Updated Version Research Articles

Can people afford to pay for health care? Evidence on inequity in financial protection in Europe

Abstract Governments have repeatedly affirmed their commitment to meeting the goals of universal health coverage (UHC) – to ensure that everyone can use the quality health services they need without experiencing financial hardship. In spite of strong political commitment to UHC, research from the WHO Regional Office for Europe shows that: This session aims to raise awareness about the most prevalent gaps in coverage in European health systems, the policies that cause them and what countries can do to address them. It will draw on findings from an updated version of the WHO study ‘Can people afford to pay for health care? New evidence on financial protection in Europe’, which covers over 35 countries in Europe, including all EU member states and many middle-income countries The session will highlight common gaps in coverage that systematically harm people with low incomes: The session will focus on how to make progress by: Keynote speaker: Charles Normand Trinity College Dublin, Dublin, Ireland Panellists: Sarah Thomson WHO Europe Kaisa Immonen European Patients' Forum (EPF)

Automatically generated detailed and lumped reaction mechanisms for low- and high-temperature oxidation of alkanes

In this work, we present a methodology on automatic generation of predictive lumped sub-mechanisms for normal and branched alkanes. This methodology aims at obtaining lumped reaction mechanisms that preserve the chemical behavior of each reaction class in the detailed model. To achieve this goal, detailed sub-mechanisms for combustion of alkanes are generated by employing an updated version of the MAMOX++ software developed in this work; recent progress in the low-temperature reaction classes and rate rules are incorporated into the updated software. Instead of computing the selectivities of several primary products with MAMOX++ and fitting the selectivities between the detailed and lumped models, this work proposes a new methodology to generate the lumped sub-mechanisms for fuel molecules. The stoichiometric parameters and the reaction rates for each reaction class in the lumped sub-mechanism are fitted to match those in the detailed model. Based on the present methodology, both the detailed and lumped sub-mechanisms for normal C5C10 alkanes and branched C5C8 alkanes, that is for 15 different fuels, are automatically generated and merged into a base chemistry model (i.e. AramcoMech 2.0), respectively. The detailed and lumped models are validated against the experimental data in the literature. The automatically generated detailed models for alkanes are able to capture the experimental targets across a wide range of conditions, demonstrating the robustness of the reaction classes and rate rules adopted. The lumped models for normal alkanes have similar performance to their respective detailed models, and are able to predict the oxidation behavior of normal alkanes. However, prediction deviations between the detailed and lumped models for branched alkanes are shown to be slightly greater.

Long-term trends of light pollution assessed from SQM measurements and an empirical atmospheric model

ABSTRACT We present long-term (4–10 yr) trends of light pollution observed at 26 locations, covering rural, intermediate, and urban sites, including the three major European metropolitan areas of Stockholm, Berlin, and Vienna. Our analysis is based on (i) night sky brightness (NSB) measurements obtained with sky quality metres (SQMs) and (ii) a rich set of atmospheric data products. We describe the SQM data reduction routine in which we filter for moon- and clear-sky data and correct for the SQM ‘aging’ effect using an updated version of the twilight method of Puschnig et al. (2021). Our clear-sky, aging-corrected data reveal short- and long-term (seasonal) variations due to atmospheric changes. To assess long-term anthropogenic NSB trends, we establish an empirical atmospheric model via multivariate penalized linear regression. Our modelling approach allows to quantitatively investigate the importance of different atmospheric parameters, revealing that surface albedo and vegetation have by far the largest impact on zenithal NSB. Additionally, the NSB is sensitive to black carbon and organic matter aerosols at urban and rural sites, respectively. Snow depth was found to be important for some sites, while the total column of ozone leaves impact on some rural places. The average increase in light pollution at our 11 rural sites is 1.7 per cent per year. At our nine urban sites, we measure an increase of 1.8 per cent per year and for the remaining six intermediate sites we find an average increase of 3.7 per cent per year. These numbers correspond to doubling times of 41, 39, and 19 yr. We estimate that our method is capable of detecting trend slopes shallower/steeper than ±1.5 per cent per year.

Методическое сопровождение обновлённого Федерального государственного образовательного стандарта начального общего образования

The article discusses scientific and methodological approaches and characterizes the updated version of the Federal State Educational Standard for Primary General Education (FSES PGE) adopted by the Ministry of Education of the Russian Federation in May 2021. The structure of the Approximate educational program and its most important part - exemplary work programs of primary school subjects are considered. On the example of the work program on the subject "World around", a description of the goals, content, planned learning outcomes is given, accompanied by comments for the teacher.

Формирование у младших школьников первоначальных основ экологической культуры: примеры методических разработок

The article discusses the problem of increasing attention to the environmental education of primary school students in accordance with the updated version of the State Educational Standard for Primary General Education (FSES PGE). The goals, methods and techniques of the process of formation of the ecological culture of younger schoolchildren at the lessons of the "The-World-Around-Us" are characterized. Examples of methodological developments in the study of various topics of this training course for the second grade are described. Particular attention is paid to familiarization with the Red Data Book of Russia and the regions.

HProteome-BSite: predicted binding sites and ligands in human 3D proteome.

Atomic-level knowledge of protein-ligand interactions allows a detailed understanding of protein functions and provides critical clues to discovering molecules regulating the functions. While recent innovative deep learning methods for protein structure prediction dramatically increased the structural coverage of the human proteome, molecular interactions remain largely unknown. A new database, HProteome-BSite, provides predictions of binding sites and ligands in the enlarged 3D human proteome. The model structures for human proteins from the AlphaFold Protein Structure Database were processed to structural domains of high confidence to maximize the coverage and reliability of interaction prediction. For ligand binding site prediction, an updated version of a template-based method GalaxySite was used. A high-level performance of the updated GalaxySite was confirmed. HProteome-BSite covers 80.74% of the UniProt entries in the AlphaFold human 3D proteome. Predicted binding sites and binding poses of potential ligands are provided for effective applications to further functional studies and drug discovery. The HProteome-BSite database is available at https://galaxy.seoklab.org/hproteome-bsite/database and is free and open to all users.

Updating nonviolent campaigns: Introducing NAVCO 2.1

In this article, we introduce an updated version of the Nonviolent and Violent Campaigns and Outcomes dataset (NAVCO 2.1), which compiles annual data on 389 nonviolent and violent mass movements for regime change, anti-occupation, and secession from 1945 to 2013. This version of the dataset corrects known coding errors in NAVCO 2.0, adds news cases (including the Arab uprisings), and codes attributes for each campaign year (such as participation size and diversity, the behavior of regime elites, repression and its effects, support from external actors, and campaign outcomes). In addition, NAVCO 2.1 adds several new attributes to each campaign-year, including more precise participation figures, more nuanced data about the scope, intensity, and degree of violent flank behavior and state repression, and further information about the parallel or alternative institutions developed by the campaign. The data reveal four key findings: (1) that the success rate of nonviolent resistance campaigns has declined since 2001; (2) that far more people have participated in nonviolent than violent campaigns in the postwar period; (3) that nonviolent campaigns suffer far fewer per-capita fatalities than armed campaigns; and (4) that incidental violence by dissidents has become a more common feature of contemporary nonviolent campaigns compared with earlier cases. The article concludes with suggestions for further research.

The Moist Quasi-Geostrophic Coupled Model: MQ-GCM 2.0

Abstract. This paper contains a description of recent changes to the formulation and numerical implementation of the Quasi-Geostrophic Coupled Model (Q-GCM), which constitute a major update of the previous version of the model (Hogg et al., 2014). The Q-GCM model has been designed to provide an efficient numerical tool to study the dynamics of multi-scale midlatitude air–sea interactions and their climatic impacts. The present additions/alterations were motivated by an inquiry into the dynamics of mesoscale ocean–atmosphere coupling and, in particular, by an apparent lack of the Q-GCM atmosphere's sensitivity to mesoscale sea-surface temperature (SST) anomalies, even at high (mesoscale) atmospheric resolutions, contrary to ample theoretical and observational evidence otherwise. Major modifications aimed at alleviating this problem include an improved radiative-convective scheme resulting in a more realistic model mean state and associated model parameters; a new formulation of entrainment in the atmosphere, which prompts more efficient communication between the atmospheric mixed layer and free troposphere; and an addition of a temperature-dependent wind component in the atmospheric mixed layer and the resulting mesoscale feedbacks. The most drastic change is, however, the inclusion of moist dynamics in the model, which may be key to midlatitude ocean–atmosphere coupling. Accordingly, this version of the model is to be referred to as the MQ-GCM model. Overall, the MQ-GCM model is shown to exhibit a rich spectrum of behaviors reminiscent of many of the observed properties of the Earth's climate system. It remains to be seen whether the added processes are able to affect in fundamental ways the simulated dynamics of the midlatitude ocean–atmosphere system's coupled decadal variability.

TSNAdb v2.0: The Updated Version of Tumor-specific Neoantigen Database

In recent years, neoantigens have been recognized as ideal targets for tumor immunotherapy. With the development of neoantigen-based tumor immunotherapy, comprehensive neoantigen databases are urgently needed to meet the growing demand for clinical studies. We have built the tumor-specific neoantigen database (TSNAdb) previously, which has attracted much attention. In this study, we provide TSNAdb v2.0, an updated version of the TSNAdb. TSNAdb v2.0 offers several new features, including (1) adopting more stringent criteria for neoantigen identification, (2) providing predicted neoantigens derived from three types of somatic mutations, and (3) collecting experimentally validated neoantigens and dividing them according to the experimental level. TSNAdb v2.0 is freely available at https://pgx.zju.edu.cn/tsnadb/.

Anisotropic GPMP2: A Fast Continuous-Time Gaussian Processes Based Motion Planner for Unmanned Surface Vehicles in Environments With Ocean Currents

In the past decade, there is an increasing interest in the deployment of unmanned surface vehicles (USVs) for undertaking ocean missions in dynamic, complex maritime environments. The success of these missions largely relies on motion planning algorithms that can generate optimal navigational trajectories to guide a USV. Apart from minimising the distance of a path, when deployed a USVs’ motion planning algorithms also need to consider other constraints such as energy consumption, the affected of ocean currents as well as the fast collision avoidance capability. In this paper, we propose a new algorithm named anisotropic GPMP2 to revolutionise motion planning for USVs based upon the fundamentals of GP (Gaussian process) motion planning (GPMP, or its updated version GPMP2). Firstly, we integrated the anisotropy into GPMP2 to make the generated trajectories follow ocean currents where necessary to reduce energy consumption on resisting ocean currents. Secondly, to further improve the computational speed and trajectory quality, a dynamic fast GP interpolation is integrated in the algorithm. Finally, the new algorithm has been validated on a WAM-V 20 USV in a ROS environment to show the practicability of anisotropic GPMP2. Note to Practitioners—The work reported in this article will be significant for USVs to conduct missions in complex, dynamic maritime environments where various obstacles and time-varying ocean currents exit. We develop this novel motion planning algorithm based on Gaussian process and optimise the trajectory using probabilistic inferences. The new algorithm can generate collision free trajectories that also minimise the influences caused by adverse ocean currents in a highly efficient way. In addition, the planning has been undertaken in a continuous-time domain making the generated trajectory have a guaranteed smoothness and readily feasible for autopilots to track. We use a coastal area with time-varying vortexes to present a challenging practical maritime environment. The presented algorithm integrates the available information about a fluid field regarding energy consumption and hazard level, along with the density of obstacles to plan a navigational route efficiently. To increase the practical performance of the proposed method, diverse models for generating ocean currents need to be developed in the future to tackle unpredictable situations.

Leptin effects: focusing on the relationship between obesity and male infertility.

The human male infertility has several causes interconnected to improper lifestyles such as smoking, sedentarism, environmental factors, toxins accumulation and energy imbalances. All these factors contribute to the obesity accompanied metabolic syndrome and hormonal alterations in the leptin-ghrelin axis. The leptin (Lep) has many pleiotropic effects in several biological systems, directly on the peripheral tissues or through the central nervous system. Many studies suggest that Lep is a key player in gonadal functions beside its documented role in reproductive regulation; however, further investigations are still necessary to elucidate all the molecular pathways involved in these mechanisms. Keeping into account that increased Lep levels in obese men are positively correlated with altered sperm parameters and testicular oxidative stress, evidence refers to Lep as a potential link between obesity and male infertility. This review represents an updated version on the concept of the Lep roles in mediating the male reproductive functions in obese patients.

Spiritual Foundations for an Ecologically Sustainable Society

This article takes a broad macroevolutionary approach to our changing relationship to Nature in the light of the teachings or the Bahá’í Faith. It suggests that humanity is in a process of evolving consciousness leading to the development of a new planetary culture based on spiritual principles. In an ecological sense, humanity has in many respects appeared to be a delinquent species running out of control. Within a larger vision of humanity’s spiritual and social evolution, however, the present environmental crisis and the race’s reaction to it can be seen as portending a momentous transformation. The process of evolving consciousness that can be discerned in emerging knowledge in physics, ecology, psychology, and other fields of science is leading to the possibility of a mature cooperative relationship between humanity and the ecosphere which gave it birth. After a brief overview of the current range of responses to environmental issues and the view of Nature on which they are based, this article will explore the basic attitudes to Nature contained within the Bahá’í writings. The second part of the article examines how the emergence of an ecologically sustainable social order is linked to basic principles of the Bahá’í Faith. Implicit throughout is the Bahá’í view of the balance and cohesion of material and spiritual realities.
 * An earlier version of this article appeared in the Journal of Bahá’í Studies 2.1 (1989): 33–57. A special pamphlet version was co-published with the Bahá’í International Community–Office of the Environment and was distributed at the 1992 Earth Summit in Brazil. The updated version in this issue was prepared for Bahá’í World Yearbook 1992-93.

Magnetic Resonance Imaging-Based Predictive Models for Clinically Significant Prostate Cancer: A Systematic Review.

Simple SummaryMagnetic resonance imaging (MRI) has allowed the early detection of PCa to evolve towards clinically significant PCa (csPCa), decreasing unnecessary prostate biopsies and overdetection of insignificant tumours. MRI identifies suspicious lesions of csPCa, predicting the semi-quantitative risk through the prostate imaging report and data system (PI-RADS), and enables guided biopsies, increasing the sensitivity of csPCa. Predictive models that individualise the risk of csPCa have also evolved adding PI-RADS score (MRI-PMs), improving the selection of candidates for prostate biopsy beyond the PI-RADS category. During the last five years, many MRI-PMs have been developed. Our objective is to analyse the current developed MRI-PMs and define their clinical usefulness through a systematic review. We have found high heterogeneity between MRI technique, PI-RADS versions, biopsy schemes and approaches, and csPCa definitions. MRI-PMs outperform the selection of candidates for prostate biopsy beyond MRI alone and PMs based on clinical predictors. However, few developed MRI-PMs are externally validated or have available risk calculators (RCs), which constitute the appropriate requirements used in routine clinical practice.MRI can identify suspicious lesions, providing the semi-quantitative risk of csPCa through the Prostate Imaging-Report and Data System (PI-RADS). Predictive models of clinical variables that individualise the risk of csPCa have been developed by adding PI-RADS score (MRI-PMs). Our objective is to analyse the current developed MRI-PMs and define their clinical usefulness. A systematic review was performed after a literature search performed by two independent investigators in PubMed, Cochrane, and Web of Science databases, with the Medical Subjects Headings (MESH): predictive model, nomogram, risk model, magnetic resonance imaging, PI-RADS, prostate cancer, and prostate biopsy. This review was made following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria and studied eligibility based on the Participants, Intervention, Comparator, and Outcomes (PICO) strategy. Among 723 initial identified registers, 18 studies were finally selected. Warp analysis of selected studies was performed with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Clinical predictors in addition to the PI-RADS score in developed MRI-PMs were age, PCa family history, digital rectal examination, biopsy status (initial vs. repeat), ethnicity, serum PSA, prostate volume measured by MRI, or calculated PSA density. All MRI-PMs improved the prediction of csPCa made by clinical predictors or imaging alone and achieved most areas under the curve between 0.78 and 0.92. Among 18 developed MRI-PMs, 7 had any external validation, and two RCs were available. The updated PI-RADS version 2 was exclusively used in 11 MRI-PMs. The performance of MRI-PMs according to PI-RADS was only analysed in a single study. We conclude that MRI-PMs improve the selection of candidates for prostate biopsy beyond the PI-RADS category. However, few developed MRI-PMs meet the appropriate requirements in routine clinical practice.

Refurbishing the Educational Escape Room for Programming: Lowering the Threshold and Raising the Ceiling

Programming education at university level has often been identified as problematic learning. At the same time, prognosis for future labour market is increased need for professionals with programming and related skills. To meet demands of future society, K-12 schools around the world have integrated programming in the curriculum. However, research show challenges for integrating programming in K-12 education. Challenges include students’ and teachers’ struggle with learning and teaching programming, lack of time to properly incorporate programming in existing teaching and learning, and insufficient support for teachers. This study addresses these challenges by designing, developing, and evaluating an educational game on programming that combines the idea of game-based learning with digital escape rooms. In the game, the player develops knowledge about programming concepts to escape 10 rooms. The study’s main research question was: What are K-12 students’ perceptions of the game and what do they considered to be important design factors for a digital escape room game on computer programming? A design science approach was used for designing, developing, and evaluating a web-based escape room game on programming. This was conducted in a five-step process: 1) Explicating the problem, 2) Defining the requirements, 3) Designing and developing the artefact, 4) Demonstrating the artefact, and 5) Evaluating the artefact. The game was tested and evaluated by 32 K-12 students with a questionnaire during the autumn semester of 2021 and spring semester of 2022. Collected data were then analysed and grouped into categories to answer the study’s aim and research question. Findings of the study show several suggestions for further development and important design factors to consider when developing a digital escape room game. The next steps of research are to combine these findings with evaluations from teachers, and to incorporate this in an updated version of the game.

Outcome-Based Education in Open Distance Learning: A Study on Its Implementation Amidst the Pandemic

The noble Malaysian Qualification Framework (MQF) has been established by the Malaysian Qualification Agency (MQA) to emphasise the obligation to apply Outcome-Based Education (OBE) for higher education in Malaysia, with the revised version of MQF introduced in the year 2019 to assure the quality of higher education continues to be on par with the current global demand. A year after the launching of the revised edition, the momentum of OBE implementation was interrupted by the unforeseen pandemic crisis, resulting in major disruptions for all higher education institutions. This study intended to explore how OBE has been implemented in a Higher Education Provider (HEP) that offers Open Distance Learning (ODL), as well as its challenges and quality improvement approaches when the implementation was impacted by the unprecedented event. The study applied a qualitative research design and adopted a purposive sampling method to select four participants to join a one-to-one semi-structured interview. Data collected were transcribed and analysed via ATLAS.ti software by using a thematic approach. The finding revealed that the ODL-HEP well-applied the updated version of the framework to achieve the ultimate goal of OBE. However, there were both positive and negative perspectives about OBE in higher education. In addition, four themes namely psychomotor domain, alternative assessment, learning outcomes achievement, and dropout of students were discovered in the OBE implementation challenges amidst the pandemic. The results for the continual quality improvement aspect also revealed five important themes to illustrate how the HEP responded to the challenges and change.

Modified Kuppuswamy socioeconomic scale: 2022 update of India

The term "socioeconomic status" (SES) refers to a measurement that takes into account a family's income, level of education, and the occupation of the family's primary breadwinner. This helps to evaluate the family overall health as well as their access to resources. Kuppuswamy SES is one of the commonest scales used to determine SES of people residing in urban areas, but it requires updating because of steady inflation in the value of rupees based on change in consumer price index. The updated version of modified Kuppuswamy socioeconomic scale for the year 2022 in India is thus presented.

Improved Real-Time Fire Warning System Based on Advanced Technologies for Visually Impaired People.

Early fire detection and notification techniques provide fire prevention and safety information to blind and visually impaired (BVI) people within a short period of time in emergency situations when fires occur in indoor environments. Given its direct impact on human safety and the environment, fire detection is a difficult but crucial problem. To prevent injuries and property damage, advanced technology requires appropriate methods for detecting fires as quickly as possible. In this study, to reduce the loss of human lives and property damage, we introduce the development of the vision-based early flame recognition and notification approach using artificial intelligence for assisting BVI people. The proposed fire alarm control system for indoor buildings can provide accurate information on fire scenes. In our proposed method, all the processes performed manually were automated, and the performance efficiency and quality of fire classification were improved. To perform real-time monitoring and enhance the detection accuracy of indoor fire disasters, the proposed system uses the YOLOv5m model, which is an updated version of the traditional YOLOv5. The experimental results show that the proposed system successfully detected and notified the occurrence of catastrophic fires with high speed and accuracy at any time of day or night, regardless of the shape or size of the fire. Finally, we compared the competitiveness level of our method with that of other conventional fire-detection methods to confirm the seamless classification results achieved using performance evaluation matrices.

A comprehensive genomic and transcriptomic dataset of triple-negative breast cancers

Molecular subtyping of triple-negative breast cancer (TNBC) is essential for understanding the mechanisms and discovering actionable targets of this highly heterogeneous type of breast cancer. We previously performed a large single-center and multiomics study consisting of genomics, transcriptomics, and clinical information from 465 patients with primary TNBC. To facilitate reusing this unique dataset, we provided a detailed description of the dataset with special attention to data quality in this study. The multiomics data were generally of high quality, but a few sequencing data had quality issues and should be noted in subsequent data reuse. Furthermore, we reconduct data analyses with updated pipelines and the updated version of the human reference genome from hg19 to hg38. The updated profiles were in good concordance with those previously published in terms of gene quantification, variant calling, and copy number alteration. Additionally, we developed a user-friendly web-based database for convenient access and interactive exploration of the dataset. Our work will facilitate reusing the dataset, maximize the values of data and further accelerate cancer research.

How to Improve Quality of Crowdsourced Cadastral Surveys

The potential for introducing voluntary citizen participation, combined with mobile services, for cadastral data collection for a systematic first registration has been thoroughly investigated and even implemented in some official projects. This data collection procedure can technically be ac-complished safely, but results have shown that many participants have difficulty in identifying the land parcels (location, shape and size) on the base-map (orthophoto, air-photo, etc.) correctly. Either they have to ask the assistance of a private professional, or there is a high risk that a number of errors may appear in the submitted crowdsourced data. This paper investigates how to improve the quality of such crowdsourced cadastral data, by adding to the base-map any available and relevant geospatial and descriptive information that may help the participants to correctly identify their land parcel. In particular, the research investigates and suggests (a) which types of available geospatial information should be added to the base-map and by whom (professionals or a group of trained volunteers), and (b) the necessary quality controls that must be made in the compilation of the advanced crowdsourced base-map—a case study follows to assess the suggested proposal. In addition, this paper provides an updated version of the crowdsourced methodology for cadastral surveys as modelled by the authors in an earlier stage of their research. This updated version briefly includes all quality controls needed to ensure the quality of a modern cadastre that the authors will further investigate in a subsequent stage.

Computational models of direct and indirect X-ray breast imaging detectors for in silico trials.

To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers areneeded. The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of theirsystems. We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open-source GPU-accelerated Monte Carlo x-ray imaging simulation code (MC-GPU). We build on the previous version of the MC-GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)-approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x-ray photon till its first interaction within the x-ray detector. On the other hand, the signal spread in the x-ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron-hole pairs or optical photons) using analytical equationsin the detector. The analytical optical spread model for the indirect detector includes the depth-dependent spread and collection of optical photons and relies on a pre-computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x-ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measureddata. We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with directdetectors. We have presented computational models of three commercially available FDA-approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC-GPU codes that can be used to replicate three systems are available in open source format throughGitHub.