Modeling Tools Applied to the Analysis of Mechanical Failures

2014 ◽  
pp. 149-181
Author(s):  
Jose Luis Otegui
Keyword(s):  
Modeling Tools

Low-Carbon Russia: Prospects after the Crisis

2009 ◽  
pp. 107-120 ◽  
Author(s):  
I. Bashmakov
Keyword(s):  
Economic Growth ◽  
Potential Energy ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Low Carbon ◽  
Modeling Tools ◽  
Gas Emissions ◽  
Scenario Approach

On the eve of the worldwide negotiations of a new climate agreement in December 2009 in Copenhagen it is important to clearly understand what Russia can do to mitigate energy-related greenhouse gas emissions in the medium (until 2020) and in the long term (until 2050). The paper investigates this issue using modeling tools and scenario approach. It concludes that transition to the "Low-Carbon Russia" scenarios must be accomplished in 2020—2030 or sooner, not only to mitigate emissions, but to block potential energy shortages and its costliness which can hinder economic growth.

Sarasota Bay: Protection of a Natural Resource

1993 ◽  
Vol 28 (3-5) ◽  
pp. 91-99
Author(s):  
R. A. Wagner ◽  
M. G. Heyl
Keyword(s):  
Wastewater Treatment ◽  
Best Management Practices ◽  
Management Practices ◽  
Treatment Plan ◽  
Management Strategies ◽  
Treatment Plant ◽  
Modeling Tools ◽  
Best Management ◽  
Sarasota Bay ◽  
Potential Benefits

As part of the Sarasota Bay National Estuary Program (NEP) evaluation of environmental problems, modeling tools were used to estimate pollution loadings from diverse sources, including surface runoff, baseflow, wastewater treatment plant discbarges, septic tanks, and direct deposition of rainfall on the bay surface. After assessing the relative impacts of the pollution sources, alternative management strategies were identified and analyzed. These strategies focused primarily on future development, and included structural and nonstructural best management practices (BMPs), as well as a regional wastewater treatment plan. Loading reductions, along with planning-level cost data and estimates of feasibility and other potential benefits, were used to identify the most promising alternatives.

Structure Guided Molecular Docking Assisted Alignment Dependent 3DQSAR Study on Steroidal Aromatase Inhibitors (SAIs) as Anti-breast Cancer Agents

2019 ◽  
Vol 16 (7) ◽  
pp. 808-817 ◽  
Author(s):  
Laxmi Banjare ◽  
Sant Kumar Verma ◽  
Akhlesh Kumar Jain ◽  
Suresh Thareja
Keyword(s):  
Breast Cancer ◽  
Molecular Docking ◽  
Aromatase Inhibitors ◽  
Direct Synthesis ◽  
3D Qsar ◽  
Chemotherapeutic Agents ◽  
Modeling Tools ◽  
Data Set ◽  
Wide Range ◽  
Steroidal Aromatase Inhibitors

Background: In spite of the availability of various treatment approaches including surgery, radiotherapy, and hormonal therapy, the steroidal aromatase inhibitors (SAIs) play a significant role as chemotherapeutic agents for the treatment of estrogen-dependent breast cancer with the benefit of reduced risk of recurrence. However, due to greater toxicity and side effects associated with currently available anti-breast cancer agents, there is emergent requirement to develop target-specific AIs with safer anti-breast cancer profile. Methods: It is challenging task to design target-specific and less toxic SAIs, though the molecular modeling tools viz. molecular docking simulations and QSAR have been continuing for more than two decades for the fast and efficient designing of novel, selective, potent and safe molecules against various biological targets to fight the number of dreaded diseases/disorders. In order to design novel and selective SAIs, structure guided molecular docking assisted alignment dependent 3D-QSAR studies was performed on a data set comprises of 22 molecules bearing steroidal scaffold with wide range of aromatase inhibitory activity. Results: 3D-QSAR model developed using molecular weighted (MW) extent alignment approach showed good statistical quality and predictive ability when compared to model developed using moments of inertia (MI) alignment approach. Conclusion: The explored binding interactions and generated pharmacophoric features (steric and electrostatic) of steroidal molecules could be exploited for further design, direct synthesis and development of new potential safer SAIs, that can be effective to reduce the mortality and morbidity associated with breast cancer.

АЛГОРИТМ РАСЧЕТА ОКОН ПРОЦЕССА ФОТОЛИТОГРАФИИ НА ОСНОВЕ МОДЕЛИ РЕЗИСТА С ПОСТОЯННЫМ ПОРОГОМ

2020 ◽  
Vol 96 (3s) ◽  
pp. 756-757
Author(s):  
Е.С. Шамин ◽  
Е.Л. Харченко
Keyword(s):  
Process Window ◽  
Model Generation ◽  
Modeling Tools ◽  
Photolithography Process

Данная работа посвящена описанию возможного алгоритма создания моделей резиста с постоянным порогом и расчета окон процесса на их основе. Приведенные изыскания реализованы в виде программного средства, использующего средства моделирования фотолитографии Mentor Graphics Calibre. This work is dedicated to the description of one of possible algorithms of constant threshold resist model generation used for photolithography process window calculation. This algorithm has been realized in the form of a program using Mentor Graphics Calibre modeling tools.

scholarly journals Biogeochemical Controls on the Redox Evolution of Earth’s Oceans and Atmosphere

Elements ◽  
2020 ◽  
Vol 16 (3) ◽  
pp. 191-196 ◽  
Author(s):  
Christopher T. Reinhard ◽  
Noah J. Planavsky
Keyword(s):  
Redox State ◽  
Modeling Tools ◽  
Evolutionary Trajectory ◽  
Geochemical Tracers ◽  
Atmosphere System ◽  
Ocean Atmosphere ◽  
Dramatic Shift ◽  
Redox Evolution

The redox state of Earth’s atmosphere has undergone a dramatic shift over geologic time from reducing to strongly oxidizing, and this shift has been coupled with changes in ocean redox structure and the size and activity of Earth’s biosphere. Delineating this evolutionary trajectory remains a major problem in Earth system science. Significant insights have emerged through the application of redox-sensitive geochemical systems. Existing and emerging biogeochemical modeling tools are pushing the limits of the quantitative constraints on ocean–atmosphere redox that can be extracted from geochemical tracers. This work is honing our understanding of the central role of Earth’s biosphere in shaping the long-term redox evolution of the ocean–atmosphere system.

scholarly journals Modeling cesium migration through Opalinus clay: a benchmark for single- and multi-species sorption-diffusion models

2021 ◽  
Author(s):  
Jesús F. Águila ◽  
Vanessa Montoya ◽  
Javier Samper ◽  
Luis Montenegro ◽  
Georg Kosakowski ◽  
...  
Keyword(s):  
Time Discretization ◽  
Single Species ◽  
Opalinus Clay ◽  
Sorption Behavior ◽  
Diffusion Experiment ◽  
Modeling Tools ◽  
Cesium Sorption ◽  
Code Performance ◽  
Good Agreement

AbstractSophisticated modeling of the migration of sorbing radionuclides in compacted claystones is needed for supporting the safety analysis of deep geological repositories for radioactive waste, which requires robust modeling tools/codes. Here, a benchmark related to a long term laboratory scale diffusion experiment of cesium, a moderately sorbing radionuclide, through Opalinus clay is presented. The benchmark was performed with the following codes: CORE2DV5, Flotran, COMSOL Multiphysics, OpenGeoSys-GEM, MCOTAC and PHREEQC v.3. The migration setup was solved with two different conceptual models, i) a single-species model by using a look-up table for a cesium sorption isotherm and ii) a multi-species diffusion model including a complex mechanistic cesium sorption model. The calculations were performed for three different cesium boundary concentrations (10−3, 10−5, 10−7 mol / L) to investigate the models/codes capabilities taking into account the nonlinear sorption behavior of cesium. Generally, good agreement for both single- and multi-species benchmark concepts could be achieved, however, some discrepancies have been identified, especially near the boundaries, where code specific spatial (and time) discretization had to be improved to achieve better agreement at the expense of longer computation times. In addition, the benchmark exercise yielded useful information on code performance, setup options, input and output data management, and post processing options. Finally, the comparison of single-species and multi-species model concepts showed that the single-species approach yielded generally earlier breakthrough, because this approach accounts neither for cation exchange of Cs+ with K+ and Na+, nor K+ and Na+ diffusion in the pore water.

scholarly journals Cytotype distribution and chloroplast phylogeography of the Actinidia chinensis complex

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhi Wang ◽  
Caihong Zhong ◽  
Dawei Li ◽  
Chunlin Yan ◽  
Xiaohong Yao ◽  
...  
Keyword(s):  
Environmental Changes ◽  
Demographic History ◽  
Wide Distribution ◽  
Historical Demography ◽  
Actinidia Chinensis ◽  
Ecological Niche Models ◽  
Subtropical China ◽  
Modeling Tools ◽  
Climatic Fluctuations ◽  
Ploidy Levels

Abstract Background Plant phylogeographic studies of species in subtropical China have mainly focused on rare and endangered species, whereas few studies have been conducted on taxa with relatively wide distribution, especially polyploid species. We investigated the cytotype and haplotype distribution pattern of the Actinidia chinensis complex, a widespread geographically woody liana with variable ploidy in subtropical China comprising two varieties, with three chloroplast fragments DNA (ndhF-rpl132, rps16-trnQ and trnE-trnT). Macroevolutionary, microevolutionary and niche modeling tools were also combined to disentangle the origin and the demographic history of the species or cytotypes. Results The ploidy levels of 3338 individuals from 128 populations sampled throughout the species distribution range were estimated with flow cytometry. The widespread cytotypes were diploids followed by tetraploids and hexaploids, whereas triploids and octoploids occurred in a few populations. Thirty-one chloroplast haplotypes were detected. The genetic diversity and genetic structure were found to be high between varieties (or ploidy races) chinensis and deliciosa. Our results revealed that these two varieties inhabit significantly different climatic niche spaces. Ecological niche models (ENMs) indicate that all varieties’ ranges contracted during the Last Inter Glacial (LIG), and expanded eastward or northward during the Last Glacial Maximum (LGM). Conclusions Pliocene and Plio-Pleistocene climatic fluctuations and vicariance appear to have played key roles in shaping current population structure and historical demography in the A. chinensis complex. The polyploidization process also appears to have played an important role in the historical demography of the complex through improving their adaptability to environmental changes.

scholarly journals Simplified Approach to Predict Food Safety through the Maximum Specific Bacterial Growth Rate as Function of Extrinsic and Intrinsic Parameters

2021 ◽  
Vol 5 (2) ◽  
pp. 22
Author(s):  
Pedro D. Gaspar ◽  
Joel Alves ◽  
Pedro Pinto
Keyword(s):  
Growth Rate ◽  
Food Safety ◽  
Information And Communication Technologies ◽  
Bacterial Growth ◽  
Low Cost ◽  
Extrinsic Factors ◽  
Bacterial Growth Rate ◽  
Modeling Tools ◽  
Simplified Approach ◽  
Food Safety And Quality

Currently, we assist the emergence of sensors and low-cost information and communication technologies applied to food products, in order to improve food safety and quality along the food chain. Thus, it is relevant to implement predictive mathematical modeling tools in order to predict changes in the food quality and allow decision-making for expiration dates. To perform that, the Baranyi and Roberts model and the online tool Combined Database for Predictive Microbiology (Combase) were used to determine the factors that define the growth of different bacteria. These factors applied to the equation that determines the maximum specific growth rate establish a relation between the bacterial growth and the intrinsic and extrinsic factors that define the bacteria environment. These models may be programmed in low-cost wireless biochemical sensor devices applied to packaging and food supply chains to promote food safety and quality through real time traceability.

scholarly journals Increasing the Density of Laboratory Measures for Machine Learning Applications

2020 ◽  
Vol 10 (1) ◽  
pp. 103
Author(s):  
Vida Abedi ◽  
Jiang Li ◽  
Manu K. Shivakumar ◽  
Venkatesh Avula ◽  
Durgesh P. Chaudhary ◽  
...  
Keyword(s):  
Hybrid Approach ◽  
Secondary Diagnosis ◽  
Healthcare Applications ◽  
Modeling Tools ◽  
Clostridioides Difficile ◽  
Laboratory Values ◽  
Diagnosis Codes ◽  
Problem Lists ◽  
Downstream Analysis ◽  
Laboratory Measures

Background. The imputation of missingness is a key step in Electronic Health Records (EHR) mining, as it can significantly affect the conclusions derived from the downstream analysis in translational medicine. The missingness of laboratory values in EHR is not at random, yet imputation techniques tend to disregard this key distinction. Consequently, the development of an adaptive imputation strategy designed specifically for EHR is an important step in improving the data imbalance and enhancing the predictive power of modeling tools for healthcare applications. Method. We analyzed the laboratory measures derived from Geisinger’s EHR on patients in three distinct cohorts—patients tested for Clostridioides difficile (Cdiff) infection, patients with a diagnosis of inflammatory bowel disease (IBD), and patients with a diagnosis of hip or knee osteoarthritis (OA). We extracted Logical Observation Identifiers Names and Codes (LOINC) from which we excluded those with 75% or more missingness. The comorbidities, primary or secondary diagnosis, as well as active problem lists, were also extracted. The adaptive imputation strategy was designed based on a hybrid approach. The comorbidity patterns of patients were transformed into latent patterns and then clustered. Imputation was performed on a cluster of patients for each cohort independently to show the generalizability of the method. The results were compared with imputation applied to the complete dataset without incorporating the information from comorbidity patterns. Results. We analyzed a total of 67,445 patients (11,230 IBD patients, 10,000 OA patients, and 46,215 patients tested for C. difficile infection). We extracted 495 LOINC and 11,230 diagnosis codes for the IBD cohort, 8160 diagnosis codes for the Cdiff cohort, and 2042 diagnosis codes for the OA cohort based on the primary/secondary diagnosis and active problem list in the EHR. Overall, the most improvement from this strategy was observed when the laboratory measures had a higher level of missingness. The best root mean square error (RMSE) difference for each dataset was recorded as −35.5 for the Cdiff, −8.3 for the IBD, and −11.3 for the OA dataset. Conclusions. An adaptive imputation strategy designed specifically for EHR that uses complementary information from the clinical profile of the patient can be used to improve the imputation of missing laboratory values, especially when laboratory codes with high levels of missingness are included in the analysis.

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