Startegy selection during exploratory behavior: sex differences, uncertainty and risk managment

This study deals with the psychological processes underlying the selection of appropriate strategy during exploratory behavior. A new device was used to assess sexual dimorphisms in spatial abilities that do not depend on spatial rotation, map reading or directional vector extraction capacities. Moreover, it makes it possible to investigate exploratory behavior as a specific response to novelty that trades off risk and reward. Risk management under uncertainty was assessed through both spontaneous searching strategies and signal detection capacities. The results of exploratory behavior, detection capacities, and decision-making strategies seem to indicate that women's exploratory behavior is based on risk-reducing behavior while men behavior does not appear to be influenced by this variable. This difference was interpreted as a difference in information processing modifying beliefs concerning the likelihood of uncertain events, and therefore influencing risk evaluation.

Why do scientists migrate? A diffusion model

The article is intended to improve our understanding of the reasons underlying the intellectual migration of scientists from well-known cognitive domains to nascent scientific fields. To that purpose we present, first, a number of findings from the sociology of science that give different insights about this phenomenon. We then attempt to bring some of these insights together under the conceptual roof of an actor-based approach linking expected utility and diffusion theory. Intellectual migration is regarded as the rational choice of scientists who decide under uncertainty and on the base of a number of decision-making variables, which define probabilities, costs, and benefits of the migration.

Evolving from inferences to decisions in the interpretation of scientific evidence

Le travail d'un(e) expert(e) en science forensique exige que ce dernier (cette dernière) prenne une série de décisions. Ces décisions sont difficiles parce qu'elles doivent être prises dans l'inévitable présence d'incertitude, dans le contexte unique des circonstances qui entourent la décision, et, parfois, parce qu'elles sont complexes suite à de nombreuse variables aléatoires et dépendantes les unes des autres. Etant donné que ces décisions peuvent aboutir à des conséquences sérieuses dans l'administration de la justice, la prise de décisions en science forensique devrait être soutenue par un cadre robuste qui fait des inférences en présence d'incertitudes et des décisions sur la base de ces inférences. L'objectif de cette thèse est de répondre à ce besoin en présentant un cadre théorique pour faire des choix rationnels dans des problèmes de décisions rencontrés par les experts dans un laboratoire de science forensique. L'inférence et la théorie de la décision bayésienne satisfont les conditions nécessaires pour un tel cadre théorique. Pour atteindre son objectif, cette thèse consiste de trois propositions, recommandant l'utilisation (1) de la théorie de la décision, (2) des réseaux bayésiens, et (3) des réseaux bayésiens de décision pour gérer des problèmes d'inférence et de décision forensiques. Les résultats présentent un cadre uniforme et cohérent pour faire des inférences et des décisions en science forensique qui utilise les concepts théoriques ci-dessus. Ils décrivent comment organiser chaque type de problème en le décomposant dans ses différents éléments, et comment trouver le meilleur plan d'action en faisant la distinction entre des problèmes de décision en une étape et des problèmes de décision en deux étapes et en y appliquant le principe de la maximisation de l'utilité espérée. Pour illustrer l'application de ce cadre à des problèmes rencontrés par les experts dans un laboratoire de science forensique, des études de cas théoriques appliquent la théorie de la décision, les réseaux bayésiens et les réseaux bayésiens de décision à une sélection de différents types de problèmes d'inférence et de décision impliquant différentes catégories de traces. Deux études du problème des deux traces illustrent comment la construction de réseaux bayésiens permet de gérer des problèmes d'inférence complexes, et ainsi surmonter l'obstacle de la complexité qui peut être présent dans des problèmes de décision. Trois études-une sur ce qu'il faut conclure d'une recherche dans une banque de données qui fournit exactement une correspondance, une sur quel génotype il faut rechercher dans une banque de données sur la base des observations faites sur des résultats de profilage d'ADN, et une sur s'il faut soumettre une trace digitale à un processus qui compare la trace avec des empreintes de sources potentielles-expliquent l'application de la théorie de la décision et des réseaux bayésiens de décision à chacune de ces décisions. Les résultats des études des cas théoriques soutiennent les trois propositions avancées dans cette thèse. Ainsi, cette thèse présente un cadre uniforme pour organiser et trouver le plan d'action le plus rationnel dans des problèmes de décisions rencontrés par les experts dans un laboratoire de science forensique. Le cadre proposé est un outil interactif et exploratoire qui permet de mieux comprendre un problème de décision afin que cette compréhension puisse aboutir à des choix qui sont mieux informés. - Forensic science casework involves making a sériés of choices. The difficulty in making these choices lies in the inévitable presence of uncertainty, the unique context of circumstances surrounding each décision and, in some cases, the complexity due to numerous, interrelated random variables. Given that these décisions can lead to serious conséquences in the admin-istration of justice, forensic décision making should be supported by a robust framework that makes inferences under uncertainty and décisions based on these inferences. The objective of this thesis is to respond to this need by presenting a framework for making rational choices in décision problems encountered by scientists in forensic science laboratories. Bayesian inference and décision theory meets the requirements for such a framework. To attain its objective, this thesis consists of three propositions, advocating the use of (1) décision theory, (2) Bayesian networks, and (3) influence diagrams for handling forensic inference and décision problems. The results present a uniform and coherent framework for making inferences and décisions in forensic science using the above theoretical concepts. They describe how to organize each type of problem by breaking it down into its différent elements, and how to find the most rational course of action by distinguishing between one-stage and two-stage décision problems and applying the principle of expected utility maximization. To illustrate the framework's application to the problems encountered by scientists in forensic science laboratories, theoretical case studies apply décision theory, Bayesian net-works and influence diagrams to a selection of différent types of inference and décision problems dealing with différent catégories of trace evidence. Two studies of the two-trace problem illustrate how the construction of Bayesian networks can handle complex inference problems, and thus overcome the hurdle of complexity that can be present in décision prob-lems. Three studies-one on what to conclude when a database search provides exactly one hit, one on what genotype to search for in a database based on the observations made on DNA typing results, and one on whether to submit a fingermark to the process of comparing it with prints of its potential sources-explain the application of décision theory and influ¬ence diagrams to each of these décisions. The results of the theoretical case studies support the thesis's three propositions. Hence, this thesis présents a uniform framework for organizing and finding the most rational course of action in décision problems encountered by scientists in forensic science laboratories. The proposed framework is an interactive and exploratory tool for better understanding a décision problem so that this understanding may lead to better informed choices.

Three essays in dynamic corporate finance

Summary Throughout my thesis, I elaborate on how real and financing frictions affect corporate decision making under uncertainty, and I explore how firms time their investment and financing decisions given such frictions. While the macroeconomics literature has focused on the impact of real frictions on investment decisions assuming all equity financed firms, the financial economics literature has mainly focused on the study of financing frictions. My thesis therefore assesses the join interaction of real and financing frictions in firms' dynamic investment and financing decisions. My work provides a rationale for the documented poor empirical performance of neoclassical investment models based on the joint effect of real and financing frictions on investment. A major observation relies in how the infrequency of corporate decisions may affect standard empirical tests. My thesis suggests that the book to market sorts commonly used in the empirical asset pricing literature have economic content, as they control for the lumpiness in firms' optimal investment policies. My work also elaborates on the effects of asymmetric information and strategic interaction on firms' investment and financing decisions. I study how firms time their decision to raise public equity when outside investors lack information about their future investment prospects. I derive areal-options model that predicts either cold or hot markets for new stock issues conditional on adverse selection, and I provide a rational approach to study jointly the market timing of corporate decisions and announcement effects in stock returns. My doctoral dissertation therefore contributes to our understanding of how under real and financing frictions may bias standard empirical tests, elaborates on how adverse selection may induce hot and cold markets in new issues' markets, and suggests how the underlying economic behaviour of firms may induce alternative patterns in stock prices.

Graphical probabilistic analysis of the combination of items of evidence

Unlike the evaluation of single items of scientific evidence, the formal study and analysis of the jointevaluation of several distinct items of forensic evidence has to date received some punctual, ratherthan systematic, attention. Questions about the (i) relationships among a set of (usually unobservable)propositions and a set of (observable) items of scientific evidence, (ii) the joint probative valueof a collection of distinct items of evidence as well as (iii) the contribution of each individual itemwithin a given group of pieces of evidence still represent fundamental areas of research. To somedegree, this is remarkable since both, forensic science theory and practice, yet many daily inferencetasks, require the consideration of multiple items if not masses of evidence. A recurrent and particularcomplication that arises in such settings is that the application of probability theory, i.e. the referencemethod for reasoning under uncertainty, becomes increasingly demanding. The present paper takesthis as a starting point and discusses graphical probability models, i.e. Bayesian networks, as frameworkwithin which the joint evaluation of scientific evidence can be approached in some viable way.Based on a review of existing main contributions in this area, the article here aims at presentinginstances of real case studies from the author's institution in order to point out the usefulness andcapacities of Bayesian networks for the probabilistic assessment of the probative value of multipleand interrelated items of evidence. A main emphasis is placed on underlying general patterns of inference,their representation as well as their graphical probabilistic analysis. Attention is also drawnto inferential interactions, such as redundancy, synergy and directional change. These distinguish thejoint evaluation of evidence from assessments of isolated items of evidence. Together, these topicspresent aspects of interest to both, domain experts and recipients of expert information, because theyhave bearing on how multiple items of evidence are meaningfully and appropriately set into context.

Liberties and constraints of the normative approach to evaluation and decision in forensic science: a discussion towards overcoming some common misconceptions

At a time when disciplined inference and decision making under uncertainty represent common aims to participants in legal proceedings, the scientific community is remarkably heterogenous in its attitudes as to how these goals ought to be achieved. Probability and decision theory exert a considerable influence, and we think by all reason rightly do so, but they go against a mainstream of thinking that does not embrace-or is not aware of-the 'normative' character of this body of theory. It is normative, in the sense understood in this article, in that it prescribes particular properties, typically (logical) coherence, to which reasoning and decision making ought to conform. Disregarding these properties can result in diverging views which are occasionally used as an argument against the theory, or as a pretext for not following it. Typical examples are objections according to which people, both in everyday life but also individuals involved at various levels in the judicial process, find the theory difficult to understand and to apply. A further objection is that the theory does not reflect how people actually behave. This article aims to point out in what sense these examples misinterpret the analytical framework in its normative perspective. Through examples borrowed mostly from forensic science contexts, it is argued that so-called intuitive scientific attitudes are particularly liable to such misconceptions. These attitudes are contrasted with a statement of the actual liberties and constraints of probability and decision theory and the view according to which this theory is normative.

Prediction in forensic science: a critical examination of common understandings

In this commentary, we argue that the term 'prediction' is overly used when in fact, referring to foundational writings of de Finetti, the correspondent term should be inference. In particular, we intend (i) to summarize and clarify relevant subject matter on prediction from established statistical theory, and (ii) point out the logic of this understanding with respect practical uses of the term prediction. Written from an interdisciplinary perspective, associating statistics and forensic science as an example, this discussion also connects to related fields such as medical diagnosis and other areas of application where reasoning based on scientific results is practiced in societal relevant contexts. This includes forensic psychology that uses prediction as part of its vocabulary when dealing with matters that arise in the course of legal proceedings.

Relative and absolute reliability of the clinical version of the Narrow Path Walking Test (NPWT) under single and dual task conditions.

Decline in gait stability has been associated with increased fall risk in older adults. Reliable and clinically feasible methods of gait instability assessment are needed. This study evaluated the relative and absolute reliability and concurrent validity of the testing procedure of the clinical version of the Narrow Path Walking Test (NPWT) under single task (ST) and dual task (DT) conditions. Thirty independent community-dwelling older adults (65-87 years) were tested twice. Participants were instructed to walk within the 6-m narrow path without stepping out. Trial time, number of steps, trial velocity, number of step errors, and number of cognitive task errors were determined. Intraclass correlation coefficients (ICCs) were calculated as indices of agreement, and a graphic approach called "mountain plot" was applied to help interpret the direction and magnitude of disagreements between testing procedures. Smallest detectable change and smallest real difference (SRD) were computed to determine clinically relevant improvement at group and individual levels, respectively. Concurrent validity was assessed using Performance Oriented Mobility Assessment Tool (POMA) and the Short Physical Performance Battery (SPPB). Test-retest agreement (ICC1,2) varied from 0.77 to 0.92 in ST and from 0.78 to 0.92 in DT conditions, with no apparent systematic differences between testing procedures demonstrated by the mountain plot graphs. Smallest detectable change and smallest real change were small for motor task performance and larger for cognitive errors. Significant correlations were observed for trial velocity and trial time with POMA and SPPB. The present results indicate that the NPWT testing procedure is highly reliable and reproducible.

Quantifying uncertainty: physicians' estimates of infection in critically ill neonates and children.

To determine the diagnostic accuracy of physicians' prior probability estimates of serious infection in critically ill neonates and children, we conducted a prospective cohort study in 2 intensive care units. Using available clinical, laboratory, and radiographic information, 27 physicians provided 2567 probability estimates for 347 patients (follow-up rate, 92%). The median probability estimate of infection increased from 0% (i.e., no antibiotic treatment or diagnostic work-up for sepsis), to 2% on the day preceding initiation of antibiotic therapy, to 20% at initiation of antibiotic treatment (P<.001). At initiation of treatment, predictions discriminated well between episodes subsequently classified as proven infection and episodes ultimately judged unlikely to be infection (area under the curve, 0.88). Physicians also showed a good ability to predict blood culture-positive sepsis (area under the curve, 0.77). Treatment and testing thresholds were derived from the provided predictions and treatment rates. Physicians' prognoses regarding the presence of serious infection were remarkably precise. Studies investigating the value of new tests for diagnosis of sepsis should establish that they add incremental value to physicians' judgment.

Mass detection on mammograms: influence of signal shape uncertainty on human and model observers.

We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

Dummy run and conformity indices in the ongoing EORTC low-grade glioma trial 22033-26033: First evaluation of quality of radiotherapy planning.

PURPOSE: Early assessment of radiotherapy (RT) quality in the ongoing EORTC trial comparing primary temozolomide versus RT in low-grade gliomas. MATERIALS AND METHODS: RT plans provided for dummy cases were evaluated and compared against expert plans. We analysed: (1) tumour and organs-at-risk delineation, (2) geometric and dosimetric characteristics, (3) planning parameters, compliance with dose prescription and Dmax for OAR (4) indices: RTOG conformity index (CI), coverage factor (CF), tissue protection factor (PF); conformity number (CN = PF x CF); dose homogeneity in PTV (U). RESULTS: Forty-one RT plans were evaluated. Only two (5%) centres were requested to repeat CTV-PTV delineations. Three (7%) plans had a significant under-dosage and dose homogeneity in one deviated > 10%. Dose distribution was good with mean values of 1.5, 1, 0.68, and 0.68 (ideal values = 1) for CI, CF, PF, and CN, respectively. CI and CN strongly correlated with PF and they correlated with PTV. Planning with more beams seems to increase PTV(Dmin), improving CF. U correlated with PTV(Dmax). CONCLUSION: Preliminary results of the dummy run procedure indicate that most centres conformed to protocol requirements. To quantify plan quality we recommend systematic calculation of U and either CI or CN, both of which measure the amount of irradiated normal brain tissue.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

Spatial planning to the test of property rights in Switzerland : an innovative land management approach to coordinate spatial planning goals with property rights interests

In Switzerland, the land management regime is characterized by a liberal attitude towards the institution of property rights, which is guaranteed by the Constitution. Under the present Swiss constitutional arrangement, authorities (municipalities) are required to take into account landowners' interests when implementing their spatial planning policy. In other words, the institution of property rights cannot be restricted easily in order to implement zoning plans and planning projects. This situation causes many problems. One of them is the gap between the way land is really used by the landowners and the way land should be used based on zoning plans. In fact, zoning plans only describe how landowners should use their property. There is no sufficient provision for handling cases where the use is not in accordance with zoning plans. In particular, landowners may not be expropriated for a non-conforming use of the land. This situation often leads to the opening of new building areas in greenfields and urban sprawl, which is in contradiction with the goals set into the Federal Law on Spatial Planning. In order to identify legal strategies of intervention to solve the problem, our paper is structured into three main parts. Firstly, we make a short description of the Swiss land management regime. Then, we focus on an innovative land management approach designed to implement zoning plans in accordance with property rights. Finally, we present a case study that shows the usefulness of the presented land management approach in practice. We develop three main results. Firstly, the land management approach brings a mechanism to involve landowners in planning projects. Coordination principle between spatial planning goals and landowners' interests is the cornerstone of all the process. Secondly, the land use is improved both in terms of space and time. Finally, the institution of property rights is not challenged, since there is no expropriation and the market stays free.

Ecological-economic optimization of biodiversity conservation under climate change

Substantial investment in climate change research has led to dire predictions of the impacts and risks to biodiversity. The Intergovernmental Panel on Climate Change fourth assessment report(1) cites 28,586 studies demonstrating significant biological changes in terrestrial systems(2). Already high extinction rates, driven primarily by habitat loss, are predicted to increase under climate change(3-6). Yet there is little specific advice or precedent in the literature to guide climate adaptation investment for conserving biodiversity within realistic economic constraints(7). Here we present a systematic ecological and economic analysis of a climate adaptation problem in one of the world's most species-rich and threatened ecosystems: the South African fynbos. We discover a counterintuitive optimal investment strategy that switches twice between options as the available adaptation budget increases. We demonstrate that optimal investment is nonlinearly dependent on available resources, making the choice of how much to invest as important as determining where to invest and what actions to take. Our study emphasizes the importance of a sound analytical framework for prioritizing adaptation investments(4). Integrating ecological predictions in an economic decision framework will help support complex choices between adaptation options under severe uncertainty. Our prioritization method can be applied at any scale to minimize species loss and to evaluate the robustness of decisions to uncertainty about key assumptions.

Functional homogenization of bumblebee communities in alpine landscapes under projected climate change

Background: Bumblebees represent an active pollinator group in mountain regions and assure the pollination of many different plant species from low to high elevations. Plant-pollinator interactions are mediated by functional traits. Shift in bumblebee functional structure under climate change may impact plant-pollinator interactions in mountains. Here, we estimated bumblebee upward shift in elevation, community turnover, and change in functional structure under climate change. Method: We sampled bumblebee species at 149 sites along the elevation gradient. We used stacked species distribution models (S-SDMs) forecasted under three climate change scenarios (A2, A1B, RCP3PD) to model the potential distribution of the Bombus species. Furthermore, we used species proboscis length measurements to assess the functional change in bumblebee assemblages along the elevation gradient. Results: We found species-specific response of bumblebee species to climate change. Species differed in their predicted rate of range contraction and expansion. Losers were mainly species currently restricted to high elevation. Under the most severe climate change scenarios (A2), we found a homogenization of proboscis length structure in bumblebee communities along the elevation gradient through the upward colonization of high elevation by species with longer proboscides. Conclusions: Here, we show that in addition to causing the shift in the distribution of bumblebee species, climate change may impact the functional structure of communities. The colonization of high elevation areas by bumblebee species with long proboscides may modify the structure of plant-pollination interaction networks by increasing the diversity of pollination services at high elevation.