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Nanofiltration guarantees high water recovery and low energy consumption in removing micropollutants (MPs). In this study, we derive a concise model to describe MP removal with nanofiltration membranes. We compare the results from the model with experimental data for the removal of 7 MPs with 5 salt concentrations using the NF270 membrane. Our findings indicate that the model accurately describes MP transport through nanofiltration membranes. Furthermore, we evaluate the effect of salt concentration on MP rejection. The results show that salt concentration impacts MP rejection differently based on MP charge and size. Increasing salt concentration decreases the rejection of counter-charged MPs that are small and increases the rejection of counter-charged MP that are large.

Designing and optimizing optical amplifiers to maximize system performance is becoming increasingly important as optical communication systems strive to increase throughput. Offline optimization of optical amplifiers relies on models ranging from white-box models deeply rooted in physics to black-box data-driven and physics-agnostic models. Here, we compare the capabilities of white-, gray- and black-box models on the challenging test case of optimizing a bidirectional distributed Raman amplifier to achieve a target frequency-distance signal power profile. We show that any of the studied methods can achieve similar frequency and distance flatness of between 1 and 3.6 dB (depending on the definition of flatness) over the C-band in an 80-km span. Then, we discuss the models’ applicability, advantages, and drawbacks based on the target application scenario, in particular in terms of flexibility, optimization speed, and access to training data.

The term ‘Sifu’ in Chinese denotes a ‘teacher’ or ‘master’ and is used to describe an individual who has attained significant expertise and mastery in a specific field, often within martial arts. In this paper, we describe the bond between us and our sifu in computer science, Professor Wang Yi.

The results of solving the problem of modeling the interaction of iron Fe3+ nanoparticles with thin bilayer membranes were represented. The purpose of the work was to create a physical model of the behavior and interaction of Fe3+ iron nanoparticles, which are located near thin films of organic substances. For this, physical model systems with thin films - BPM (bilayer phospholipid membranes) and BLM (bilayer lipid membranes) were considered and analyzed, and iron nanoparticles were introduced into these systems. To fulfill the given task, the data search methods ("data mining") obtained by the gas-liquid chromatography were used, as well as ones obtained in experiments with registration of transmembrane electric currents through artificial two-layer BPM and BLM membranes, and partially ones from the experiments on natural membranes with technique of voltage clamp. Since the applied FeCl3 undergoes hydrolysis, the formed hydroxyl groups interact with BLM membranes, also participating in the sum of interaction effects. Thus, it was concluded about the important role of hydroxyl groups in the mechanism of anionic selectivity of BLM, which is a confirmation of previously obtained research data. A number of effects with participation of ionophores, which increase the ion permeability of artificial BLM membranes, were also considered; they can bind metal ions due to ion-dipole interaction. The described system with a membrane and iron (III) ions located near it can be used to study a number of phenomena on both artificial and natural membranes, for example, when iron nanoparticles were absorbed by human body from the environment. For all considered cases, known physical and physico-chemical regularities and the corresponding developed mathematical apparatus were verified. Namely, analytical expressions based on electrostatic interactions of electric charges associated with Fe3+ ions and localized on membrane surfaces were valid for describing the considered effects. The

In this work, the photocatalytic degradation process under visible light in a batch photoreactor was investigated using computational fluid dynamics (CFD). The removal of tetracycline (TC) by the ZnO/PbBiO2Cl photocatalyst was modeled using the single organic species model based on Langmuir-Hinshelwood kinetics. In addition, the hydrodynamic behavior of the two-phase flow inside the photoreactor was simulated using the Eulerian-Lagrangian approach. In this study, the kinetic of the degradation reaction, velocity field of suspension, and concentration of TC were investigated. Based on the CFD results, it has been determined that a rotational velocity of 250 rpm in the reactor is the optimal speed that leads to the highest homogeneity (approximately 95 %) in suspension. Therefore, more light is absorbed by performing experiments in high-quality mixing, and maximum degradation can be achieved. The kinetic study showed that the degradation rate follows pseudo-first-order kinetics. The effect of different weight percentages of PbBiO2Cl and various loading of ZnO/PbBO2Cl on the degradation rate was also examined. The results showed that the 0.5 g/l of ZnO/PbBO2Cl (40 %) is the optimal amount. The degradation reaction kinetic constant was also calculated about 200 × 10−4 min−1. Finally, the obtained modeling results demonstrate excellent agreement with the experimental data.

Anthropogenic activities, such as using fossil fuels for energy production, synthesizing carbon-based products, and employing nitrogen fertilizers to meet the ever-growing food demand, have drastically disrupted the planet's carbon and nitrogen cycles. These activities effectively lead to global warming, eutrophication, and NOx production. Hence, the world is in need of coming up with new sustainable technological advancements to meet the demands of fuel synthesis, carbon-based material manufacturing and food production without impacting the world's natural carbon and nitrogen cycles. One proposed solution is to utilize pyrolysis of sustainable biomass to produce biochar, bio-oil, and pyrolysis gas. The bio-oil obtained from this process can be used in a CO2 reforming step, effectively converting it into syngas with a suitable H2/CO ratio for chemical synthesis or fuel production. The produced biochar can, through a CO2 activation step and adsorption of nitrogen, be used as a fertilizer. Lastly, combustion of the produced pyrolysis gas generates energy for the other processes in the system. In this master thesis, the aim was to evaluate the impact of the process on carbon and nitrogen cycles, analyze energy and carbon flows throughout the process, and optimize operational conditions to maximize syngas production. In addition, the study also addressed several research questions. These included investigating whether the process necessitates the introduction of external sustainable energy, and assessing the overall environmental impact of the process. To answer these research questions and overall aim, a model of the process was made in Aspen Plus V.14 in combination with a literature study on the biochars effect on the nitrogen cycle. The results indicate that up to 70% of the carbon going into the process can be successfully sequestered through the optimization of pyrolysis for bio-oil production and subsequently of syngas yield in CO2 reforming. The study also saw t, Biomassa och Teknologi för en Hållbar Framtid Genom pyrolys omvandlas biomassa till biokol, bioolja och biogas, vilket minskar beroendet av fossila bränslen och ger hållbara kemikalier, bränslen och energi. Detta motverkar global uppvärmning samtidigt som biokolet minskar behovet av gödningsmedel, vilket motverkar övergödning av våra sjöar och hav. Sedan den industriella revolutionen har människan använt kol och olja till allt från energi, tillverkning av plaster och läkemedel, samt för att värma våra hem och driva våra bilar. Denna användning har släppt ut stora mängder koldioxid (CO2) i atmosfären, vilket i sin tur lett till den globala uppvärmningen. Samtidigt har avverkning av skogar, som annars skulle absorbera CO2 genom fotosyntesen, ytterligare rubbat det naturliga kolkretsloppet. Dessutom har överanvändning av kvävebaserade gödningsmedel rubbat kvävekretsloppet och orsakat övergödning i våra sjöar och hav, vilket har påverkat många ekosystem. För att återställa balansen i dessa kretslopp på vår planet måste vi hitta nya teknologier för att hantera dessa problem. En föreslagen lösning är pyrolys av trä, stjälkar och matavfall. Pyrolys innebär att organiskt material upphettas till temperaturer ofta runt 300 upp till 1300 grader Celsius utan av syre. Detta bryter ner biomassan till biokol, bioolja och biogas istället för koldioxid och vatten som vid förbränning. Dessa produkter har flera användningsområden: biokolet kan modifieras och användas som gödningsmedel, biooljan kan genom CO2-reformering omvandlas till syngas för tillverkning av kemikalier och bränslen, och biogasen kan förbrännas för att ge energi till resten av processen. Processen är inte bara koldioxidneutral utan även kol negativ, vilket innebär att den tar bort koldioxid från atmosfären och binder den i biokol och syngasprodukter. Detta kan hjälpa till att återställa ett naturligt kol- och kvävekretslopp och motverka global uppvärmning och övergödning. Målet med det här exjobbet var att utvärdera

Arenas and large entertainment venues host significant crowds during events, presenting challenges in evacuation safety management, particularly during emergencies such as fires or terrorist threats. In this study, critical aspects of arena evacuation are investigated, with a focus on methodology to identify local densities in key three-dimensional arena spaces where merging flows occur during emergency evacuations. Through a literature review, existing research and theories related to evacuation safety in arenas are analyzed, emphasizing the importance of considering local densities in evacuation planning. Additionally, a simplified method for measuring local density in 3D is developed, mainly for the key areas where merging flows occur at different levels, improving the overall safety of the evacuation process. Furthermore, evacuation simulations may present issues in representing flow and density at highly congested merging points such as stairs and gates. Consequently, a simple control volume method for crowd density measurement is proposed, providing an easy approach to quantifying local density in critical areas of the arena. This method was applied to a small-scale experiment using real-world data. The resulting crowd density measurements obtained through the control volume method were then compared with those obtained from modeling the same experiment using an appropriate evacuation model that is suitable for high local density scenarios. Moreover, a case study has been conducted (the Pala Alpitour Arena) to offer insights into crowd movement and evacuation dynamics in a real-world setting with high local density at merging points. Through simulating evacuation scenarios at full capacity, the study highlights critical factors influencing evacuation dynamics, particularly in areas with high local densities., Arenas and other sports grounds host thousands of people during events, presenting challenges in terms of evacuation safety management, particularly during emergencies such as fires. While existing safety regulations typically focus on global density metrics, there is a growing recognition of the importance of assessing local densities in evacuation planning. The aim of the thesis is to define simple methodology to identify local densities in key three- dimensional arena spaces where merging flows occur during emergency evacuations. As effective crowd management requires consideration not only of the global density but also of the local density using a simple method for estimation. The thesis will also verify the applicability of adopting evacuation modeling for high local density scenarios in arenas. This study has reviewed existing research and theories, highlighting the importance of considering local densities in evacuation planning. Traditional approaches often rely on global density, overlooking the intricacies of crowd behavior in critical areas of arenas. By developing a simple method for measuring local density in 3D, the overall safety of the evacuation process is improved. The simple control volume method is applied on a small-scale test. The local densities and the flows are obtained. Those results from the real-world data are compared to the modeling results for the same layout of the test. The modeling results showed relatively lower values compared to the real-world result particularly in terms of flow and density at the merging points of stairs and gates. The modeled outflow from the stairs was lower than observed in reality, affecting both stair density and evacuation time. Additionally, the reduced outflow from the stairs resulted in lower inflow at the gates, decreasing gate density compared to real-world data. The main findings showed that while a straightforward method using control volumes provides useful insights, current evacuation models str

In the past decade, there has been a major shift in automotive propulsion systems from fossil fuel vehicles to environmentally friendly, zero-emission transportation. This has made hydrogen-powered vehicles a hot topic. Volvo Group has launched a fuel cell truck to promote energy transition. A fuel cell consists of two electrodes (anode and cathode) and an electrolyte membrane inserted between them. A single fuel cell can produce a theoretical voltage of about 1.2 volts. Proton exchange membrane fuel cells (PEMFCs) are considered to be commercially promising fuel cells due to their high efficiency, low-temperature operation, high power density, fast start-up, and system robustness. However, in reality, the voltage output will drop due to various polarization losses. In order to effectively utilize fuel cells, mathematical models must be established to predict the system behaviour under different conditions such as load current, reaction gas pressure, temperature, and stack voltage through computer simulation during the design stage. Research shows that PEMFC faces some problems when operating below 80°C and above 120°C. Medium-temperature PEMFC can achieve a good balance. However, it is still unclear how changes in each parameter within the fuel cell will affect the output performance. This thesis combines previous research and attempts to explain the effects of different parameters on the polarization curve in the model. This work will provide direction for the calibration of more accurate fuel cell models., The research objective of this paper is fuel cells. Fuel cells are a power generation device that can convert the energy stored in hydrogen into electrical energy. Because the reaction of hydrogen and oxygen only produces water, fuel cells are ideal for clean energy. At the same time, because there is no movable structure in the components of fuel cells, they are easy to produce and have a long life. There is a great development prospect in the future. Among many different types of fuel cells, proton exchange membrane fuel cells are the fuel cells with the most commercial potential. Because they are lighter than other designs and have lower operating temperatures and higher efficiency. They can also be started and stopped quickly when in use. They can be used to make fuel cell vehicles. It is currently found that proton exchange membrane fuel cells operating at temperatures of 80℃ to 120℃ have many advantages. Including fast reaction rate and low cooling system load. To predict and analyze the working performance of this fuel cell, it is necessary to model and analyze it on a computer. The purpose of this study is to determine in which direction more detailed modelling needs to be developed in the future through simple model construction. At the end of this thesis, a model with an acceptable of accuracy was obtained under a relatively simple setting, and some suggestions for further modelling in the future were put forward. Including further analysis of the movement process of the reactants inside the fuel cell and quantitative research on certain specific parameters.

Lack of eye contact and imitation deficits are frequently targeted in behavioral interventions for children with autism spectrum disorder (ASD). In this study, we examined the effects of prompting and modeling on the imitation skills and eye contact of three Arabic-speaking young children with ASD in Syria. A multiple baseline design with a withdrawal component was used to evaluate the effects of the intervention in a clinical setting, at a center for children with special needs, and in follow-up sessions conducted in the participants’ homes. All participants’ imitative responses and eye contact increased when prompting and modeling were used. Our findings support the effectiveness of prompting and modeling on imitation skills.

Le collage est une problématique qui survient lors du pressage des comprimés pharmaceutiques. Son occurrence résulte en l’obtention de comprimés défectueux réduisant ainsi l’efficacité du procédé de pressage. Malgré toutes les récentes études portant sur le collage, les mécanismes conduisant à son avènement ne sont pas connus. Ainsi, une étude phénoménologique du procédé de pressage s’avère nécessaire. La recherche dans cette thèse a comme hypothèse que les molécules d’eau contenues dans les particules de poudre sont la cause probable du déclenchement du mécanisme conduisant au collage. Ainsi l’objectif général de cette investigation est l’étude du comportement du contenu en eau des particules de poudre au cours du pressage. Dans un premier temps, les coefficients de transport de l’humidité dans les comprimés pharmaceutiques ont été déterminés en se basant sur le test standard ASTM D6539. Les poudres pharmaceutiques étant hygroscopiques, l’hélium a été utilisé comme gaz pour déterminer la perméabilité absolue, les coefficients de diffusivité, de transfert et de perméabilité de l’humidité dans les comprimés à différentes densités relatives. Les coefficients déterminés ont été utilisés dans un deuxième temps pour modéliser le comportement des molécules d’eau au cours du pressage. Le logiciel de simulation numérique COMSOL Multiphysics 5.4 a été utilisé. Les modèles phénoménologiques de Drucker-Prager-Cap et de HAM (Heat, Moisture and Air) ont permis de simuler les variations thermomécaniques et de teneur en eau dans le lit de poudre au cours du pressage. La densité relative des comprimés fabriqués, une sonde proche infrarouge et une caméra thermique ont permis de valider les résultats thermomécaniques et de variation d’humidité obtenus avec la modélisation. La modélisation a montré que le contenu en eau des particules de poudre s’évapore au cours du pressage sous l’effet de l’augmentation de la température du lit de poudre. La mesure de la teneur en eau de surface des, Sticking is a problematic that occurs during the pressing of pharmaceutical tablets. Its occurrence results in defective tablets thus reducing the efficiency of the tableting process. Despite all the recent studies on tablet sticking, the mechanism leading to its build-up is not well understood. Therefore, a phenomenological study of the tableting process becomes necessary. The work presented in this document assumes that the water content of the powder particles triggers the mechanism leading to sticking. Consequently, the general objective of this investigation is the study of the behavior of the powder particles water content during tableting. Initially, the moisture transport coefficients in pharmaceutical tablets were determined based on the ASTM D6539 standard test. Since pharmaceutical powders are hygroscopic, helium was used to determine the absolute permeability, diffusivity, transfer, and permeability coefficients of moisture in tablets at different relative densities. Furthermore, these coefficients were used to simulate the behavior of water molecules during tableting. The numerical simulation software COMSOL Multiphysics 5.4 was used. The phenomenological models of Drucker-Prager-Cap and HAM (Heat, Moisture and Air) were used to simulate the thermomechanical variations and water content in the powder bed during tableting. The relative density of the manufactured tablets, a near-infrared probe and a thermal camera were used to validate the thermomechanical and water content variation results obtained with the modeling. The simulation results showed that the water content of the powder particles evaporates during tableting because of the increase of the powder bed temperature. The measurement of the tablets surface water content just after ejection showed that the surface water content is higher than that of the initial powder fed into the press die. This result suggests that an accumulation of evaporated water molecules occurs at the punch – p

Fare planning in public transport is important from the view of passengers as well as of operators. In this paper, we propose a bi-objective model that maximizes the revenue as well as the number of attracted passengers. The potential demand per origin-destination pair is divided into demand groups that have their own willingness how much to pay for using public transport, i.e., a demand group is only attracted as public transport passengers if the fare does not exceed their willingness to pay. We study the bi-objective problem for flat and distance tariffs and develop specialized algorithms to compute the Pareto front in quasilinear or cubic time, respectively. Through computational experiments on structured data sets we evaluate the running time of the developed algorithms in practice and analyze the number of non-dominated points and their respective efficient solutions.

Constraint programming (CP) modeling languages, like MiniZinc, Essence and CPMpy, play a crucial role in making CP technology accessible to non-experts. Both solver-independent modeling frameworks and solvers themselves are complex pieces of software that can contain bugs, which undermines their usefulness. Mutational fuzz testing is a way to test complex systems by stochastically mutating input and verifying preserved properties of the mutated output. We investigate different mutations and verification methods that can be used on the constraint specifications directly. This includes methods proposed in the context of SMT problem specifications, as well as new methods related to global constraints, optimization, and solution counting/preservation. Our results show that such a fuzz testing approach improves the overall code coverage of a modeling system compared to only unit testing, and is able to find bugs in the whole toolchain, from the modeling language transformations themselves to the underlying solvers.

Despite the fact that much attention is paid to the safe operation of nuclear power plants, there is a possibility of an accident with the release of radionuclides. This is especially true in Ukraine, where there is a threat of the damage to nuclear reactors as a result of military operations. It is impossible to research the distribution of products emergency releases radioactive substances in laboratory conditions. Therefore, the only tool for the development predicting of an accident is the modeling the spread of a radionuclides cloud. The purpose of the research is a modeling the distribution of emergency release products in a nuclear power plant unit, suitable for the operative assessment of a development an accident. Results of the research: The mathematical model of the distribution emission products of a nuclear power plant has been developed, which takes into account the value of the initial activity of emission products, the rate of the settling radioactive particles, the wind speed components, the intensity changes radionuclide emission over time. The technique for solving the boundary value problem of modeling in conditions of a complex shape of the computational domain, taking into account the presence of obstacles to the spread of emission products has been developed. The use of the velocity potential equation in evolutionary form allows us to speed up the calculation process. The chosen splitting scheme of an alternating-triangular method allows to find the speed potential according to the explicit form at each splitting step. This allowed software implementation of the CFD model. The visualized models of the emission cloud distribution allow to determine the radiation situation in any place of the emission product distribution zone. The developed model makes it possible to quickly predict the development of an accident in space and time, which makes it possible to take measures to protect people from exposure in the shortest possible time. Concl

Having reliable methods to estimate anthropogenic emissions of Greenhouse Gases (GHG) is of vital importance to design efficient strategies to mitigate the effects of climate change. One of these methods is the MOVES (Motor Vehicle Emission Simulator) software designed by the United States Environmental Protection Agency (EPA). Another methodology is the one implemented by the National Meteorological Institute (NMI) of Costa Rica, which is based on the guidelines of the Intergovernmental Panel on Climate Change (IPCC). The objective of this paper is to determine the feasibility of using MOVES in the Costa Rican context to obtain local factors that improve GHG emission estimates for vehicular mobile sources in Costa Rica in 2014. For these there were evaluated two scenarios of estimated GHG emissions calculated using the MOVES modeling software and the calculation methodology implemented by the NMI. Information was collected from different official sources to supply data to both methodologies and perform the analysis. Likewise, a quantitative comparison was made with a Likert scale to determine the reliability of the two methods. As a result, MOVES calculate higher GHG emission values than the IMN methodology. The analysis with the Likert scale showed that the reliability of the data used for MOVES methodology for Costa Rica is lower than that data used by the IMN. In conclusion, the methodology for calculating GHG emissions by MOVES and by the IMN provide an upper and lower range for the calculation of GHG emissions. Likewise, both methodologies propose complementary approaches to the study of GHG emissions., Contar con métodos confiables para estimar las emisiones antropogénicas de Gases de Efecto Invernadero (GEI) es de vital importancia para diseñar estrategias eficientes para mitigar los efectos del cambio climático. Uno de estos métodos es el software MOVES (Motor Vehicle Emission Simulator) diseñado por la Agencia de Protección Ambiental de los Estados Unidos (US-EPA). Otra metodología es la implementada por el Instituto Meteorológico Nacional (IMN) de Costa Rica, la cual se basa en las directrices del Panel Intergubernamental de Cambio Climático (IPCC). El objetivo de este trabajo es determinar la factibilidad de utilizar MOVES en el contexto costarricense para la obtención de factores locales que mejoren las estimaciones de emisiones de GEI para fuentes móviles vehiculares en Costa Rica en el 2014. Para esto se evaluaron dos escenarios de emisiones estimadas de GEI calculados mediante el software de modelado MOVES y la metodología de cálculo implementada por el IMN. Para esto se recopiló información de diferentes fuentes oficiales para suplir de datos a ambas metodologías y realizar el análisis. Asimismo, se realizó una comparación cuantitativa con una escala Likert para determinar la confiabilidad de los dos métodos. Como resultados se determinó que MOVES calcula valores de emisión de GEI más altos que la metodología del IMN. Relacionado con esto, el análisis con las categorías Likert demostró que la confiabilidad de los datos de la metodología MOVES para Costa Rica es menor que los utilizados por el IMN. En conclusión la metodología de cálculo de emisiones de GEI por MOVES y por el IMN brindan un rango superior e inferior al cálculo de emisiones de GEI. Asimismo, ambas metodologías plantean aproximaciones complementarias al estudio de las emisiones de GEI.

In recent years, there has been an exploration of innovative electric grid concepts centered around power routers, devices capable of controlling power flows as desired. One of which is the Power Router Grid, a novel high-controllable network design fully based on power routers. Its ability to arbitrarily change power flows inside controllable lines raises the challenge of determining the optimal operation within such systems. This paper aims to push further the analysis of the operation and benefits of such networks by proposing a novel optimization model tailored for power router grids based on the most recent literature for the convexification of optimal power flows. Moreover, it demonstrated that radial-based models can be expanded for grids meshed through power routers. The model presented is also convex in the form of a second-order cone, ensuring a global optimum for diverse grid configurations. It has been implemented in Python using the PYOMO modeling language and applied to three case studies investigating the effects of power router operation modes on the grid’s optimal operation and associated costs. Results show that the definition of the power router grid design and the ports operation mode must be carefully decided when demand uncertainty of over 25% is taken into consideration. Moreover, controlling power flow near lines of higher impedance can lead up to a 21% increase in line losses., This publication is part of the project TED2021-131753B-I00, funded by MICIU/AEI/ 10.13039/501100011033 and by the European Union “NextGenerationEU*/PRTR”. The work of Andreas Sumper is supported by the ICREA Academia program. Eduard Bullich-Massagué is a lecturer of the Electrical Engineering Department of UPC of the Serra Húnter Programme., Postprint (published version)

Wireless communication offers significant advantages in terms of flexibility, coverage and maintenance compared to wired solutions and is being actively deployed in the industry. IEEE 802.15.4 standardizes the Physical and the Medium Access Control (MAC) layer for Low Power and Lossy Networks (LLNs) and features Timeslotted Channel Hopping (TSCH) for reliable, low-latency communication with scheduling capabilities. Multiple scheduling schemes were proposed to address Quality of Service (QoS) in challenging scenarios. However, most of them are evaluated through simulations and experiments, which are often time-consuming and may be difficult to reproduce. Analytical modeling of TSCH performance is lacking, as only one-hop communication with simplified traffic patterns is considered in state-of-the-art. This work proposes a new framework based on queuing theory and combinatorics to evaluate end-to-end delays in multihop TSCH networks of arbitrary topology, traffic and link conditions. The framework is validated in simulations using OMNeT++ and shows below 6% root-mean-square error (RMSE), providing quick and reliable latency estimation tool to support decision-making and enable formalized comparison of existing scheduling solutions.

The description of various loading types within the frame of viscoelasticity, such as creep–recovery and stress relaxation in a wide time scale, by means of the same model and similar model parameters is always an interesting topic. In the present work, a viscoelastic model that was analyzed in previous works has been utilized to describe the main standard loading types of viscoelasticity with the same set of model parameters. The relaxation function of this model includes a distribution function followed by the energy barriers that need to be overcome by the molecular domains when a stress field is applied. This distribution function attains a decisive role in the analysis and it was shown that it can be determined on the basis of the loss modulus master curve experimental results. Thereafter, requiring no additional parameters, the creep compliance, the relaxation modulus of poly-lactic acid (PLA) in a wide time scale, as well as creep–recovery at various stresses could be predicted. It was also found that by employing the distribution function associated with the PLA matrix, the creep–recovery experimental data of PLA/hybrid nanocomposites could subsequently be predicted. Therefore, the proposed analysis was shown to be a useful method to predict the material’s viscoelastic response, Peer Reviewed, Postprint (published version)

Modern trends in engine construction are inextricably linked to the improvement of power units by modernizing existing models. The introduction of a forced to 1100 kW diesel engine of the DN type allows to increase the efficiency and bring the equipment in line with modern requirements in a short time and with lower costs. The key method of improvement is the modernization of the supercharging system, which increases power without increasing the dimensions and weight of the engine, as well as improves technical and economic characteristics. A combined supercharging system with a low-pressure turbocharger (LPT) and a high-pressure drive compressor (HPT) is proposed, which work together or separately depending on the operating mode. The use of a mathematical model of the workflow made it possible to carry out a computational and experimental study of the proposed system in the modes of maximum power and maximum torque, confirming its high efficiency. The use of modern technologies and materials, as well as the introduction of innovative design and modeling methods, allows to create more reliable and durable power units. Modernization of the supercharging system is one of the most important directions in the development of modern engine construction, which allows to achieve an increase in the level of specific power, improvement of fuel economy and environmental characteristics of engines by ensuring optimal conditions for their operation in various operating conditions and in a wide range of operating modes. The paper presents the research results of the proposed two-stage supercharging scheme of the DN type diesel engine, which makes it possible to achieve a power of 1100 kW. It is shown that this scheme has advantages over the traditional one, as it makes it possible to provide a higher boost pressure in a wider range of crankshaft RPM, as well as to reduce power consumption from the crankshaft to drive the compressor at modes close to the nominal ones. These factor

Bakalářská práce se zabývá problematikou 3D grafiky, jejím zpracováním a užití v různých oblastech. Práce se zaměřuje především na program Blender, ve kterém je zpracován i výstup. Výstupem práce je animace vymodelovaného objektu., The bachelor thesis deals with the issue of 3D graphics, its processing, and its applications in various fields. The thesis primarily focuses on the Blender software, in which the output is processed. The output of the thesis is an animation of a modeled object., Fakulta ekonomicko-správní, Student přednesl obhajobu práce: Modelování a animace v Blenderu. Cílem bakalářské práce je představit problematiku 3D grafiky. Ukázat její fáze, základní proces vytváření a užití. Práce vysvětluje pojem renderování a výběr vhodné počítačové sestavy pro práci s 3D grafikou. Dále práce přiblíží využití render farem. Výstupem je animace vymodelovaného objektu. Otázky dle posudku vedoucího práce: K práci mám jednu otázku. Pohovořte o bezplatných farmách na rendrování? Student otázku zodpověděl, Dokončená práce s úspěšnou obhajobou

This dissertation examines the problems of optimizing the selection of the datasets and experiments used for parameterizing machine learning-based electrochemical battery models. The key idea is that data selection, or “probing” can empower such models to achieve greater fidelity levels. The dissertation is motivated by the potential of battery models to enable theprediction and optimization of battery performance and control strategies. The literature presents multiple battery modeling approaches, including equivalent circuit, physics-based, and machine learning models. Machine learning is particularly attractive in the battery systems domain, thanks to its flexibility and ability to model battery performance and aging dynamics. Moreover, there is a growing interest in the literature in hybrid models that combine the benefits of machine learning with either the simplicity of equivalent circuit models or the predictiveness of physics-based models or both. The focus of this dissertation is on both hybrid and purely data-driven battery models. Moreover, the overarching question guiding the dissertation is: how does the selection of the datasets and experiments used for parameterizing these models affect their fidelity and parameter identifiability? Parameter identifiability is a fundamental concept from information theory that refers to the degree to which one can accurately estimate a given model’s parameters from input-output data. There is substantial existing research in the literature on battery parameter identifiability. An important lesson from this literature is that the design of a battery experiment can affect parameter identifiability significantly. Hence, test trajectory optimization has the potential to substantially improve model parameter identifiability. The literature explores this lesson for equivalent circuit and physics-based battery models. However, there is a noticeable gap in the literature regarding identifiability analysis and optimization for

The use of predictive modeling in Cultural Heritage Resource Management (CHRM) archaeology has become commonplace since its foundational principals were established in the 1980s, but criticisms of the practice persist, often centered around their lack of theory and dehumanization of the archaeological record. Proximity to water, typically expressed in the United States as distance to streamline data from the National Hydrography Dataset (NHD), is one of the most utilized variables when creating predictive models for Precontact period sites, but how does the variable “distance to streamline” compare to other hydrologic variables? In this thesis I seek to answer the question “how do distance to stream confluences and distance to wetlands compare to distance to streamline when attempting to predict Precontact site locations in the Virginia Piedmont?”The publication Quantifying the Present and Predicting the Past: Theory, Method, and Application of Archaeological Predictive Modeling (Altschul et al. 1988) is considered foundational to the practice of predictive modeling in archaeology; it is referenced frequently in modern theoretical works and throughout this thesis. The approaches to creating archaeological predictive models are typically divided into two camps: models that utilize an inductive, or correlative, approach and models that utilize a deductive, or theory driven, approach. Rather than establishing distance correlations between wetlands and stream confluences with previously recorded site data, I utilize a deductive approach where I establish the importance of those variables through archaeological theory pertaining to subsistence and settlement patterns and test their value with site data. Inductive associational models are very good at showing that archaeological site distribution is strongly patterned, but they often lack the explanatory framework that would be useful for management decisions based on their findings. The Study Area the models are tested o

The object of this study is the operational model of a reconnaissance-fire system. The problem that was solved is the lack of an approach to building a model of the functioning of a combat system, in particular a reconnaissance-fire system, which would take into account the influence of all subsystems and include the necessary number of system states. An improved procedure for building an adapted operational model of the reconnaissance-fire system has been proposed. The essence of the improved methodology is the formalization of processes through the definition of system states and intensities of transitions from state to state. The improved procedure is based on the Kolmogorov-Chapman equations and the goal tree construction method. A feature of the improved methodology is the breakdown of the states of the reconnaissance-fire system by hierarchy levels, which allows taking into account more necessary states of the system. The field of practical use of the improved methodology is planning and management processes during the development of action algorithms during combat operations. An adapted operational model of the reconnaissance-fire system has been built. The essence of the model is to determine the probability of the reconnaissance-fire system being in a certain state based on the Chapman-Kolmogorov equations, taking into account the necessary level of detail in the process of its operation. Special feature of the proposed model is that it makes it possible to model by taking into account 39 states of the system with the necessary accuracy both for the system as a whole and separately for subsystems. This is explained by the fact that the test of the adequacy of the model showed that the discrepancy of the results is within the statistical error from 2 to 9 %. The field of application of the adapted operational model of the reconnaissance-fire system is the processes of making a decision on the application of the operation of the intelligence-fire system durin

The kinematics of gear cutting and the modeling algorithm for the cutting-in of the cutting tool into the workpiece is described. This important stage of the cutting process is one of the most dangerous not only in gear turning, but in any machining process, and therefore requires careful study. Analyzing the results of research in this area, and taking into account the rapid development of a relatively new method of gear cutting, we can conclude that there are still a large number of unsolved problems during machining. This is primarily due to the complex kinematics of the process and the associated difficulties in reproducing the cut. In describing the kinematics of gear cutting, we have presented methods for creating a gear cutting simulation model, as well as the coordinate systems required to convert the tool profile coordinate system into the workpiece profile coordinate system. Using the CAD environment, the solid models involved in the process reproduce the cutting process with the best accuracy available. For each of these positions, the exact position of the cutter and the intermediate position of the workpiece at that time were determined. In a specific example, the algorithm was used to generate undeformed cutting profiles for external spur gears with different cutting strategies. In addition, an analytical method was applied to calculate the position of the transition surface and the maximum chip thickness and area were determined and confirmed by simulation for various process parameters, namely depth of cut and number of working transitions. The comparison between the analytically calculated maximum chip thickness and the simulated maximum chip thickness shows a good agreement. The obtained chip thicknesses and cut areas can be used as indicators to control the cutting process and to optimize the process. The nature of the change in chip geometry for different strategies and transitions was determined. With complete information on the geometric values

Diets rich in fruit and vegetables (F&Vs) improve cognitive functioning and reduce the risk of non-communicable diseases in children. Nevertheless, 59% of Dutch children do not meet recommended intake levels. Given the importance of color in children's food choices, the concept of “eat the rainbow” presents a promising approach. This project aimed to evaluate the effects of a modeling- and reward-based intervention to stimulate the consumption of colorful foods to increase willingness to taste different F&Vs among children aged 3–7 years. 164 children from Dutch elementary schools participated in a nested cluster randomized multi-arm parallel design study. During two morning school breaks, children were invited to choose from ten F&Vs in five different colors. Their willingness to taste and ad libitum intake were recorded. The first session served as a baseline with no intervention, while the second session involved either the Miffy intervention (modeling- and reward-based), a reward-only intervention (reward-based), or a control session. In the Miffy intervention, children listened to a story about Miffy eating the rainbow before tasting F&Vs and they received colored stickers (e.g., red sticker for tomatoes, green sticker for celery) upon tasting them. In the reward-only intervention, children received a sticker upon tasting a food. The Miffy group showed a higher probability (P(tasted) = 0.39) of tasting a food product compared to the control group (P(tasted) = 0.29; OR = 0.63, p = .04). No significant differences were observed between the Miffy and reward-only groups or between the reward-only and control groups. Both interventions did not significantly impact intake or liking of the foods. The Miffy-themed intervention demonstrates potential to enhance children's willingness to taste F&Vs, primarily due to the use of non-food incentives.

Contextualización: en este artículo se desarrolló un marco referencial para la evaluación dinámica y prospectiva de la sostenibilidad del bioetanol de caña, como herramienta para los tomadores de decisiones en Colombia. Vacío de conocimiento: no se han desarrollado modelos dinámicos con la formulación de escenarios viables o deseados. La evaluación de aspectos ambientales y sostenibilidad siempre se realiza con información pasada y datos históricos, pocas veces se hace con modelos prospectivos y no se vinculan restricciones o escenarios no deseados. Así, se debe modelar una cadena de suministro general de bioetanol, conectando variables que representen indicadores de sostenibilidad. Los indicadores modelados fueron propuestos por Global Bioenergy Partnership (GBEP). Propósito: se construye un modelo para la evaluación de indicadores de sostenibilidad y saber si el comportamiento del sistema evoluciona por las regiones deseadas, que corresponderían a los objetivos del sector y metas de sostenibilidad. Metodología: se desarrolla un modelo con dinámica de sistemas y, para la integración de la modelación con la evaluación de la sostenibilidad, se utiliza el concepto de restricciones desarrollado en la teoría de la viabilidad; aquí las regiones deseadas del estado del sistema se sugieren y se definen como escenarios deseados, de alerta y no deseados. Resultados y conclusiones: este modelo ha sido probado con la información de una cadena productiva de bioetanol a partir de caña de azúcar en Colombia con una capacidad instalada de 450 millones de litros al año, utilizando dos indicadores de sostenibilidad que fueron diseñados y simulados, junto con la evaluación de estrategias de mejora. Estos indicadores son el consumo de agua y el empleo en la producción de bioetanol. Los resultados muestran hallazgos importantes para modelar, monitorear y evaluar la sostenibilidad en el sector de los biocombustibles, utilizando indicadores y brindando un método para implementar las mejo, Contextualization: This paper has a framework for prospective assessment of sustainability in bioethanol in a dynamical way, this is important as a tool for policymakers in Colombia. Knowledge gap: No dynamic models have been developed with the formulation of viable or desired scenarios. The evaluation of environmental aspects and sustainability is always carried out with past information and historical data, it is rarely carried out with prospective models and no restrictions or unwanted scenarios are linked. A general bioethanol supply chain must be modeled, connecting variables that represent sustainability indicators. The modeled indicators were proposed by the Global Bioenergy Partnership (GBEP). Purpose: A model is built to evaluate sustainability indicators and know if the trend behavior of the system evolves through the desired regions that would correspond to the sustainability objectives and goals of the sector. Methodology: A model is developed with System Dynamics and to integrate the modeling with the evaluation of sustainability, the concept of constraints, developed in the Viability Theory, is used; Here, the desired regions of the system state are suggested and defined as desired, alert, and undesired scenarios. Results and conclusions: The model have been tested with the information of a bioethanol production chain from sugarcane in Colombia with an installed capacity of 450 million liters per year, using two sustainability indicators that were designed and simulated using the constraint regions. These indicators are water consumption and jobs in bioethanol production. The results show important findings for modeling, monitoring, and assessing sustainability in the biofuels sector, using indicators and providing a method of implementing the best practices for sustainability using defined desired regions of the systems.

The electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI) system is developed for visual representation and adaptive enhancement on noise modeling in ECG-based signal processing. Percentage root mean square difference () was measured between the modeled noisy signals and the samples of the original ECG. Moreover, cross correlation and root mean square error () were performed between the noisy EEG signals and the denoised ones which resulted from WT denoising technique initially to evaluate the effectiveness of the WT denoising technique. The results show that the WT was successfully removed different types of proposed models of noises. This study will help medical doctors, clinicians, physicians, and technicians to eliminate different types of noise. Moreover, the project could be crucial for the process of automatic diagnosis of different heart diseases.

Support as a field of practical activity of leading specialists is still not very clearly defined and, moreover, there is a widespread opinion that such a field does not exist at all, that the task of psychologists is not to support the development of activity systems, but only to provide psychological support for the management process. By the way, the development of modern management psychology as a field at the intersection of psychology and management revealed gaps and contradictions in standard models of the development of a specialist's personality. The latter in particular explains the backwardness of some countries in this regard. Studies of the consequences of limited rationality, social preferences, and the lack of self-control of the development situation have shown that human traits systematically affect management decisions, as well as performance results. In the post-industrial era, it is necessary to reveal the influence of the psychological (in particular, leadership) potential of a modern specialist ("passionate spirit") on national dignity. A leader is a person who wants not only to find himself in life, but also to realize himself in it: fully, fully exhausting his inner potential. A question arises regarding the psychological support of the development of socio-technical systems of activity, and above all in the project management system. The scientific basis of professional management psychology is based on the developed characteristics and patterns. A practical warehouse is used by a number of diagnostic, expert and other workers who are able to achieve the necessary efficiency of activity.

Nowadays, when computer technologies are used in all fields of science and technology, it is almost impossible to imagine the activi-ties of various institutions, including scientific and educational ones, without modeling various objects and processes. The peculiarity of the design and construction of flying apparatus requires the use of modern methods of information processing, creation of drawings and modeling of individual processes. Given the diversity of computer software, it is important to identify at which stages which software packages can be effectively ex-ploited. The purpose of writing this article was to focus on the 3D Max software package, its various advantages and shortcomings in the processes of modeling the behavior of combustion components in the tanks of flying apparatus. For this, the survey research method was used. The results of which were presented in this article. According to the results of the study, it can be noted that the use of the 3D Max software package, for the purpose of modeling the behavior of the fuel component in the tanks, has theoretical and practical value. The study of certain advantages and disadvantages of such mod-eling specified the problem and its relevance. The modeling process using the 3D Max software package was subject to a number of fairly strict and specific requirements. One of the main requirements was the possibility of creating research objects in strict compliance with the parameters necessary for the reproduction of the most reliable model with the maximum pos-sible consideration of the operating factors in the conditions of the software package in order to achieve the realism of the process. The article highlights the most striking advantages of modeling using the 3D Max software package. As for the shortcomings, the author hopes that later, with the ad-vent of more powerful computer systems, they will be almost insignificant. The use of modeling the behavior of fuel components in aircraft tanks using

Forecasting flood and drought events requires accurate modeling tools. Hydraulic river models are based on estimates of riverbed geometry which are traditionally collected in situ. The novel Ice, Cloud and Land Elevation Satellite 2 [ICESat-2] lidar altimetry mission with 6 simultaneous high-resolution laser beams provides the opportunity to define river cross-section geometries as well as observe water surface elevation [WSE] and water surface slope spatially resolved along the river chainage. This paper describes a method to utilize terrain altimetry and water surface slope estimates to define complete river geometries from ICESat-2 data products, using the diffusive wave approximation to calculate depth in the submerged section not penetrated by the lidar. Exemplifying the method, cross-sections are defined for a stretch of the Mekong River. Hydrodynamic model results of the stretch are compared with ICESat-2 WSE estimates and in situ gauging station time series. Insights in river characteristics from satellite imagery and the ICESat-2 slope estimates allow for fine-tuning of the cross-sections using spatially varying Manning numbers. The final model achieves a root mean square error against the ICESat-2 WSE of 0.676 m and average Kling-Gupta Efficiency against gauging station time series of 0.880. The method is limited by the diffusive wave approximation resulting in inaccurate cross-section estimates in sections with supercritical flow or significant acceleration. Errors can be identified from ICESat-2 WSE estimates and reduced with additional cross-sections. Combined with hydrological models, the method will allow for cross-section definition without in situ data.

Landslides and slope processes constitute one of the most frequent natural hazards in valleys near major rivers and mountainous regions. The surface layer, characterized by its relatively loose composition, is prone to sliding due to a combination of distinct natural and human-related factors. Specific sections along the right bank of the Danube River in Smederevo city exhibit significant susceptibility to landslide activation, often leading to substantial material losses and posing a risk to the local population. The initial step in the provided research involves analyzing existing literature and mapping landslides within the study area. The initial analysis covers both natural conditions and anthropogenic activities. The second step includes establishing a geospatial database in the Geographic Information System and generating eight thematic maps. In the third step, different weight coefficients were assigned to the criteria, which facilitated the creation of the Landslide Susceptibility Index using the Best–Worst Method. Subsequently, in the fourth step, a composite map illustrating landslide susceptibility was produced. According to this research, about 4% of the territory of Smederevo, or 19.3 km2, is highly or very highly susceptible to landslides. These localities are located on the right bank of the Danube River and around the Ralja River. Receiver operating characteristic-area under the curve value indicates very high predictive power (approximately 1), thus suggesting the reliability of the used methodology. This visualization of areas highly prone to such occurrences empowers policymakers to implementmore effective environmental protectionmeasures and institute sustainable management practices for agricultural parcels in this region. Also, the provided research represents the inaugural integration of advanced remote sensing techniques and interdisciplinary investigations, offering deeper insights into landslide activity in the study area and yielding more

An elastoviscoplastic constitutive equation is proposed to describe both the elastic and rate-dependent plastic deformation behavior of Carbopol® dispersions, commonly used to study yield-stress fluids. The model, a variant of the nonlinear Maxwell model with stress-dependent relaxation time, eliminates the need for a separate Herschel-Bulkley yield stress. The stress dependence of the viscosity was determined experimentally by evaluating the steady-state flow stress at a constant applied shear rate and by measuring the steady-state creep rate at constant applied shear stress. Experimentally, the viscosity’s stress-dependence was confirmed to follow the Ree-Eyring model. Furthermore, it is shown that the Carbopol® dispersions used here obey time-stress superposition, indicating that all relaxation times experience the same stress dependence. This was demonstrated by building a compliance mastercurve using horizontal shifting on a logarithmic time axis of creep curves measured at different stress levels and by constructing mastercurves of the storage- and loss-modulus curves determined independently by orthogonal superposition measurements at different applied constant shear stresses. Overall, the key feature of the proposed constitutive equation is its incorporation of a nonlinear stress-activated change in relaxation time, which enables a smooth transition from elastic to viscous behavior during start-up flow experiments. This approach bypasses the need for a distinct Herschel-Bulkley yield stress as a separate material characteristic. Additionally, the model successfully replicates the observed steady-state flow stress in transient-flow scenarios and the steady-state flow rate in creep experiments, underlining its effectiveness in capturing the material’s dynamic response. Finally, the one-dimensional description is readily extended to a full three-dimensional finite-strain elastoviscoplastic constitutive equation.

Composition drift in radical copolymerization is a topic of practical importance for the synthesis of homogeneous statistical copolymers and gradient copolymers, which generally does not receive much attention in most polymer chemistry textbooks. The aim of this paper is to provide a tutorial on the topic in which we provide some additional theory in a straightforward and accessible manner and show that composition drift can easily be described quantitatively. Furthermore we show how to circumvent composition drift in a semi-batch approach and by using a continuous stirred tank reactor (CSTR).

With the advent of 3D printing, advanced geometries started replacing the conventional designs in electric machines. Various modified rotor, stator and coil designs are 3D printed to enhance the machine properties and minimize the losses but there are still some heat losses generated which can cause temperature rise inside the motor and disturb the stability of machine, unless this heat is removed from the machine properly. Motors use conventional housing with fins or cooling systems to remove this heat but it provides poor heat transfer and affects the performance of the motor. This paper focuses on developing Triply Periodic Minimal Surfaces (TPMS) housing structures with varying heights, volume fractions and cell sizes to optimize heat management in the motor. TPMS provides heat dissipation in multiple directions as compared to conventional fin. They provide a large surface area to volume ratio, hence better heat dissipation & heat distribution within the structure, improving performance and saving material. Mathematical modeling and numerical simulations of these structures using Finite Volume Method are done, and results of each structure are investigated and compared. Comparison with another research work is also done to justify the results. Finally, an optimal structure is chosen to replace the original housing structure. Comparative analysis is done to study the improvement in properties. Results are compared with conventional housing. Complete heat analysis of the original and proposed design is presented. Heat distribution and propagation is carried out. Improved results and the future scope of the project is presented.© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighte

Sustainability should become a key concern in the next generation of engineered systems. While this expectation is relatively straightforward, the question of how to get there is less obvious. The multi-dimensional and intricate nature of sustainability poses challenges in designing sustainable systems and analyzing sustainability properties. Finding trade-offs between economic, environmental, societal, and technological aspects of sustainability is a wicked problem and calls for advanced modeling and simulation methods. In this paper, we report on a panel discussion held at the 28th Working Conference on Exploring Modeling Methods for Systems Analysis and Development (EMMSAD) with four esteemed experts representing four complementary and often conflicting perspectives on the role of modeling for sustainability – stakeholders, digitalization, degrowth and IT, and ethics. We report the key arguments of the panelists, discuss the roles of modeling in the analysis and design of sustainable systems, and, finally, elaborate on the conflicts among the perspectives, their effects, and potential resolutions.

The article discusses the process of modeling the economic efficiency of management of strategic changes at industrial enterprises in order to form competitive advantages. The key aspects of the system approach to strategic change are analyzed, including the analysis of the internal and external environment, goal setting, development of models of economic efficiency and continuous monitoring of results. Particular attention is paid to the use of financial and non-financial indicators for comprehensive evaluation of the effectiveness of changes. It is substantiated that modeling the economic efficiency of management of strategic changes is an important tool for achieving long-term success and formation of sustainable competitive advantages of industrial enterprises. It is proved that modeling the economic efficiency of the process of managing strategic changes is an important tool for achieving and maintaining the competitive advantages of enterprise. The use of financial and non-financial indicators allows you to objectively assess the effectiveness of the implemented changes and make informed decisions. Successful implementation of strategic changes contributes to improving the efficiency of the enterprise, customer satisfaction and overall competitiveness in the Market. The conclusions of the article contain recommendations for the development and implementation of systematic approaches to the management of strategic changes, the use of innovative technologies, taking into account complex performance indicators and maintaining the flexibility and adaptability of enterprises.

This Article shares the proceedings from the August 29th, 2023 (day 1) workshop "Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives". The focus of the day was on model parametrization; regulatory authorities from Canada, the USA, Sweden, Belgium, and Norway presented their views on PBBM case studies submitted by industry members of the IQ consortium. The presentations shared key questions raised by regulators during the mock exercise, regarding the PBBM input parameters and their justification. These presentations also shed light on the regulatory assessment processes, content, and format requirements for future PBBM regulatory submissions. In addition, the day 1 breakout presentations and discussions gave the opportunity to share best practices around key questions faced by scientists when parametrizing PBBMs. Key questions included measurement and integration of drug substance solubility for crystalline vs amorphous drugs; impact of excipients on apparent drug solubility/supersaturation; modeling of acid-base reactions at the surface of the dissolving drug; choice of dissolution methods according to the formulation and drug properties with a view to predict the in vivo performance; mechanistic modeling of in vitro product dissolution data to predict in vivo dissolution for various patient populations/species; best practices for characterization of drug precipitation from simple or complex formulations and integration of the data in PBBM; incorporation of drug permeability into PBBM for various routes of uptake and prediction of permeability along the GI tract.

Soft computing techniques have become popular for solving complex engineering problems and developing models for evaluating structural material properties. There are limitations to the available methods, including semi-empirical equations, such as overestimating or underestimating outputs, and, more importantly, they do not provide predictive mathematical equations. Using gene expression programming (GEP) and artificial neural networks (ANNs), this study proposes models for estimating recycled aggregate concrete (RAC) properties. An experimental database compiled from parallel studies, and a large amount of literature was used to develop the models. For compressive strength prediction, GEP yielded a coefficient of determination (R2) value of 0.95, while ANN achieved an R2 value of 0.93, demonstrating high reliability. The proposed predictive models are both simple and robust, enhancing the accuracy of RAC property estimation and offering a valuable tool for sustainable construction.

This paper presents a streamlined approach to describing potential habitats for red deer (Cervus elaphus) in situations where in situ data collected through observations and monitoring are absent or insufficient. The main objectives of this study were as follows: (a) to minimize the negative effects of limited in situ data; (b) to identify landscape features with a functional relationship between habitat quality and landscape structure; and (c) to use imprecise in situ data for statistical analyses to specify these relationships. The test area was located in the eastern part of Mecklenburg-Western Pomeriania (Germany). For this area, remotely sensed forest maps were used to determine landscape metrics as independent variables. Dichotomous habitat suitability was determined based on hunting distances over a five-year period. Ecological and biological habitat requirements of red deer were derived from suitable landscape measures, which served as model inputs. Correlation analysis identified the most relevant independent landscape metrics. Logistic regression then tested various metric combinations at both class and landscape levels to assess habitat suitability. Within the model variants, the contagion index, edge density, and percentage of forested area showed the largest relative impact on habitat suitability. The approach can also be applied to other mammals, provided there are appropriate structural preferences and empirical data on habitat suitability.