example, researchers may want to assess whether the results change substantially when different subsets of data points (e.g., sets formed by demographic characteristics) are used in the analysis, or when different models (e.g., with or without log transformations) are estimated on the data. Releasing the results of such stability analyses leaks information about the data subjects. When the underlying data are confidential, the data stewards and analysts may seek to bound this information leakage. We present methods for stability analyses that can satisfy differential privacy, a definition of data confidentiality providing such bounds. We use regression modeling as the motivating example. The basic idea is to split the data into disjoint subsets, compute a measure summarizing the difference between the published and alternative analysis on each subset, aggregate these subset estimates, and add noise to the aggregated value to satisfy differential privacy. We illustrate the methods using regressions in which an analyst compares coefficient estimates for different groups in the data, and in which analysts fit two different models on the data. [ABSTRACT FROM AUTHOR]

Porting software to new target architectures is a common challenge, particularly when dealing with low-level functionality in drivers or OS kernels that interact directly with hardware. Traditionally, adapting code for different hardware platforms has been a manual and error-prone process. However, with the growing demand for dependability and the increasing hardware diversity in systems like the IoT, new software development approaches are essential. This includes rigorous methods for verifying and automatically porting Real-Time Operating Systems (RTOS) to various devices. Our framework addresses this challenge through formal methods and code generation for embedded RTOS. We demonstrate a hardware-specific part of a kernel model in Event-B, ensuring correctness according to the specification. Since hardware details are only added in late modeling stages, we can reuse most of the model and proofs for multiple targets. In a proof of concept, we refine the generic model for two different architectures, also ensuring safety and liveness properties. We then showcase automatic low-level code generation from the model. Finally, a hardware-independent factorial function model illustrates more potential of our approach. [ABSTRACT FROM AUTHOR]

Fictional entertainment can serve as a vivid and easily comprehensible source of knowledge, but only if audiences are able to tell its kernel of truth apart from fantasy. In this article, we use the lens of social epistemology to develop a theoretical framework of knowledge acquisition and verification practices for fictional entertainment that integrates various extant lines of work on entertainment education, perceived realism, information processing, credibility assessment, and verification strategies. To flesh out the conceptual model derived from top-down theoretical integration, we use an inductive, bottom-up approach to theory building, assisted by qualitative research. The resulting model describes knowledge acquisition from fiction as an essentially social process characterized by a combination of epistemic trust and epistemic vigilance toward fictional content and sources, in which credibility is assessed via social knowledge sharing and verification practices. [ABSTRACT FROM AUTHOR]

The paper presents a new cost-effective magnetic circuit structure of a coreless permanent magnet synchronous motor (PMSM) with 16 poles and 12 coils for a mass production fan drive unit. 2D and 3D numerical models of the coreless PMSM were developed. Optimisation calculations were carried out using the field model of the machine. Multistage calculations were performed using the professional FEM package, ANSYS Maxwell and the author's proprietary finite element method (FEM) code. On the basis of the conducted tests and analysis of the obtained results, the "optimal" magnetic circuit structure of the PMSM motor was selected. The prototype motor was subjected to measurement to verify the developed models and the proposed design approach that takes advantage of finite element analysis (FEA). [ABSTRACT FROM AUTHOR]

Background Tens of thousands of underage tobacco buy attempts are conducted each year for research, compliance, and public health surveillance. However, little research has qualitatively examined the perceptions and experiences of underage buyers participating in these programs. We sought to understand underage buyers' experiences and gather recommendations for protocol improvements. Methods We conducted semi-structured interviews in the fall of 2022 to assess experiences with underage tobacco product purchasing. Participants (N  = 19, 58% male, 42% White) were research assistants aged 18–20 in New Jersey, New York, or North Carolina. Interviews examined purchasing experiences in relation to store characteristics, clerk interactions, and buyer identities. We used deductive and inductive thematic coding to explore key themes related to buyer experiences. Results We identified four themes: (1) non-chain stores lacked consistency in verifying age; (2) female data collectors experienced uncomfortable situations more frequently than male data collectors; (3) not identifying with the store's typical demographics impacted purchase attempts; and (4) participants suggested improvements for inspections and research during training. Discussion Retailer education, widespread adoption of ID scanners, and enforcement could increase standardization of ID requests and verification. Male and female buyers can be trained on what they might expect based on their gender, as well as how to maneuver through unwanted situations. Consideration of shared identity is important for future waves of data collection and research. Efforts to improve training include more extensive mock purchase training with supervisors well-versed in this area. Implications Electronic ID verification and promoting compliance at non-chain retailers could impact access to tobacco products for underage buyers. Training for underage buyers in research and compliance assessments should focus on ways to enhance data collectors' confidence when making a purchase attempt, which may improve the validity of the rate of sales to individuals under 21. [ABSTRACT FROM AUTHOR]

Approximately 50% of colorectal cancer (CRC) patients would develop metastasis with poor prognosis, therefore, it is necessary to effectively predict metastasis in clinical treatment. In this study, we aimed to establish a machine-learning model for predicting metastasis in CRC patients by considering radiomics and transcriptomics simultaneously. Here, 1023 patients with CRC from three centers were collected and divided into five queues (Dazhou Central Hospital n  = 517, Nanchong Central Hospital n  = 120 and the Cancer Genome Atlas (TCGA) n  = 386). A total of 854 radiomics features were extracted from tumor lesions on CT images, and 217 differentially expressed genes were obtained from non-metastasis and metastasis tumor tissues using RNA sequencing. Based on radiotranscriptomic (RT) analysis, a novel RT model was developed and verified through genetic algorithms (GA). Interleukin (IL)-26, a biomarker in RT model, was verified for its biological function in CRC metastasis. Furthermore, 15 radiomics variables were screened through stepwise regression, which was highly correlated with the IL26 expression level. Finally, a radiomics model (RA) was established by combining GA and stepwise regression analysis with radiomics features. The RA model exhibited favorable discriminatory ability and accuracy for metastasis prediction in two independent verification cohorts. We designed multicenter, multi-scale cohorts to construct and verify novel combined radiomics and genomics models for predicting metastasis in CRC. Overall, RT model and RA model might help clinicians in directing personalized diagnosis and therapeutic regimen selection for patients with CRC. [ABSTRACT FROM AUTHOR]

Given the widespread misinformation problem in societies across the globe, scholars aiming to combat misinformation wish to change verification behaviors at the individual level. To map what is known about media users' verification behaviors, this study reviewed 52 articles and analyzed how verification research has progressed so far. The results indicate that verification research has been conducted since 2000 but has increased considerably in recent years. However, a clear definition and a standard measure of verification behaviors were missing. Theories and methodologies from different disciplines have been adopted to investigate verification behaviors. The examined variables are diverse, but the overall understanding of the findings is fragmented. Interestingly, the COVID-19 pandemic boosted the number of studies on media users' verification behaviors and brought changes to the direction of the research. This review calls for a better conceptualization and validated measures of verification behaviors and examinations of verification in more diverse contexts. [ABSTRACT FROM AUTHOR]

Lack of an accurate, publicly available database of burn/trauma resources creates challenges in providing burn care. In response to this gap, our group developed the National Injury Resource Database (NIRD), a comprehensive database of all US burn centers (BC) and trauma centers (TC) and their capabilities. Lists of all national BC and TC were obtained from the American Burn Association (ABA), the American College of Surgeons, and every state department of health. Data was cross-checked and included BC/TC were linked with a 7-digit identification number using the American Hospital Association Quick Search guide. Each center's resources and verification status were validated with electronic or telephonic communications. The final database includes 135 BC and 617 TC, of which 18 are BC-only, 500 are TC-only, and 117 are combined BC/TC. ABA-verified BC (n = 76) are only found in Washington DC and 31 states, and 8 states have no BC. In the last 10 years, a net increase of 7 burn centers was found nationally. The ABA's online BC directory is outdated. NIRD represents the only up-to-date, comprehensive listing of BC and TC in existence. It categorizes all currently operating BC and TC across myriad classifications of designation and capabilities. • National Injury Resource Database (NIRD) is a comprehensive listing of all US burn & trauma centers. • NIRD lists burn and trauma center resources, designations, & verifications. • The 76 ABA-verified burn centers are clustered in 31 states & DC. • Eight states have no burn centers, verified or unverified. [ABSTRACT FROM AUTHOR]

We herein present for the first time the phosphylated (*) tetrapeptide (TP)-adduct GlyGluSer198*Ala generated from butyrylcholinesterase (BChE) with proteinase K excellently suited for the verification of exposure to toxic organophosphorus nerve agents (OPNA). Verification requires bioanalytical methods mandatory for toxicological and legal reasons. OPNA react with BChE by phosphonylation of the active site serine residue (Ser198) forming one of the major target protein adducts for verification. After its enzymatic cleavage with pepsin, the nonapeptide (NP) PheGlyGluSer*AlaGlyAlaAlaSer is typically produced as biomarker. Usually OPNA occur as racemic mixtures of phosphonic acid derivatives with the stereocenter at the phosphorus atom, e.g. (±)-VX. Both enantiomers react with BChE, but the adducted NP does not allow their chromatographic distinction. In contrast, the herein introduced TP-adducts appeared as two peaks when using a stationary reversed phase (1.8 µm) in micro-liquid chromatography–electrospray ionisation tandem-mass spectrometry (µLC–ESI MS/MS) analysis. These two peaks represent diastereomers of the (+)- and (−)-OPNA adducted to the peptide that comprises chiral L-amino acids exclusively. Concentration- and time-dependent effects of adduct formation with (±)-VX and its pure enantiomers (+)- and (−)-VX as well as with (±)-cyclosarin (GF) were investigated in detail characterising enantioselective adduct formation, stability, ageing and spontaneous reactivation. The method was also successfully applied to samples from a real case of pesticide poisoning as well as to samples of biomedical proficiency tests provided by the Organisation for the Prohibition of Chemical Weapons. [ABSTRACT FROM AUTHOR]

This paper presents a technique for repairing errors in GPU kernels written in CUDA or OpenCL due to data races and barrier divergence. Our novel extension to prior work can also remove barriers that are deemed unnecessary for correctness. We implement these ideas in our tool called GPURepair, which uses GPUVerify as the verification oracle for GPU kernels. We also extend GPUVerify to support CUDA Cooperative Groups, allowing GPURepair to suggest inter-block synchronization for repairing a CUDA kernel if deemed necessary. To the best of our knowledge, GPURepair is the only tool that can propose a fix for intra-block data races and barrier divergence errors for both CUDA and OpenCL kernels. It is also the only tool that can propose fixes for inter-block data races in CUDA kernels. We perform extensive experiments on about 750 kernels and provide a comparison with prior work. We demonstrate the superiority of GPURepair through its capability to fix more kernels and its unique ability to remove redundant barriers and handle inter-block data races. We have also enhanced the initial version of GPURepair to support incremental solving during the repair process. This enhancement improves the performance of GPURepair by about 25% for the test suite that we have used. [ABSTRACT FROM AUTHOR]

We present an accreditation protocol for analogue, i.e., continuous-time, quantum simulators. For a given simulation task, it provides an upper bound on the variation distance between the probability distributions at the output of an erroneous and errorfree analogue quantum simulator. As its overheads are independent of the size and nature of the simulation, the protocol is ready for immediate usage and practical for the long term. It builds on the recent theoretical advances of strongly universal Hamiltonians and quantum accreditation as well as experimental progress toward the realization of programmable hybrid analogue-digital quantum simulators [ABSTRACT FROM AUTHOR]

The safety and stability of metal hydride reactor (MHR) structure are significantly important for normal operations of hydrogen isotope storage and supply system. Moreover, considering that the experiments of studying the fatigue and creep properties of MHR structure are always time, money, difficulty and energy consuming. To further improve the service life of MHR as well as lower the failure risk, this paper proposes a system integration method based on ASME code validation, which combines genetic algorithm (GA) and back propagation neural network (BPNN) for rapid assessment of creep-fatigue life (CFL) and optimal design of structural parameters. First, numerical simulation is applied to perform thermal-mechanical coupled finite element analysis and verified by ASME code. Then, parametric sensitivity analysis and experimental design of parameter-based training set based on Taguchi method were performed, and response values are obtained from physical models combined with numerical simulations. Finally, a parametric optimization procedure combining BPNN and GA is developed based on the training data. In the workflow, parametric data flow is passed through the experimental design, numerical simulation, prediction and optimization processes. The results show that the proposed BPNN proxy model based on ASME code validation has good performance in predicting the life of MHR. Based on this, the life of the MHR is improved by 8% compared to the reference sample. • The correlation between creep-fatigue life (CFL) of metal hydride reactor (MHR) and design parameters is established. • Numerical models combining BPNN with ASME Code are available for assessment of CFL of MHR. • The sensitivity analysis is applied to measure the effect of design parameters on CFL of MHR. • Optimal design scheme of MHR is performed through an integrated design optimization method. [ABSTRACT FROM AUTHOR]

The specification of requirements and tests are crucial activities in automotive development projects. However, due to the increasing complexity of automotive systems, practitioners fail to specify requirements and tests for distributed and evolving systems with complex interactions when following traditional development processes. To address this research gap, we propose a technique that starts with the early identification of validation concerns from a stakeholder perspective, which we use to systematically design tests that drive a scenario‐based modeling and analysis of system requirements. To ensure complete and consistent requirements and test specifications in a form that is required in automotive development projects, we develop a Model‐Based Systems Engineering (MBSE) methodology. This methodology supports system architects and test designers in the collaborative application of our technique and in maintaining a central system model, in order to automatically derive the required specifications. We evaluate our methodology by applying it at KOSTAL (Tier1 supplier) and within student projects as part of the masters program Embedded Systems Engineering. Our study corroborates that our methodology is applicable and improves existing requirements and test specification processes by supporting the integrated and stakeholder‐focused modeling of product and validation systems, where the early definition of stakeholder and validation concerns fosters a problem‐oriented, iterative and test‐driven requirements modeling. [ABSTRACT FROM AUTHOR]

A review of software dynamic analysis methods is presented, mainly focusing on the methods supported by tools targeted on software security verification and applicable to system software. Fuzzing, runtime verification and dynamic symbolic execution techniques are considered in detail. Dynamic taint data analysis methods and tools are excluded since gathering technical details on them is complicated. The review of fuzzing and dynamic symbolic execution is focused mostly on the techniques to solve various problems that arise during operation of the tools rather than the particular tools that amount to a number greater than 100. In addition, the fuzzing counteraction techniques are considered. [ABSTRACT FROM AUTHOR]

Although deepfakes are conventionally regarded as dangerous, we know little about how deepfakes are perceived, and which potential motivations drive doubt in the believability of deepfakes versus authentic videos. To better understand the audience's perceptions of deepfakes, we ran an online experiment (N = 829) in which participants were randomly exposed to a politician's textual or audio-visual authentic speech or a textual or audio-visual manipulation (a deepfake) where this politician's speech was forged to include a radical right-wing populist narrative. In response to both textual disinformation and deepfakes, we inductively assessed (1) the perceived motivations for expressed doubt and uncertainty in response to disinformation and (2) the accuracy of such judgments. Key findings show that participants have a hard time distinguishing a deepfake from a related authentic video, and that the deepfake's content distance from reality is a more likely cause for doubt than perceived technological glitches. Together, we offer new insights into news users' abilities to distinguish deepfakes from authentic news, which may inform (targeted) media literacy interventions promoting accurate verification skills among the audience. [ABSTRACT FROM AUTHOR]

Background SmeYZ is a constitutively expressed efflux pump in Stenotrophomonas maltophilia. Previous studies demonstrated that: (i) smeYZ inactivation causes compromised swimming, oxidative stress tolerance and aminoglycoside resistance; and (ii) the ΔsmeYZ -mediated pleiotropic defects, except aminoglycoside susceptibility, result from up-regulation of entSCEBB′FA and sbiAB operons, and decreased intracellular iron level. Objectives To elucidate the modulatory role of SmeQ, a novel cytoplasmic protein, in ΔsmeYZ -mediated pleiotropic defects. Methods The presence of operons was verified using RT–PCR. The role of SmeQ in ΔsmeYZ -mediated pleiotropic defects was assessed using in-frame deletion mutants and functional assays. A bacterial adenylate cyclase two-hybrid assay was used to investigate the protein–protein interactions. Gene expression was quantified using quantitative RT–PCR (RT–qPCR). Results SmeYZ and the downstream smeQ formed an operon. SmeQ inactivation in the WT KJ decreased aminoglycoside resistance but did not affect swimming and tolerance to oxidative stress or iron depletion. However, smeQ inactivation in the smeYZ mutant rescued the ΔsmeYZ -mediated pleiotropic defects, except for aminoglycoside susceptibility. In the WT KJ, SmeQ positively modulated SmeYZ pump function by transcriptionally up-regulating the smeYZQ operon. Nevertheless, in the smeYZ mutant, SmeQ exerted its modulatory role by up-regulating entSCEBB′FA and sbiAB operons, decreasing intracellular iron levels, and causing ΔsmeYZ -mediated pleiotropic defects, except for aminoglycoside susceptibility. Conclusions SmeQ is the first small protein identified to be involved in efflux pump function in S. maltophilia. It exerts modulatory effect by transcriptionally altering the expression of target genes, which are the smeYZQ operon in the WT KJ, and smeYZQ , entSCEBB′FA and sbiAB operons in smeYZ mutants. [ABSTRACT FROM AUTHOR]

Background Bacterial membrane vesicles (BMVs) are novel vehicles of antibiotic resistance gene (ARG) transfer in Gram-negative bacteria, but their role in the spread of ARGs in Gram-positive bacteria has not been defined. The purpose of this study was to evaluate the role of MVs in the transmission of antimicrobial resistance in Gram-positive bacteria. Methods A linezolid-resistant Enterococcus faecalis CQ20 of swine origin was selected as the donor strain. Linezolid-susceptible E. faecalis SC032 of human origin, Enterococcus faecium BM4105 and Escherichia coli were selected as recipient strains. The presence of plasmids (pCQ20-1 and pCQ20-2) and an optrA -carrying transposon Tn 6674 in CQ20, MVs and vesiculants was verified by WGS or PCR. MVs were isolated with density gradient centrifugation, and MV-mediated transformation was performed to assess the horizontal transferability of MVs. The MICs for CQ20 and its vesiculants were determined by the broth microdilution method. Results CQ20-derived MVs (CQ20-MV) were isolated, and PCR identified the presence of two plasmids and the optrA gene in the CQ20-MVs. MV-mediated transformation to E. faecalis SC032 and E. faecium BM4105 was successfully performed, and the WGS data also showed that both plasmids pCQ20-1 and pCQ20-2 and optrA -carrying transposon Tn 6674 were transferred to E. faecalis SC032 and E. faecium BM4105, but failed for E. coli. Additionally, vesiculants that had acquired ARGs still had the ability to spread these genes via MVs. Conclusions To our knowledge, this is the first report of MV-mediated co-transfer of ARG-carrying plasmids and transposons in the Gram-positive bacterium E. faecium. [ABSTRACT FROM AUTHOR]

To assess the usefulness of the EP31-A-IR guideline published by the Clinical and Laboratory Standards Institute (CLSI) to perform the periodic verification of results' comparability between several analyzers. Twenty-four biochemistry parameters that could be measured in different analyzers were included: albumin, alkaline phosphatase, alanine aminotransferase, amylase, aspartate aminotransferase, calcium, chloride, C-reactive protein, creatine kinase, creatinine, direct bilirubin, gamma glutamyl transferase, glucose, lactate dehydrogenase, magnesium, phosphate, potassium, sodium, total bilirubin, total cholesterol, total protein, triglycerides, urea and uric acid. In accordance with the EP31-A-IR guideline: (1) Patient samples were selected considering the concentration or activity of interest. (2) Acceptance criteria were established specifically for each concentration or activity level. A quality specification based on biological variation or on state of the art was selected, considering the analytical performance of the available technology. (3) Maximum allowable differences (MAD) between analyzers were calculated. (4) Measurements were performed as stated in appendix B of the guideline. (5) Maximum differences between analyzers were calculated. Results were considered comparable when the maximum difference was less than or equal to the MAD. For the 24 parameters evaluated, any difference between analyzers exceeded the MAD. The EP31-A-IR guideline proved to be useful for periodic verification of results' comparability. However, it must be considered that, to be practicable, it may require to adjust the acceptance criteria in accordance to the analytical performance of the available technology; as well as the number of analytical measurements conforming to the laboratory resources. [ABSTRACT FROM AUTHOR]

Objective To construct and verify the early warning model of the hypothermic risk factors during laparoscopic surgery in the patients with colorectal cancer in order to guide the clinical preventive measures. Methods A total of 475 patients with colorectal cancer undergoing laparoscopic surgery in this hospital from January 2020 to December 2021 were selected. Eighty-three patients with hypothermia during surgery served as the validation group (n=83) and the other served as the non-hypothermia control group (n= 392). The general data in the two groups were collected. The univariate analysis and multivariate analysis were adopted to analyze the risk factors of hypothermia during laparoscopic surgery in the patients with colorectal cancer. Then the early warning model was constructed and its accuracy was verified. Results The incidence rate of hypothermia during surgery in 475 patients with colorectal cancer was 17.47% (83/475). The univariate and multivariate logistic regression analysis results showed that the anesthesia time 3 h, operating room temperature 23 °C, BMI 24 kg/m², age 60 years old, intraoperative fluid infusion volume 1 000 mL were the independent risk factors for intraoperative hypothermia (P<0.05). The early warning model: logistic (P)=-2. 213+2.580×(age) +1.608×(BMI)+1,460× (operating room temperature) +1.254× (anesthesia time) +1.119× (intraoperative fluid infusion volume). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was 0.709 (95%CI 0.631-0.789). The calibration curve showed that the calibration curve was in good agreement with the actual curve, indicating that the model had good discrimination and good prediction fitting (P<0.001). The result of Hosmer-lemeshow test was χ²=162. 181, P<0.001, indicating that the prediction was more accurate. Conclusion The constructed early warning model has good accuracy and discrimination, which could effectively predict the probability of hypothermia during surgery. [ABSTRACT FROM AUTHOR]

AbstractA new nuclear data library for the advanced lattice physics code CASMO5 has been prepared based on JENDL-5. In JENDL-5, the range of data, such as the number of nuclides, has been dramatically expanded for general-purpose applications. At the same time, many essential nuclides for conventional light water reactor (LWR) analysis have also been modified based on state-of-the-art evaluations. The new JENDL-5–based CASMO5 library was prepared by replacing as much of the nuclear data of the current CASMO5 ENDF/B-VII.1–based library as possible with JENDL-5. This study performs initial verification and validation of the new library under typical LWR conditions. Verifications were performed based on the Organisation for Economic Co-operation and Development/Nuclear Energy Agency burnup credit criticality safety benchmark phase III-C, and the calculated kinf and fuel compositions of the boiling water reactor fuel assembly were compared with reported benchmark results. Comparison with the MCNP6.2 result was also performed using the same benchmark model. In addition, a tank-type critical assembly critical experiment and Takahama-3 postirradiation experiment were used for validation. The results indicate that the new library performs well and is comparable to the ENDF/B-VII.1–based library in predictions of reactivity and fuel compositions for typical LWR systems. [ABSTRACT FROM AUTHOR]

Introduction. Dosimetry verification is required before starting each treatment. The legal regulations do not clearly define one method of plan verification. Therefore, it is allowed to perform measurements (electronic portal imaging device [EPID]) or calculations using an independent system. Portal dosimetry using EPID matrices was compared with the RadCalcTM system v. 7.1.4.1, performing independent dose distribution calculations. Materials and methods. Treatment plans were made for 150 patients treated with the photon 6MV VMAT technique. Three groups of patients were studied: those treated for breast cancer, those treated for prostate cancer, and those irradiated to the prostate area with nodes. Then, the dosimetry verification was carried out on the accelerator using the EPID portal and compared with the independent RadCalc software calculation results. Results. Comparison of tumor proportion score (TPS) vs. EPID and vs. RC calculations for breast, prostate, and prostate with nodes showed no significant statistical differences. Regardless of the size (volume) of the clinical target volume (CTV) area, no significant difference was observed, although there was a greater agreement for large CTVs compared to small ones. Similarly, there was no significant difference in the compared methods based on depth, but there was a better agreement for small depths than large ones. Conclusions. Verification methods in the study groups showed compliance of the measured (EPID) and calculated (RadCalc) doses with the values planned in the TPS. This confirms that verification for patients treated with radiotherapy can be performed with any of these methods. However, for radiosurgical techniques, it is better to use the EPID method because the RadCalc method may give false negative results. [ABSTRACT FROM AUTHOR]

The article provides an overview of the philosophy of geometrical product specifications (GPS), which are, in addition to material specifications, a key component of effective planning and production of mechanical products as well as communication between partners in these processes. The principles and basic rules for precise and unambiguous specification of all requirements are embodied in a series of ISO GPS standards. It includes standards that describe the required accuracy of geometrical features of size and geometrical tolerances. An overview of the fundamental principles and rules imposed by the current ISO GPS standards and their content was carried out. This includes a description of the organization of the ISO GPS system and a summary of the content of the more relevant standards, which have recently undergone multiple revisions. The ISO GPS standards are based on the duality principle of specification and verification. In the present research, we focused primarily on geometrical specifications, while omitting the parallel pillar of verification, which, according to the ISO GPS matrix model, contains an even greater number of standards that define this area in more detail. [ABSTRACT FROM AUTHOR]

Dynamical seasonal forecast models are improving with time but tend to underestimate the amplitude of atmospheric circulation variability and to have lower skill in predicting summer variability than in winter. Here, we construct Nonlinear AutoRegressive Moving Average models with eXogenous inputs (NARMAX) to develop the analysis of drivers of North Atlantic atmospheric circulation and jet‐stream variability, focusing on the East Atlantic (EA) and Scandinavian (SCA) patterns as well as the North Atlantic Oscillation (NAO) index. New time series of these indices are developed from empirical orthogonal function (EOF) analysis. Geopotential height data from the ERA5 reanalysis are used to generate the EOFs. Sets of predictors with known associations with these drivers are developed and used to formulate a sliding‐window NARMAX model. This model demonstrates a high degree of predictive accuracy, as indicated by its average correlation coefficients over the testing period (2006–2021): 0.78 for NAO, 0.83 for EA and 0.68 for SCA. In comparison, the SEAS5 and GloSea5 dynamical forecast models exhibit lower correlations with observed circulation changes: for NAO, the correlation coefficients are 0.51 for SEAS5 and 0.34 for GloSea5, for EA they are 0.15 and 0.09, respectively, and for SCA, they are 0.28 and 0.24, respectively. Comparison of NARMAX predictions with forecasts and hindcasts from the SEAS5 and GloSea5 models highlights areas where NARMAX can be used to help improve seasonal forecast skill and inform the development of dynamical models, especially in the case of summer. [ABSTRACT FROM AUTHOR]

A model of an information system describes its processes and how resources are involved in these processes to manipulate data objects. This paper presents an extension to the Petri nets formalism suitable for describing information systems in which states refer to object instances of predefined types and resources are identified as instances of special object types. Several correctness criteria for resource- and object-aware information systems models are proposed, supplemented with discussions on their decidability for interesting classes of systems. These new correctness criteria can be seen as generalizations of the classical soundness property of workflow models concerned with process control flow correctness. [ABSTRACT FROM AUTHOR]

This study presents a series of structured and adaptive processes aimed at tracking and verifying transactions recorded on the blockchain. Permissioned blockchains are employed across diverse enterprises for various purposes, including data recording, management, the utilization of blockchain services, and authentication. However, the processes of data tracking and transactions incur substantial resource and time expenditure. Furthermore, there is potential for information asymmetry within the blockchain ledger due to data breach attacks. Consequently, we propose a contract structured as a hash chain to mitigate resource and time consumption in the tracking and verification processes by organizing transaction hash values and content in a hash chain format based on cryptography. We generate a hash chain for the recorded transactions along the process line and expedite the tracking and verification process by navigating the relevant hash chain. This approach achieves faster and more accurate tracking procedures compared to conventional transaction tracking processes, simultaneously maintaining data symmetry within the blockchain ledger. We conduct a comparative analysis of a contract-based hash-chain-employing structure and two contracts related to tracking in terms of tracking time, CPU usage, and network traffic, among other metrics. The findings suggest that structuring transaction data in the form of a hash chain significantly enhances the efficiency and integrity of the data-tracking and verification processes. Consequently, in this study, we advocate for the adoption of contracts based on the hash chain format when leveraging the blockchain for tracking and verification purposes across various institutions. [ABSTRACT FROM AUTHOR]

The lack of sufficient guarantee about the authenticity of running smart contracts is a major entry barrier to blockchain networks. By authenticity,we refer to the smart contract ownership or provenance; this implies perfect matching between a published source-code and the corresponding running version of a given smart contract. Block verifiers are services that check the provenance authenticity of the logic contained in blockchain networks. Nevertheless, as a block verifier is an external verification service, it consumes time to use it; and the derived overhead may not comply with temporal requirements of time-sensitive domains like cyber-physical systems. Such systems require that the temporal cost of using external services is assessed prior to the final system deployment. To the best of our knowledge, there are no previous contributions on the determination of the temporal cost of the smart-contract provenance verification process. This paper presents the design and implementation of a middleware that assesses the temporal overhead of accessing the verification services; the middleware is hosted in the global ledger and runs the verification services over large sets of smart contracts. Our contribution is validated by providing an implementation on a real blockchain network, employing actual smart contract verifier logic, and analysing the temporal behavior of the overall system operations to comply with the time-sensitive requirements of cyber-physical systems. [ABSTRACT FROM AUTHOR]

News media organizations are a part of the institution of public knowledge. Through journalism, news media organizations inform and educate the public on matters of public concern. However, the digitalization of news media and new affordances brought forth by digital technology have challenged the journalistic field. Complexity in the news media landscape, particularly with the proliferation of fake news, has pushed greater demand for news organizations to ensure that news produced is correctly and accurately verified, especially in newsrooms' adoption of user-generated content (UGC). Breaking news reports are more prone to the utilization of UGC as newsrooms compete for immediacy. For 24-hour news channels, its credible image is vital for future sustainability in a challenging media landscape. This study adopts the gatekeeping theory as it identifies the verification process by two 24-hour news channels—BBC World News and Al Jazeera English—as part of daily news operations. Based on in-depth interviews conducted with news media practitioners from both news channels, five methods of verification are adopted. [ABSTRACT FROM AUTHOR]

Simple Summary: Mining SNPs or genes associated with important traits is important for fine-wool sheep breeding. We screened 20 SNPs associated with important traits of Alpine Merino sheep, such as birth weight, bundle strength, cleaning rate, and fiber diameter, of which 8 were monomorphic locis and 12 were polymorphic locis. These findings provide a theoretical basis for genomic selection and molecular breeding. SNPs associated with important traits of fine-wool sheep that were previously obtained through genome-wide association analysis screening were verified and analyzed. A total of 20 SNPs related to birth weight, bundle strength, cleaning rate, and fiber diameter were screened using whole-genome resequencing, and the SNPshot assay was used to detect and analyze polymorphisms. This study found that, among the 20 SNPs associated with important traits in Alpine Merino sheep, 8 were monomorphic and 12 were polymorphic, of which 6 showed moderate polymorphisms and 6 showed low polymorphisms. The heterozygosity of the 12 polymorphic loci ranged from 0.10 to 0.49, the effective number of alleles ranged from 1.11 to 1.98, and the polymorphic information content ranged from 0.09 to 0.37. The chi-square test showed that only RHPN2:g.42678119T>G and RALYL:g.90030866A>G were in Hardy–Weinberg disequilibrium (p < 0.05); the other loci were in equilibrium (p > 0.05). These SNPs associated with important traits in Alpine Merino sheep provide a theoretical basis for genomic selection and molecular design breeding. [ABSTRACT FROM AUTHOR]

Chlorine is a toxic industrial chemical that has been used as a chemical weapon in recent armed conflicts. Confirming human exposure to chlorine has proven challenging, and there is currently no established method for analyzing human biomedical samples to unambiguously verify chlorine exposure. In this study, two chlorine-specific biomarkers: palmitoyl-oleoyl phosphatidylglycerol chlorohydrin (POPG-HOCl) and the lipid derivative oleoyl ethanolamide chlorohydrin (OEA-HOCl) are shown in bronchoalveolar lavage fluid (BALF) samples from spontaneously breathing pigs after chlorine exposure. These biomarkers are formed by the chemical reaction of chlorine with unsaturated phospholipids found in the pulmonary surfactant, which is present at the gas-liquid interface within the lung alveoli. Our results strongly suggest that lipid chlorohydrins are promising candidate biomarkers in the development of a verification method for chlorine exposure. The establishment of verified methods capable of confirming the illicit use of toxic industrial chemicals is crucial for upholding the principles of the Chemical Weapons Convention (CWC) and enforcing the ban on chemical weapons. This study represents the first published dataset in BALF revealing chlorine biomarkers detected in a large animal. Furthermore, these biomarkers are distinct in that they originate from molecular chlorine rather than hypochlorous acid. [Display omitted] • Detection of two phospholipid biomarkers, intact POPG-HOCl and its derivate OEA-HOCl, in BALF from pig after chlorine exposure • The chlorine specific biomarkers were detectable despite mild acute lung injury • These findings is one step closer the goal of a method for verification of chlorine exposure in humans [ABSTRACT FROM AUTHOR]

Verification activities are intended to reduce the costs of system development by identifying design errors before deploying the system. However, subcontractors in multi‐firm projects are motivated to implement locally cost‐effective verification strategies over verification strategies that benefit the main contractor. Incentivizing verification activities is one mechanism by which the contractor can motivate subcontractors to implement verification strategies desirable to the contractor. In this paper, we present a belief‐based modeling concept for determining optimal verification strategies for general development plans. The results show that the optimal incentives are a function of the subordinate firm's beliefs and the influence exerted by the subordinate firm on the supervising firm with respect to verification activities. [ABSTRACT FROM AUTHOR]

The welfare of fishes and aquatic invertebrates is important, and several jurisdictions have included these taxa under welfare regulation in recent years. Regulation of welfare requires use of scientifically validated welfare criteria. This is why applying Mertonian skepticism toward claims for sentience and pain in fishes and aquatic invertebrates is scientifically sound and prudent, particularly when those claims are used to justify legislation regulating the welfare of these taxa. Enacting welfare legislation for these taxa without strong scientific evidence is a societal and political choice that risks creating scientific and interpretational problems as well as major policy challenges, including the potential to generate significant unintended consequences. In contrast, a more rigorous science-based approach to the welfare of aquatic organisms that is based on verified, validated and measurable endpoints is more likely to result in "win-win" scenarios that minimize the risk of unintended negative impacts for all stakeholders, including fish and aquatic invertebrates. The authors identify as supporters of animal welfare, and emphasize that this issue is not about choosing between welfare and no welfare for fish and aquatic invertebrates, but rather to ensure that important decisions about their welfare are based on scientifically robust evidence. These ten reasons are delivered in the spirit of organized skepticism to orient legislators, decision makers and the scientific community, and alert them to the need to maintain a high scientific evidential bar for any operational welfare indicators used for aquatic animals, particularly those mandated by legislation. Moving forward, maintaining the highest scientific standards is vitally important, in order to protect not only aquatic animal welfare, but also global food security and the welfare of humans. [ABSTRACT FROM AUTHOR]

To design the complex of diagnostics and technical systems of the T-15MD tokamak, a three-dimensional CAD model is used, which includes all structural elements of the tokamak and surrounding heating and diagnostic systems, technical systems such as vacuum pumping and data acquisition systems, etc. Use of the CAD model allows us to take into account the relative location of adjacent systems and the tokamak geometry and integrate newly designed systems. This approach is applied to the design of ITER and used for the first time for Russian tokamaks. In order to provide the most comprehensive matching of the CAD model to the real T-15MD it is necessary to perform verification of the CAD model. This paper presents a method of the verification of the CAD model of T-15MD tokamak complex based on the data of the laser geodesic scanning and the results of assessing the accuracy of the performed work. [ABSTRACT FROM AUTHOR]

Presented are the materials for the certification of the MCU-HTR software package, which implements the Monte Carlo method, as applied to the calculation of the neutronic characteristics of high-temperature gas-cooled reactors and critical assemblies with fuel based on microparticles with a multilayer coating. A verification matrix for certification of the MCU-HTR software package has been developed. All calculations were carried out using a special methodology that enables taking into account the double heterogeneity of fuel arrangement in the core and a detailed full-scale description of the geometry of the calculated objects. The volume of results obtained is unique in terms of completeness and content for the practice of calculating such systems. The calculated reaction rate distributions, efficiency of control rods, and neutronic functionals for start-up experiments of the HTTR reactor with prismatic fuel blocks, the pebble bed HTR-10 reactor, and the experimental configurations implemented on the VHTRC critical assembly are presented. Disagreement between the calculated values and experimental data for the listed characteristics is estimated. [ABSTRACT FROM AUTHOR]

Tropical cyclone (TC) genesis prediction is a major scientific challenge to the TC operation and research community. This report surveys the current status of TC genesis forecasts by a number of major operational centers covering the key ocean basins across both hemispheres. Since IWTC-9, we see an emergence of probabilistic TC genesis forecast products by operational centers, typically supported by the statistical processing of a combination of ensemble prediction and satellite analysis, covering time periods of couple of days to weeks ahead. The prevalence of multi-center grand ensemble approach highlights the uncertainties involved and the forecast challenges in quantitative genesis prediction. While operational practice might differ across agencies, verification efforts generally report a steady or slightly improving skill level in terms of reliability, which likely results from the continual improvement in global numerical weather prediction capability. [ABSTRACT FROM AUTHOR]

The possibility of extended predictions of the Russian river streamflow is considered based on dynamic approach, in which the HBV-96 water-balance runoff formation model is used jointly with the extended ensemble meteorological forecast obtained with the INM5 model. Twelve river basins located in different climatic and physiographic zones of Russia were selected for analysis. The average annual and average monthly discharges, as well as the annual maximum streamflow, were predicted with a lead time of 1–5 years. The test on the reanalysis data for the period from 1980 to 2020 has shown that the applied dynamic approach makes it possible to adequately assess possible interannual fluctuations in the streamflow and its intraannual distribution. The ensemble of forecasts of the annual and maximum streamflow for the period 2023–2026 obtained using the HBV-96 and INM5 models is consistent with the data on the water regime of the analyzed rivers. [ABSTRACT FROM AUTHOR]

A method for short-range forecasting of average daily streamflow is proposed. The method uses the HBV-96 conceptual model of river runoff formation and the COSMO-Ru operational numerical weather prediction system. The method has been implemented for 546 river basins located throughout Russia. An archive of the required hydrometeorological information for the period from 2010 to 2019 has been formed. The method has been developed using the data for the first seven years and verified on independent material with the ones for the last three years. The verification results have shown that the method allows obtaining satisfactory forecasts for a quite large number of river basins. The results make it possible to use the proposed method within the framework of an automated system for preparing and issuing short-range forecasts for the Russian river streamflow. [ABSTRACT FROM AUTHOR]

Apache Spark is a high-speed computing engine for processing massive data. With its widespread adoption, there is a growing need to analyze its correctness and temporal properties. However, there is scarce research focused on the verification of temporal properties in Spark programs. To address this gap, we employ the code-level runtime verification tool UMC4M based on the Modeling, Simulation, and Verification Language (MSVL). To this end, a Spark program S has to be translated into an MSVL program M, and the negation of the property P specified by a Propositional Projection Temporal Logic (PPTL) formula that needs to be verified is also translated to an MSVL program M1; then, a new MSVL program "M and M1" can be compiled and executed. Whether program S violates the property P is determined by the existence of an acceptable execution of "M and M1". Thus, the key issue lies in how to formalize model Spark programs using MSVL programs. We previously proposed a solution to this problem—using the MSVL functions to perform Resilient Distributed Datasets (RDD) operations and converting the Spark program into an MSVL program based on the Directed Acyclic Graph (DAG) of the Spark program. However, we only proposed this idea. Building upon this foundation, we implement the conversion from RDD operations to MSVL functions and propose, as well as implement, the rules for translating Spark programs to MSVL programs based on DAG. We confirm the feasibility of this approach and provide a viable method for verifying the temporal properties of Spark programs. Additionally, an automatic translation tool, S2M, is developed. Finally, a case study is presented to demonstrate this conversion process. [ABSTRACT FROM AUTHOR]

The electronics industry has made remarkable progress over the past 25 years in reducing the emission intensity of long-lived volatile fluorinated compounds (FCs) that typically represent 80 to 90% of uncontrolled direct (scope 1) greenhouse gas (GHG) emissions during the manufacturing of semiconductor, display, and photovoltaic devices. However, while Normalized Emission Rates (NERs) have decreased in terms of CO2-equivalent emissions per surface area of electronic devices produced, absolute FC emissions from the sector have continued to grow at a compound annual rate of 3.4% between 1995 and 2020. Despite these trends, industry has not, to date, renewed their sectoral commitments to strengthen global FC emission reduction goals for the 2020–2030 decade, and it is unlikely that recently announced net-zero emission objectives from a few leading companies can reverse upwards industry emission trends in the near-term. Meanwhile, the persisting gap between "top-down" atmospheric measurements-based FC emission estimates and "bottom-up" emissions estimates is increasingly concerning as recent studies suggest that the gap is likely due, in part, to an underestimation of FC emissions from the electronics sector. Thus, the accuracy of industry-average (Tier 2) emission factors is increasingly questionable. Considering that most FCs essentially permanently persist in the atmosphere on a human time scale, the electronics industry needs to reassert its collective leadership on climate action, increase its ambition to reduce absolute emissions, and ground net-zero commitments in science by embarking on a concerted effort to monitor, report, and verify their process and abatement emission factors. To this effect, this article provides practicable solutions to cross-check bottom-up and top-down emission factors at the facility level and suggests that further implementing cost-effective FC abatement technologies, possibly in conjunction with a sectoral cap-and-trade mechanism, can help achieve residual FC emission levels compatible with net-zero neutralization principles and the 1.5 °C objective of the Paris Agreement. [ABSTRACT FROM AUTHOR]

Backgrounds: The size of medical strategies is expected to grow in conjunction with the expansion of modern diseases' complexity. When a strategy includes more than ten statements, its manual management becomes very challenging, and in some cases, impossible. As a result, the updates they get may result in the unavoidable appearance of anomalies. This causes an interruption in the outflow of imperfect knowledge. Methods: In this paper, we propose an approach called TAnom-HS to verify healthcare strategies. We focus on the management and maintenance, in a convenient and automatic way, of a large strategy to guarantee knowledge accuracy and enhance the efficiency of the inference process in healthcare systems. Results: We developed a prototype of our proposal and we applied it on some cases from the BioPortal repository. The evaluation of both steps of TAnom-HS proved the efficiency of our proposal. Conclusion: To increase ontologies expressiveness, a set of rules called strategy is added to it. TAnom-HS is a two-step approach that treats anomalies in healthcare strategies. Such a task helps to take automatic and efficient healthcare decisions. [ABSTRACT FROM AUTHOR]

Objective: Explore the influencing factors of high-risk colorectal adenomas, construct a risk prediction model, and validate it. Methods: A retrospective analysis was conducted on the data of 1408 patients with colorectal adenoma who underwent diagnosis and treatment at the People’s Hospital Affiliated to Jiangsu University from January 2021 to December 2021. They were divided into high-risk colorectal adenoma group (759 cases) and non high-risk colorectal adenoma group (649 cases) based on their pathological characteristics. Use logistic regression analysis to screen independent risk factors for high-risk colorectal adenomas and establish a risk prediction model, and verify the application effectiveness of the prediction model. Results: The results of Logistic regression analysis showed that the location of the lesion was the rectum, hypertension, hyperlipidemia, age≥53 years, and smoking were independent risk factors for high-risk colorectal adenomas (P＜0.05）. Based on the above factors, a column chart model was established to predict the risk of high-risk colorectal adenomas. The Hosmer-Lemeshow test and receiver operating characteristic curve (ROC) analysis showed that the risk prediction model had good fit and predictive performance, and could be used for risk prediction of high-risk adenomas. Conclusion: The location of the lesion is the rectum, hypertension, hyperlipidemia, age ≥53 years, and smoking are independent risk factors for high-risk colorectal adenomas. Clinicians can provide early preventive intervention for high-risk patients to slow down the occurrence of high-risk adenomas. [ABSTRACT FROM AUTHOR]