Theory of Transmission through disordered superlattices

We derive a theory for transmission through disordered finite superlattices in which the interface roughness scattering is treated by disorder averaging. This procedure permits efficient calculation of the transmission thr ough samples with large cross-sections. These calculations can be performed utilizing either the Keldysh or the Landauer-B\"uttiker transmission formalisms, both of which yield identical equations. For energies close to the lowest miniband, we demonstrate the accuracy of the computationally efficient Wannier-function approximation. Our calculations indicate that the transmission is strongly affected by interface roughness and that information about scale and size of the imperfections can be obtained from transmission data.Comment: 12 pages, 6 Figures included into the text. Final version with minor changes. Accepted by Physical Review

Spin relaxation in (110) and (001) InAs/GaSb superlattices

We report an enhancement of the electron spin relaxation time (T1) in a (110) InAs/GaSb superlattice by more than an order of magnitude (25 times) relative to the corresponding (001) structure. The spin dynamics were measured using polarization sensitive pump probe techniques and a mid-infrared, subpicosecond PPLN OPO. Longer T1 times in (110) superlattices are attributed to the suppression of the native interface asymmetry and bulk inversion asymmetry contributions to the precessional D'yakonov Perel spin relaxation process. Calculations using a nonperturbative 14-band nanostructure model give good agreement with experiment and indicate that possible structural inversion asymmetry contributions to T1 associated with compositional mixing at the superlattice interfaces may limit the observed spin lifetime in (110) superlattices. Our findings have implications for potential spintronics applications using InAs/GaSb heterostructures.Comment: 4 pages, 2 figure

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use, and pave the way to further large scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multistakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two round, modified Delphi process to collect and analyse expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 predefined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. 123 experts participated in the first round of Delphi, 138 in the second, 16 in the consensus meeting, and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI specific reporting items (made of 28 subitems) and 10 generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we have developed a guideline comprising key items that should be reported in early stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings

Cross-Cultural Differences on Work-to-Family Conflict and Role Satisfaction: A Taiwanese-British Comparison

The aim of this research was to explore relations between work and family demands and resources, work-to-family conflict (WFC), and work and family outcomes in a cross-cultural comparative context involving Taiwanese and British employees. Two-hundred and sixty-four Taiwanese employees and 137 British employees were surveyed using structured questionnaires. For both Taiwanese and British employees, work and family demands were positively related to WFC, whereas work resources were negatively related to WFC. Furthermore, WFC was negatively related to family satisfaction. More importantly, we found that nation moderated relationships between work resources and WFC, WFC and work, and family satisfaction. Specifically, work resources had a stronger protective effect for Taiwanese than British in reducing WFC, whereas WFC had a stronger detrimental effect on role satisfaction for British than Taiwanese. It is recommended that both culture-general and culture-specific effects should be taken into consideration in designing future WFC research and family friendly managerial practices

Clinical Validation of a Virtual Environment Test for Safe Street Crossing in the Assessment of Acquired Brain Injury Patients with and without Neglect

Part 1: Long and Short PapersInternational audienceAcquired brain injury (ABI) is a complex disease that involves loss of brain functions related to cognitive and motor capabilities and that can produce unilateral spatial neglect (USN). The heterogeneity of the symptoms of these disorders causes a lack of consensus on suitable tools for evaluation and treatment. Recently, several studies have initiated the application of virtual reality (VR) systems as an evaluation instrument for neuropsychological disorders. Our main objective was to evaluate the validity of the VR Street Crossing Test (VRSCT) as an assessment tool. Twenty-five patients with ABI were evaluated with traditional tests and with the VRSCT. The results showed significant correlations between the conventional tests and the measures obtained with the VRSCT in non-negligent patients. Moreover, the VRSCT indicated significant differences in performance of negligent and non-negligent subjects. These pilot results indicate that ABI patients with and without USN can be assessed by the therapists using the VRSCT system as a complementary tool

Il Virus del lavoro da remoto

Abstract. Ensemble classifiers combine the classification results of several classifiers. Simple ensemble methods such as uniform averaging over a set of models usually provide an improvement over selecting the single best model. Usually probabilistic classifiers restrict the set of possible models that can be learnt in order to lower computational complexity costs. In these restricted spaces, where incorrect modelling assumptions are possibly made, uniform averaging sometimes performs even better than bayesian model averaging. Linear mixtures over sets of models provide an space that includes uniform averaging as a particular case. We develop two algorithms for learning maximum a posteriori weights for linear mixtures, based on expectation maximization and on constrained optimizition. We provide a nontrivial example of the utility of these two algorithms by applying them for one dependence estimators.We develop the conjugate distribution for one dependence estimators and empirically show that uniform averaging is clearly superior to BMA for this family of models. After that we empirically show that the maximum a posteriori linear mixture weights improve accuracy significantly over uniform aggregation

On the need for pro-poor land administration in disaster risk management

There exists an intensifying and multifaceted relationship between rapid population growth, the increasing occurrence of natural disasters, and demands for land tenure security. Consequently, there is growing agreement on the need to adopt pro-poor land administration approaches, ones that better address the needs of the poor living in disaster prone contexts. Vulnerable communities and exposed lands could benefit from emerging pro-poor land administration, however, thus far, application of the pro-poor mind-set has gained minimal traction in the disaster risk management agenda. Using a research synthesis, existing evidence is analysed and consolidated, and a new inclusive conceptual framework is built; one that illustrates the underutilised potential for pro-poor land administration in disaster risk management. The developed framework explains the interactions between three identified and fundamental global change forces (people, land and disaster) and the three disaster risk drivers (vulnerability, exposure and hazard). The framework illustrates how pro-poor approaches can simultaneously have impacts on both land tenure security and disaster risk management. The conceptual framework is considered a first step toward an implementable strategy for applying pro-poor land administration technologies in the context of disaster risk management. Ultimately, pro-poor land administration should enable the poor to minimise vulnerabilities and disaster risks through an inclusive land tenure security approach to prevent, mitigate, prepare and respond to natural disasters