Miracle-dz/UniFAR-FTUs huggingface dataset:
Série Scientifique Scientific Series the Rate of Risk Aversion May Be Lower than You Think the Rate of Risk Aversion May Be Lower than You Think

Reproduction partielle permise avec citation du document source, incluant la notice ©. Short sections may be quoted without explicit permission, if full credit, including © notice, is given to the source. Les cahiers de la série scientifique (CS) visent à rendre accessibles des résultats de recherche effectuée au CIRANO afin de susciter échanges et commentaires. Ces cahiers sont écrits dans le style des publications scientifiques. Les idées et les opinions émises sont sous l'unique responsabilité des auteurs et ne représentent pas nécessairement les positions du CIRANO ou de ses partenaires. This paper presents research carried out at CIRANO and aims at encouraging discussion and comment. The observations and viewpoints expressed are the sole responsibility of the authors. They do not necessarily represent positions of CIRANO or its partners. Résumé / Abstract A l'aide de données sur la consommation des ménages et d'équations d'Euler, cet article estime le taux d'aversion au risque relatif. Ces équations d'Euler sont les implications de structures de marché qui ne permettent pas toujours aux agents de s'assurer parfaitement. Cet article porte plus particulièrement sur des tests de l'équation d'Euler inconditionnelle. Dans le cadre d'un agent représentatif, ce type de test mène aux rejets les plus intuitivement convaincants des modèles d'évaluation d'actifs, comme l'énigme de la prime de risque et l'énigme du taux sans risque. Lorsque l'on ignore les erreurs de mesure de la consommation, les erreurs de l'équation d'Euler ne sont pas statistiquement différents de zéro pour les valeurs du taux d'aversion au risque relatif comprises entre 1 et 3. Lorsque l'on tient compte de la présence des erreurs de mesure, les estimations conservatrices du taux d'aversion au risque relatif pour les participants à un marché d'actifs indiquent une valeur entre 2 et 8. Ces résultats suggèrent que le taux d'aversion au risque pourrait être plus bas que ce qui est couramment perçu. Par conséquent, l'imperfection des marchés pourrait servir à résoudre les énigmes d'évaluation d'actifs. This paper estimates the rate of relative risk aversion using Euler equations based on household-level consumption data. These Euler equations are implications of market structures that do not necessarily allow agents to perfectly insure themselves. The paper focuses on tests of the unconditional Euler equation. In representative-agent frameworks, this type of test leads to the most intuitively convincing rejections of asset-pricing models, such as the equity premium puzzle and the riskfree rate puzzle. When measurement error in consumption is ignored, …
Quantum random walks with decoherent coins

The quantum random walk has been much studied recently, largely due to its highly nonclassical behavior. In this paper, we study one possible route to classical behavior for the discrete quantum walk on the line: the presence of decoherence in the quantum ''coin'' which drives the walk. We find exact analytical expressions for the time dependence of the first two moments of position, and show that in the long-time limit the variance grows linearly with time, unlike the unitary walk. We compare this to the results of direct numerical simulation, and see how the form of the position distribution changes from the unitary to the usual classical result as we increase the strength of the decoherence.
Investment decisions and uncertainty in the power generation sector

The purpose of this paper has been to analyse how increased market uncertainties affects the timing and technological choice of investment projects in the power sector with focus on the Swedish situation using two different investment behavioural assumptions. The investment model assumes stochastic input prices (fuel prices), output price (electricity) and emission permit price. In addition, the green certificate scheme presently used in Sweden is deterministically incorporated in the model. The technology choices included are offshore wind power, gas-fired power and biomass power. The results suggests that biopower is the most likely technology choice under both investment behavioural assumptions and regardless if investment timing, driven by the policies. The likelihood of choosing gas power increases over time and likelihood of choosing wind power decreases over time, driven by the relative capital requirements per unit of output for the two technologies. Wind power would benefit is a lower discount rate is used.
Metacognitive-strategy training promotes decision-making ability in older adults

Abstract Research on decision making and aging has shown that some decision-making skills decrease with age. Despite these age-related declines, no study has yet investigated the possibility of promoting improvements in decision-making skills in older adults. The present study was designed to address this gap in literature by examining the efficacy of a metacognitive-strategy decision-making training on practiced and non-practiced tasks. The training was based on the use of specific metacognitive principles and analytical strategies for promoting an analytical mode of thinking in the decision-making process. We examined 66 older adults (Mage= 67.52 years, SD = 5.38; age range 60-81) assigned to two training groups: a metacognitive-strategy decision-making training group and an active control group involved in a strategic memory intervention. Both training groups attended four 2-hour training sessions conducted once a week. Results showed that, after intervention, the decision-making training group improved their decision-making skills significantly more than the active control training group. Crucially, the positive effect of the training was evident in both practiced and non-practiced decision-making tasks. This is the first study investigating the efficacy of a decision-making training in older adults based on metacognitive and strategic principles.
Truth by Repetition: Explanations and Implications

People believe repeated information more than novel information; they show a repetition-induced truth effect. In a world of “alternative facts,” “fake news,” and strategic information management, understanding this effect is highly important. We first review explanations of the effect based on frequency, recognition, familiarity, and coherent references. On the basis of the latter explanation, we discuss the relations of these explanations. We then discuss implications of truth by repetition for the maintenance of false beliefs and ways to change potentially harmful false beliefs (e.g., “Vaccination causes autism”), illustrating that the truth-by-repetition phenomenon not only is of theoretical interest but also has immediate practical relevance.
Author ' s personal copy Premotor cortex mediates perceptual performance

a r t i c l e i n f o Articulatory goals have long been proposed to mediate perception. Examples include direct realist and constructivist (analysis by synthesis) theories of speech perception. Although the activity in brain regions involved with action production has been shown to be present during action observation (Mirror Neuron System), the relationship of this activity to perceptual performance has not been clearly demonstrated at the event level. To this end we used functional magnetic resonance imaging fMRI and magnetoencephalography MEG to measure brain activity for correct and incorrect trials of an auditory phonetic identification in noise task. FMRI analysis revealed activity in the premotor cortex including the neighboring frontal opercular part of Broca's area (PMC/Broca's) for both perception and production tasks involving the same phonetic stimuli (potential mirror system site) that was significantly greater for correct over incorrect perceptual identification trials. Time–frequency analysis of single trials conducted over MEG current localized to PMC/Broca's using a hierarchical variational Bayesian source analysis technique revealed significantly greater event-related synchronization ERS and desynchronization ERD for correct over incorrect trials in the alpha, beta, and gamma frequency range prior to and after stimulus presentation. Together, these fMRI and MEG results are consistent with the hypothesis that articulatory processes serve to facilitate perceptual performance, while further dispelling concerns that activity found in ventral PMC/Broca's (mirror system) is merely a product of covert production of the perceived action. The finding of performance predictive activity prior to stimulus onset as well as activity related to task difficulty instead of information available in stimulation are consistent with constructivist and contrary to direct realist theories of perception.
First demonstration of airborne SAR tomography using multibaseline L-band data

In this paper for the first time the successful experimental realisation of airborne SAR tomography is demonstrated. The authors present the concept of aperture synthesis for 3D-imaging for the case of the multibaseline imaging geometry and discuss the limits arising from the limited number of flight tracks and their irregular spatial distribution. Finally they address the experimental requirements for SAR tomography and show some experimental results using a multibaseline data set acquired in L-band by DLR's experimental SAR (E-SAR) on a testsite near Oberpfaffenhofen/Germany.
NBI cystoscopy and bipolar electrosurgery in NMIBC management – An overview of daily practice

Introduction: The standard non-muscle invasive bladder cancer (NMIBC) endoscopic diagnosis suffers from the frequently unsatisfactory white light evaluation accuracy leading to residual lesions being left behind. Monopolar transurethral resection of bladder tumors (TURBT) is marked by a substantial morbidity rate requiring further amelioration. Methods: Small size tumors (under 1 cm) are feasible for “en bloc" resection. Bipolar TURBT was defined as being able to challenge the gold-standard status of monopolar resection due to the reduced complication rates. Plasma-button vaporization was introduced as a promising large bladder tumors’ ablation modality. Narrow band imaging (NBI) cystoscopy became an increasingly popular method of enhancing tumor detection. Results: The “en bloc" resection of small size or thin pedicle tumors provides the conditions for avoiding tumoral tissue scattering. Bipolar resection is characterized by decreased perioperative bleeding risks and faster patient recovery. Plasma-button vaporization gained confirmation as an innovative approach, able to dispose large tumor bulks under complete control while minimizing the associated morbidity. NBI cystoscopy is a useful tool in identifying CIS lesions, small papillary tumors or extended margins of large tumor formations. As a cost-free technique, it may be extensively used both during the NMIBC initial diagnostic as well as during follow-up evaluation protocol. Conclusions: Having in mind the various modalities of ameliorating the bladder cancer diagnostic and treatment, NMIBC management should be tailored in accordance with the particularities of each case.
Predictors of answer quality in online Q&A sites

Question and answer (Q&A) sites such as Yahoo! Answers are places where users ask questions and others answer them. In this paper, we investigate predictors of answer quality through a comparative, controlled field study of responses provided across several online Q&A sites. Along with several quantitative results concerning the effects of factors such as question topic and rhetorical strategy, we present two high-level messages. First, you get what you pay for in Q&A sites. Answer quality was typically higher in Google Answers (a fee-based site) than in the free sites we studied, and paying more money for an answer led to better outcomes. Second, we find that a Q&A site's community of users contributes to its success. Yahoo! Answers, a Q&A site where anybody can answer questions, outperformed sites that depend on specific individuals to answer questions, such as library reference services.
A random matrix model for elliptic curve L-functions of finite conductor

We propose a random-matrix model for families of elliptic curve L-functions of finite conductor. A repulsion of the critical zeros of these L-functions away from the centre of the critical strip was observed numerically by Miller (2006 Exp. Math. 15 257–79); such behaviour deviates qualitatively from the conjectural limiting distribution of the zeros (for large conductors this distribution is expected to approach the one-level density of eigenvalues of orthogonal matrices after appropriate rescaling). Our purpose here is to provide a random-matrix model for Miller’s surprising discovery. We consider the family of even quadratic twists of a given elliptic curve. The main ingredient in our model is a calculation of the eigenvalue distribution of random orthogonal matrices whose characteristic polynomials are larger than some given value at the symmetry point in the spectra. We call this sub-ensemble of SO(2N) the excised orthogonal ensemble. The sieving-off of matrices with small values of the characteristic polynomial is akin to the discretization of the central values of L-functions implied by the formulae of Waldspurger and Kohnen–Zagier. The cut-off scale appropriate to modelling elliptic curve L-functions is exponentially small relative to the matrix size N. The one-level density of the excised ensemble can be expressed in terms of that of the well-known Jacobi ensemble, enabling the former to be explicitly calculated. It exhibits an exponentially small (on the scale of the mean spacing) hard gap determined by the cut-off value, followed by soft repulsion on a much larger scale. Neither of these features is present in the one-level density of SO(2N). When N → ∞ we recover the limiting orthogonal behaviour. Our results agree qualitatively with Miller’s discrepancy. Choosing the cut-off appropriately gives a model in good quantitative agreement with the number-theoretical data.
The Effects of Postoperative Brachial Plexus Block Using MgSO4 on the Postoperative Pain after Upper Extremity Surgery

Background Although a brachial plexus block can be used to provide anesthesia and analgesia for upper extremity surgery, its effects using MgSO4 on postoperative pain management have not been reported. The aim of this study was to evaluate brachial plexus block using MgSO4 on postoperative analgesia. Methods Thirty-eight patients who were scheduled to undergo upper extremity surgery were randomly allocated into two groups: patients receiving axillary brachial plexus block with 0.2% ropivacaine 20 ml and normal saline 2 ml (group S) or 0.2% ropivacaine 20 ml and MgSO4 200 mg (group M). Before extubation, the blocks were done and patient controlled analgesia was started, and then, the patients were transported to a postanesthetic care unit. The postoperative visual analogue scale (VAS), opioid consumption, and side effects were recorded. Results The two groups were similar regarding the demographic variables and the duration of the surgery. No differences in VAS scores were observed between the two groups. There was no statistically significant difference in opioid consumption between the two groups. Nausea was observed in three patients for each group. Conclusions Axillary brachial plexus block using MgSO4 did not reduce the level of postoperative pain and opioid consumption.
Value co-creation within buyer-seller relationships in knowledge-intensive business services

Purpose of the paper and literature addressed: Collaborative processes play an important role in the business marketing literature, as close interaction between buyers and sellers is a key to understanding inter-organizational exchanges. The recently emerged Service-Dominant logic also emphasises the importance of interaction and relationships in all exchange. Compared with the IMP discourse, the S-D logic puts more emphasis on the role of the customer by arguing that value is always defined and co-created by the customer. The point of departure in this paper is that the conceptual thinking of S-D logic can be drawn on to bring insight into value creation in buyer-seller relationships, particularly regarding the co-creation role of the customer. Many streams of literature assume that certain businesses involve such complex and unique knowledge and skills and high level of specialization, that both the seller and the buyer face challenges during value creation. The purpose of the paper is to analyze how value is cocreated within buyer-seller relationships in knowledge-intensive business services. We provide new knowledge to answer the following questions: What kind of activities and process elements constitute the value co-creation process? What kinds of resources do the seller and the buyer contribute to value co-creation? How do the inherent features of knowledge-intensive business services, such as information asymmetry and customization, influence value co-creation within buyer-seller relationships? The paper draws on literature in the domains of industrial marketing, S-D logic and professional services marketing. Research method: Value co-creation is examined through conceptual analysis and empirical data collected through qualitative theme interviews within companies offering and buying professional business-to-business services in Finland. Research findings: The study findings demonstrate how the characteristics of knowledge-intensive services, particularly the inherent information asymmetry and perceived risk, influence value-creation, and thereby increase understanding of co-creation of complex offerings in the b-to-b markets. We argue that complex offerings need to not only be co-created, but also co-clarified: the content of exchange needs to be communicated and some kind of consensus concerning the
Efficient Processing of RDF Queries with Nested Optional Graph Patterns in an RDBMS

Relational technology has shown to be very useful for scalable Semantic Web data management. Numerous researchers have proposed to use RDBMSs to store and query voluminous RDF data using SQL and RDF query languages. In this article, we study how RDF queries with the socalled well-designed graph patterns and nested optional patterns can be efficiently evaluated in an RDBMS. We propose to extend relational databases with a novel relational operator, nested optional join (NOJ), that is more efficient than left outer join in processing nested optional patterns of well-designed graph patterns. We design three efficient algorithms to implement the new operator in relational databases: (1) nested-loops NOJ algorithm (NL-NOJ); (2) sortmerge NOJ algorithm (SM-NOJ); and (3) simple hash NOJ algorithm (SH-NOJ). Based on a real-life RDF dataset, we demonstrate the efficiency of our algorithms by comparing them with the corresponding left outer join implementations and explore the effect of join selectivity on the performance of our algorithms.
IMPROVED ESTIMATION FOR ROBUST ECONOMETRIC REGRESSION MODELS

Summary The t distribution has proved to be a useful alternative to the normal distribution in many econometric regression models, especially when robust estimation is desired. In this work, we consider a nonlinear heteroskedastic Student t regression model. We suppose the observations to be independently t distributed, with the location and scale parameters for each observation being related to linear combinations of some explanatory variables, through regular, and possibly nonlinear, completely known link functions. We obtain the second order biases of the maximum likelihood estimates of the coefficients of those linear combinations and show that the biases will only depend on the first two derivatives of the link functions. We also express the biases in a closed matrix form, allowing them to be easily computed, in practical applications, from auxiliary generalized linear regressions. We discuss some important special cases and present Monte Carlo simulation results indicating that the bias-corrected estimates outperform the corresponding uncorrected estimates for relatively small sample sizes. An example with real data showing the usefulness of bias correction for this model is also presented.
High-dimensional risk-constrained dynamic asset allocation via Markov stochastic dual dynamic programming

Dynamic portfolio optimization has a vast literature exploring different simplifications by virtue of computational tractability of the problem. Previous works provide solution methods considering unrealistic assumptions, such as no transactional costs, small number of assets, specific choices of utility functions and oversimplified price dynamics. Other more realistic strategies use heuristic solution approaches to obtain suitable investment policies. In this work, we propose a high-dimensional riskconstrained dynamic asset allocation model and efficiently solve it using the stochastic dual dynamic programming algorithm. We consider multiple assets, transactional costs and a Markov factor model for asset returns. We impose one-period conditional value-at-risk (CVaR) constraints, arguing that it is reasonable to assume that an investor knows how much he is willing to lose in a given period. In contrast to dynamic risk measures as the objective function, our time-consistent model has relatively complete recourse and a straightforward lower bound, considering a maximization problem. We present empirical results for an illustrative 3-asset model comparing the optimal policy with selected benchmarks and solve a realistic 100-asset model guaranteeing a sufficiently small optimality gap with high probability. To the best of our knowledge, this is the first systematic approach for solving realistic high-dimensional dynamic stochastic asset allocation problems.
Self-care Concept Analysis in Cancer Patients: An Evolutionary Concept Analysis

Background: Self-care is a frequently used concept in both the theory and the clinical practice of nursing and is considered an element of nursing theory by Orem. The aim of this paper is to identify the core attributes of the self-care concept in cancer patients. Materials and Methods: We used Rodgers′ evolutionary method of concept analysis. The articles published in English language from 1980 to 2015 on nursing and non-nursing disciplines were analyzed. Finally, 85 articles, an MSc thesis, and a PhD thesis were selected, examined, and analyzed in-depth. Two experts checked the process of analysis and monitored and reviewed the articles. Results: The analysis showed that self-care concept is determined by four attributes of education, interaction, self-control, and self-reliance. Three types of antecedents in the present study were client-related (self-efficacy, self-esteem), system-related (adequate sources, social networks, and cultural factors), and healthcare professionals-related (participation). Conclusion: The self-care concept has considerably evolved among patients with chronic diseases, particularly cancer, over the past 35 years, and nurses have managed to enhance their knowledge about self-care remarkably for the clients so that the nurses in healthcare teams have become highly efficient and able to assume the responsibility for self-care teams.