Quantum Transport Through a Stretched Spin--1 Molecule

We analyze the electronic transport through a model spin-1 molecule as a function of temperature, magnetic field and bias voltage. We consider the effect of magnetic anisotropy, which can be generated experimentally by stretching the molecule. In the experimentally relevant regime the conductance of the unstretched molecule reaches the unitary limit of the underscreened spin- 1 Kondo effect at low temperatures. The magnetic anisotropy generates an antiferromagnetic coupling between the remaining spin 1/2 and a singular density of quasiparticles, producing a second Kondo effect and a reduced conductance. The results explain recent measurements in spin-1 molecules [Science 328 1370 (2010)].Comment: 5 pages, 3 figures, minor changes, accepted for publication in EP

Mapping the Shadow Economy: Spatial Variations in the use of High Denomination Bank Notes in Brussels

The aim of this paper is to map the spatial variations in the size of the shadow economy within Brussels. Reporting data provided by the National Bank of Belgium on the deposit of high denomination banknotes across bank branches in the 19 municipalities of the Brussels-Capital Region, the finding is that the shadow economy is concentrated in wealthier populations and not in deprived or immigrant communities. The outcome is a call to transcend the association of the shadow economy with marginalized groups and the wider adoption of this indirect method when measuring spatial variations in the shadow economy

Carrot and Stick: How Reemployment Bonuses and Benefit Sanctions Affect Job Finding Rates

To increase their transition from welfare to work, benefit recipients in the municipality of Rotterdam were exposed to various financial incentives, including both carrots to sticks. Once their benefit spell exceeded one year, welfare recipients were entitled to a reemployment bonus if they found a job that lasted at least six months. However, they could also be punished for noncompliance with eligibility requirements and face a sanction, i.e. a temporary reducing of their benefits. In this paper we investigate how benefit sanctions and reemployment bonuses affect job finding rates of welfare recipients. We find that benefit sanctions were effective in bringing unemployed from welfare to work more quickly while reemployment bonuses were not.welfare to work, financial incentives, timing-of-events, dynamic selection

Quotient-Comprehension Chains

Quotients and comprehension are fundamental mathematical constructions that can be described via adjunctions in categorical logic. This paper reveals that quotients and comprehension are related to measurement, not only in quantum logic, but also in probabilistic and classical logic. This relation is presented by a long series of examples, some of them easy, and some also highly non-trivial (esp. for von Neumann algebras). We have not yet identified a unifying theory. Nevertheless, the paper contributes towards such a theory by introducing the new quotient-and-comprehension perspective on measurement instruments, and by describing the examples on which such a theory should be built.Comment: In Proceedings QPL 2015, arXiv:1511.0118

The asymptotic structure of nearly unstable non-negative integer-valued AR(1) models

This paper considers non-negative integer-valued autoregressive processes where the autoregression parameter is close to unity. We consider the asymptotics of this `near unit root' situation. The local asymptotic structure of the likelihood ratios of the model is obtained, showing that the limit experiment is Poissonian. To illustrate the statistical consequences we discuss efficient estimation of the autoregression parameter and efficient testing for a unit root.Comment: Published in at http://dx.doi.org/10.3150/08-BEJ153 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

GTA: Groupware task analysis Modeling complexity

The task analysis methods discussed in this presentation stem from Human-Computer Interaction (HCI) and Ethnography (as applied for the design of Computer Supported Cooperative Work CSCW), different disciplines that often are considered conflicting approaches when applied to the same design problems. Both approaches have their strength and weakness, and an integration of them does add value to the early stages of design of cooperation technology. In order to develop an integrated method for groupware task analysis (GTA) a conceptual framework is presented that allows a systematic perspective on complex work phenomena. The framework features a triple focus, considering (a) people, (b) work, and (c) the situation. Integrating various task-modeling approaches requires vehicles for making design information explicit, for which an object oriented formalism will be suggested. GTA consists of a method and framework that have been developed during practical design exercises. Examples from some of these cases will illustrate our approach

Split-2 Bisimilarity has a Finite Axiomatization over CCS with<br> Hennessy&#39;s Merge

This note shows that split-2 bisimulation equivalence (also known as timed equivalence) affords a finite equational axiomatization over the process algebra obtained by adding an auxiliary operation proposed by Hennessy in 1981 to the recursion, relabelling and restriction free fragment of Milner's Calculus of Communicating Systems. Thus the addition of a single binary operation, viz. Hennessy's merge, is sufficient for the finite equational axiomatization of parallel composition modulo this non-interleaving equivalence. This result is in sharp contrast to a theorem previously obtained by the same authors to the effect that the same language is not finitely based modulo bisimulation equivalence

Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning

Although aviation accidents are rare, safety incidents occur more frequently and require a careful analysis to detect and mitigate risks in a timely manner. Analyzing safety incidents using operational data and producing event-based explanations is invaluable to airline companies as well as to governing organizations such as the Federal Aviation Administration (FAA) in the United States. However, this task is challenging because of the complexity involved in mining multi-dimensional heterogeneous time series data, the lack of time-step-wise annotation of events in a flight, and the lack of scalable tools to perform analysis over a large number of events. In this work, we propose a precursor mining algorithm that identifies events in the multidimensional time series that are correlated with the safety incident. Precursors are valuable to systems health and safety monitoring and in explaining and forecasting safety incidents. Current methods suffer from poor scalability to high dimensional time series data and are inefficient in capturing temporal behavior. We propose an approach by combining multiple-instance learning (MIL) and deep recurrent neural networks (DRNN) to take advantage of MIL's ability to learn using weakly supervised data and DRNN's ability to model temporal behavior. We describe the algorithm, the data, the intuition behind taking a MIL approach, and a comparative analysis of the proposed algorithm with baseline models. We also discuss the application to a real-world aviation safety problem using data from a commercial airline company and discuss the model's abilities and shortcomings, with some final remarks about possible deployment directions