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Against the backdrop of Gaza and Europe’s muted response, this essay reflects on Elad Lapidot’s challenge to recognize the violence hidden in the language of peace.

Discontinuous Galerkin (DG) methods are promising high order discretizations for unsteady compressible flows. Here, we focus on Numerical Weather Prediction (NWP). These flows are characterized by a fine resolution in z-direction and low Mach numbers, making the system stiff. Thus, implicit time integration is required and for this a fast, highly parallel, low-memory iterative solver for the resul

Functional analysis of quantitative expression data is becoming common practice within the proteomics and transcriptomics fields; however, a gold standard for this type of analysis has yet not emerged. To grasp the systemic changes in biological systems, efficient and robust methods are needed for data analysis following expression regulation experiments. We discuss several conceptual and practica

Background The alpha-emitter radium-223 (Ra-223) is a bone-seeking radionuclide studied as a new treatment for patients with bone metastases from hormone-refractory prostate cancer. We aimed to study mature outcomes from a randomised, multicentre, phase II study of Ra-223. Methods Patients with hormone-refractory prostate cancer and bone pain needing external-beam radiotherapy were assigned to fou

This article explores various attempts to critique the law with reference to an authority or idea that is seen as transcending law in its existing forms. As heuristic tools, I use a distinction be-tween prophetic and apocalyptic discourses, the former referring to discourses that remain scep-tical to the possibility of suspending law in any absolute sense; the latter describing discourses that art

This article probes the writings of the Jewish Trotskyist thinker Daniel Bensaïd (1946–2010) in light of recent debates on political theology. In contrast to what is sometimes explicitly referred to as ‘apocalyptic political theology’, it makes a case for what may be described as a ‘prophetic political theology’. Yet it is not obvious to claim Bensaïd as a proponent for such a project, since he ex

Background: Desmoplastic melanoma (DM) is a rare subtype, accounting for less than 5% of primary cutaneous invasive melanomas. DM often arises in chronically sun-exposed skin, in older individuals. While the incidence of cutaneous melanoma has increased globally, trends specific to DM are less documented and studies on survival outcomes for DM are inconsistent. Objectives: To study patient and tum

We present MubyNet - a feed-forward, multitask, bottom up system for the integrated localization, as well as 3d pose and shape estimation, of multiple people in monocular images. The challenge is the formal modeling of the problem that intrinsically requires discrete and continuous computation, e.g. grouping people vs. predicting 3d pose. The model identifies human body structures (joints and limb

Objective: To investigate the association of different aspects of cognitive impairment, depression and anxiety with walking difficulties in daily life in persons with mild PD.Background: Walking difficulties in daily life are common among persons with Parkinson’s disease (PD) and may cause falls and near falls, limitations in activity, restrictions in participation and decrease in quality of life.

In this paper, we describe a new system to extract, index, search, and visualize entities in Wikipedia. To carry out the entity extraction, we designed a high-performance, multilingual, entity linker and we used a document model to store the resulting linguistic annotations. The entity linker, HEDWIG, extracts the mentions from text usinga string matching Engine and links them toentities with a co

In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation. We focus on the P4Pfr problem, but the methods we propose are applicable to a more general setting. Previous approaches to P4Pfr suffer from artificial degeneracies which come from their formulation and not the geometry of the original problem. In this paper we show how to avoi

Atmospheric inversion approaches are expected to play a critical role in future observation-based monitoring systems for surface fluxes of greenhouse gases (GHGs), pollutants and other trace gases. In the past decade, the research community has developed various inversion software, mainly using variational or ensemble Bayesian optimization methods, with various assumptions on uncertainty structure

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Un

The learning with errors (LWE) problem is one of the main mathematical foundations of post-quantum cryptography. One of the main groups of algorithms for solving LWE is the Blum–Kalai–Wasserman (BKW) algorithm. This paper presents new improvements of BKW-style algorithms for solving LWE instances. We target minimum concrete complexity, and we introduce a new reduction step where we partially reduc

In this paper, we present a side-channel attack on a first-order masked implementation of IND-CCA secure Saber KEM. We show how to recover both the session key and the long-term secret key from 24 traces using a deep neural network created at the profiling stage. The proposed message recovery approach learns a higher-order model directly, without explicitly extracting random masks at each executio

Beamforming technology plays a significant role in source localization and quantification. As traditional delay-and-sum beamformers generally yield low spatial resolution, as well as suffer from the occurrence of spurious sources, different forms of deconvolution methods have been proposed in the literature. In this work, we propose two approaches based on a sparse reconstruction framework combine