A GIF++ Gamma Irradiation Facility at the SPS H4 Beam Line

The current document describes a proposal to implement a new gamma irradiation facility, combined with a high-energy particle beam in the SPS H4 beam line in hall EHN1. This new GIF++ facility is motivated by strong needs from the LHC and sLHC detector and accelerator communities for the tests of LHC components and systems

Hybrid Software Development Approaches in Practice: A European Perspective

Agile and traditional development approaches are used in combination in todays software development. To improve the understanding and to provide better guidance for selecting appropriate development approaches, it is important to analyze such combinations in practice. Results obtained from an online survey strongly confirm that hybrid development approaches are widely used in industry. Our results show that hybrid development approaches: (i) have become reality for nearly all companies; (ii) are applied to specific projects even in the presence of company-wide policies for process usage; (iii) are neither planned nor designed but emerge from the evolution of different work practices; and, (iv) are consistently used regardless of company size or industry secto

NatCSNN: A Convolutional Spiking Neural Network for recognition of objects extracted from natural images

Biological image processing is performed by complex neural networks composed of thousands of neurons interconnected via thousands of synapses, some of which are excitatory and others inhibitory. Spiking neural models are distinguished from classical neurons by being biological plausible and exhibiting the same dynamics as those observed in biological neurons. This paper proposes a Natural Convolutional Neural Network (NatCSNN) which is a 3-layer bio-inspired Convolutional Spiking Neural Network (CSNN), for classifying objects extracted from natural images. A two-stage training algorithm is proposed using unsupervised Spike Timing Dependent Plasticity (STDP) learning (phase 1) and ReSuMe supervised learning (phase 2). The NatCSNN was trained and tested on the CIFAR-10 dataset and achieved an average testing accuracy of 84.7% which is an improvement over the 2-layer neural networks previously applied to this dataset.Comment: 12 page

The intensive care infection score - a novel marker for the prediction of infection and its severity

Background: The prediction of infection and its severity remains difficult in the critically ill. A novel, simple biomarker derived from five blood-cell derived parameters that characterize the innate immune response in routine blood samples, the intensive care infection score (ICIS), could be helpful in this respect. We therefore compared the predictive value of the ICIS with that of the white blood cell count (WBC), C-reactive protein (CRP) and procalcitonin (PCT) for infection and its severity in critically ill patients. Methods: We performed a multicenter, cluster-randomized, crossover study in critically ill patients between January 2013 and September 2014. Patients with a suspected infection for which blood cultures were taken by the attending intensivist were included. Blood was taken at the same time for WBC, ICIS, CRP and PCT measurements in the control study periods. Results of imaging and cultures were collected. Patients were divided into groups of increasing likelihood of infection and invasiveness: group 1 without infection or with possible infection irrespective of cultures, group 2 with probable or microbiologically proven local infection without blood stream infection (BSI) and group 3 with BSI irrespective of local infection. Septic shock was assessed. Results: In total, 301 patients were enrolled. CRP, PCT and ICIS were higher in groups 2 and 3 than group 1. The area under the receiver operating characteristic curve (AUROC) for the prediction of infection was 0.70 for CRP, 0.71 for PCT and 0.73 for ICIS (P < 0.001). For the prediction of septic shock the AUROC was 0.73 for CRP, 0.85 for PCT and 0.76 for ICIS. These AUROC did not differ fro

Cumulative energetic costs of military aircraft, recreational and natural disturbance in roosting shorebirds

Knowing the consequences of disturbance for multiple species and all disturbance sources is crucial to mitigate disturbance impacts in densely populated areas. However, studies that observe the complete disturbance landscape to estimate cumulative costs of disturbance are scarce. Therefore, we quantified responses, frequencies and energetic costs of disturbance of four shorebird species on five high tide roosts in the Wadden Sea. Roosts were located either in a military air force training area or were predominantly affected by recreational disturbance. In the military training area, infrequent transport airplanes and bombing jets elicited the strongest responses, whereas regular, predictable activities of jet fighters and small civil airplanes elicited far smaller responses. Disturbance occurred more frequently at roosts near recreational than near military activities, as recreation was prohibited in the military area during operation days. On average, birds took flight due to military, recreational or natural disturbance (e.g. raptors) 0.20–1.27 times per hour. High tide disturbance increased daily energy expenditure by 0.1%–1.4%, of which 51% was due to anthropogenic disturbance in contrast to natural disturbance. Costs were low for curlews Numenius arquata, oystercatchers Haematopus ostralegus and gulls Larus spp, but higher – and potentially critical – for bar-tailed godwits Limosa lapponica as they were most susceptible to aircraft and raptors. Given that bar-tailed godwits have previously been found to be least susceptible to walker disturbances, our results suggest that interspecific differences in susceptibility depend on disturbance source type. In our study area, aircraft disturbance impacts can be reduced by avoiding jet fighter activities during periods when high water levels force birds closer to military targets and by limiting bombing and transport airplane exercises

Data reduction in statistical inference

Abstract: Generalized definitions of the invariance, (partial) sufficiency and ancillarity principles are given in a measure-theoretic context. Data reduction in statistical inference is described in terms of these pril&apos;.ciples