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Extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (E. coli) in animals are considered a human health threat, because this type of bacteria can serve as a reservoir of antibiotic resistant genes and act as a continuous threat of the emergence of new resistant bacteria, in addition to the direct effect of making infection untreatable. Although the prevalence of ESBL producing bacteria in broilers was drastically reduced in the Netherlands, chicken meat still has the highest prevalence among meat products. Therefore, further control of the ESBL-producing E. coli in the broiler production chain is important to reduce public health risks. The main objectives of this study were to evaluate the effectiveness of intervention scenarios to reduce the transmission of ESBL-producing E. coli in the broiler production chain and to quantitatively estimate the risk to public health. In this study, we developed two different types of transmission models that described the observed time-related decline in prevalence during a production round: one with time-dependent decline in susceptibility and one with partial immunity to phylogenetic groups. Both models incorporated the environmental contamination effect between production rounds and within flocks. The parameter values, including transmission rate and recovery rate, were estimated by Approximate Bayesian computation (ABC) method using data from a longitudinal study in a Dutch organic broiler farm. We applied the models to the three production stages in the broiler production chain, beginning from the Parent Stock (PS) farms, the hatcheries, and to the broiler farms. In our models, eggs were collected from different parent stock farms and transported to the hatchery and from there to a broiler farm.The size of a flock and the number of farms were adjusted to the Dutch situation. Both models were able to describe the observed dynamics within and between the production stages equally well, with estimated ESBL-prod

This master's thesis aims to establish a foundation for model-based engineering of drill rigs through the development, evaluation, and utilization of simulation models. Specifically, the project focused on creating a simulation model of the hydraulic tramming system in the SmartRoc D65 surface drill rig. The uncalibrated model was validated against physical tests conducted on the SmartRoc T35 drill rig, and the results provided accurate predictions with some room for improvement. The model sets a basis for identifying power losses and future potential optimization through electrification. A modeling methodology was developed to aid in the development of other simulation models representing a physical system. The thesis highlights the strengths and limitations of a quasi-static model when applied to dynamic systems. The findings suggest areas for future improvement and underscore the importance of continuous model refinement to enhance calculation accuracy.

Global supply chains are facing significant challenges due to the changes in supply and demand. This will increase the need for flexible and sustainable management. Lean production is a widely adopted methodology that companies use to enhance efficiency, reduce costs, and shorten lead times by optimizing internal logistics systems. Mapping and visualization tools are essential for understanding and improving transportation processes within companies while minimizing waste.The objective of this study is to provide companies with clearer insights into theirinternal transport flows through lean production and facility planning. By mappingtheir structures, companies can enhance their decision-making processes. This studyaims to achieve an understanding of the need for internal transport flow mappingthrough various methods and analyses. It also seeks to increase knowledge ofdifferent tools within lean production and facility planning to visualize the currentstate of internal transportation between buildings.The study was conducted through interviews, observations, and GPS measurements to map the transport processes at Xylem. Data were analyzed both qualitatively and quantitatively to ensure high scientific quality. The results and current state analysiswere based on these methods, leading to reliable conclusions about Xylem's current state.By using various lean tools and facility planning techniques, it is possible to create a mapping that provides companies with insights into their current situation. Several improvement suggestions for the current structure and work methods can potentially create faster flows with fewer misunderstandings in the work process. The study concludes that flow mapping functions as a tool to create a simplified simulation model. By interviewing and observing drivers and using diagrams to show utilization and time distribution, it is possible to analyze and examine internal transport planning and identify unnecessary waste.

The report presents a study of the operations at Rollmek AB. Rollmek is a company that manufactures various components for Panthera wheelchairs including backrests, chassis and leg rests. The thesis aims to develop various improvement proposals for the case company's painting department with regard to increasing production capacity. To achieve the goal, a simulation model has been constructed in the simulation program FACTS Analyzer, which reflects the department in question. The simulation model is based on three different variants with five different colours. For the construction of simulation models, data collected via various qualitative and quantitative research methods, including time studies, observations, and interviews. Improvement proposals that were developed were implemented in the simulation model and experimented based on the project's requirements. The study's results have led to five specific suggestions for improvement. Through the use of simulation models, data has been generated on the number of units produced and units produced/hour for the three product variations with associated color variations. With the help of these improvement suggestions, the company could implement them in production to increase its capacity to meet future demand.

Global supply chains are facing significant challenges due to the changes in supply and demand. This will increase the need for flexible and sustainable management. Lean production is a widely adopted methodology that companies use to enhance efficiency, reduce costs, and shorten lead times by optimizing internal logistics systems. Mapping and visualization tools are essential for understanding and improving transportation processes within companies while minimizing waste.The objective of this study is to provide companies with clearer insights into theirinternal transport flows through lean production and facility planning. By mappingtheir structures, companies can enhance their decision-making processes. This studyaims to achieve an understanding of the need for internal transport flow mappingthrough various methods and analyses. It also seeks to increase knowledge ofdifferent tools within lean production and facility planning to visualize the currentstate of internal transportation between buildings.The study was conducted through interviews, observations, and GPS measurements to map the transport processes at Xylem. Data were analyzed both qualitatively and quantitatively to ensure high scientific quality. The results and current state analysiswere based on these methods, leading to reliable conclusions about Xylem's current state.By using various lean tools and facility planning techniques, it is possible to create a mapping that provides companies with insights into their current situation. Several improvement suggestions for the current structure and work methods can potentially create faster flows with fewer misunderstandings in the work process. The study concludes that flow mapping functions as a tool to create a simplified simulation model. By interviewing and observing drivers and using diagrams to show utilization and time distribution, it is possible to analyze and examine internal transport planning and identify unnecessary waste.

This master's thesis aims to establish a foundation for model-based engineering of drill rigs through the development, evaluation, and utilization of simulation models. Specifically, the project focused on creating a simulation model of the hydraulic tramming system in the SmartRoc D65 surface drill rig. The uncalibrated model was validated against physical tests conducted on the SmartRoc T35 drill rig, and the results provided accurate predictions with some room for improvement. The model sets a basis for identifying power losses and future potential optimization through electrification. A modeling methodology was developed to aid in the development of other simulation models representing a physical system. The thesis highlights the strengths and limitations of a quasi-static model when applied to dynamic systems. The findings suggest areas for future improvement and underscore the importance of continuous model refinement to enhance calculation accuracy.

The report presents a study of the operations at Rollmek AB. Rollmek is a company that manufactures various components for Panthera wheelchairs including backrests, chassis and leg rests. The thesis aims to develop various improvement proposals for the case company's painting department with regard to increasing production capacity. To achieve the goal, a simulation model has been constructed in the simulation program FACTS Analyzer, which reflects the department in question. The simulation model is based on three different variants with five different colours. For the construction of simulation models, data collected via various qualitative and quantitative research methods, including time studies, observations, and interviews. Improvement proposals that were developed were implemented in the simulation model and experimented based on the project's requirements. The study's results have led to five specific suggestions for improvement. Through the use of simulation models, data has been generated on the number of units produced and units produced/hour for the three product variations with associated color variations. With the help of these improvement suggestions, the company could implement them in production to increase its capacity to meet future demand.

Long truck queues and congestion around terminals is a common sight, however they come with many negative externalities for all the stakeholders involved. Truck Appointment System (TAS) is the most commonly used system to face these problems, but it still has some drawbacks and limitations. Consequently, in this research an extension of the typical TAS is proposed in order to improve its performance. The main components of this system are the use of truck dependent time-windows, the utilization of real-time information and the adaptive trucks rescheduling model. The duration of the arrival time-windows is longer than the actual service times, allowing overlap between time-windows. Thus, the actual service sequence might be different from the reserved one. To determine the actual loading sequence an Optimization model is developed, which is run periodically while utilizing real-time truck information. A chemical plant is used as a case study in this research. The performance of the proposed TAS is assessed with the use of a Simulation model. The outcomes of this research suggest that the a less strict TAS can significantly improve the system’s performance, especially trucks’ waiting times. Also, the system’s resilience against disruptions and the plant’s environmental footprint are improved, while queues are reduced., Transport, Infrastructure and Logistics

This investigative article analyzed the use of simulation tools in the teaching of theoretical subjects in the field of higher education. The study was carried out specifically in the Industrial Electricity Technology program of the Santander Technological Units in Bucaramanga, Colombia. It begins with a review of bibliographic background that validates the topic and was complemented with a survey carried out among the population of the academic program. With the above, the need to apply simulation in certain subjects was confirmed and through the analysis of mortality studies carried out in the program, it was detected that the subject of electrical circuits was the one that most needed said intervention. In the end, these findings are used to support the importance of developing a new didactic model which will be a doctoral work to be carried out at the UMECIT University of Panama by the authors., Este artículo investigativo analizó el uso de herramientas de simulación en la enseñanza de asignaturas teóricas en el ámbito de la educación superior, El estudio se realizó específicamente en el programa de Tecnología en Electricidad Industrial de las Unidades Tecnológicas de Santander en Bucaramanga, Colombia. Se inicia con una revisión de antecedentes bibliográficos que validan el tema y se complementó con una encuesta realizada a la población del programa académico. Con lo anterior se confirmó la necesidad de aplicar la simulación en ciertas asignaturas y mediante el análisis de estudios de mortalidad realizados en el programa, se detectó que la asignatura de circuitos eléctricos era la que más necesitaba de dicha intervención. Al final, estos hallazgos son utilizados para respaldar la importancia de desarrollar un nuevo modelo didáctico el cual será un trabajo doctoral a realizarse en la Universidad UMECIT de Panamá por parte de los autores.

This investigative article analyzed the use of simulation tools in the teaching of theoretical subjects in the field of higher education. The study was carried out specifically in the Industrial Electricity Technology program of the Santander Technological Units in Bucaramanga, Colombia. It begins with a review of bibliographic background that validates the topic and was complemented with a survey carried out among the population of the academic program. With the above, the need to apply simulation in certain subjects was confirmed and through the analysis of mortality studies carried out in the program, it was detected that the subject of electrical circuits was the one that most needed said intervention. In the end, these findings are used to support the importance of developing a new didactic model which will be a doctoral work to be carried out at the UMECIT University of Panama by the authors., Este artículo investigativo analizó el uso de herramientas de simulación en la enseñanza de asignaturas teóricas en el ámbito de la educación superior, El estudio se realizó específicamente en el programa de Tecnología en Electricidad Industrial de las Unidades Tecnológicas de Santander en Bucaramanga, Colombia. Se inicia con una revisión de antecedentes bibliográficos que validan el tema y se complementó con una encuesta realizada a la población del programa académico. Con lo anterior se confirmó la necesidad de aplicar la simulación en ciertas asignaturas y mediante el análisis de estudios de mortalidad realizados en el programa, se detectó que la asignatura de circuitos eléctricos era la que más necesitaba de dicha intervención. Al final, estos hallazgos son utilizados para respaldar la importancia de desarrollar un nuevo modelo didáctico el cual será un trabajo doctoral a realizarse en la Universidad UMECIT de Panamá por parte de los autores.

The study of energy consumption in buildings, particularly residential ones, brings with it significant socio-economic and environmental implications, as it accounts for approximately 40% of CO2 emissions, 18% in the case of residential buildings, in Europe. On a number of levels, energy consumption serves as a key parameter in urban sustainability indicators and energy plans. Access to data on energy consumption is crucial for energy planning, management, knowledge generation, and awareness. Urban Building Energy Models (UBEMs), which are emerging tools for simulating energy consumption at neighborhood scale, allow for more efficient intervention and energy rehabilitation planning. However, UBEM validation requires reliable reference data, which are often challenging to obtain at urban scale due to privacy concerns and data accessibility issues. Recent advances, such as automation and open data utilization, are proving promising in addressing these challenges. This study aims to provide a standardized UBEM validation process by presenting a case study that was carried out utilizing open data to develop bottom-up engineering models of residential energy demand at urban scale, with a resolution level of individual buildings, and a subsequent adjustment and validation using reference tools. This study confirms that the validated GIS-UBEM model heating and cooling demands and consumption fall within the confidence bands of ±15% and ±12.5%, i.e., the confidence bands required for the approval of official alternative simulation methods for energy certification. This paves the way for its application in urban-scale studies and practices with a well-established margin of confidence, covering a wide range of building typologies, construction models, and climates comparable to those considered in the validation process. The primary application of this model is to determine the starting point and subsequent evaluation of improvement scenarios at a district scale, examining is

Since many ecosystem services involve spatial scales beyond farm size, their preservation and management in agricultural systems depend on the interaction of the landowners. For the analysis of such interactive land use a generic dynamic land-use model is developed that considers different payoff structures in a systematic manner and relates land-use dynamics to these payoff structures. A landowner's own payoff depends on the land use on neighboring land parcels. The landowners’ payoffs are interpreted in a game-theoretic manner which allows for a game-theoretic classification of the different land-use dynamics generated by the model. The model is analyzed to determine the proportion, spatial aggregation and temporal turnover of land-use measures. The model results are applied to a number of cases from literature in which the management of ecosystem services involves a regional scale, including pollinator conservation, pest control, and coordination incentives for the conservation of species in fragmented landscapes. Four main domains of model behavior are identified and related to the payoff structures (type of game), characterized by the proportions and temporal turnover of land-use measures, and by whether the system has one or two stable equilibria. An important determinant of the land-use dynamics is the spatial heterogeneity of the landowners' payoffs which. It affects the domain and the location in the domain by which the land-use dynamics are characterized.

Space weather is the field within the space sciences that studies how the Earths magnetosphere is influenced by the Sun. The Sun is constantly emitting dangerous radiation and plasma which in some cases can affect or damage the systems on Earth. Scientists have an interest in studying this interaction and therefore visualizations of space weather data are useful. OpenSpace is an interactive software that visualizes the entire known universe with real-time data. OpenSpace supports a range of different visualization methods and techniques, for this work, the relevant visualization tools are field lines and cut planes. GAMERA is a simulation model that simulates a wide range of situations where plasma is subjected to the influence of magnetic fields, the simulations are based on curvilinear grids. This project focuses on implementing data from GAMERA into OpenSpace. OpenSpace already supports a variety of different simulation models, although none that uses curvilinear grids for the data. The curvilinear grid can adapt to the specific shape and geometry of the data, allowing for more accurate data representation. The project aims to create a pipeline for reading data files from simulation runs and visualize it as field lines and cut planes. The files used in this project contain data suitable for volumes and field lines. The method was to first develop a reader to extract and manage desired data from HDF5 files in which the simulation data is stored. The data used to visualize field lines is rendered with an already existing component in OpenSpace. Secondly, a slice operation was developed to extract cut planes from the files containing data for volume visualization, these are then visualized with the help of a component for rendering cut planes which was developed during this work. The work led to a pipeline that reads and manages simulation data from GAMERA and the data is successfully visualized. However, there is room for improvement in color rendering, robustness, Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

Space weather is the field within the space sciences that studies how the Earths magnetosphere is influenced by the Sun. The Sun is constantly emitting dangerous radiation and plasma which in some cases can affect or damage the systems on Earth. Scientists have an interest in studying this interaction and therefore visualizations of space weather data are useful. OpenSpace is an interactive software that visualizes the entire known universe with real-time data. OpenSpace supports a range of different visualization methods and techniques, for this work, the relevant visualization tools are field lines and cut planes. GAMERA is a simulation model that simulates a wide range of situations where plasma is subjected to the influence of magnetic fields, the simulations are based on curvilinear grids. This project focuses on implementing data from GAMERA into OpenSpace. OpenSpace already supports a variety of different simulation models, although none that uses curvilinear grids for the data. The curvilinear grid can adapt to the specific shape and geometry of the data, allowing for more accurate data representation. The project aims to create a pipeline for reading data files from simulation runs and visualize it as field lines and cut planes. The files used in this project contain data suitable for volumes and field lines. The method was to first develop a reader to extract and manage desired data from HDF5 files in which the simulation data is stored. The data used to visualize field lines is rendered with an already existing component in OpenSpace. Secondly, a slice operation was developed to extract cut planes from the files containing data for volume visualization, these are then visualized with the help of a component for rendering cut planes which was developed during this work. The work led to a pipeline that reads and manages simulation data from GAMERA and the data is successfully visualized. However, there is room for improvement in color rendering, robustness, Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

El propòsit d’aquest estudi és realitzar un model de simulació de la transmissió de potència des de la sortida del motor dièsel al tren de rodadura d’una màquina de construcció amb accionament oleohidràulic de circuit tancat, mitjançant la tècnica de Bond Graph. La transmissió a modelitzar és de la perforadora P105-TT, de CONSTRUCCIONES MECÁNICAS LLAMADA S.L.. Actualment, les erugues de la màquina són accionades mitjançant una transmissió oleohidràulica en circuit obert tipus LS (Load-Sensing). S’aprofita que el fabricant està estudiant de canviar a circuit tancat, per tal de realitzar-ne el model de la màquina modificada, a fi i efecte de disposar d’una eina per conèixer el seu comportament i la seva eficiència abans de la seva implantació. Inicialment, s’exposa la tècnica de Bond Graph, així com les característiques del software utilitzat i els tipus de transmissions hidroestàtiques. També es mencionen els estudis previs, que han servit com a punt de partida o de referència en el desenvolupament del model. Seguidament, es detallen els submodels creats de BG dels components que integren la transmissió de la màquina, així com les equacions que els defineixen. Es realitza un estudi de la màquina P105-TT modificada, i dels components que l’integren i de les seves prestacions. A continuació, s’integren els models de BG en un diagrama de Bond Graph troncal, de la transmissió hidroestàtica en circuit tancat. Aquest és paramètric, és a dir, mitjançant l’ús de paràmetres i variables es defineixen les equacions que caracteritzen els components del sistema que es vol simular. El model s’ha validat amb un cicle teòric, simulat amb el programa 20-sim. Aquest ha permès observar el comportament de la transmissió així com de les seves pèrdues. La validació s’ha dut a terme comparant la resposta de la simulació als cicles teòrics amb els càlculs analítics corresponents. Un cop validat el model amb el cicle teòric, aquest s’ha sotmès a un cicle de treball real, per determinar en qu

Interpersonal communication is critical in training, licensing, and post-graduate maintenance of certification in veterinary medicine. Simulation has a vital role in advancing these skills, but even sophisticated simulation models have pedagogic limitations. Specifically, with learning goals and case scenarios designed by instructors, interaction with simulated participants (SPs) can become performative or circumscribed to evaluative assessments. This article describes co-constructive veterinary simulation (CCVS), an adaptation of a novel approach to participatory simulation that centers on learner-driven goals and individually tailored scenarios. CCVS involves a first phase of scriptwriting, in which a learner collaborates with a facilitator and a professional actor in developing a client-patient case scenario. In a second phase, fellow learners have a blinded interaction with the SP-in-role, unaware of the underlying clinical situation. In the final part, all learners come together for a debriefing session centered on reflective practice. The authors provide guidelines for learners to gain maximal benefit from their participation in CCVS sessions and describe thematic possibilities to incorporate into the model, with specific case examples drawn from routine veterinary practice. Finally, the authors outline challenges and future directions toward implementing CCVS in veterinary medical education toward the ultimate goal of professional growth and co-evolution as veterinary practitioners.

Eusocial Hymenoptera are often characterized by having facultatively or obligately sterile worker castes. However, findings across an increasing number of species are that some workers are non-natal-they have 'drifted' away from where they were born and raised. Moreover, drifters are often indistinguishable from natal workers in the work and benefits provided to joined groups. This seems an evolutionary paradox of providing benefits to potentially unrelated individuals over close kin. Rather than being mistakes, drifting is proposed to be adaptive if joiners either gain inclusive fitness by preferentially moving to other kin groups or through generalized reciprocity in which exchanging workers across groups raises group-level genetic diversity and creates social heterosis. It is unclear, however, if reciprocity is unlikely because of a susceptibility to cheating. In resolving this question, a series of evolutionary simulations show: (1) Reciprocity can persist under a range of genetic assumptions and scenarios of cheating, (2) cheating almost always evolves, but can be expressed in a variety of ways that are not always predictable, (3) the inclusive fitness hypothesis is equally or more susceptible to cheating. Moreover, existing data in Hymenoptera (although not extensive) are more consistent with generalized reciprocity. This supports a hypothesis that drifting, as a phenomenon, may more often reflect maximization of group and parental fitness rather than fitness gains for the individual drifters.

Energy is the main driving force to raise the economy of a nation. The demand for energy grows proportionally with the population of the country. The combined cycle technology is one of the most efficient and widely used technologies for power generation these days if natural gas is utilized as fuel. To meet the ever-growing electric energy demand with decreasing fossil fuel resources, it is necessary to further improve the performances of power generation systems. This can be done either by installing new plants with improved technology or by reducing losses within the existing plants. The present work investigates the thermodynamic performance of the existing Brayton-Rankine power plant currently in operation in India with actual operating data. Energy and exergy analyses of the said plant have been carried out through a computational model coded in MATLAB taking into consideration the important aspect of identifying the places and components of maximum thermodynamic losses which is the originality in the present work. Using the combustion energy of the fuel, which is 759.290 MW, the theoretical value of net power generated, overall thermal efficiency and exergetic efficiency of the plant is estimated to be 317.381 MW, 41.79 %, and 40.19 % respectively. The combustion chambers of the two gas turbines are turned out to be the most irreversible component with the maximum percentage of exergy destruction (14.9 %).

The spray drying process is widely established in the industry worldwide. However, due to its complexity in predicting variables, the technology is often regarded as a "Black box" process. In this study, a model based on energy and mass balances is designed and validated using Matlab/Simulink software and real data from a medium-sized machinery, specifically the Production Minor manufactured by GEA NIRO S/A. Additionally, the simulation incorporates a heat recovery system based on a heat pump, and its economic feasibility is examined.The simulation is validated for a narrow range of variables and demonstrates an accuracy of approximately 95% in most cases.The heat recovery system achieves an average natural gas savings of 0.43 kg/h. However, this saving is accompanied by an additional electrical consumption of 2.1 kW resulting from the operation of the heat pump.The economic feasibility study of the heat recovery system reveals an extra production cost of 0.1€/h in exchange for a 36% average reduction in natural gas dependency.

In a world with high energy cost, the efficiency of motors becomes increasingly important. Thereby, the understanding of loss mechanics is of great significance and having accurate simulation models for the efficiency of motors is crucial. Bosch Rexroth Mellansel has developed a new radial piston hydraulic motor with high power, capable of operating at high torque and speed. In this master thesis the newly developed motor will be examined and undergo a lab test to determine its efficiency. The results from this will then be used to improve the current simulation model and aim for a physical model that align with the efficiency results. Furthermore, the loss mechanics of the motor is important and will be studied during this thesis. The loss mechanics in a motor can be split into two parts, hydro-mechanical and volumetric losses. Hydro-mechanical losses refer to the losses due to both friction and hydraulic flow. The losses in the fluid flow are in turn divided into two parts, the major losses and the minor losses which are the friction losses in the fluid and the losses due to geometric changes in the channels respectively. The volumetric losses are on the other hand the losses from internal and external leakage of the hydraulic fluid, and compression flow which is the extra flow that occurs when the fluid changes density. In order to determine efficiency values from a radial piston hydraulic motor, a test specification was written containing the information needed to perform the test, including two different methods, the pressure and torque method, and the sensors needed to measure the different parameters. For the hydro-mechanical efficiency the uncertainty is 0.1% for the pressure method and 0.15% for the torque method. The test was performed for several different rotational speeds and different pressure points. An improved model was developed from the test results by testing and optimization, and it was found that having the losses due to geometric changes i

Biomass combustion is a carbon–neutral method to generate heat and power and is integral to combating climate change. The wet scrubber is a promising device for recovering heat and reducing particle emissions from flue gas, under the driving force of new European Union legislation. Here, the heat recovery of a wet scrubber was investigated using process data and computer simulations. The process data showed that the scrubber could continuously recover heat corresponding to 10–20% of the energy input. The simulation model consists of two interlinked modules: Module 1 simulates droplet movement in the scrubber, while Module 2 uses the output of Module 1 to predict the heat recovery. The model was validated against process data, showing a mean error of 5.6%. Further optimization was based on the validated model by varying different process parameters, including nozzle position and moisture addition to the flue gas. Moisture addition was shown to be a feasible strategy for potentially increasing heat recovery by up to 3.3%. These results indicate that heat recovery in wet scrubbers is a feasible way to make particle removal cost effective in medium-scale combustion facilities, and that the developed simulation model can play an important role in optimizing these processes.

Biomass combustion is a carbon–neutral method to generate heat and power and is integral to combating climate change. The wet scrubber is a promising device for recovering heat and reducing particle emissions from flue gas, under the driving force of new European Union legislation. Here, the heat recovery of a wet scrubber was investigated using process data and computer simulations. The process data showed that the scrubber could continuously recover heat corresponding to 10–20% of the energy input. The simulation model consists of two interlinked modules: Module 1 simulates droplet movement in the scrubber, while Module 2 uses the output of Module 1 to predict the heat recovery. The model was validated against process data, showing a mean error of 5.6%. Further optimization was based on the validated model by varying different process parameters, including nozzle position and moisture addition to the flue gas. Moisture addition was shown to be a feasible strategy for potentially increasing heat recovery by up to 3.3%. These results indicate that heat recovery in wet scrubbers is a feasible way to make particle removal cost effective in medium-scale combustion facilities, and that the developed simulation model can play an important role in optimizing these processes.

The spray drying process is widely established in the industry worldwide. However, due to its complexity in predicting variables, the technology is often regarded as a "Black box" process. In this study, a model based on energy and mass balances is designed and validated using Matlab/Simulink software and real data from a medium-sized machinery, specifically the Production Minor manufactured by GEA NIRO S/A. Additionally, the simulation incorporates a heat recovery system based on a heat pump, and its economic feasibility is examined.The simulation is validated for a narrow range of variables and demonstrates an accuracy of approximately 95% in most cases.The heat recovery system achieves an average natural gas savings of 0.43 kg/h. However, this saving is accompanied by an additional electrical consumption of 2.1 kW resulting from the operation of the heat pump.The economic feasibility study of the heat recovery system reveals an extra production cost of 0.1€/h in exchange for a 36% average reduction in natural gas dependency.

In a world with high energy cost, the efficiency of motors becomes increasingly important. Thereby, the understanding of loss mechanics is of great significance and having accurate simulation models for the efficiency of motors is crucial. Bosch Rexroth Mellansel has developed a new radial piston hydraulic motor with high power, capable of operating at high torque and speed. In this master thesis the newly developed motor will be examined and undergo a lab test to determine its efficiency. The results from this will then be used to improve the current simulation model and aim for a physical model that align with the efficiency results. Furthermore, the loss mechanics of the motor is important and will be studied during this thesis. The loss mechanics in a motor can be split into two parts, hydro-mechanical and volumetric losses. Hydro-mechanical losses refer to the losses due to both friction and hydraulic flow. The losses in the fluid flow are in turn divided into two parts, the major losses and the minor losses which are the friction losses in the fluid and the losses due to geometric changes in the channels respectively. The volumetric losses are on the other hand the losses from internal and external leakage of the hydraulic fluid, and compression flow which is the extra flow that occurs when the fluid changes density. In order to determine efficiency values from a radial piston hydraulic motor, a test specification was written containing the information needed to perform the test, including two different methods, the pressure and torque method, and the sensors needed to measure the different parameters. For the hydro-mechanical efficiency the uncertainty is 0.1% for the pressure method and 0.15% for the torque method. The test was performed for several different rotational speeds and different pressure points. An improved model was developed from the test results by testing and optimization, and it was found that having the losses due to geometric changes i

Energy demand forecasting has been more vital in recent years with countries setting goals to become climate neutral by 2050. Indeed, energy demand forecasting allows the understanding of drivers of the energy demand in all sectors of the economy. It also allows the planning of transformation of the future energy system. This study focuses on forecasting energy demand in Europe using a multi-country bottom-up modelling approach. The work explores ways of collecting large quantity of data to feed an energy model and method of completion for missing data series. It also aims at studying attributes that make a model user friendly and easy to use for the modelling of several countries. A model and a database are developed to answer these questions. A case application is conducted on the specific topic of the phase out of internal combustion engines in the EU to validate model dynamics and practical use. It is found that an energy demand forecasting model is easier and more time efficient to use with an included historical database. The case study shows that multi-country modelling can be relevant for policy assessment. Finally, improvements and future developments are proposed for the present work., Prognoser för energiefterfrågan har blivit allt viktigare under de senaste åren i och med att länder har satt upp mål om att bli klimatneutrala senast 2050. Prognoser för energiefterfrågan gör det möjligt att förstå drivkrafterna bakom energiefterfrågan inom alla ekonomiska sektorer. Det gör det också möjligt att planera omvandlingen av det framtida energisystemet. Denna studie fokuserar på prognoser för energiefterfrågan i Europa med hjälp av en bottom-up-modelleringsmetod för flera länder. I arbetet undersöks olika sätt att samla in stora mängder data för att mata en energimodell och metoder för att komplettera saknade dataserier. Det syftar också till att studera attribut som gör en modell användar vänlig och lätt att använda för modellering av flera länder. En modell och en databas utvecklas för att besvara dessa frågor. För att validera modellens dynamik och praktiska användning genomförs en fallstudie om utfasningen av förbränningsmotorer i EU. Det visar sig att en modell för prognostisering av energiefterfrågan är enklare och mer tidseffektiv att använda med en inkluderad historisk databas. Fallstudien visar att modeller för flera länder kan vara relevanta för policybedömning. Slutligen föreslås förbättringar och framtida utveckling för det aktuella arbetet.

Energy demand forecasting has been more vital in recent years with countries setting goals to become climate neutral by 2050. Indeed, energy demand forecasting allows the understanding of drivers of the energy demand in all sectors of the economy. It also allows the planning of transformation of the future energy system. This study focuses on forecasting energy demand in Europe using a multi-country bottom-up modelling approach. The work explores ways of collecting large quantity of data to feed an energy model and method of completion for missing data series. It also aims at studying attributes that make a model user friendly and easy to use for the modelling of several countries. A model and a database are developed to answer these questions. A case application is conducted on the specific topic of the phase out of internal combustion engines in the EU to validate model dynamics and practical use. It is found that an energy demand forecasting model is easier and more time efficient to use with an included historical database. The case study shows that multi-country modelling can be relevant for policy assessment. Finally, improvements and future developments are proposed for the present work., Prognoser för energiefterfrågan har blivit allt viktigare under de senaste åren i och med att länder har satt upp mål om att bli klimatneutrala senast 2050. Prognoser för energiefterfrågan gör det möjligt att förstå drivkrafterna bakom energiefterfrågan inom alla ekonomiska sektorer. Det gör det också möjligt att planera omvandlingen av det framtida energisystemet. Denna studie fokuserar på prognoser för energiefterfrågan i Europa med hjälp av en bottom-up-modelleringsmetod för flera länder. I arbetet undersöks olika sätt att samla in stora mängder data för att mata en energimodell och metoder för att komplettera saknade dataserier. Det syftar också till att studera attribut som gör en modell användar vänlig och lätt att använda för modellering av flera länder. En modell och en databas utvecklas för att besvara dessa frågor. För att validera modellens dynamik och praktiska användning genomförs en fallstudie om utfasningen av förbränningsmotorer i EU. Det visar sig att en modell för prognostisering av energiefterfrågan är enklare och mer tidseffektiv att använda med en inkluderad historisk databas. Fallstudien visar att modeller för flera länder kan vara relevanta för policybedömning. Slutligen föreslås förbättringar och framtida utveckling för det aktuella arbetet.

Biomass combustion is a carbon–neutral method to generate heat and power and is integral to combating climate change. The wet scrubber is a promising device for recovering heat and reducing particle emissions from flue gas, under the driving force of new European Union legislation. Here, the heat recovery of a wet scrubber was investigated using process data and computer simulations. The process data showed that the scrubber could continuously recover heat corresponding to 10–20% of the energy input. The simulation model consists of two interlinked modules: Module 1 simulates droplet movement in the scrubber, while Module 2 uses the output of Module 1 to predict the heat recovery. The model was validated against process data, showing a mean error of 5.6%. Further optimization was based on the validated model by varying different process parameters, including nozzle position and moisture addition to the flue gas. Moisture addition was shown to be a feasible strategy for potentially increasing heat recovery by up to 3.3%. These results indicate that heat recovery in wet scrubbers is a feasible way to make particle removal cost effective in medium-scale combustion facilities, and that the developed simulation model can play an important role in optimizing these processes.

A new stochastic and spatial model was developed to evaluate the potential spread of classical swine fever virus (CSFV) within- and between-farms, and considering the specific farm-to-farm contact network. Within-farm transmission was simulated using a modified SI model. Between-farm transmission was assumed to occur by direct contacts (i.e. animal movement) and indirect contacts (i.e. local spread, vehicle and person contacts) and considering the spatial location of farms. Control measures dictated by the European legislation (i.e. depopulation of infected farms, movement restriction, zoning, surveillance, contact tracing) were also implemented into the model. Model experimentation was performed using real data from Segovia, one of the provinces with highest density of pigs in Spain, and results were presented using the mean, 95% probability intervals [95% PI] and risk maps. The estimated mean [95% PI] number of infected, quarantined and depopulated farms were 3 [1,17], 23 [0,76] and 115 [0,318], respectively. The duration of the epidemic was 63 [26,177] days and the most important way of transmission was associated with local spread (61.4% of the infections). Results were consistent with the spread of previous CSFV introductions into the study region. The model and results presented here may be useful for the decision making process and for the improvement of the prevention and control programmes for CSFV., Ministerio de Ciencia e Innovación (España), Universidad Complutense, Junta de Castillla y León, Ministerio de Medio Ambiente y Medio Rural y Marino (España), Depto. de Análisis Matemático y Matemática Aplicada, Fac. de Ciencias Matemáticas, TRUE, pub

Energy is the main driving force to raise the economy of a nation. The demand for energy grows proportionally with the population of the country. The combined cycle technology is one of the most efficient and widely used technologies for power generation these days if natural gas is utilized as fuel. To meet the ever-growing electric energy demand with decreasing fossil fuel resources, it is necessary to further improve the performances of power generation systems. This can be done either by installing new plants with improved technology or by reducing losses within the existing plants. The present work investigates the thermodynamic performance of the existing Brayton-Rankine power plant currently in operation in India with actual operating data. Energy and exergy analyses of the said plant have been carried out through a computational model coded in MATLAB taking into consideration the important aspect of identifying the places and components of maximum thermodynamic losses which is the originality in the present work. Using the combustion energy of the fuel, which is 759.290 MW, the theoretical value of net power generated, overall thermal efficiency and exergetic efficiency of the plant is estimated to be 317.381 MW, 41.79 %, and 40.19 % respectively. The combustion chambers of the two gas turbines are turned out to be the most irreversible component with the maximum percentage of exergy destruction (14.9 %).

Landscape fragmentation and defaunation have major impacts on plant dispersal and dynamics. However, whether the impact of such perturbations on seed dispersal and recruitment change in sign and strength across habitats and spatial scales, and whether they amplify or buffer each other, remains largely unknown. To evaluate, for the first time, the joint impact of fragmentation and defaunation on seed dispersal effectiveness (SDE) across spatial scales (e.g., short- and long-distance seed dispersal), we utilized the long-term field data of a mammal-dispersed tree (Pyrus bourgaeana) in a spatially explicit individual-based model. By means of simulation experiments, we evaluated the effects of different levels of landscape fragmentation and defaunation on SDE and tree recruitment. Our simulation results revealed that the direction and magnitude of the fragmentation effect on SDE depended on its strength (mild, severe) and the spatial scale considered. Severe fragmentation decreased SDE for short- and intermediate-distance seed dispersal. Interestingly, mild and severe fragmentation increased SDE of long-distance seed dispersal, suggesting a positive effect of such perturbations (i.e., an increase in the proportion of successful long-distance dispersal events). Though defaunation had a consistently negative effect on overall SDE, its magnitude was highly species- and spatial–scale-dependent. The impact of defaunation on seed dispersal distance was also species-specific: the proportion of long-distance dispersal increased under total badger (Meles meles) defaunation but decreased under total fox (Vulpes vulpes) defaunation. A pervasive integration of seed dispersal distance into the SDE framework is essential to most comprehensively understand the scale-dependent nature of human activity impacts on plant dynamics. In the long term, strong perturbations (landscape fragmentation and defaunation) could select either for or against long-distance seed dispersal, altering in di

This research focuses on optimizing the performance of a hybrid warehouse system that combines automation with manual picking processes. The study utilizes a case study of an online grocer, Picnic, and investigates the allocation of orders within a buffer and the configuration of the manual picking process. The research identifies the key performance metrics for the system, including the number of late totes, average sojourn time, average stack throughput time, and picker productivity. Several factors impacting the system's performance are examined, such as buffer lane selection and group formation strategies, minimum and maximum group sizes, number of workers, pick times, and input data. Through comprehensive experimentation and simulation modelling, the study reveals that prioritizing the deadline of totes for buffer lane selection and the IPB time for group formation results in the best system performance. The research also suggests that the configuration of the manual process should consider the group size should be adjusted based on the expected workload. The study identifies the consolidation stations as a significant bottleneck in the system, and repairing them promptly on busy days is essential to maintain performance. The research provides practical implications for Picnic, emphasizing efficient buffer allocation and group formation strategies. In conclusion, this research offers valuable insights into enhancing the performance of hybrid warehouse systems. Companies like Picnic can improve operational efficiency and customer satisfaction by optimizing buffer allocation, buffer lane selection, and group formation. The findings from this research can serve as a basis for further optimization and decision-making in similar warehouse setups., Engineering and Policy Analysis

The research on sustainable energy is growing, among which, wind energy catching growing attention and the potential has been supported by more and more countries. Compared with onshore wind farms, offshore wind farms have more advantages including the abundant wind resource at the offshore location and more possible construction areas. While for an offshore wind farm, the operation and maintenance cost is the most significant part and fleet management contributes a lot to it. In order to optimize the fleet size and mix problem for an offshore wind farm based on a simulation method, this thesis has performed a few research steps. Firstly, a literature view on the modeling methods of fleet size and mix problems for offshore wind farms is finished. Different modeling methods and different factors considered in the model are viewed. Then, two simulation models, the open-loop simulation model and the feedforward simulation model, are introduced, including the model inputs, model agent and process, and model outputs. Afterward, the simulation-optimization methodology is introduced and the optimization algorithm used in this research is introduced. Next, one case study using two models separately for a long-term optimization and a short-term optimization is executed and followed by the results of these two simulation models as well as the comparison of the results from them. This thesis aims to combine the optimization method with a simulation model for offshore wind farms, which can be regarded as a decision support tool for fleet size and mix problems and is expected to be a practical technology for the operator/researcher of the offshore wind farm in the future., Mechanical Engineering | Multi-Machine Engineering

Background As mental health in adulthood is related to mental status during adolescence, school-based interventions have been proposed to improve resilience. The objective of this study was to build a simulation model representing the natural history of mental disorders in childhood, adolescence and youth to estimate the cost-effectiveness of the UPRIGHT school-based intervention in promoting resilience and mental health in adolescence. Methods We built a discrete event simulation model fed with real-world data (cumulative incidence disaggregated into eight clusters) from the Basque Health Service database (609,381 individuals) to calculate utilities (quality-adjusted life years [QALYs]) and costs for the general population in two scenarios (base case and intervention). The model translated changes in the wellbeing of adolescents into different risks of mental illnesses for a time horizon of 30 years. Results The number of cases of anxiety was estimated to fall by 5,125 or 9,592 and those of depression by 1,269 and 2,165 if the effect of the intervention lasted 2 or 5 years respectively. From a healthcare system perspective, the intervention was cost-effective for all cases considered with incremental cost-utility ratios always lower than €10,000/QALY and dominant for some subgroups. The intervention was always dominant when including indirect and non-medical costs (societal perspective). Conclusions Although the primary analysis of the trial did not did not detect significant differences, the UPRIGHT intervention promoting positive mental health was dominant in the economic evaluation from the societal perspective. Promoting resilience was more cost-effective in the most deprived group. Despite a lack of information about the spillover effect in some sectors, the economic evaluation framework developed principally for pharmacoeconomics can be applied to interventions to promote resilience in adolescents. As prevention of mental health disorders is even more necessa

Landscape fragmentation and defaunation have major impacts on plant dispersal and dynamics. However, whether the impact of such perturbations on seed dispersal and recruitment change in sign and strength across habitats and spatial scales, and whether they amplify or buffer each other, remains largely unknown. To evaluate, for the first time, the joint impact of fragmentation and defaunation on seed dispersal effectiveness (SDE) across spatial scales (e.g., short- and long-distance seed dispersal), we utilized the long-term field data of a mammal-dispersed tree (Pyrus bourgaeana) in a spatially explicit individual-based model. By means of simulation experiments, we evaluated the effects of different levels of landscape fragmentation and defaunation on SDE and tree recruitment. Our simulation results revealed that the direction and magnitude of the fragmentation effect on SDE depended on its strength (mild, severe) and the spatial scale considered. Severe fragmentation decreased SDE for short- and intermediate-distance seed dispersal. Interestingly, mild and severe fragmentation increased SDE of long-distance seed dispersal, suggesting a positive effect of such perturbations (i.e., an increase in the proportion of successful long-distance dispersal events). Though defaunation had a consistently negative effect on overall SDE, its magnitude was highly species- and spatial–scale-dependent. The impact of defaunation on seed dispersal distance was also species-specific: the proportion of long-distance dispersal increased under total badger (Meles meles) defaunation but decreased under total fox (Vulpes vulpes) defaunation. A pervasive integration of seed dispersal distance into the SDE framework is essential to most comprehensively understand the scale-dependent nature of human activity impacts on plant dynamics. In the long term, strong perturbations (landscape fragmentation and defaunation) could select either for or against long-distance seed dispersal, altering in di

In this thesis, research was done in the area of interacting particle systems. Especially, the symmetric exclusion process with local perturbations was investigated. These perturbations, were in the form of sinks and sources, which add or take away particles at certain rates. Moreover, simulations were done for the asymmetric exclusion process. This process took place on a ring, with the addition of a source. For the symmetric exclusion process with sinks and sources, certain expressions were proven for the expected occupancy of a site. For the simulations, the main goal was to find out how the jumping rates and starting density, influenced the time to get to the fully occupied state, at different source rates. The first proof was for a source at an arbitrary site. From this expression, one could see that if the rates were recurrent, the system converged to the fully occupied state. If, however, the rates were transient, the system had a limiting density. Thereafter, it was shown that if a sink and source are placed in the same arbitrary site, the system always converged to a density, which under the Bernoulli measure, was not equal to the fully occupied state. The fact that the sink and source were in the same site, was an indispensable condition. Subsequently, the case of countably many sources was investigated. For which it was also shown that recurrent rates always yield a fully occupied state, as time tends to infinity. Whereas transient rates, once again, caused a limiting density. Moreover, the special case of a simple random walk in three dimensions or higher was investigated. If, for distances far away from the origin, the source rates could be bounded above by a certain function, then the system would not converge to the fully occupied state. Also, another proof showed that a recurrent set of source sites would always let the process converge to a fully occupied state. Lastly, similar conditions for one time dependent source at the origin were proven. Name, Applied Mathematics | Applied Physics

Highly Pathogenic Avian Influenza (HPAI) H5N1 is considered endemic in most parts of Indonesia and constitutes an important risk for broiler production, especially in Western Java which has the highest poultry population in the country. Most broiler farms in Western Java are smallholder farms that operate under different business types: independent (i.e., revenues based on market price and live bird weight), price-contract (i.e., revenues based on a contract selling price and live bird weight) or makloon (i.e., revenues based on a management fee per sold bird). Many studies focus on the epidemiological impacts of HPAI at the regional level, and insights into the economic impact at the farm level are scarce, especially in the Indonesian context. Meanwhile, a single HPAI outbreak could disrupt smallholder broiler farmers' primary source of income. Therefore, this study aimed to evaluate the economic impact of HPAI outbreaks under different response scenarios (i.e., no action, stamping out, and early selling) on typical Western Java smallholder broiler farms. Furthermore, the effect of different farm business types and the existence of a sick-bird market on the economic effects of HPAI outbreaks were evaluated. We developed a dynamic stochastic bio-economic simulation model to simulate epidemiological and economic impacts of HPAI outbreaks on a typical Western Java smallholder broiler farm during one production round. Our results show that the economic consequences of HPAI outbreaks for independent and price-contract farms are considerable, ranging from, on average, 1.2-62.7 million Indonesian Rupiah (IDR) losses (€76.9 to €3919), depending on the moment of and response to infection, compared to an expected gross margin of 5.3 million IDR (€331) under normal circumstances. The economic loss for makloon farms was substantially lower than for other business types, reducing their incentive to implement biosecurity. The economic impacts were sensitive to changes in a diver

The replication of blood vessels for training and research purposes is possible with the help of additively manufactured (AM) models. However, a meaningful evaluation of the quality of the haptics, here concentrating on friction characteristics, of additively manufactured blood vessel models compared to human vessels is difficult and often only based on subjective assessments. To enable an objective comparison of friction of different AM materials, tests were performed in which a braided stent was pulled through straight test tubes. The force required to do so was measured. The same test setup was used to examine animal blood vessels so that these results could be compared with the findings of the AM materials. In addition, physicians were asked for their assessment of the haptics concerning friction of different materials. Summarizing the results, for the tested Formlabs materials Flexible 80A and Elastic 50A, it can be stated that Flexible 80A is strongly recommended for the replication of blood vessels - even though it is comparatively smooth. The Elastic 50A should only be used for training with increased difficulty since the models are stickier and a flipping of instruments is possible. Coating the materials only involve effort that is not reflected in the benefits.

Biomass combustion is a carbon–neutral method to generate heat and power and is integral to combating climate change. The wet scrubber is a promising device for recovering heat and reducing particle emissions from flue gas, under the driving force of new European Union legislation. Here, the heat recovery of a wet scrubber was investigated using process data and computer simulations. The process data showed that the scrubber could continuously recover heat corresponding to 10–20% of the energy input. The simulation model consists of two interlinked modules: Module 1 simulates droplet movement in the scrubber, while Module 2 uses the output of Module 1 to predict the heat recovery. The model was validated against process data, showing a mean error of 5.6%. Further optimization was based on the validated model by varying different process parameters, including nozzle position and moisture addition to the flue gas. Moisture addition was shown to be a feasible strategy for potentially increasing heat recovery by up to 3.3%. These results indicate that heat recovery in wet scrubbers is a feasible way to make particle removal cost effective in medium-scale combustion facilities, and that the developed simulation model can play an important role in optimizing these processes.

Mastitis is a production disease in dairy farming that causes economic losses. Especially chronic mastitis (i.e., mastitis cases continuing longer than 28 days) can substantially affect the risk of transmission of intramammary infections (IMI) and total milk production losses. Insights into the impact of chronic mastitis on production and farm economics are needed to guide chronic mastitis decision-making. We aimed to estimate the costs of chronic mastitis with a Monte Carlo simulation model in which the costs of chronic mastitis were estimated as part of the total mastitis costs. The model simulated milk yields, IMI dynamics, somatic cell count (SCC), and pregnancy status on an average Dutch dairy farm with 100 cow places over 9 years. The model was parameterized using information from the literature and actual sensor data from automatic milking system (AMS) farms. The daily subclinical milk production losses were modeled using a generalized additive model and sensor data. Transmission of IMI was modeled as well. The model results indicated median total costs of mastitis of € 230 per generic IMI case (i.e., a weighted average of all pathogens). The most substantial cost factors were the extra mastitis cases due to transmission, culling, and milk production losses. Other significant costs originated from dry cow treatments and diverted milk. The model also indicated median total costs due to chronic mastitis of € 118 (51 % of the total mastitis costs). The share of chronic mastitis relative to the total mastitis costs was substantial. Transmission of contagious bacteria had the largest share among the chronic mastitis costs (51 % of the costs of chronic cases). The large share of chronic mastitis costs in the total mastitis costs indicates the economic importance of these mastitis cases. The results of the study point to the need for future research to focus on chronic mastitis and reducing its presence on the AMS dairy farm.

Biomass combustion is a carbon–neutral method to generate heat and power and is integral to combating climate change. The wet scrubber is a promising device for recovering heat and reducing particle emissions from flue gas, under the driving force of new European Union legislation. Here, the heat recovery of a wet scrubber was investigated using process data and computer simulations. The process data showed that the scrubber could continuously recover heat corresponding to 10–20% of the energy input. The simulation model consists of two interlinked modules: Module 1 simulates droplet movement in the scrubber, while Module 2 uses the output of Module 1 to predict the heat recovery. The model was validated against process data, showing a mean error of 5.6%. Further optimization was based on the validated model by varying different process parameters, including nozzle position and moisture addition to the flue gas. Moisture addition was shown to be a feasible strategy for potentially increasing heat recovery by up to 3.3%. These results indicate that heat recovery in wet scrubbers is a feasible way to make particle removal cost effective in medium-scale combustion facilities, and that the developed simulation model can play an important role in optimizing these processes.

Landscape fragmentation and defaunation have major impacts on plant dispersal and dynamics. However, whether the impact of such perturbations on seed dispersal and recruitment change in sign and strength across habitats and spatial scales, and whether they amplify or buffer each other, remains largely unknown. To evaluate, for the first time, the joint impact of fragmentation and defaunation on seed dispersal effectiveness (SDE) across spatial scales (e.g., short- and long-distance seed dispersal), we utilized the long-term field data of a mammal-dispersed tree (Pyrus bourgaeana) in a spatially explicit individual-based model. By means of simulation experiments, we evaluated the effects of different levels of landscape fragmentation and defaunation on SDE and tree recruitment. Our simulation results revealed that the direction and magnitude of the fragmentation effect on SDE depended on its strength (mild, severe) and the spatial scale considered. Severe fragmentation decreased SDE for short- and intermediate-distance seed dispersal. Interestingly, mild and severe fragmentation increased SDE of long-distance seed dispersal, suggesting a positive effect of such perturbations (i.e., an increase in the proportion of successful long-distance dispersal events). Though defaunation had a consistently negative effect on overall SDE, its magnitude was highly species- and spatial–scale-dependent. The impact of defaunation on seed dispersal distance was also species-specific: the proportion of long-distance dispersal increased under total badger (Meles meles) defaunation but decreased under total fox (Vulpes vulpes) defaunation. A pervasive integration of seed dispersal distance into the SDE framework is essential to most comprehensively understand the scale-dependent nature of human activity impacts on plant dynamics. In the long term, strong perturbations (landscape fragmentation and defaunation) could select either for or against long-distance seed dispersal, altering in di

Staphylococcus aureus (S. aureus) strains with considerable genetic and phenotypic differences have previously been identified. The economic and epidemiologic impact of S. aureus mastitis has been investigated, but none of these studies took differences between strains into account. Here we aimed to investigate how differences between S. aureus strains affect the economic and epidemiologic outcome of various intervention strategies against clinical and subclinical intramammary infections. Five S. aureus strains were modelled using a stochastic bio-economic model simulating a dairy herd of 200 cows using single-day time steps. The strain characteristics of the five simulated S. aureus strains (general, contagious, spill-over, clinical and persistent) were based on divergent phenotypes as described in literature. Outcomes of the model included incidence (both clinical and subclinical), number of antibiotic treatment days, number of culled cows, and net income. Intervention strategies against clinical and subclinical intramammary infections were based on (variations of) intramammary antibiotic treatment, testing, and culling. Both single and multiple pathogen (intramammary infection caused by S. aureus, Escherichia coli, and non-aureus staphylococci) scenarios were simulated to determine the effect of the five S. aureus strains on the impact of 19 different intervention strategies. The results showed that the incidence (both clinical and subclinical), number of treatment days, number of culled cows, and net income varied considerably for the different S. aureus strains. Comparison of the model outcomes within and between strains showed that for most intervention strategies the relative impact differed per strain. However, the intervention strategy with the best outcome for most variables and strains was the culling of cows with a recovery probability lower than 50%. This shows that the relative economic and epidemiologic impact of most of the modelled intervention s

In this paper is concerned with real world problems were simulation theory using Monte’s Carlo simulation technique. The simulation theory is an account of our everyday ability to make sense of the behavior of others. This paper makes a try to use Monte-carlo simulation technique inclusive of simulation theory troubles to provide an explanation for how the combination of these strategies in agriculture will no longer only assist in reducing of the triumphing problems in agriculture however additionally lead to better efficiency.

The river Waal is part of an economic important transport-corridor that connects the ports of Antwerp, Rotterdam and Amsterdam to Germany. Ongoing processes such as (1) climate change, (2) large scale river bed erosion and (3) up-scaling of vessels threaten the future navigability of the river. This will lead to massive economic damages as taken in 2018 (Strengs et al., 2020). Canalisation of the river by means of weir-lock complexes is a considered by Rijkswaterstaat to improve inland navigation during periods of low discharge and prevent economic damages. This leads to the primary goal of this study; investigate the required lock capacity to provide smooth and reliable passage of the river Waal now and in the future. A literature review was conducted to assess the future development of the drivers of the worsening navigation conditions and to gain insight in market- and fleet developments. The developments in the drivers underline the urgency for measures. The development of the fleet navigating on the river Waal is characterised by up-scaling for the past 20 year. This trend is expected to continue the coming years. Future market developments are very uncertain due to the energy transition and the nitrogen crisis, making it very difficult to make accurate projections on future fleet intensities and compositions. Therefore a range of traffic intensities is used to characterise future fleets that encounter the lock complexes. The number and locations of the lock complexes is investigated by analysing available nautical depths and water levels along the river Waal for several stationary discharges at Lobith. Water levels are set up to a level such that navigation for all vessels (fully loaded) is possible. From a financial perspective it is most attractive to minimise the number of weir-lock complexes, however this is contrary to flood safety aspects on the river Waal. Installation of two weir lock complexes is considered plausible taking into ac, Civil Engineering | Hydraulic Engineering

In this paper is concerned with real world problems were simulation theory using Monte’s Carlo simulation technique. The simulation theory is an account of our everyday ability to make sense of the behavior of others. This paper makes a try to use Monte-carlo simulation technique inclusive of simulation theory troubles to provide an explanation for how the combination of these strategies in agriculture will no longer only assist in reducing of the triumphing problems in agriculture however additionally lead to better efficiency.

The transition towards greener mobility will play a significant role in decarbonizing the economy. Hence, policy makers need tools that allow them to test alternatives towards that goal. This drive has led to the development of increasingly accurate transport models, with the latest generation being activity-based transport demand models. These models, however, are hard to build, as they are very data-intensive and complex, therefore in this research project a methodology is conceived which attempts to use readily available data from the Dutch travel demand survey (ODiN) and open source software such as ActivitySim, originally developed as a package in Python to make activity-based models in the United States. While a very time-intensive task, the data was able to be processed for use in ActivitySim. The data was mostly complete, but needed to be complemented with data from the \textcite{centraal_bureau_voor_de_statistiek_statline_2019}, and information about members of the household other than the survey respondent, and joint tours, is missing. The data, however, can be processed in a way that can be reapplied in the future, which lowers the barrier to develop a model with Dutch survey data. Choice is modeled as logit discrete choice models, and the estimation of the parameters required is facilitated by ActivitySim, which has built-in functionality to support it, and with an integrated workflow the model parameters can be estimated with little effort. With this procedure, and choosing workplace and school locations in advance, a good degree of accuracy was achieved, but it was shown that the sampling method used to deal with the very large choice set introduced significant bias to the model output, as observed in the travel distances, which were shorter in the simulated output than in the observations in the survey data. While ActivitySim has a sampling methodology to deal with large choice sets, an alternative method, Stratified Importa, Public repository containing source code, model configurations and data processing scripts https://github.com/davidmatheus002/activity_based_modeling.git, Engineering and Policy Analysis

This thesis estimates potential runway throughput gains using a reduced wake separation based on the 123 most prevalent aircraft in the United States fleet. The analysis considers Runway Occupancy Time (ROT) constraint factors and existing geometric design factors. This research extracts the historic data from Airport Surface Detection Equipment Model X (ASDE-X) for analysis. The Runway Exit Design Interactive Model (REDIM) is used to optimize the runway exit locations and reduce ROT. The runway throughput and safety factors are generated from a Monte Carlo runway simulator. This thesis focuses on selected US airport runways that could benefit from geometric optimization. The study aims to estimate ROT improvements through improved runway exit locations and the changes in runway throughput considering ROT constraint factors. The results of the thesis show that Dallas Fort Worth International Airport (DFW) runway 35C and Denver International Airport (DEN) runway 16R have the potential to improve the ROT. After the optimization to locate runway exits, the ROT time of the RECAT group F and G aircraft (greater than 90% of the arrivals) was reduced by three to five seconds (a very significant effect). After the ROT reductions and with the application of reduced wake separation criteria with the ROT constraint factor applied, the arrival-only capacity of DFW runway 35C improved by 3.5 arrivals per hour. The arrival-only capacity on DEN runway 16R improved by 2.14 arrivals per hour. Both runways maintained a probability of violation between time-based separation and ROT time at around 1.5%. The study concludes that the application of reduced wake separation criteria alone is a necessary but insufficient condition to improve the efficiency of arrival runways. Through careful improvements of runway exit locations, reductions in ROT provide reliability and efficiency to the operation of runways.

Background: Advances in sports medicine, rehabilitation applications and diagnostics of neuromuscular disorders are based on the analysis of skeletal muscle contractions. Recently, medical imaging techniques have transformed the study of muscle contractions, by allowing identifcation of individual motor units’ activity, within the whole studied muscle. However, appropriate image-based simulation models, which would assist the continued development of these new imaging methods are missing. This is mainly due to a lack of models that describe the complex interaction between tissues within a muscle and its surroundings, e.g., muscle fbres, fascia, vasculature, bone, skin, and subcutaneous fat. Herein, we propose a new approach to overcome this limitation. Methods: In this work, we propose to use deep learning to model the authentic intramuscular skeletal muscle contraction pattern using domain-to-domain translation between in silico (simulated) and in vivo (experimental) image sequences of skeletal muscle contraction dynamics. For this purpose, the 3D cycle generative adversarial network (cycleGAN) models were evaluated on several hyperparameter settings and modifcations. The results show that there were large diferences between the spatial features of in silico and in vivo data, and that a model could be trained to generate authentic spatio-temporal features similar to those obtained from in vivo experimental data. In addition, we used diference maps between input and output of the trained model generator to study the translated characteristics of in vivo data. Results: This work provides a model to generate authentic intra-muscular skeletal muscle contraction dynamics that could be used to gain further and much needed physiological and pathological insights and assess and overcome limitations within the newly developed research feld of neuromuscular imaging.

Background: Advances in sports medicine, rehabilitation applications and diagnostics of neuromuscular disorders are based on the analysis of skeletal muscle contractions. Recently, medical imaging techniques have transformed the study of muscle contractions, by allowing identifcation of individual motor units’ activity, within the whole studied muscle. However, appropriate image-based simulation models, which would assist the continued development of these new imaging methods are missing. This is mainly due to a lack of models that describe the complex interaction between tissues within a muscle and its surroundings, e.g., muscle fbres, fascia, vasculature, bone, skin, and subcutaneous fat. Herein, we propose a new approach to overcome this limitation. Methods: In this work, we propose to use deep learning to model the authentic intramuscular skeletal muscle contraction pattern using domain-to-domain translation between in silico (simulated) and in vivo (experimental) image sequences of skeletal muscle contraction dynamics. For this purpose, the 3D cycle generative adversarial network (cycleGAN) models were evaluated on several hyperparameter settings and modifcations. The results show that there were large diferences between the spatial features of in silico and in vivo data, and that a model could be trained to generate authentic spatio-temporal features similar to those obtained from in vivo experimental data. In addition, we used diference maps between input and output of the trained model generator to study the translated characteristics of in vivo data. Results: This work provides a model to generate authentic intra-muscular skeletal muscle contraction dynamics that could be used to gain further and much needed physiological and pathological insights and assess and overcome limitations within the newly developed research feld of neuromuscular imaging.

Background: Advances in sports medicine, rehabilitation applications and diagnostics of neuromuscular disorders are based on the analysis of skeletal muscle contractions. Recently, medical imaging techniques have transformed the study of muscle contractions, by allowing identifcation of individual motor units’ activity, within the whole studied muscle. However, appropriate image-based simulation models, which would assist the continued development of these new imaging methods are missing. This is mainly due to a lack of models that describe the complex interaction between tissues within a muscle and its surroundings, e.g., muscle fbres, fascia, vasculature, bone, skin, and subcutaneous fat. Herein, we propose a new approach to overcome this limitation. Methods: In this work, we propose to use deep learning to model the authentic intramuscular skeletal muscle contraction pattern using domain-to-domain translation between in silico (simulated) and in vivo (experimental) image sequences of skeletal muscle contraction dynamics. For this purpose, the 3D cycle generative adversarial network (cycleGAN) models were evaluated on several hyperparameter settings and modifcations. The results show that there were large diferences between the spatial features of in silico and in vivo data, and that a model could be trained to generate authentic spatio-temporal features similar to those obtained from in vivo experimental data. In addition, we used diference maps between input and output of the trained model generator to study the translated characteristics of in vivo data. Results: This work provides a model to generate authentic intra-muscular skeletal muscle contraction dynamics that could be used to gain further and much needed physiological and pathological insights and assess and overcome limitations within the newly developed research feld of neuromuscular imaging.