Temporal Justification Logic

Justification logics are modal-like logics with the additional capability of recording the reason, or justification, for modalities in syntactic structures, called justification terms. Justification logics can be seen as explicit counterparts to modal logics. The behavior and interaction of agents in distributed system is often modeled using logics of knowledge and time. In this paper, we sketch some preliminary ideas on how the modal knowledge part of such logics of knowledge and time could be replaced with an appropriate justification logic

Nonparametric regression penalizing deviations from additivity

Due to the curse of dimensionality, estimation in a multidimensional nonparametric regression model is in general not feasible. Hence, additional restrictions are introduced, and the additive model takes a prominent place. The restrictions imposed can lead to serious bias. Here, a new estimator is proposed which allows penalizing the nonadditive part of a regression function. This offers a smooth choice between the full and the additive model. As a byproduct, this penalty leads to a regularization in sparse regions. If the additive model does not hold, a small penalty introduces an additional bias compared to the full model which is compensated by the reduced bias due to using smaller bandwidths. For increasing penalties, this estimator converges to the additive smooth backfitting estimator of Mammen, Linton and Nielsen [Ann. Statist. 27 (1999) 1443-1490]. The structure of the estimator is investigated and two algorithms are provided. A proposal for selection of tuning parameters is made and the respective properties are studied. Finally, a finite sample evaluation is performed for simulated and ozone data.Comment: Published at http://dx.doi.org/10.1214/009053604000001246 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation

Many modern computer vision and machine learning applications rely on solving difficult optimization problems that involve non-differentiable objective functions and constraints. The alternating direction method of multipliers (ADMM) is a widely used approach to solve such problems. Relaxed ADMM is a generalization of ADMM that often achieves better performance, but its efficiency depends strongly on algorithm parameters that must be chosen by an expert user. We propose an adaptive method that automatically tunes the key algorithm parameters to achieve optimal performance without user oversight. Inspired by recent work on adaptivity, the proposed adaptive relaxed ADMM (ARADMM) is derived by assuming a Barzilai-Borwein style linear gradient. A detailed convergence analysis of ARADMM is provided, and numerical results on several applications demonstrate fast practical convergence.Comment: CVPR 201

Frequency-selective single photon detection using a double quantum dot

We use a double quantum dot as a frequency-tunable on-chip microwave detector to investigate the radiation from electron shot-noise in a near-by quantum point contact. The device is realized by monitoring the inelastic tunneling of electrons between the quantum dots due to photon absorption. The frequency of the absorbed radiation is set by the energy separation between the dots, which is easily tuned with gate voltages. Using time-resolved charge detection techniques, we can directly relate the detection of a tunneling electron to the absorption of a single photon

Helical recorder

Tape recorder, using metallic tape, has a minimum of moving parts and no belts. It permits long-term bulk storage in extreme environments, and has less weight and bulk than present recording equipment

Lifecycle-Support in Architectures for Ontology-Based Information Systems

Ontology-based applications play an increasingly important role in the public and corporate Semantic Web. While today there exist a range of tools and technologies to support specific ontology engineering and management activities, architectural design guidelines for building ontology-based applications are missing. In this paper, we present an architecture for ontology-based applications—covering the complete ontology-lifecycle—that is intended to support software engineers in designing and developing ontology based-applications. We illustrate the use of the architecture in a concrete case study using the NeOn toolkit as one implementation of the architecture

Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors

While single measurement vector (SMV) models have been widely studied in signal processing, there is a surging interest in addressing the multiple measurement vectors (MMV) problem. In the MMV setting, more than one measurement vector is available and the multiple signals to be recovered share some commonalities such as a common support. Applications in which MMV is a naturally occurring phenomenon include online streaming, medical imaging, and video recovery. This work presents a stochastic iterative algorithm for the support recovery of jointly sparse corrupted MMV. We present a variant of the Sparse Randomized Kaczmarz algorithm for corrupted MMV and compare our proposed method with an existing Kaczmarz type algorithm for MMV problems. We also showcase the usefulness of our approach in the online (streaming) setting and provide empirical evidence that suggests the robustness of the proposed method to the distribution of the corruption and the number of corruptions occurring.Comment: 13 pages, 6 figure

[Examinations of cattle births with a special focus on Coxiella burnetii].

Cattle births can carry the risk of transmissible and zoonotic diseases. The focus of the present study was the excretion of Coxiella (C.) burnetii during cattle births. Small ruminants are considered as the main reservoir of C. burnetii. Cattle are often subclinical carriers and their role as potential reservoir has not been fully elucidated until now, although the excretion of Coxiella has been demonstrated during cattle birth. The study recorded all births, caesarean sections and one abortion in 40 cattle at the ruminant clinic of the Vetsuisse Faculty in Bern in the study period from March 2019 to March 2020. A placenta -, milk - and fecal sample was examined for antigen diagnostics using polymerase chain reaction (PCR). In addition, a serum sample was analyzed to detect C. burnetii-specific antibodies. Antigen and/or antibodies (placenta, n=8/9; milk, n=2/9; faeces, n=1/9; serology n= 3/9) were detected in 22,5 % of the cows (n=9/40) without the presence of specific clinical symptoms. It is essential to sensitize contact persons to this zoonosis, since Coxiella can trigger Q-fever in humans

Is attention deficit/hyperactivity disorder among men associated with initiation or escalation of substance use at 15-month follow-up? A longitudinal study involving young Swiss men.

Young adults with attention deficit/hyperactivity disorder (ADHD) show higher substance use disorder (SUD) prevalence relative to non-ADHD controls; few longitudinal studies have examined the course of substance use with reference to conduct disorder (CD). We compared initiation and escalation of substance use at 15-month follow-up in men screened positive or negative for ADHD (ADHD(+) versus ADHD(-) ), controlling for CD presence in early adolescence. Participants were recruited during August 2010 and November 2011 from the census of all young men who have to pass mandatory army conscription from three of six Swiss Army recruitment centres. A two-wave data collection was performed via questionnaires at baseline and 15-month follow-up as a part of the longitudinal Cohort Study on Substance Use Risk Factors. Recruitment centres in Lausanne, Windisch and Mels, responsible for 21 cantons in German- and French-speaking areas of Switzerland. Consecutive sample of 5103 male Swiss Army conscripts who provided informed consent and responded to questionnaires at baseline and 15-month follow-up. Their mean age was 20.0 (standard deviation = 1.21) years at baseline. ADHD and CD were assessed using the adult ADHD Self-Report Scale and the MINI International Neuropsychiatric Interview Plus, respectively, at baseline, and substance use was measured via self-administered substance use questionnaires at baseline and follow-up. Compared with the ADHD(-) group, the ADHD(+) group (n = 215, 4.2%) showed heavier baseline substance use and increased likelihood of alcohol (χ(2)  = 53.96; P < 0.001), tobacco (χ(2)  = 21.73; P < 0.001) and cannabis use disorders (χ(2)  = 48.43; P < 0.001). The extent of alcohol, tobacco and cannabis use in the two groups remained stable from baseline to follow-up (no escalation). The ADHD(+) group was more likely to initiate substance use compared with the ADHD(-) group (higher initiation rates), particularly with amphetamines [odds ratio (OR) = 3.81; 95% confidence interval (CI) = 2.20-6.60; P < 0.001] and non-medical use of ADHD medication (OR = 4.45; 95% CI = 2.06-9.60; P < 0.001). CD was associated with initiation of substance use but did not mediate the associations between ADHD and substance use, revealing that the impact of ADHD on substance use was independent of CD. For men in their early 20s, attention deficit/hyperactivity disorder is a risk factor for continued heavier but not escalating use of alcohol, tobacco and cannabis when already consuming these substances, compared with young men with no ADHD. It is also a risk factor for initiating the use of cannabis, stimulants, hallucinogens and sedatives, independent of conduct disorder in early adolescence