Modeling Of Transformation Research Articles

Mountain Arable Land Abandonment (1968–2018) in the Romanian Carpathians: Environmental Conflicts and Sustainability Issues

The agricultural mountain landscape in the Romanian Carpathians follows the same change trend in other European mountains, from variety and individuality to simplification and uniformization. Our paper proposes two complementary case studies from the Southern Carpathians—Poiana Mărului and Fundata, representative areas for the entire Carpathian ecoregion. The research focuses on a remote sensing approach with Corona KH-4B (1968) and Planet Scope (2018) images at 2.0–3.0 m resolution used for mapping arable plots pattern and size change. Landscape transformation modelling is focused on four-hectare sampled grid for both case study areas, followed by a landscape metric analysis. Fundata area is the most transformed, where arable plots disappeared under the service-based economy pressure. Poiana Mărului shows an earlier stage of landscape transformation, where the arable land abandonment process is incipient. The spatial and statistical analysis and field survey confirmed that tourism changed the traditional agricultural landscape, generating potential environmental conflicts and indicating the sustainability degree.

Solid-state formation of CO and H2CO via the CHOCHO + H reaction

ABSTRACT Glycolaldehyde (CHOCH2OH) and ethylene glycol (HOCH2CH2OH) are among many complex organic molecules detected in the interstellar medium (ISM). Astrophysical models proposed very often that the formation of these compounds would be directly linked to the hydrogenation of glyoxal (CHOCHO), a potential precursor which is not yet detected in the ISM. We have performed, in this work, surface and bulk hydrogenations of solid CHOCHO under ISM conditions in order to confirm or invalidate the astrophysical modelling of glyoxal transformation. Our results show that the hydrogenation of glyoxal does not lead to the formation of detectable amounts of heavier organic molecules such as glycolaldehyde and ethylene glycol but rather to lighter CO-bearing species such as CO, H2CO, and CO–H2CO, a reaction intermediate resulting from an H-addition–elimination process on CHOCHO and where CO is linked to H2CO. The solid phase formation of such a reaction intermediate has been confirmed through the neon matrix isolation of CO–H2CO species. Additionally, the CHOCHO + H solid-state reaction might also lead to the production of CH3OH formed under our experimental conditions as a secondary product resulting from the hydrogenation of formaldehyde.

A Meta-Analysis Evaluating the Risk of Bleeding-Related Adverse Events with Defibrotide Treatment

Introduction: Defibrotide is approved for adult and pediatric patients with hepatic veno-occlusive disease/sinusoidal obstruction syndrome (VOD/SOS) with renal or pulmonary dysfunction after hematopoietic cell transplantation (HCT) in the United States and Canada and for patients aged >1 month with severe hepatic VOD/SOS post-HCT in the European Union. The recommended dose is 6.25 mg/kg every 6 hours given as a 2-hour intravenous (IV) infusion. Defibrotide has been shown in vitro to reduce endothelial cell (EC) activation and promote EC-mediated fibrinolysis. Post-HCT patients with VOD/SOS are often at a high risk for bleeding events. In a phase 3 study of patients with VOD/SOS post-HCT, rates of bleeding-related adverse events (AEs) with defibrotide were generally similar to matched historic controls (Richardson PG, et al. Blood. 2016;127[13]:1656-1665). To broaden our understanding of the risk of bleeding events associated with defibrotide treatment, this meta-analysis assessed the incidence and risk of bleeding-related AEs with defibrotide treatment in studies outside of the VOD/SOS and HCT setting, using published literature. Methods: PubMed and Embase were searched from database inception through July 24, 2018 for studies using defibrotide (controlled trials with ≥1 arm assessing an intervention of interest, observational/retrospective studies, retrospective or post hoc analyses, and case series with ≥10 patients). Studies of patients with VOD/SOS or HCT, case reports with <10 patients, and reviews were excluded. Publications were evaluated for the presence of data on endpoints of interest, which included any bleeding-related event and overall safety or efficacy summaries; all studies with available data were included in the analysis. Overall bleeding rate was estimated for defibrotide and controls using the Freeman-Tukey double arcsine transformation and random-effects modeling (Stata Software). The risk ratio of bleeding was calculated using the Mantel-Haenszel method and random-effects modeling (RevMan 5.3 Software). Overall bleeding rate and risk ratio of bleeding were calculated from studies that used the IV defibrotide formulation; studies using oral or intramuscular formulations were excluded from these calculations. Results: A total of 1,857 records were identified in the search; 124 studies reported on defibrotide and 19 contained data related to bleeding and were included in the analysis. Of the 19 included studies, 2 had >1,000 patients. An IV defibrotide formulation was used in 12 studies; the other 7 used intramuscular or oral delivery or more than one method of defibrotide administration. The most common indications were prevention of deep vein thrombosis (11 of 19) and treatment of thrombosis (3 of 19). Most studies (14 of 19) had 2 treatment arms; among these studies, heparin was the most common comparator (11 of 14). For the other 5 of 19 studies, 4 studies were single-arm and 1 study had 3 arms. The majority of studies (16 of 19) were conducted in adults; the other 3 studies did not specify patients' age. The most commonly administered defibrotide dose was 800 mg daily (14 of 19 studies). Bleeding rate and risk ratio of bleeding were calculated based upon data from the 12 studies that used IV defibrotide. Rates of bleeding events reported in the 12 studies with IV defibrotide ranged from 0% to 10% in individual studies and the estimated overall bleeding rate was 1% (95% confidence interval [CI]: 0.00-0.03). In 10 studies with control treatments (9 calcium heparin, 1 urokinase), rates of bleeding events ranged from 1% to 37%, with 7 studies having rates ≥10%. Across the 10 control studies, the estimated overall bleeding rate for controls was 11% (95% CI: 0.05-0.20). Among the 8 studies with available data on IV defibrotide and controls (7 calcium heparin, 1 urokinase), the risk ratio for bleeding events with IV defibrotide versus controls was 0.36 (95% CI: 0.24-0.52; P <0.00001; Figure). Conclusions: This meta-analysis of defibrotide use outside of the VOD/SOS setting suggests that the bleeding risk with defibrotide is low, and there is comparable risk of bleeding with defibrotide treatment versus controls such as heparin or urokinase. Important limitations of this analysis include variations in AE reporting across studies and the use of a defibrotide dose that is lower than the currently approved recommendation in the majority of studies. Disclosures Tappe: Jazz Pharmaceuticals: Employment, Equity Ownership. Aggarwal:Jazz Pharmaceuticals: Consultancy. Topaloglu:Jazz Pharmaceuticals: Consultancy. Iacobelli:Massimo Iacobelli: Consultancy. OffLabel Disclosure: The abstract describes a meta-analysis of defibrotide (indicated for VOD/SOS) in the non-VOD/SOS setting. As this analysis drew data from existing literature, no patients were administered defibrotide for off-label indications in the course of this analysis.

Modeling of Martensite Transformation in White Layer under Thermo-mechanical Coupling in Hard-Cutting Process

Martensite volume fraction determines the hardness and wear resistance of workpiece, predicting the martensite volume fraction of the white layer is of great significance for improving the surface quality of the workpiece. Accordingly, a theoretical model on the martensite volume fraction was developed in combination with the martensite transformation temperature model and the hard-cutting FE model. A finite element (FE) model of the hard-cutting was established to obtain the stress distribution of the workpieces. A calculation model of martensite phase transformation temperature $$M_{\text{S}}$$ under the influence of the cooling rate and stress was deduced based on the change of Gibbs free energy. A theoretical model of martensite volume fraction $$f_{\text{M}}$$ of the white layer was developed based on the $$M_{\text{S}}$$ and the FE simulations. The $$f_{\text{M}}$$ calculated by the theoretical model is in accordance with the experimental result. The effects of cutting speed, feed rate, flank wear and tool rake angle on the $$f_{\text{M}}$$ in the white layers were predicted and analyzed; the results show that the $$f_{\text{M}}$$ decreases first and then increases with the cutting speed, decreases with the feed rate and the flank wear, and increases with the tool rake angle.

Geochemical modelling of multimineral evolution for a 15-month experiment

The impact of hyper-alkaline leachate released from the cementitious barrier of a geological disposal facility on the host rock is a significant issue for the safety assessment of long-term nuclear disposal. However, modelling of multimineral transformations, multiple chemical reactions and multiple secondary-phase pathways remains a challenge due to uncertainties in parameters and a limited available database describing the kinetics of dissolution/precipitation reactions. In this study, a new modelling approach, mixed kinetic–equilibrium, was employed to study the complex reactions occurring in an experimental system consisting of Borrowdale Volcanic Group rocks permeated with a hyper-alkaline leachate for over 15 months. The modelling suggests that dissolution of primary dolomite, quartz, calcite and potassium (K) feldspar in the host rock initially drives the chemical evolution of this system. The subsequent precipitation of several secondary phases, including calcite, brucite, talc and calcium–silicate–hydrate phases, is predicted to control the long-term chemical equilibria and mineralogical composition of the host rock impacted by the alkaline leachate. The results from the modelling provide a deeper understanding of the long-term interactions between the host rock and high pH leachate, with dolomite predicted to be a major controlling phase on the geochemical evolution of the system.

ANALYSIS OF SOIL ORGANIC MATTER TRANSFORMATION DYNAMICS MODELS

In this paper we consider the models describing the dynamics of soil organic matter transformation. The results of practical implementation of the ROMUL, CENTURY and ROTHAMSTED models are presented. These models propose theoretical approaches to the modelling of organic remains transformation based on describing physicochemical processes during humus formation with differential relations. Following the analysis, their strengths and weaknesses have been distinguished.

Математическое моделирование миграции и многостадийных превращений химических веществ в подземных водах

Математическое моделирование миграции и многостадийных превращений химических веществ в подземных водах

Advanced selective key point detection techniques

SAR imaging needs precise registration process to get recompensation or setoff between two or more images for a certain area. Generally, operational goal of registration process is a geometrical transformation for the input leading to geometrically agreement for input images. Coregistration step can be used in a lot of fields as change detection, mosaicking, super-resolution images creation, … etc. Registration process can be classified into two main classes: Classical or Automatic methods. For the classical approach, the anchor points are picked out manually and then the transformation modeling is performed, that leads to more time consuming and low output accuracy. Automatic detection of these anchor points aims to recover the functionality of non-automated processes. Registration process should recover many problems such as illumination changes, variations of intensity, Different sensors, noise, … etc. Its applications are mainly dependent on errors, such as multi temporal; multi view; or multi modal, occurred during capturing process. Feature detection, as a step of image registration process, obtains a group of anchors, that are stable and informativeness, or patches under varying conditions. Also, it is critical for the detector to have robustness against viewpoint changes, brightness changes, and other deformations. Detailed discussion and investigation are paid, in this manuscript, for the common corner detectors helping to be familiar with the various applied techniques for feature detection. Our goal is to examine a combination hypothesis of these methods into an advanced selective one.

(Invited) Mesoscale Modeling of Solid-State Hydrogen Storage Mechanisms

Metal hydrides have been considered as a promising class of solid-state hydrogen storage materials owing to their excellent volumetric and gravimetric storage densities, which can overcome critical technological limits of the currently available high-pressure hydrogen gas storage approach. Solid-state hydrogen storage mechanisms involve the complicated coupling of chemical/physical processes over vast ranges of multiple length and time scales. These include surface reactions with hydrogen gas; surface/bulk/interface mass transport processes; structural modifications occurring under operation; and intermediate phase nucleation-and-growth processes associated with hydrogen incorporation. Essentially, these are collective dynamic processes of atomic/molecular species that determine the thermodynamics and kinetics of nano- or micro-level characteristics. The mesoscale continuum modeling framework can provide a unified platform for integrating the necessary atomistic approaches, which typically provide higher accuracy for nanoscale chemical processes, and continuum approaches, which offer far greater flexibility and scalability and can describe materials at the microstructural level. In this presentation, we demonstrate our integrated effort as part of the DOE Hydrogen Storage Materials—Advanced Research Consortium(HyMARC) under the Energy Materials Network(EMN) towards the multiscale modeling of hydrogen storage mechanisms in metal hydrides for hydrogen storage. Specifically, we will report our recent efforts on the development of an integrated mesoscale modeling framework that can directly incorporate parameters derived from predictive atomistic modeling approaches such as ab initiocalculations and molecular dynamics simulations. Representative case studies will be presented, including beyond-ideal thermodynamic modeling of complex hydrides, effective mass transport/mechanical response modeling for complex hydride microstructures, and phase-field modeling of reaction-induced phase transformations of simple or complex metal hydrides during the (re/de)hydrogenation.

Pothole Detection Based on Disparity Transformation and Road Surface Modeling.

Pothole detection is one of the most important tasks for road maintenance. Computer vision approaches are generally based on either 2D road image analysis or 3D road surface modeling. However, these two categories are always used independently. Furthermore, the pothole detection accuracy is still far from satisfactory. Therefore, in this paper, we present a robust pothole detection algorithm that is both accurate and computationally efficient. A dense disparity map is first transformed to better distinguish between damaged and undamaged road areas. To achieve greater disparity transformation efficiency, golden section search and dynamic programming are utilized to estimate the transformation parameters. Otsu's thresholding method is then used to extract potential undamaged road areas from the transformed disparity map. The disparities in the extracted areas are modeled by a quadratic surface using least squares fitting. To improve disparity map modeling robustness, the surface normal is also integrated into the surface modeling process. Furthermore, random sample consensus is utilized to reduce the effects caused by outliers. By comparing the difference between the actual and modeled disparity maps, the potholes can be detected accurately. Finally, the point clouds of the detected potholes are extracted from the reconstructed 3D road surface. The experimental results show that the successful detection accuracy of the proposed system is around 98.7% and the overall pixel-level accuracy is approximately 99.6%.

Multiphysics modeling of phase transformation and microhardness evolution in laser direct deposited Ti6Al4V

This paper investigates the phase transformations occurring in laser direct deposited Ti6Al4V and assesses the microhardness of the as-built components using predictive modeling tools. A three-dimensional laser direct deposition (LDD) model was utilized to predict the geometry and thermal history of the multi-track LDD process. The predicted free surface geometry, fusion zone (FZ) and heat affected zone (HAZ) boundaries were in good agreement with experimental results. Temperature profiles and cooling rates were extracted from the validated LDD model and incorporated into a two-dimensional phase prediction model to determine phase transformations in FZ and HAZ regions. In the FZ, the high peak temperature and high cooling rate produced a complete α’ martensitic microstructure, which was predicted with the phase transformation model and observed experimentally. Within the HAZ, a low peak temperature and correspondingly low heating and cooling rates led to a mixture of α’ martensite, transformed and untransformed α phase in the final microstructure. When depositing the subsequent tracks, the LDD process produces overlapped HAZ regions, which contain a higher volume fraction of α’ martensite due to the repeated heating cycles. Based on the volume fraction of α’ martensite and α phase in the final microstructure, the microhardness within different zones of a three-track Ti6Al4V deposit was accurately predicted.

Heat flow model based on lattice Boltzmann method for modeling of heat transfer during phase transformation

PurposeA fundamental principle of materials engineering is that the microstructure of a material controls the properties. The phase transformation is an important phenomenon that determines the final microstructure. Recently, many analytical and numerical methods were used for modeling of phase transformation, but some limitations can be seen in relation to the choice of the shape of growing grains, introduction of varying grain growth rate and modeling of diffusion phenomena. There are also only few comprehensive studies that combine the final microstructure with the actual conditions of its formation. Therefore, the objective of the work is a development of a new hybrid model based on lattice Boltzmann method (LBM) and cellular automata (CA) for modeling of the diffusional phase transformations. The model has a modular structure and simulates three basic phenomena: carbon diffusion, heat flow and phase transformation. The purpose of this study is to develop a model of heat flow with consideration of enthalpy of transformation as one of the most important parts of the proposed new hybrid model. This is one of the stages in the development of the complex model, and the obtained results will be used in a combined solution of heat flow and carbon diffusion during the modeling of diffusion phase transformations.Design/methodology/approachDifferent values of overheating/overcooling affect different values in the enthalpy of transformation and thus the rate of transformation. CA and LBM are used in the hybrid model in part related to heat flow. LBM is used for modeling of heat flow, while CA is used for modeling of the microstructure evolution during the phase transformation.FindingsThe use of LBM and CA in one numerical solution creates completely new possibilities for modeling of phase transformations. CA and LBM in comparison with commonly used approaches significantly simplify interface and interaction between different parts of the model, which operates in a common domain. The CA can be used practically for all possible processes that consist of nucleation and grains growth. The advantages of the LBM method can be well used for the simulation of heat flow during the transformation, which is confirmed by numerical results.Practical implicationsThe developed heat flow model will be combined with the carbon diffusion model at the next stage of work, and the new complex hybrid model at the final stage will provide new solutions in numerical simulation of phase transformations and will allow comprehensive modeling of the diffusional phase transformations in many processes. Heating, annealing and cooling can be considered.Originality/valueThe paper presents the developed model of heat flow (temperature module), which is one of the main parts of the new hybrid model devoted to modeling of phase transformation. The model takes into account the enthalpy of transformation, and the connection with the model of microstructure evolution was obtained.

Formation Transformation Based on Leader-Follower Algorithm

A method based on the leader-follower algorithm is proposed for transformation among the formations. The introduction of the greedy algorithm, behavior-based control and virtual structure help realize the region division and the calculation of the distribution of the leaders and followers in target formation. Collision detection and collision avoidance are proposed to solve path conflicts with error free feedback and effectively maintain the stability of motion. The modeling of transformation is simulated by the shape from a line to a wedged, in which the formation is adjusted by the distance difference obtained by feedback. The experimental results show that it is feasible and effective to implement the formation conversion and formation control, and the system possess a better robustness and stability.

Human capital of the Arctic: problems and development prospects

The goal of the present research is to make comparative analysis of the development of human capital of circumpolar countries as the primary factor of sustainable development of the Arctic regions. In the context of Russia’s Arctic policy formation, the study of foreign countries experience in the development of human capital in the Arctic territories is seen by us particularly topical. In the course of the study, the main characteristics of the Arctic territories of the circumpolar states were identified, and their specific characteristics were determined. These include low population density, uncomfortable weather and climatic conditions, inaccessibility and farness of settlements from economic and administrative centres, the raw material orientation and non-diversified nature of the economy. The multidirectional migration processes, as well as migration influence on the characteristics of the population and, hence, on the structure and quality of human capital were determined as essential features of the territorial development of circumpolar countries. The main problems of the qualitative accumulation and effective use of human capital in the Arctic territories of the circumpolar countries, the key of which is the phenomenon of unemployment, were revealed. For the Arctic territories of Russia, poverty of the population, a high proportion of poor families with children, and low life expectancy have been were defined as a threat to the degradation of human capital. The general strategic lines of circumpolar states in the development of the Arctic territories which are relevant for the Russian state regulation of the development of the Arctic territories were determined. The study was carried out within the framework of project AAAA-A18-118051590118-0 “Comprehensive interdisciplinary research and economic and mathematical modeling of the socio-economic transformation and management of regions and municipalities of the North-Arctic territories of Russia”.

Model driven transformation development (MDTD): An approach for developing model to model transformation

Abstract Context In the Model Driven Development (MDD) approach, model transformations are responsible for the semi-automation of software development process converting models between different abstraction levels. The development of model transformations involves a complexity inherent to the transformation domain, in addition to the complexity of software development in general. Therefore, the construction of model transformations requires software engineering feature such as processes and languages to facilitate its development and maintenance. Objective This paper presents a framework to develop unidirectional relational model transformation using the MDD approach itself, which integrates: (i) a software development process suitable for the model transformation domain (ii) a Domain specific language for transformation modeling (iii) a transformation chain, to (semi) automate the proposed process, and (iv) a development environment to support it. Methods The proposal systematizes the development of model transformation, following the MDD principles. An iterative and incremental process guides transformation development from requirement specification to transformation codification. The proposal has been evaluated through a case study and a controlled experiment. Results The framework enables model transformation specification at a high abstraction level and (semi) automatically transforms it into models at a low abstraction level until the transformation code. The results of the case study showed that people with different levels of knowledge of MDD, or without experience in transformation languages, were able to develop transformations through the framework and generated executable code. Conclusions The framework integrates the essential elements involved in the development of model transformation and enables the abstraction of technological details. The results of the case study and controlled experiment showed the feasibility of the proposal and its use in dealing with the complexity involved in model transformation development.

PORTFOLIO DIVERSIFICATION AND OIL PRICE SHOCKS: A SECTOR WIDE ANALYSIS

This paper investigates the time-varying relationship between the oil price and disaggregated stock market of India using Dynamic conditional correlation multivariate GARCH and Continuous Wavelet Transformation modelling approaches. Our findings reveal the evolving relationship between the oil price and disaggregated stock market. The correlations are generally volatile before the 2007-08 crisis but since then the correlations are positive implying no diversification benefits for the investors during rising oil prices. As emerging markets in general, and India in particular, is expected to increase its share of oil consumption in the world's energy market, therefore for the stock market to grow, especially the oil-intensive industries, we recommend the government should increase its reliance on alternative energy resources. Furthermore, as rising oil prices can also have its adverse effect through exchange rate channel, we suggest the monetary policies should be time varying to manage the oil inflationary pressures arising out of extreme volatility in the oil prices.Keywords: DCC-GARCH, CWT, Disaggregated stock market, India, Oil price shocks, Diversification.JEL Classifications: C50; G10; O53; Q43DOI: https://doi.org/10.32479/ijeep.7747

New insights on nucleation and transformation process in temperature-induced martensitic transformation

Understanding mechanisms of the nucleation and transformation sequence is of critical importance to control temperature-induced martensitic transformations and hence retained austenite. In the present work, quasi-in-situ Electron Backscattering Diffraction and Transmission Electron Microscopy were employed to investigate the nucleation and transition in a prototype austenitic stainless steel. Detailed evidence was provided, that nucleation could occur on new defects generated during cryogenic treatment, and not just on pre-existing defects. Moreover, transformation follows both austenite → ε-martensite → α′-martensite and austenite → α′-martensite routes, their associated mechanisms, and crystallographic characteristics were analysed. These new insights could provide further guidelines for the optimization and modelling of martensitic transformation.

Physical and Numerical Modeling of Infragravity Wave Generation and Transformation on Coral Reef Platforms

AbstractWave transformation across reef platforms strongly controls sediment transport processes and coral reef island morphodynamics with infragravity (IG) waves playing an important contributing role. A small‐scale (1:50) laboratory experiment and prototype numerical modeling are used to explore the characteristics of IG wave motion on coral reefs. The slope of the fore reef is the key factor controlling the mechanism of IG wave generation. Steep slopes (>1/10) are dominated by landward and seaward propagating breakpoint‐forced long waves, whereas incoming and then released bound long waves become increasingly important for slopes <1/20. The breakpoint‐forced long wave mechanism is the more effective generator of IG energy, and the most energetic IG motion (normalized by incident wave motion) is generated on reef platforms with a fore reef slope > 1/6. The water level relative to the reef platform hreef is also a key factor, and the largest IG waves are generated for a ratio between hreef and offshore significant wave height Hs,o of −0.25 to 0.75, that is, when most waves break across the reef slope and a fully saturated surf zone extends across the reef platform. An island on the reef platform substantially increases the contribution of IG waves to the total wave spectrum, but increased reef surface roughness reduces IG importance. Under the most optimal conditions, the IG wave height averaged across the platform is 20–30% of the incident offshore wave height. The geomorphic influence of IG waves is considered most significant for reef platforms with energetic waves breaking on the steepest fore reefs.

New York City Panel on Climate Change 2019 Report Chapter 5: Mapping Climate Risk

New York City Panel on Climate Change 2019 Report Chapter 5: Mapping Climate Risk

Cellular Automaton Modeling of Phase Transformation of U-Nb Alloys during Solidification and Consequent Cooling Process

Abstract The microstructure evolution of U-Nb alloys during solidification and consequent cooling process was simulated using a cellular automaton (CA) model. By using this model, ϒ phase precipitation and monotectoid decomposition were simulated, and dendrite morphology of ϒ phase, Nb microsegregation and kinetics of monotectoid decomposition were obtained. To validate the model, an ingot of U-5.5Nb (wt.%) was produced and temperature measuring experiment was carried out. As-cast microstructure at different position taken from the ingot was investigated by using optical microscope and SEM. The effect of cooling rate on ϒ phase precipitation and monotectoid decomposition of U-Nb alloys was also studied. The simulated results were compared with the experimental results and the capability of the model for quantitatively predicting the microstructure evolution of U-Nb alloys during solidification and consequent cooling process was assessed.