Computational Tools Research Articles

Evaluation of output factors of different radiotherapy planning systems using Exradin W2 plastic scintillator detector.

This study aims to evaluate the output factors (OPF) of different radiation therapy planning systems (TPSs) using a plastic scintillator detector (PSD). The validation results for determining a practical field size for clinical use were verified. The implemented validation system was an Exradin W2 PSD. The focus was to validate the OPFs of the small irradiation fields of two modeled radiation TPSs using RayStation version 10.0.1 and Monaco version 5.51.10. The linear accelerator used for irradiation was a TrueBeam with three energies: 4, 6, and 10MV. RayStation calculations showed that when the irradiation field size was reduced from 10 × 10 to 0.5 × 0.5cm2, the results were within 2.0% of the measured values for all energies. Similarly, the values calculated using Monaco were within approximately 2.0% of the measured values for irradiation field sizes between 10 × 10 and 1.5 × 1.5cm2 for all beam energies of interest. Thus, PSDs are effective validation tools for OPF calculations in TPS. A TPS modeled with the same source data has different minimum irradiation field sizes that can be calculated. These findings could aid in verification of equipment accuracy for treatment planning requiring highly accurate dose calculations and for third-party evaluation of OPF calculations for TPS.

Multilevel Intervention Stepped Wedge Designs (MLI-SWDs).

Multilevel interventions (MLIs) hold promise for reducing health inequities by intervening at multiple types of social determinants of health consistent with the socioecological model of health. In spite of their potential, methodological challenges related to study design compounded by a lack of tools for sample size calculation inhibit their development. We help address this gap by proposing the Multilevel Intervention Stepped Wedge Design (MLI-SWD), a hybrid experimental design which combines cluster-level (CL) randomization using a Stepped Wedge design (SWD) with independent individual-level (IL) randomization. The MLI-SWD is suitable for MLIs where the IL intervention has a low risk of interference between individuals in the same cluster, and it enables estimation of the component IL and CL treatment effects, their interaction, and the combined intervention effect. The MLI-SWD accommodates cross-sectional and cohort designs as well as both incomplete (clusters are not observed in every study period) and complete observation patterns. We adapt recent work using generalized estimating equations for SWD sample size calculation to the multilevel setting and provide an R package for power and sample size calculation. Furthermore, motivated by our experiences with the ongoing NC Works 4 Health study, we consider how to apply the MLI-SWD when individuals join clusters over the course of the study. This situation arises when unemployment MLIs include IL interventions that are delivered while the individual is unemployed. This extension requires carefully considering whether the study interventions will satisfy additional causal assumptions but could permit randomization in new settings.

Short-flow-time expansion of quark bilinears through next-to-next-to-leading order QCD

The gradient-flow formalism proves to be a useful tool in lattice calculations of quantum chromodynamics. For example, it can be used as a scheme to renormalize composite operators by inverting the short-flow-time expansion of the corresponding flowed operators. In this paper, we consider the short-flow-time expansion of five quark bilinear operators, the scalar, pseudoscalar, vector, axialvector, and tensor currents, and compute the matching coefficients through next-to-next-to-leading order QCD. Among other applications, our results constitute one ingredient for calculating bag parameters of mesons within the gradient-flow formalism on the lattice.

Contribution of advanced windows and façades to buildings decarbonization: A comprehensive review

On a global level the building sector consumes about 45.00% of energy consumption, contributes about 40.00% to emission, uses 30.00% of water and impacts the environment by generating 30.00% of waste. Although windows are important components of a building that provide natural lighting and ventilation and establish necessary contact with the external environment necessary for healthy indoor ambient, they permit entry of undesirable solar heat in summer and allow escaping heat from the indoor ambient in cold seasons, which aggravate the building needs for energy and increase its contribution to atmospheric emissions. The present investigation provides a review on research, development, and applications of advanced windows in the building sector. The introduction highlights the importance and contribution of advanced glazing technology to improving energy, comfort, and thermal performance of buildings. The review includes natural illumination and ventilation, thermal comfort and discusses the effects of window to wall ratio on natural illumination and ventilation of windows and façades. The review also covers recent developments in glazed windows and façades including performance enhancements by using reflective solar films, vacuum glazing, windows with filling materials, windows with water flow, window with phase change material, window with stagnant inert gas filling, ventilated windows and façades and windows with aerogel. A special section was also included on smart glazing for windows and façades showing the new tendencies and applications in the building industry. Since commercial programs and open access codes are handy tools for simulation and performance calculations a section is dedicated to these codes. The conclusion section contains the most relevant conclusion of the review as well as future trends in research and developments in the area. The topics included in this review can be helpful for experienced and young researchers, practicing engineers and general readers interested in windows and façades.

Mengukur Pengaruh Kualitas Pelayanan Terhadap Kepuasan dan Loyalitas Pengguna Perpustakaan UMS

This research aims to evaluate the impact or effects of effect of Service, information control, and the Library as a Place on the satisfaction and loyalty of library users. The samples in this test were active students and users who utilized library services at the Muhammadiyah University of Surakarta. Sampling was done using a purposive sampling technique to obtain a total of 150 respondents. The data management is carried out using the SmartPLS 3.0 statistical calculation tool and it can be stated that the effect of Service, Information Control, and Library as Place has a significant effect and has a positive impact on user satisfaction and loyalty so the hypothesis can be accepted.

Uniform Modeling of Heat Production Costs in Single-Family and Multi-Family Houses

To ensure a fair and extensive comparison of different heating systems four representative buildings including their heat demand for space heating and domestic hot water were defined. A model for the heat production costs has been developed based on existing methods like the VDI 2067 part 1 [1] and the simplified approach for the calculation of the "Levelised Cost of Heat" (LCoH) of the IEA SHC Task 54 "Price Cost reduction in solar thermal systems" [2]. The developed model includes the costs of purchase, installation, operation, maintenance and disposal and was implemented in an EXCEL calculation tool which enables the calculation of the total life cycle costs (LCC), the levelized cost of heat (LCoH) and the CO2 emissions over the lifetime of the system.

Stratified homotopy theory of topological ∞-stacks: A toolbox

We exploit the theory of ∞-stacks to provide some basic definitions and calculational tools regarding stratified homotopy theory of stratified topological stacks.

Idiopathic Pulmonary Fibrosis: From Common Microscopy to Single-Cell Biology and Precision Medicine.

Idiopathic pulmonary fibrosis is a chronic, progressive, and usually fatal lung disease of unknown etiology and is included in the large, complex, and heterogeneous group of interstitial lung diseases (ILD). IPF is characterized by an aberrant activation of epithelial cells and fibroblasts and excessive accumulation of extracellular matrix, resulting in the progressive destruction of the lung architecture. Here we approach the fascinating historical evolution of our knowledge about this disorder from the past century, when most efforts were focused on ILD classification and terminology, until the current century, when the explosive progress in molecular genetics, epigenetics, and multiomics, as well as the development of complex computational tools, resulted in a huge advance in unveiling the pathogenic mechanisms of the disease. Recent advances in artificial intelligence, machine and deep learning, and artificial neural networks show promising results in identifying lung fibrotic patterns in high-resolution computed tomography or helping to create a tissue genomic classifier for specific diagnosis. Finally, incipient approaches to precision medicine are ongoing in the area of pharmacogenetics.

Machine Learning Memory Kernels as Closure for Non-Markovian Stochastic Processes.

Finding the dynamical law of observable quantities lies at the core of physics. Within the particular field of statistical mechanics, the generalized Langevin equation (GLE) comprises a general model for the evolution of observables covering a great deal of physical systems with many degrees of freedom and an inherently stochastic nature. Although formally exact, GLE brings its own great challenges. It depends on the complete history of the observables under scrutiny, as well as the microscopic degrees of freedom, all of which are often inaccessible. We show that these drawbacks can be overcome by adopting elements of machine learning from empirical data, in particular coupling a multilayer perceptron (MLP) with the formal structure of GLE and calibrating the MLP with the data. This yields a powerful computational tool capable of describing noisy complex systems beyond the realms of statistical mechanics. It is exemplified with a number of representative examples from different fields: from a single colloidal particle and particle chains in a thermal bath to climatology and finance, showing in all cases excellent agreement with the actual observable dynamics. The new framework offers an alternative perspective for the study of nonequilibrium processes opening also a new route for stochastic modeling.

Performance gap analysis for Korean building energy efficiency certification

Performance gap between predicted and measured building energy use can be caused by simplifications and assumptions introduced in the building energy modeling process, uncertainties in building operation such as heating and cooling setpoint temperature, operational hours, occupant behavior, heat generated from lights and equipment, etc. In South Korea, the building energy efficiency certification system (BEEC) evaluates annual energy use intensity (EUI, kWh/m2/yr) and assigns ten certificate levels using ECO2, a EUI calculation tool developed by the Korean government that is based on ISO 52016 and DIN V 18599. Firstly, we collected information on 158 non-residential BEEC-certified buildings and their actual energy usage data. Subsequently, we analyzed the performance gap between predicted and measured EUI for 158 non-residential buildings in terms of building types, heating and cooling degree days, chiller types, gross floor area, window-wall ratio, and envelope U-value. The study reveals that the performance gap is significant, showing mean absolute error ranging from 21.3 to 417.4 kWh/m2/yr, mean biased error from −3.2 to 73.4 %, and the coefficient of variance of the root mean squared error from 57.0 to 304.9 %, respectively. It is also noteworthy that even individual building’s annual consumption during eight years (2014–2021) is annually fluctuating, indicating that even the performance gap is a moving target. This study reassures that building energy certification in the design stage should be understood as a rating, not for a prediction because of many unpredictable and stochastic behavior of building energy systems and occupants.

The MED_EAT-IT approach: A modelling study to develop feasible, sustainable and nutritionally targeted dietary patterns based on the Planetary health diet

In 2019, the EAT-Lancet Commission introduced the Planetary Health Diet (PHD), a guide for creating 2500 kcal/day country-specific sustainable diets that promote health while reducing the environmental impact associated with food systems. The PHD was previously adapted to the Italian food context, resulting in the EAT-IT dietary pattern. However, this adaptation revealed several challenges in terms of nutritional adequacy, feasibility, and environmental impact. This study reports on strategies to improve the previous pattern and align it more closely with the Mediterranean Diet, resulting in the MED_EAT-IT pattern. The study also explores feasible strategies for adapting this pattern to different energy targets, enhancing its scalability and promoting personalized approaches. For the optimization of this pattern, a specific calculation tool was developed to introduce variation to the pattern, considering realistic and feasible serving sizes and frequency of consumption. This tool integrates a defined food ontology, food composition data, and two environmental impact metrics (Carbon and Water Footprint). To optimize nutritional adequacy, several adaptations of the amount within the different food groups were made, for instance by increasing cereals and animal source by 25.5% kcal/day and 36.2% kcal/day respectively compared to EAT-IT. The resulting 2500 kcal/die pattern meets all nutritional requirements except for vitamin D and does not hamper the possibility to limit environmental impact (Carbon Footprint increased only by 12.2% but Water Footprint decreased by 6.3%). Lower energy targets were achieved by modulating amounts of the different food groups to ensure nutritional adequacy. The strategies and tools proposed here could aid in optimizing dietary plans, evaluating their potential for environmental impact reduction, and identifying issues that could hinder their adoption. Furthermore, the analyses carried out pave the way for the potential future development of new or improved foods that may contribute to the optimization of nutritional and environmental impact of diets.

Computational methods for processing and interpreting mass spectrometry-based metabolomics.

Metabolomics has emerged as an indispensable tool for exploring complex biological questions, providing the ability to investigate a substantial portion of the metabolome. However, the vast complexity and structural diversity intrinsic to metabolites imposes a great challenge for data analysis and interpretation. Liquid chromatography mass spectrometry (LC-MS) stands out as a versatile technique offering extensive metabolite coverage. In this mini-review, we address some of the hurdles posed by the complex nature of LC-MS data, providing a brief overview of computational tools designed to help tackling these challenges. Our focus centers on two major steps that are essential to most metabolomics investigations: the translation of raw data into quantifiable features, and the extraction of structural insights from mass spectra to facilitate metabolite identification. By exploring current computational solutions, we aim at providing a critical overview of the capabilities and constraints of mass spectrometry-based metabolomics, while introduce some of the most recent trends in data processing and analysis within the field.

Northern Nevada Public Health: Utilizing the Public Health Workforce Calculator and Workforce Capacity Self-assessment Tools to Develop a Framework for Workforce Investment.

Health departments nationally are critically understaffed and lack infrastructure support. By examining current staffing and allocations through a Foundational Public Health Services (FPHS) lens at the Northern Nevada Public Health (NNPH), there is an opportunity to make a strong case for greater investment if current dedicated full-time equivalents are inadequate and to guide which investments in public health workforce are prioritized. To assess the use of the Public Health Workforce Calculator (calculator) and other tools to identify and prioritize FPHS workforce needs in a field application. Field application of the calculator in conjunction with the use of FPHS workforce capacity self-assessment tools. NNPH. NNPH and Public Health Foundation (PHF). From June 2022 through April 2023, PHF collaborated with NNPH, serving Washoe County, to provide expertise and assistance as NNPH undertook an assessment of its workforce needs based upon the FPHS model. Comparison of the calculator output with FPHS workforce capacity self-assessment tools. The calculator and the FPHS capacity self-assessment process yielded complementary FPHS workforce capacity gap data. The use of a structured and transparent process, coupled with additional tools that included prioritizing needs, provided a viable and sustainable process for public health workforce investment planning. NNPH successfully utilized the results to bolster a supplemental funding request and a state public health appropriation. The use of the calculator and an FPHS workforce capacity self-assessment in a facilitated and structured process such as that used by NNPH to identify staffing priorities may hold promise as an approach that could be used to support decision-making and justification for infrastructure resources when funding for public health increases in the future.

Advancements in artificial intelligence-driven techniques for interventional cardiology.

This paper aims to thoroughly discuss the impact of artificial intelligence (AI) on clinical practice in interventional cardiology (IC) with special recognition of its most recent advancements. Thus, recent years have been exceptionally abundant in advancements in computational tools, including the development of AI. The application of AI development is currently in its early stages, nevertheless new technologies have proven to be a promising concept, particularly considering IC showing great impact on patient safety, risk stratification and outcomes during the whole therapeutic process. The primary goal is to achieve the integration of multiple cardiac imaging modalities, establish online decision support systems and platforms based on augmented and/or virtual realities, and finally to create automatic medical systems, providing electronic health data on patients. In a simplified way, two main areas of AI utilization in IC may be distinguished, namely, virtual and physical. Consequently, numerous studies have provided data regarding AI utilization in terms of automated interpretation and analysis from various cardiac modalities, including electrocardiogram, echocardiography, angiography, cardiac magnetic resonance imaging, and computed tomography as well as data collected during robotic-assisted percutaneous coronary intervention procedures. Thus, this paper aims to thoroughly discuss the impact of AI on clinical practice in IC with special recognition of its most recent advancements.

Test blanket modules piping systems calculation method according to RCC-MRx code

The ITER Test Blanket Modules (TBMs) are installed and operated inside the vacuum vessel (VV) at equatorial ports located within port plugs (PP). The Pipe Forest (PF) is a network of pipes connecting the Ancillary Equipment Unit (AEU) to the TBMs. Depending of the TBM, the Pipe Forest includes various piping system such as Water Coolant (350°, 188 bars), Helium Coolant (500°, 100 bars) Lithium Lead and Tritium Extraction System. During operating states, the Pipe Forest main function is to withstand loads in normal, incidental and accidental situations according to RCC-MRx code criteria (including design rules for mechanical components for fusion installations). It includes severe thermomechanical loadings due to the thermal expansion added to seismic and vertical displacements events. In addition, the PF layout must satisfy constructability in constraint environments and maximize the space available for man access, which constitutes a real challenge for design.Since no existing RCC-MRx post-processing tool exists off the shelves, a specific methodology for pipe stress analysis is being developed by ITER, CEA and ASSYSTEM. This methodology starts with a post-processing calculation tool of stresses and reaction forces for looping back into the structural calculation. Moreover, a specific extraction module from 3D model to processing tool allows the conversion of CAD data to calculation entry files. Finally, a feedback loop is also re-integrated into the core CAD model through an import module, enabling the tracking of displacements and evaluate the impact of incorporating pipe movements into the analysis.This paper describes the pipe stress analysis methodology and its application for Pipe Forest system design life cycle. It covers the historical evolution of the routing including introduction of expansion loops. More recently, it incorporates the integrated calculation of the entire port cell, spanning from the back of the TBM sets, up to the connection pipes of the vertical shaft.

Proposed method for identifying industrial hydrogen demands – Structural basics of a transferable procedure model

Numerous studies emphasize the relevance of green hydrogen for defossilizing industrial production. However, green hydrogen remains a costly and scarce commodity. Besides conventional hydrogen production in centralized large-scale chemical factories, so-called green technologies like electrolysis and bio-based hydrogen production enable rather decentralized hydrogen hubs. Such hubs obviate cost-intensive transportation by regionally interlinking supply and demand. Purposeful deployment of confined resources for establishing such infrastructure for green hydrogen production is necessary to achieve greenhouse gas-emission reduction on a long-term system level. For doing so, detailed data concerning geospatial and temporal occurring industrial hydrogen demands is essential. This article provides structural basics of a transferable procedure model for determining such data within variable system boundaries. Therefore, 44 current and potential future industrial hydrogen applications are identified and associated with calculation principles for quantifying location-based demands. The elaboration of a scenario approach based on location-specific influencing factors enables the consideration of regional characteristics and the consequential varying implementation rate of hydrogen technologies. An accompanying calculation tool is provided to enable low-threshold application of the presented procedure model.

Modeling acoustic wavefields from moving sources in the presence of a time-varying free surface

Marine vibrators are increasingly being recognized as a viable alternative to seismic airguns for ocean-bottom acquisition due to their ability to generate more low-frequency content and their less adverse impact on marine wildlife. However, their use introduces processing challenges, such as the Doppler effect and time-dependent source-receiver offsets, which are negligible in conventional airgun acquisition. In addition, the time-varying nature of the sea surface during the multisecond acquisition time introduces further challenges for processing and inversion. To accurately account for source motion and time-varying sea-surface effects in seismic data processing, we develop a reliable and robust numerical modeling tool. We use a mimetic finite-difference method in a generalized coordinate system to model the full acoustic wavefield triggered by a moving source in the presence of a time-varying sea surface. Our approach uses a time- and space-dependent coordinate transformation, which tracks the source movement and conforms to the irregular time-varying sea surface, to map an irregular physical domain in Cartesian coordinates to a regular computational domain in generalized coordinates. We formulate this coordinate transformation such that the coordinate systems conformally match below the ocean-bottom level. Numerical examples demonstrate that this approach is accurate and stable, even for an unrealistically exaggerated sea state. This computational tool is not limited to modeling but also could be used to develop advanced processing techniques for marine vibrator data, such as imaging and inversion.

Long-term, landscape-level assessment of aquatic pesticide exposure to identify amphibian ontological traits affecting vulnerability.

Amphibians worldwide are threatened by habitat loss, some of which is driven by a changing climate, as well as exposure to pesticides, among other causes. The timing and duration of the larval development phase vary between species, thereby influencing the relative impacts of stochastic hydroregime conditions as well as potential aquatic pesticide exposure. We describe the stages of breeding through metamorphosis for eight amphibian species, based on optimal hydroregime conditions, and use a model of pesticide fate and exposure representative of central Florida citrus groves to simulate hydrodynamics based on observed weather data over a 54-year period. Using the Pesticide in Water Calculator and Plant Assessment Tool, we estimated daily wetland depth and pyraclostrobin exposure, with label-recommended application quantities. Species' timing and duration of larval development determined the number of years of suitable hydroregime for breeding and the likelihood of exposure to peak aquatic concentrations of pyraclostrobin. Although the timing of pesticide application determined the number of surviving larvae, density-dependent constraints of wetland hydroregime also affected larval survival across species and seasons. Further defining categorical amphibian life history types and habitat requirements supports the development of screening-level assessments by incorporating environmental stochasticity at the appropriate temporal resolution. Subsequent refinement of these screening-level risk assessment strategies to include spatially explicit landscape data along with terrestrial exposure estimates would offer additional insights into species vulnerability to pesticide exposure throughout the life cycle. Computational simulation of ecologically relevant exposure scenarios, such as these, offers a more realistic interpretation of differential agrichemical risk among species based on their phenology and habits and provides a more situation-specific risk assessment perspective for threatened species. Integr Environ Assess Manag 2024;00:1-10. Published 2024. This article is a U.S. Government work and is in the public domain in the USA.

A set of calculation tools supporting the design, modelling and application of plywood-based seismic retrofitting interventions on timber floors in existing buildings

The application of timber-based strengthening solutions to existing wooden and masonry structures, combines several benefits, such as reversibility, compatibility, lightness, sustainability, affordability, and effectiveness. With reference to existing timber floors, an efficient method to enhance their seismic response is the fastening of an overlay of plywood panels to the existing sheathing, an intervention that greatly improves in-plane strength, stiffness, and energy dissipation. In order to promote the use of this retrofitting solution in practice, this work presents a set of calculation tools supporting the design and advanced numerical modelling of timber diaphragms strengthened with plywood panels. The suite of tools allows to first estimate the full nonlinear, cyclic in-plane response of the strengthened diaphragms starting from the geometrical and material properties of the existing sheathing and the plywood overlay, as well as the mechanical characteristics of the fasteners. As second step, such estimated in-plane response can be transformed into a constitutive law for performing nonlinear numerical simulations, by means of a user-supplied subroutine developed for finite element software DIANA FEA. The presented calculation examples and the performed validation against reference studies from literature, show that the developed tools can provide an accurate estimate of the in-plane response of the diaphragms, and enable an efficient numerical simulation of their seismic behaviour. The implemented tools can be used to both obtain preliminary indication for plywood-based seismic retrofitting design, and to calibrate the interventions on existing diaphragms based on the specific characteristics and needs of a building, relying on the adaptability and versatility of this strengthening method.

Verification of 2021 IDF-DAR risk assessment tool for fasting Ramadan in patients with diabetes attending primary health care in The Kingdom of Bahrain: The DAR-BAH study

BackgroundThere is a high prevalence of diabetes mellitus among Muslim adult patients. Those Muslims are required to fast the holy month of Ramadan. However, the Islam religion exempted some people with medical issues. It was not clear if all the patients with diabetes were considered medically unfit to fast Ramadan. Therefore, IDF-DAR group created a new risk calculator to categorize the patients with diabetes to advise with or against fasting accordingly. ObjectiveThis study is validating the IDF-DAR tool in assessing the accuracy of IDF-DAR risk calculator tool on adult patients with diabetes visiting primary health care in the Kingdom of Bahrain. The study will facilitate the health care professionals’ decision to exempt the patients from fasting. MethodsIt is a prospective, randomized study for Ramadan 1444/2023 to assess the new IDF-DAR risk score tool that predicts the complications and the negative outcome of fasting during Ramadan. It included pre- and post-Ramadan questionnaires. 757 patients were selected randomly from the patients list of the central diabetes clinics in primary health care for pre-Ramadan risk assessment scoring. Post-Ramadan a phone a questionnaire was done to evaluate the ability of fasting and the occurrence of adverse events. ResultsOut of the 757 participants, 611 were included in the study. The mean age of the studied population was 59.8 years and 52.8 % of them were female. 630 (95.3 %) had type 2 diabetes. According to the new IDF-DAR risk calculator, 184 (27.8 %) were categorized as low risk (≤3 score), 252 (38.1 %) as moderate risk (3–6 score), and 225 (34 %) as high risk (>6 score). The percentage of patients completed their 30 days fasting successfully without reporting adverse events in the low, moderate, and high-risk groups were 92.4 %, 89.3 %, 74.7 % respectively. There was significant increased risk in breaking the fast between the low-risk group and high-risk group with a p-value of <0.001. Similarly, there was significant increased risk in breaking the fast between the moderate-risk group and high-risk group with p-value of <0.001. The main reason of breaking the fast was hypoglycemic attacks. The leading factors that play a significant role in increasing the risk of adverse events during fasting Ramadan were type 1 diabetes mellitus, the presence of previous hypoglycemia attacks, the presence of renal impairment, and negative previous Ramadan experience. ConclusionThe new IDF-DAR risk calculator is a good tool to predict both the ability to fast Ramadan and the probability of experiencing adverse events (mainly hypoglycemia) in people with diabetes mellitus in Kingdom of Bahrain.