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When people make choices, the items they consider are often embedded in a context (of other items). How this context affects the valuation of the specific item is an important question. High-value context might make items appear less attractive because of contrast-the tendency to normalize perception of an object relative to its background-or more attractive because of assimilation-the tendency to group objects together. Alternatively, a high-value context might increase prior expectations about the item's value. Here, we investigated these possibilities. We examined how unavailable context items affect choices between two target items, as well as the willingness-to-pay for single targets. Participants viewed sets of three items for several seconds before the target(s) were highlighted. In both tasks, we found a significant assimilation-like effect where participants were more likely to choose or place a higher value on a target when it was surrounded by higher-value context. However, these context effects were only significant for participants' fastest choices. Using variants of a drift-diffusion model, we established that the unavailable context shifted participants' prior expectations towards the average values of the sets but had an inconclusive effect on their evaluations of the targets during the decision (i.e. drift rates). In summary, we find that people use context to inform their initial valuations. This can improve efficiency by allowing people to get a head start on their decision. However, it also means that the valuation of an item can change depending on the context.

Collective dynamics play a key role in everyday decision-making. Whether social influence promotes the spread of accurate information and ultimately results in adaptive behavior or leads to false information cascades and maladaptive social contagion strongly depends on the cognitive mechanisms underlying social interactions. Here we argue that cognitive modeling, in tandem with experiments that allow collective dynamics to emerge, can mechanistically link cognitive processes at the individual and collective levels. We illustrate the strength of this cognitive computational approach with two highly successful cognitive models that have been applied to interactive group experiments: evidence-accumulation and reinforcement-learning models. We show how these approaches make it possible to simultaneously study (a) how individual cognition drives social systems, (b) how social systems drive individual cognition, and (c) the dynamic feedback processes between the two layers., Deutsche Forschungsgemeinschaft https://doi.org/10.13039/501100001659, Science of Intelligence, Peer Reviewed

A degenerate parabolic system consisting in two continuity equations for densities of charged particles and in the Poisson equation for an electric potential is considered. We show the finite speed of propagation, a waiting time property for the vacuum (null) sets and a property of formation of vacuum. The proofs are based on energy methods. Furthermore, some results on the uniqueness of solutions are proved by using different duality methods., Depto. de Análisis Matemático y Matemática Aplicada, Fac. de Ciencias Matemáticas, TRUE, pub

This paper is about the drift-diffusion equations for semiconductors. Existence and uniqueness of weak solutions are obtained. The existence is proved by using the regularization technique. The proof of the uniqueness is interesting., DGICYT (Spain), Depto. de Análisis Matemático y Matemática Aplicada, Fac. de Ciencias Matemáticas, TRUE, pub

The temporal and spatial localization of vacuum sets of the solutions to the drift-diffusion equations for semiconductors is studied in this paper. It is shown that if there are vacuum sets initially then there are vacuum sets for a small time, which shows the finite propagation speed of the support of the densities. It is also shown that for a certain recombination-generation rate there is no dilation of the initial support, and under some condition on the recombination-generation rate the vacuum will develop after a certain time even if there is no vacuum initially. These results are proved based on a local energy method for free boundary problems., Depto. de Análisis Matemático y Matemática Aplicada, Fac. de Ciencias Matemáticas, TRUE, pub

When a person makes a decision, it is automatically accompanied by a subjective probability judgement of the decision being correct, in other words, a (local) confidence judgement. Confidence judgements have, among other things, an effect on justifications of future decisions and behaviour. A better understanding of the metacognitive processes responsible for these confidence judgements could improve behaviour models. To date, confidence judgements are mostly studied in a fundamental manner. Little to no research has been done into confidence in more dynamic tasks. Such applied research could render insights on whether fundamental principles also hold for real-life tasks. It could also have practical relevance for several applications. Driving is amongst the areas for which an improved understanding of the decision making and accompanied confidence judgements can be useful, for instance in order to improve driving assistance systems. However, current studies on driving behaviour are merely focused on decision making and do not take confidence into account. In this study, we made a first attempt of connecting these two fields of research by investigating the confidence of drivers in left-turn gap acceptance decisions in a driver simulator experiment (N=17). The study showed that confidence can be related to the gap size with respect to the oncoming vehicle, described by the time-to-arrival and the distance gap. Confidence increases with the gap size for gap accepting decisions and decreases with the gap size for gap rejecting decisions. In addition, we concluded that confidence can be related to the driving behaviour, and that confidence is negatively related to the decision response time. Moreover, we found that confidence judgements can best be captured with the use of an extended dynamic drift diffusion decision model of which the drift rate of the evidence accumulator as well as the decision boundaries are functions of the time-to-arrival and distance gap, Mechanical Engineering | Vehicle Engineering | Cognitive Robotics

Este artículo pertenece a un número especial de Advances in Nanotechnology of Perovskite and Silicon Solar Cells, In the Atacama Desert, the spectral distribution of solar radiation differs from the global standard, showing very high levels of irradiation with a particularly high ultraviolet content. Additionally, the response of photovoltaic (PV) technologies is spectrally dependent, so it is necessary to consider local conditions and type of technology to optimize PV devices since solar cells are usually designed for maximum performance under standard testing conditions (STC). In this work, we determined geometrical and doping parameters to optimize the power of an n-type bifacial passivated emitter and rear totally diffused solar cell (n-PERT). Six parameters (the thicknesses of cell, emitter, and back surface field, as well as doping concentration of emitter, base, and back surface field) were used to optimize the cell under the Atacama Desert spectrum (AM 1.08) and under standard conditions (AM 1.5) through a genetic algorithm. To validate the model, the calculated performance of the n-PERT cell was compared with experimental measurements. Computed and experimental efficiencies showed a relative difference below 1% under STC conditions. Through the optimization process, we found that different geometry and doping concentrations are necessary for cells to be used in the Atacama Desert. Reducing the thickness of all layers and increasing doping can lead to a relative increment of 5.4% in the cell efficiency under AM 1.08. Finally, we show the potential effect of metallization and the viability of reducing the thicknesses of the emitter and the back surface field., Depto. de Análisis Matemático y Matemática Aplicada, Fac. de Ciencias Matemáticas, Instituto de Matemática Interdisciplinar (IMI), TRUE, pub

When searching for a target object, we engage in a continuous "look-identify" cycle in which we use known features of the target to guide attention toward potential targets and then to decide whether the selected object is indeed the target. Target information in memory (the target template or attentional template) is typically characterized as having a single, fixed source. However, debate has recently emerged over whether flexibility in the target template is relational or optimal. On the basis of evidence from two experiments using college students (Ns = 30 and 70, respectively), we propose that initial guidance of attention uses a coarse relational code, but subsequent decisions use an optimal code. Our results offer a novel perspective that the precision of template information differs when guiding sensory selection and when making identity decisions during visual search.

Organic solar cells (OSCs) are emerging low-cost, easy production photovoltaics. Their efficiency is strongly affected by the interface physics that needs to be researched. In this thesis, the interface physics of metal/inorganic semiconductor and metal/organic semiconductor contacts is considered. The basic structures and operation principles of OSCs are reviewed and a detailed description of the drift-diffusion model (DDM) used for modeling the OSCs is included. An extensive and detailed literature review of different physical effects that can cause the S-kink appearance in the current density-voltage (J-V) characteristics of OSCs is presented. The original research results on ITO/(poly(3,4‒ethilenedioxythiophene):poly (styrenesulfonate))PEDOT:PSS/(poly(3‒hexylthiophene))P3HT:(1‒(3‒methoxycarbonyl)propyl‒1‒phenyl‒[6,6]‒methanofullerene) PCBM/Al and ITO/PEDOT:PSS/P3HT:(indene‒C60 bisadduct) ICBA/Al solar cells are presented and discussed. The influence of the surface processes on the shape of OSCs’ J-V characteristics has been investigated by DDM. The surface recombination and thermal injection of charge carriers on the anode and cathode are taken into account through boundary conditions. It is deduced that there are two different types of S-shape deviations in OSCs' J-V characteristics, one arises from the reduced surface recombination velocities (SRVs), and the other is attributed to the large (>0.2eV) injection barrier height for electrons. The measured J-V characteristics of ITO/PEDOT:PSS/P3HT:PCBM/Al and ITO/PEDOT:PSS/P3HT:ICBA/Al solar cells are reproduced well by the DDM. It is anticipated that the S-shaped J-V curves of ITO/PEDOT:PSS/P3HT:ICBA/Al solar cells originate from the large electron barrier height on the cathode, rather than by the reduction of the SRVs., Органске соларне ћелије су јефтине фотоволтаичне направе лаке производње. Њихова ефикасност јако зависи од контактне физике на електродним спојевима коју треба истражити. У овој тези, у уводном делу, разматрана је физика на споју метала и неорганског полупроводника, као и на споју метала и органског полупроводника. Представљене су основне структуре и описан је принцип рада органских соларних ћелија (ОСЋ), а дрифт-дифузиони модел (ДДМ) који се користи за моделовање ОСЋ је детаљно размотрен. Саставни део дисертације је и опсежан преглед литературе на тему различитих физичких ефеката који могу проузроковати појаву S-девијације струјно-напонске (I-V) карактеристике ОСЋ. Спроведено је оригнално истраживање на ITO/(poly(3,4‒ethilenedioxythiophene):poly (styrenesulfonate))PEDOT:PSS/(poly(3‒hexylthiophene))P3HT:(1‒(3‒methoxycarbonyl)propyl‒1‒phenyl‒[6,6]‒methanofullerene) PCBM/Al and ITO/PEDOT:PSS/P3HT:(indene‒C60 bisadduct) ICBA/Al соларним ћелијама и добијени резултати су представљени и продискутовани. Утицај површинских процеса на облик I-V карактеристике ОСЋ је испитан помоћу ДДМ. Површинска рекомбинација и термичка инјекција носилаца наелектрисања на аноди и катоди узете су у обзир кроз граничне услове. Закључено је да постоје две различите врсте S-девијације I-V криве ОСЋ. Прва врста потиче од редукованих брзина површинске рекомбинације (БПР) док се друга врста може приписати великој висини инјекционе баријере (>0,2eV) за електроне. Измерене I-V карактеристике ITO/PEDOT:PSS/P3HT:PCBM/Al и ITO/PEDOT:PSS/P3HT:ICBA/Al соларних ћелија су добро репродуковане помоћу ДДМ. Утврђено је да S-девијација I-V кривих ITO/PEDOT:PSS/P3HT:ICBA/Al соларних ћелија потиче од велике висине инјекционе баријере за електроне на катоди, а не од редукованих БПР.

Knowledge without awareness, or implicit knowledge, influences a variety of behaviors. It is unknown however, whether implicit knowledge of statistical structure informs visual perceptual decisions or whether explicit knowledge of statistical probabilities is required. Here, we measured visual decision-making performance using a novel task in which humans reported the orientation of two differently colored translational Glass patterns; each color associated with different orientation probabilities. The task design allowed us to assess participants’ ability to learn and use a general orientation prior as well as a color specific feature prior. Classifying decision-makers based on a questionnaire revealed that both implicit and explicit learners implemented a general orientation bias by adjusting the starting point of evidence accumulation in the drift diffusion model framework. Explicit learners additionally adjusted the drift rate offset. When subjects implemented a stimulus specific bias, they did so by adjusting primarily the drift rate offset. We conclude that humans can learn priors implicitly for perceptual decision-making and depending on awareness implement the priors using different mechanisms.

Knowledge without awareness, or implicit knowledge, influences a variety of behaviors. It is unknown however, whether implicit knowledge of statistical structure informs visual perceptual decisions or whether explicit knowledge of statistical probabilities is required. Here, we measured visual decision-making performance using a novel task in which humans reported the orientation of two differently colored translational Glass patterns; each color associated with different orientation probabilities. The task design allowed us to assess participants’ ability to learn and use a general orientation prior as well as a color specific feature prior. Classifying decision-makers based on a questionnaire revealed that both implicit and explicit learners implemented a general orientation bias by adjusting the starting point of evidence accumulation in the drift diffusion model framework. Explicit learners additionally adjusted the drift rate offset. When subjects implemented a stimulus specific bias, they did so by adjusting primarily the drift rate offset. We conclude that humans can learn priors implicitly for perceptual decision-making and depending on awareness implement the priors using different mechanisms.

Dishonesty erodes society. Although much is known about dishonesty, the process leading up to the decision of whether to be honest or dishonest is often assumed to be homogenous and is not well understood. In this paper, we take a more nuanced approach and explore more closely the process of deciding whether to cheat or be honest when an opportunity to cheat arises. We do this in two laboratory eye tracking experiments. In our first experiment (n = 193), we identify heterogeneity in the decision to cheat. Some decisions on whether to cheat or be honest exhibit relatively little variation and appear to be oriented towards cheating (or honesty) with apparently little consideration of the alternative, whereas other decisions seem to be characterized by a higher degree of consideration for both decision alternatives. Our second experiment (n = 299) demonstrates that a gaze dependent intervention in the choices process is able to affect the behavioral outcomes.

Пояснювальна записка дисертації за обсягом становить 73 сторінки, містить 31 рисунок та 4 таблиці. Використано 35 бібліографічних джерел. Актуальність теми. Одночасно зі зменшенням розмірів елементів інтегральних мікросхем вирішення теплових проблем пристроїв, що входять до їх складу набуває все більшої актуальності. Інтегральні схеми, що використовуються у військовій, автомобільній та атомній промисловості потребують високих робочих температур. Дослідження впливу різних факторів на самонагрів FinFET пристроїв є перспективним. Проте наразі чисельних досліджень процесів самонагріву в тривимірних транзисторах типу FinFET недостатньо. Зв'язок роботи з науковими програмами, планами, темами. Науково-дослідна робота за темою дисертації проводилася за власною ініціативою на кафедрі ФЕС НТУУ «КПІ імені Ігоря Сікорського». Мета дисертаційної роботи полягає в дослідженні впливу масштабування кремнієвого транзистору типу FinFET на потужність, що виділяється та зростання температури всередині пристрою. Досягнення мети передбачає вирішення таких задач: – Побудова структурної моделі FinFET; – Розрахунок розподілу потенціалу та вольт-амперних характеристик; – Дослідження процесу теплогенерації; – Побудова розподілу температури всередині пристрою; – Дослідження впливу геометрії на самонагрів транзистору; – Аналіз впливу нанорозмірних ефектів у каналі FinFET на процес самонагріву. Об’єктом дослідження є кремнієвий транзистор типу FinFET з розмірами 32 нм. Предметом дослідження є фактори, які впливають на процес самонагріву тривимірних транзисторів типу FinFET. Методи дослідження. Комп’ютерне моделювання структури FinFET. Побудова розподілу потенціалу шляхом чисельного розв’язання рівняння Пуассона. Одержання вольт-амперних характеристик згідно з моделлю дрейфу та дифузії. Чисельне моделювання процесу самонагріву FinFET. Були отримані наступні результати: 1. Проведено чисельне моделювання структури та процесів самонагріву FinFET транзистору за допомогою програмного пакету GTS Framewo, The thesis explanatory note contains 73 pages 4 tables and 31 figures with 35 names of bibliographic sources. The objective of this work is influence of FinFET-type silicon transistor parameters on its thermal characteristics. The purpose of this work is to investigate the influence of scaling of FinFET-type silicon transistor at power dissipation and temperature growth. The challenges are: to design FinFET structure; to calculate distribution of potential and transfer characteristics; to study heat generation; to calculate temperature distribution inside device; to investigate influence of geometry on self-heating of FinFET; to analyze influence of nanoscale effects in FinFET channel on its self-heating. The object of study is a silicon 32 nm FinFET device. The subject is an influence of different factors on self-heating of the FinFET type 3D transistor. Investigation methods. FinFET computer design. Numerical solution of Poisson equation. Obtaining of transfer characteristics according to drift-diffusion model. Numerical simulation of FinFET self-heating. Next results were received: 1. Numerical modelling of FinFET structure and process of self-heating using GTS Framework was conducted. 2. Influence of changes in device geometry at FinFET self-heating was investigated. Decreasing of device power dissipation due to geometry changes was demonstrated. 3. Increasing of heat flux density due to decreasing of device size was determined. 4. Influence of decreasing of device size on max temperature was studied. 5. Impact of nanoscale effects at FinFET self-heating was analyzed. Decreasing of channel heat conductivity leads to increasing of device max temperature. 6. Effect of channel heat conductivity decreasing on dissipated power was determined. Scientific novelty follows the definition of influence of geometry factor and heat conduction of nanoscale silicon at FinFET self-heating. The significance of the results. It was found that channel size decreasing allows reducin

When deciding between different options, animals including humans face the dilemma that fast decisions tend to be erroneous, whereas accurate decisions tend to be relatively slow. Recently, it has been suggested that differences in the efficacy with which animals make a decision relate closely to individual behavioural differences. In this paper, we tested this hypothesis in a unique unicellular organism, the slime mould Physarum polycephalum. We first confirmed that slime moulds differed consistently in their exploratory behaviour from 'fast' to 'slow' explorers. Second, we showed that slow explorers made more accurate decisions than fast explorers. Third, we demonstrated that slime moulds integrated food cues in time and achieved higher accuracy when sampling time was longer. Lastly, we showed that in a competition context, fast explorers excelled when a single food source was offered, while slow explorers excelled when two food sources varying in quality were offered. Our results revealed that individual differences in accuracy were partly driven by differences in exploratory behaviour. These findings support the hypothesis that decision-making abilities are associated with behavioural types, even in unicellular organisms.

Decisions based on affectively relevant stimuli, such as food items, hardly follow strictly rational rules. Being hungry, the food's caloric density, and the subjective valence attributed to various foods are known factors that modulate food choices. Yet, how these factors relatively and altogether contribute to the food choice process is still unknown. In this study, we showed 16 healthy young adults low- and high-calorie food when hungry or fed, and we asked them to evaluate the valence of each visually-presented food. To compute the relative influence of hunger, caloric density and valence on food choice, we applied a hierarchical drift diffusion model (HDDM). Results indicated that hunger, caloric density and valence affected how fast participants accumulated information in favor of the chosen item over the other. When fed, participants were faster in choosing low-calorie foods and foods with a higher valence. Conversely, when hungry, participants were faster in choosing high-calorie foods, including food items with lower subjective valence. All in all, these findings confirm the complex nature of food choices and the usefulness of nuanced computational models to address the multifaceted nature of decision-making and value assessment processes affecting food selection.

The laser-induced current carrier generation and transport under large biasing voltages in photoconductive materials located in electrode gap region of photoconductive antennas is a complex process involving many different phenomena that interact with each other in intricate ways. Given the large biasing voltages employed, a simple model that assumes that the carriers travel along the biasing field lines allows to retain the basic features of the photocarrier generation process. The model is presented in detail and results for a typical interdigitated electrode are shown to well agree with measures found in the literature., This work was supported in part by the Spanish Inter-Ministerial Commission on Science and Technology (CICYT) under projects TEC201678028-C3-1 and, by FEDER and the Unidad de Excelencia Maria de Maeztu MDM-2016-0600, which is financed by the Agencia Estatal de Investigacion, Spain, and by Catalan Research Group 2017 SGR219., Peer Reviewed, Postprint (published version)

The combination of recent drought conditions, closing of biomass processing plants, increased open-burning permit costs, and current practices of agriculture and forest management have created an abundant amount of biomass that is causing increased green house gas (GHG) emissions and potential for catastrophic wild fires. This has motivated the search for innovative solutions for the usage of biomass and its byproducts.Activated carbons are highly valuable products with endless applications in the food and pharmaceutical industries, among others. While the conventional (physical) activation process involves exposing biochar to superheated steam, the addition of electric fields is being analyzed as an innovative alternative to the energy-intensive physical activation process. The application of an electric field creates a plasma discharge in the gases and induces Joule heating in the carbonaceous material. The main objective of this dissertation is to investigate the dynamics of charge/Joule heat transport and thermal runaway. The purpose is to induce thermal breakdown (high temperatures) in biomass, biochar, and graphite with low energy input and in short amounts of time. This concept was explored through numerical simulation using an electric-thermal model and two variations of a hydrodynamic model, which were developed as part of this work. Results show that Joule heating indeed produces high temperatures in the order of seconds for wood, and in fractions of a second for biochar and graphite -- with low energy input. A second objective is to produce and assess activated carbons derived from agricultural residues and forest woody biomass. In this work, physical activation of peach pit biochar was explored. BET surface areas up to nearly 600 m^2/g were obtained. Though these values are significant, they are still lower than those of commercial activated carbons (>1000 m^2/g). However, these are promising results, especially, because these materials have the poten

Previous research on public-good games revealed greater contributions by fast decision-makers than by slow decision-makers. Interpreting greater contributions as generosity, this has been seen as evidence of generosity being intuitive. We caution that fast decisions are more prone to error, and that mistakes, rather than preferences, may drive the observed comparative static. Varying the location of the equilibrium in public-good games with a unique dominant strategy, we show that the location of the equilibrium determines whether contributions are larger for fast decision-makers than for slow decision-makers. Replicating previous results, we find that fast decision-makers give more than slow decision-makers when the equilibrium is below the mid-point of the strategy set, but that this result is reversed when the equilibrium is above the mid-point. Consistent with fast decisions being more prone to error, we find that individuals who make (or have to make) fast decisions are insensitive to incentives, more often make mistakes, and are less likely to make equilibrium contributions. These findings make clear that we must control for the rate of errors if we are to draw inference on preferences from response time.

The combination of recent drought conditions, closing of biomass processing plants, increased open-burning permit costs, and current practices of agriculture and forest management have created an abundant amount of biomass that is causing increased green house gas (GHG) emissions and potential for catastrophic wild fires. This has motivated the search for innovative solutions for the usage of biomass and its byproducts.Activated carbons are highly valuable products with endless applications in the food and pharmaceutical industries, among others. While the conventional (physical) activation process involves exposing biochar to superheated steam, the addition of electric fields is being analyzed as an innovative alternative to the energy-intensive physical activation process. The application of an electric field creates a plasma discharge in the gases and induces Joule heating in the carbonaceous material. The main objective of this dissertation is to investigate the dynamics of charge/Joule heat transport and thermal runaway. The purpose is to induce thermal breakdown (high temperatures) in biomass, biochar, and graphite with low energy input and in short amounts of time. This concept was explored through numerical simulation using an electric-thermal model and two variations of a hydrodynamic model, which were developed as part of this work. Results show that Joule heating indeed produces high temperatures in the order of seconds for wood, and in fractions of a second for biochar and graphite -- with low energy input. A second objective is to produce and assess activated carbons derived from agricultural residues and forest woody biomass. In this work, physical activation of peach pit biochar was explored. BET surface areas up to nearly 600 m^2/g were obtained. Though these values are significant, they are still lower than those of commercial activated carbons (>1000 m^2/g). However, these are promising results, especially, because these materials have the poten

Previous research on public-good games revealed greater contributions by fast decision-makers than by slow decision-makers. Interpreting greater contributions as generosity, this has been seen as evidence of generosity being intuitive. We caution that fast decisions are more prone to error, and that mistakes, rather than preferences, may drive the observed comparative static. Varying the location of the equilibrium in public-good games with a unique dominant strategy, we show that the location of the equilibrium determines whether contributions are larger for fast decision-makers than for slow decision-makers. Replicating previous results, we find that fast decision-makers give more than slow decision-makers when the equilibrium is below the mid-point of the strategy set, but that this result is reversed when the equilibrium is above the mid-point. Consistent with fast decisions being more prone to error, we find that individuals who make (or have to make) fast decisions are insensitive to incentives, more often make mistakes, and are less likely to make equilibrium contributions. These findings make clear that we must control for the rate of errors if we are to draw inference on preferences from response time.

We study the quasi-neutral limit in an optimal semiconductor design problem constrained by a nonlinear, nonlocal Poisson equation modeling the drift-diffusion equations in thermal equilibrium. While a broad knowledge of the asymptotic links between the different models in the semiconductor model hierarchy exists, there are so far no results on the corresponding optimization problems available. Using a variational approach we end up with a bilevel optimization problem, which is thoroughly analyzed. Further, we exploit the concept of Γ-convergence to perform the quasi-neutral limit for the minima and minimizers. This justifies the construction of fast optimization algorithms based on the zero space charge approximation of the drift diffusion model. The analytical results are underlined by numerical experiments confirming the feasibility of our approach.

Perceptual decisions arise after considering the available sensory evidence [1]. When sensory information is unreliable, a good strategy is to rely on previous experience in similar situations to guide decisions [2-6]. It is well known that patients with Parkinson's disease (PD) are impaired at value-based decision-making [7-11]. How patients combine past experience and sensory information to make perceptual decisions is unknown. We developed a novel, perceptual decision-making task and manipulated the statistics of the sensory stimuli presented to patients with PD and healthy participants to determine the influence of past experience on decision-making. We show that patients with PD are impaired at combining previously learned information with current sensory information to guide decisions. We modeled the results using the drift-diffusion model (DDM) and found that the impairment corresponds to a failure in adjusting the amount of sensory evidence needed to make a decision. Our modeling results also show that two complementary mechanisms operate to implement a bias when two sets of priors are learned concurrently. Asymmetric decision threshold adjustments, as reflected by changes in the starting point of evidence accumulation, are responsible for a general choice bias, whereas the adjustment of a dynamic bias that develops over the course of a trial, as reflected by a drift-rate offset, provides the stimulus-specific component of the prior. A proper interplay between these two processes is required to implement a bias based on concurrent, stimulus-specific priors in decision-making. We show here that patients with PD are impaired in these across-trial decision threshold adjustments.

As humanity's energy consumption continues to increase for the coming decades, with our knowledge of traditional fossil fuels' deleterious effects on our planetary ecosystem, it is evident that development of clean, economical, and renewable energy sources is one of the great remaining problems faced by our species. Photovoltaic technologies, particularly those based on organic materials, have been suggested as potentially viable solutions to our energy demands. However, several deficiencies of organic photovoltaic devices, specifically their relatively low power conversion efficiency, has hampered their adoption for large-scale energy production. One of the main causes of these deficiencies is the imprecise control of the distribution of the active materials within these photovoltaic devices. This dissertation presents a series of semiconductor device modeling simulations, which were conducted to elucidate the various effects of the morphology of active components on organic photovoltaic devices' charge transport properties and photovoltaic performance. Our simulations illustrate how subtle variations in the active layer morphology can both hinder and benefit device performance in surprising ways. This indicates the need for novel processing techniques, which allow precise control of device morphology, in order for organic photovoltaic devices to be competitive with other contemporary renewable energy technologies.

We investigate how stable individuals’ risk attitudes are with respect to changes in cognitive load. In a laboratory experiment using pairwise lottery choice and a within-subject design, we showthat putting subjects under load via a concurrent working-memory task significantly increases their risk aversion. Subjects made significantly faster choices under load. Regardless of load, they responded faster when choosing the less risky option in safe–risky trials, but not in risky–risky trials. We discuss how these findings relate to both dual-system and unitarysystem theories of decision making.We observe that predictions of both recent dual-system and drift–diffusion models of the decision-making process are confirmed by our data and argue for a convergence of these to-date separate strands of the literature.

The optimization of turbine density in wind farms entails a trade-off between the usage of scarce, expensive land and power losses through turbine wake effects. A quantification and prediction of the wake effect, however, is challenging because of the complex aerodynamic nature of the interdependencies of turbines. In this paper, we propose a parsimonious data driven econometric wake model that can be used to predict production losses of existing and potential wind parks. Motivated by simple engineering wake models, the predicting variables are wind speed, turbine alignment angle, and distance. By utilizing data from two wind parks in Germany, a significantly better prediction of wake effect losses is attained compared to the standard Jensen model. A scenario analysis reveals that a distance between turbines can be reduced up to three times the rotor size without entailing substantial production losses. In contrast, a suboptimal configuration of turbines with respect to the main wind direction can result in production losses that are five times higher.

As humanity's energy consumption continues to increase for the coming decades, with our knowledge of traditional fossil fuels' deleterious effects on our planetary ecosystem, it is evident that development of clean, economical, and renewable energy sources is one of the great remaining problems faced by our species. Photovoltaic technologies, particularly those based on organic materials, have been suggested as potentially viable solutions to our energy demands. However, several deficiencies of organic photovoltaic devices, specifically their relatively low power conversion efficiency, has hampered their adoption for large-scale energy production. One of the main causes of these deficiencies is the imprecise control of the distribution of the active materials within these photovoltaic devices. This dissertation presents a series of semiconductor device modeling simulations, which were conducted to elucidate the various effects of the morphology of active components on organic photovoltaic devices' charge transport properties and photovoltaic performance. Our simulations illustrate how subtle variations in the active layer morphology can both hinder and benefit device performance in surprising ways. This indicates the need for novel processing techniques, which allow precise control of device morphology, in order for organic photovoltaic devices to be competitive with other contemporary renewable energy technologies.

Perceptual decisions arise after considering the available sensory evidence [1]. When sensory information is unreliable, a good strategy is to rely on previous experience in similar situations to guide decisions [2-6]. It is well known that patients with Parkinson's disease (PD) are impaired at value-based decision-making [7-11]. How patients combine past experience and sensory information to make perceptual decisions is unknown. We developed a novel, perceptual decision-making task and manipulated the statistics of the sensory stimuli presented to patients with PD and healthy participants to determine the influence of past experience on decision-making. We show that patients with PD are impaired at combining previously learned information with current sensory information to guide decisions. We modeled the results using the drift-diffusion model (DDM) and found that the impairment corresponds to a failure in adjusting the amount of sensory evidence needed to make a decision. Our modeling results also show that two complementary mechanisms operate to implement a bias when two sets of priors are learned concurrently. Asymmetric decision threshold adjustments, as reflected by changes in the starting point of evidence accumulation, are responsible for a general choice bias, whereas the adjustment of a dynamic bias that develops over the course of a trial, as reflected by a drift-rate offset, provides the stimulus-specific component of the prior. A proper interplay between these two processes is required to implement a bias based on concurrent, stimulus-specific priors in decision-making. We show here that patients with PD are impaired in these across-trial decision threshold adjustments.

Perceptual decisions arise after considering the available sensory evidence [1]. When sensory information is unreliable, a good strategy is to rely on previous experience in similar situations to guide decisions [2-6]. It is well known that patients with Parkinsons disease (PD) are impaired at value-based decision-making [7-11]. How patients combine past experience and sensory information to make perceptual decisions is unknown. We developed a novel, perceptual decision-making task and manipulated the statistics of the sensory stimuli presented to patients with PD and healthy participants to determine the influence of past experience on decision-making. We show that patients with PD are impaired at combining previously learned information with current sensory information to guide decisions. We modeled the results using the drift-diffusion model (DDM) and found that the impairment corresponds to a failure in adjusting the amount of sensory evidence needed to make a decision. Our modeling results also show that two complementary mechanisms operate to implement a bias when two sets of priors are learned concurrently. Asymmetric decision threshold adjustments, as reflected by changes in the starting point of evidence accumulation, are responsible for a general choice bias, whereas the adjustment of a dynamic bias that develops over the course of a trial, as reflected by a drift-rate offset, provides the stimulus-specific component of the prior. A proper interplay between these two processes is required to implement a bias based on concurrent, stimulus-specific priors in decision-making. We show here that patients with PD are impaired in these across-trial decision threshold adjustments.

We investigate how stable individuals’ risk attitudes are with respect to changes in cognitive load. In a laboratory experiment using pairwise lottery choice and a within-subject design, we showthat putting subjects under load via a concurrent working-memory task significantly increases their risk aversion. Subjects made significantly faster choices under load. Regardless of load, they responded faster when choosing the less risky option in safe–risky trials, but not in risky–risky trials. We discuss how these findings relate to both dual-system and unitarysystem theories of decision making.We observe that predictions of both recent dual-system and drift–diffusion models of the decision-making process are confirmed by our data and argue for a convergence of these to-date separate strands of the literature.

We investigate how stable individuals’ risk attitudes are with respect to changes in cognitive load. In a laboratory experiment using pairwise lottery choice and a within-subject design, we showthat putting subjects under load via a concurrent working-memory task significantly increases their risk aversion. Subjects made significantly faster choices under load. Regardless of load, they responded faster when choosing the less risky option in safe–risky trials, but not in risky–risky trials. We discuss how these findings relate to both dual-system and unitarysystem theories of decision making.We observe that predictions of both recent dual-system and drift–diffusion models of the decision-making process are confirmed by our data and argue for a convergence of these to-date separate strands of the literature.

The optimization of turbine density in wind farms entails a trade-off between the usage of scarce, expensive land and power losses through turbine wake effects. A quantification and prediction of the wake effect, however, is challenging because of the complex aerodynamic nature of the interdependencies of turbines. In this paper, we propose a parsimonious data driven econometric wake model that can be used to predict production losses of existing and potential wind parks. Motivated by simple engineering wake models, the predicting variables are wind speed, turbine alignment angle, and distance. By utilizing data from two wind parks in Germany, a significantly better prediction of wake effect losses is attained compared to the standard Jensen model. A scenario analysis reveals that a distance between turbines can be reduced up to three times the rotor size without entailing substantial production losses. In contrast, a suboptimal configuration of turbines with respect to the main wind direction can result in production losses that are five times higher.

The optimization of turbine density in wind farms entails a trade-off between the usage of scarce, expensive land and power losses through turbine wake effects. A quantification and prediction of the wake effect, however, is challenging because of the complex aerodynamic nature of the interdependencies of turbines. In this paper, we propose a parsimonious data driven econometric wake model that can be used to predict production losses of existing and potential wind parks. Motivated by simple engineering wake models, the predicting variables are wind speed, turbine alignment angle, and distance. By utilizing data from two wind parks in Germany, a significantly better prediction of wake effect losses is attained compared to the standard Jensen model. A scenario analysis reveals that a distance between turbines can be reduced up to three times the rotor size without entailing substantial production losses. In contrast, a suboptimal configuration of turbines with respect to the main wind direction can result in production losses that are five times higher.

The transport properties of a series of n- and p-type Si diodes have been studied by the ion beam induced charge (IBIC) technique using a 4 MeV proton microbeam. The samples were irradiated with 17 MeV protons at fluences ranging from 1 × 1012 to 1 × 1013 p/cm2 in order to produce a uniform profile of defects with depth. The analysis of the charge collection efficiency (CCE) as a function of the reverse bias voltage has been carried out using an upgraded drift-diffusion (D-D) model which takes into account the possibility of carrier recombination not only in the neutral substrate, as the simple D-D model assumes, but also within the depletion region. This new approach for calculating the CCE is fundamental when the drift length of carriers cannot be considered as much greater that the thickness of the detector due to the ion induced damage. From our simulations, we have obtained the values of the carrier lifetimes for the pristine and irradiated diodes, which have allowed us to calculate the effective trapping cross sections using the one dimension Shockley-Read-Hall model. The results of our calculations have been compared to the data obtained using a recently developed Monte Carlo code for the simulation of IBIC analysis, based on the probabilistic interpretation of the excess carrier continuity equations.

Does the similarity between two items change over time? Previous studies (Goldstone & Medin, 1994; Gentner & Brem, 1999) have found suggestive results but have relied on interpreting complex interaction effects from “deadline” decision tasks in which the decision making process is not well understood (Luce, 1986). Using a self-paced simple decision task in which the similarity between two items can be isolated from strategic decision processes using computational modeling techniques (Ratcliff, 1978), we show strong evidence that the similarity between two items changes over time and shifts in systematic ways. The change in similarity from early to late processing in Experiment 1 is consistent with the theory of structural alignment (Gentner, 1983; Goldstone & Medin, 1994), and Experiment 2 demonstrates evidence for a stronger influence of thematic knowledge than taxonomic knowledge in early processing of word associations (Lin & Murphy, 2001).

The present paper provides an accurate drift-diffusion model of the graphene field-effect transistor (GFET). A precise yet mathematically simple current-voltage relation is derived by focusing on device physics at energy levels close to the Dirac point. With respect to previous work, our approach extends modeling accuracy to the low-voltage biasing regime and improves the prediction of current saturation. These advantages are highlighted by a comparison study of the drain current, transconductance, output conductance, and intrinsic gain. The model has been implemented in Verilog-A and is compatible with conventional circuit simulators. It is provided as a tool for the exploration of GFET-based integrated circuit design. The model shows good agreement with measurement data from GFET prototypes., Peer Reviewed, Postprint (published version)

Adjusting the work function of the two electrodes to the energy levels of the intrinsic active materials of an organic solar cell is crucial for a good device performance. Often, injection barriers (in combination with selective contacts blocking one charge carrier species) caused by a misaligned metal work function or extraction barriers resulting from insulating intentional or unintentional interlayers between metal and active layers, result in a decrease in fill factor seen in the extreme case in S-shaped current–voltage (J–V) characteristics. To avoid this S-kink, it is essential to identify its origin, desirably applying a simple experimental method. We propose an approach based on analyses of current–voltage data as a function of illumination intensity. A normalization of the J–V curves at the saturated photocurrent reveals distinctive features for each type of barrier. We apply the method to planar heterojunction small-molecule and bulk heterojunction polymer solar cells with oxidized metal electrode or plasma-treated active layer and explain the theory with a drift-diffusion model., Funding Agencies|BMBF (OPEG)|13N9720|Reiner Lemoine foundation||Science Council (V)||Swedish Energy Agency||Knut and Alice Wallenberg Foundation

Adjusting the work function of the two electrodes to the energy levels of the intrinsic active materials of an organic solar cell is crucial for a good device performance. Often, injection barriers (in combination with selective contacts blocking one charge carrier species) caused by a misaligned metal work function or extraction barriers resulting from insulating intentional or unintentional interlayers between metal and active layers, result in a decrease in fill factor seen in the extreme case in S-shaped current–voltage (J–V) characteristics. To avoid this S-kink, it is essential to identify its origin, desirably applying a simple experimental method. We propose an approach based on analyses of current–voltage data as a function of illumination intensity. A normalization of the J–V curves at the saturated photocurrent reveals distinctive features for each type of barrier. We apply the method to planar heterojunction small-molecule and bulk heterojunction polymer solar cells with oxidized metal electrode or plasma-treated active layer and explain the theory with a drift-diffusion model., Funding Agencies|BMBF (OPEG)|13N9720|Reiner Lemoine foundation||Science Council (V)||Swedish Energy Agency||Knut and Alice Wallenberg Foundation

Adjusting the work function of the two electrodes to the energy levels of the intrinsic active materials of an organic solar cell is crucial for a good device performance. Often, injection barriers (in combination with selective contacts blocking one charge carrier species) caused by a misaligned metal work function or extraction barriers resulting from insulating intentional or unintentional interlayers between metal and active layers, result in a decrease in fill factor seen in the extreme case in S-shaped current–voltage (J–V) characteristics. To avoid this S-kink, it is essential to identify its origin, desirably applying a simple experimental method. We propose an approach based on analyses of current–voltage data as a function of illumination intensity. A normalization of the J–V curves at the saturated photocurrent reveals distinctive features for each type of barrier. We apply the method to planar heterojunction small-molecule and bulk heterojunction polymer solar cells with oxidized metal electrode or plasma-treated active layer and explain the theory with a drift-diffusion model., Funding Agencies|BMBF (OPEG)|13N9720|Reiner Lemoine foundation||Science Council (V)||Swedish Energy Agency||Knut and Alice Wallenberg Foundation

Adjusting the work function of the two electrodes to the energy levels of the intrinsic active materials of an organic solar cell is crucial for a good device performance. Often, injection barriers (in combination with selective contacts blocking one charge carrier species) caused by a misaligned metal work function or extraction barriers resulting from insulating intentional or unintentional interlayers between metal and active layers, result in a decrease in fill factor seen in the extreme case in S-shaped current–voltage (J–V) characteristics. To avoid this S-kink, it is essential to identify its origin, desirably applying a simple experimental method. We propose an approach based on analyses of current–voltage data as a function of illumination intensity. A normalization of the J–V curves at the saturated photocurrent reveals distinctive features for each type of barrier. We apply the method to planar heterojunction small-molecule and bulk heterojunction polymer solar cells with oxidized metal electrode or plasma-treated active layer and explain the theory with a drift-diffusion model., Funding Agencies|BMBF (OPEG)|13N9720|Reiner Lemoine foundation||Science Council (V)||Swedish Energy Agency||Knut and Alice Wallenberg Foundation

We consider an exponentially fitted discontinuous Galerkin method for advection dominated problems and propose a block solver for the resulting linear systems. In the case of strong advection the solver is robust with respect to the advection direction and the number of unknowns.

Adjusting the work function of the two electrodes to the energy levels of the intrinsic active materials of an organic solar cell is crucial for a good device performance. Often, injection barriers (in combination with selective contacts blocking one charge carrier species) caused by a misaligned metal work function or extraction barriers resulting from insulating intentional or unintentional interlayers between metal and active layers, result in a decrease in fill factor seen in the extreme case in S-shaped current–voltage (J–V) characteristics. To avoid this S-kink, it is essential to identify its origin, desirably applying a simple experimental method. We propose an approach based on analyses of current–voltage data as a function of illumination intensity. A normalization of the J–V curves at the saturated photocurrent reveals distinctive features for each type of barrier. We apply the method to planar heterojunction small-molecule and bulk heterojunction polymer solar cells with oxidized metal electrode or plasma-treated active layer and explain the theory with a drift-diffusion model., Funding Agencies|BMBF (OPEG)|13N9720|Reiner Lemoine foundation||Science Council (V)||Swedish Energy Agency||Knut and Alice Wallenberg Foundation