Quantum-like models cannot account for the conjunction fallacy

Human agents happen to judge that a conjunction of two terms is more probable than one of the terms, in contradiction with the rules of classical probabilities—this is the conjunction fallacy. One of the most discussed accounts of this fallacy is currently the quantum-like explanation, which relies on models exploiting the mathematics of quantum mechanics. The aim of this paper is to investigate the empirical adequacy of major quantum-like models which represent beliefs with quantum states. We first argue that they can be tested in three different ways, in a question order effect configuration which is different from the traditional conjunction fallacy experiment. We then carry out our proposed experiment, with varied methodologies from experimental economics. The experimental results we get are at odds with the predictions of the quantum-like models. This strongly suggests that this quantum-like account of the conjunction fallacy fails. Future possible research paths are discussed

Pectoralis Nerve Block Compared to Thoracic Paravertebral Nerve Block in the Mastectomy Patient: Evidence-Based Practice Recommendations

Patients undergoing a mastectomy are at increased risk of becoming opioid dependent. Most patients undergoing a mastectomy are diagnosed with breast cancer, and the use of opioids is known to aid in cancer metastasizing due to the suppression of the body\u27s natural killer cells. In addition, regional anesthesia, also known as a nerve block, has long provided a reduction in sensation by blocking the nerve pathway, thus numbing the feeling of pain in the operative area. The Pectoralis nerve block (PECS) and the Thoracic Paravertebral block (TPVB) are used in patients undergoing a mastectomy to help reduce the severity of pain that the body perceives. These nerve block aid in the reduction of supplemental analgesia postoperatively, allowing a lower number of opioids to be consumed. The project\u27s primary purpose is the development of evidence-based clinical recommendations which can be utilized to reduce the intensity of perceived pain for patients undergoing a mastectomy. The recommendations will be determined by selecting which nerve block provides the most significant reduction in the visual acuity scale (VAS) score. Along with the longest time from when the surgery is completed to when the patient first asks for supplemental analgesia by comparing multiple randomized control trial articles comparing the two nerve blocks. The project includes a plan for implementing these evidence-based practice recommendations through education and training, monitoring outcomes, and providing changes to the recommendations if the results are not desirable

Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is an inflammatory response that is accompanied by poor diffusion of oxygen across the alveolar-capillary membrane. Unfortunately, ARDS has a high mortality rate close to 43% when suffering from serve ARDS. ARDS cases in the United States range from 64.2 to 78.9 cases per 100,000 people. Early symptoms of ARDS are subtle and are common in many diseases processes. Such symptoms are tachycardia, tachypnea, and dyspnea. Late symptoms are right-sided heart failure, pulmonary hypertension, hypercarbia, and cyanosis. Common triggers of ARDS are sepsis, pulmonary insults such as pneumonia, pancreatitis, trauma, drug overdoses, and blood transfusions. ARDS has three phases, acute exudative phase, proliferation phase, and fibrotic phase. Once a patient enters that fibrotic stage treatment is an uphill battle. Early detection is key in mortality prevention. If placed on a mechanical ventilator ensure tidal volumes of 6 ml/kg, as well as watching for higher driving pressures in the prevention of more alveolar trauma. Prone postponing has shown great success in improving patient outcomes. Along with neuromuscular block-aid and a multimodal pharmaceutical approach. ARDS comes with many possible complications such as blood clots, pneumothorax, prolonged breathing problems, and even death. ARDS needs to be found early and treated aggressively to promote the best patient outcomes

Closed surfaces and character varieties

The powerful character variety techniques of Culler and Shalen can be used to find essential surfaces in knot manifolds. We show that module structures on the coordinate ring of the character variety can be used to identify detected boundary slopes as well as when closed surfaces are detected. This approach also yields new number theoretic invariants for the character varieties of knot manifolds.Comment: 28 pages, 1 figur

NON ASYMPTOTIC EFFICIENCY OF A MAXIMUM LIKELIHOOD ESTIMATOR AT FINITE NUMBER OF SAMPLES

International audienceIn estimation theory, the asymptotic (in the number of samples) efficiency of the Maximum Likelihood (ML) estimator is a well known result [1]. Nevertheless, in some scenarios, the number of snapshots may be small. We recently investigated the asymptotic behavior of the Stochastic ML (SML) estimator at high Signal to Noise Ratio (SNR) and finite number of samples [2] in the array processing framework: we proved the non-Gaussiannity of the SML estimator and we obtained the analytical expression of the variance for the single source case. In this paper, we generalize these results to multiple sources, and we obtain variance expressions which demonstrate the non-efficiency of SML estimates

L’intégration des marchés émergents et la modélisation des rendements des actifs risqués

We want to test the ability of conditional and non-conditional CAPM models to explain the returns on emerging markets as a function of their integration with world markets. We use data on 16 developed markets and 10 emerging markets together with data on the Casablanca Stock Exchange (CSE) before and after the reforms of 1990. We obtain the following results. First, the correlation coefficients between returns on developed and emerging markets are very small and sometimes negative. Second, the conditional APT (as well as the conditional CAPM) has a lower predictive ability for emerging markets than for developed markets. Third, Morocco financial markets are more integrated with world markets since the reforms (excess returns and non-conditional ß more in line with expectations) but the conditional APT performs rather poorly in explaining returns. This suggests that we are still far from having a good model of a structure as complex as the CSE. Nous cherchons à vérifier la capacité des modèles CAPM conditionnels et non conditionnels à expliquer les rendements sur les marchés émergents en fonction de leur intégration au marché mondial. Nous utilisons des données sur 16 marchés développés et 10 marchés en émergence et des données sur la bourse de Casablanca (BVC) avant et après les réformes financières de 1990. Nous obtenons les résultats suivants. (1) Les corrélations entre les rendements des marchés émergents et les rendements des marchés développés et du marché mondial sont très faibles et parfois négatives. (2) L’APT conditionnel (et le CAPM conditionnel) a une capacité prédictive plus faible pour les marchés émergents que pour les marchés développés. (3) Suite aux réformes financières de 1990, les marchés financiers marocains sont davantage intégrés au marché mondial (rendements excédentaires et ß non conditionnel plus conformes aux anticipations), mais l’APT conditionnel explique mal le rendement du marché marocain. Notre étude confirme que nous n’avons pas encore une modélisation très performante d’une structure aussi complexe que la BVC.

Non-efficacité et non-gaussianité asymptotiques d'un estimateur du maximum de vraisemblance à fort rapport signal sur bruit

National audienceEn théorie de l'estimation, dans le cas d'observations indépendantes de mêmes densités de probabilité, l'efficacité asymptotique en le nombre T d'observations de la méthode du Maximum de Vraisemblance (MV) est un résultat bien connu qui permet d'appréhender ses performances lorsque T est grand. Dans certaines situations, le nombre d'observations peut être faible et ce résultat ne s'applique plus. Dans le cadre du traitement d'antenne et d'une modélisation stochastique des signaux émis par les sources, nous remédions à cette lacune lorsque le Rapport Signal sur Bruit (RSB) est grand. Nous montrons que dans cette situation, l'estimateur du MV est asymptotiquement (en RSB) non-efficace et non-gaussien

Unconditional maximum likelihood performance at finite number of samples and high signal-to-noise ratio

International audienceThis correspondence deals with the problem of estimating signal parameters using an array of sensors. In source localization, two main maximum-likelihood methods have been introduced: the conditional maximum-likelihood method which assumes the source signals nonrandom and the unconditional maximum-likelihood method which assumes the source signals random. Many theoretical investigations have been already conducted for the large samples statistical properties. This correspondence studies the behavior of unconditional maximum likelihood at high signal-to-noise ratio for finite samples. We first establish the equivalence between the unconditional and the conditional maximum-likelihood criterions at high signal-to-noise ratio. Then, thanks to this equivalence we prove the non-Gaussianity and the non-efficiency of the unconditional maximum-likelihood estimator. We also rediscover the closed-form expressions of the probability density function and of the variance of the estimates in the one source scenario and we derive a closed-form expression of this estimator variance in the two sources scenario

Computational Thinking Integration into Middle Grades Science Classrooms: Strategies for Meeting the Challenges

This paper reports findings from the efforts of a university-based research team as they worked with middle school educators within formal school structures to infuse computer science principles and computational thinking practices. Despite the need to integrate these skills within regular classroom practices to allow all students the opportunity to learn these essential 21st Century skills, prior practice has been to offer these learning experiences outside of mainstream curricula where only a subset of students have access. We have sought to leverage elements of the research-practice partnership framework to achieve our project objectives of integrating computer science and computational thinking within middle science classrooms. Utilizing a qualitative approach to inquiry, we present narratives from three case schools, report on themes across work sites, and share recommendations to guide other practitioners and researchers who are looking to engage in technology-related initiatives to impact the lives of middle grades students