The book offers an overview of the history, cases and material of the European Law Moot Court Competition (ELMC). The ELMC is today considered the most prestigious moot court within the field of European Union Law and one of the most important moot court competitions in the world.Published at the occasion of the 35th anniversary of the competition, the book aims to both motivate students and guide

BACKGROUND: The COVID-19 pandemic has highlighted the importance of evidence-informed priority setting and situational analysis in pandemic preparedness and response. Health Technology Assessment (HTA) has been identified as an essential tool for evidence-informed decision-making in healthcare. However, the potential role of HTA in pandemic preparedness and response in Africa has yet to be explore

Manual motor performance declines with age, but the extent to which age influences the acquisition of new skills remains a topic of debate. Here, we examined whether older healthy adults show less training-dependent performance improvements during a single session of a bimanual pinch task than younger adults. We also explored whether physical and cognitive factors, such as grip strength or motor-c

This article suggests a model for lexical verb semantics that unifies Halliday’s model for transitivity with Langacker’s concept of base and profile and also with a model for situation type (cf. Smith 1997). It is claimed that verbs adhere to one of four macro domains: the material, the social, the mental or the relational domain. Within these domains there are numerous types of verbs, such as mot

Electrons from a laser wakefield accelerator have a limited energy gain due to dephasing and are prone to emittance growth, causing a large divergence. In this paper, we experimentally show that adjusting the plasma density profile can address both issues. Shock-assisted ionisation injection is used to produce 100 MeV quasi-monoenergetic electron bunches in the primary part of the accelerator. Dow

Language learners must become able to perceive and process new speech sounds in order to segment words and sentences. The process of obtaining these skills is, to a high degree, implicit. However, research attempting to find the neuroanatomical correlates of such an implicit learning system has mostly used artificial grammar or serial reaction time tasks that are lacking in linguistic relevance. ILanguage learning involves implicitly acquiring a sensitivity for novel speech sounds and phonological structure [1]. Implicit learning skill differs between individuals [2] and this individual difference could potentially be reflected in the quality of white matter tracts relevant for speech perception and production [3] or for implicit sequence learning [4]. Implicit learning of speech has been

Reformer för tillväxt bör stå i fokus för den ekonomiska debatten – inte vem som kan spendera mest pengar på kortsiktiga projekt. Det skriver Fredrik N G Andersson och Lars Jonung.

Implicit sequence learning (ISL) has been studied using a variety of tasks two of which have been particularly influential: the serial reaction time task (SRTT) and the artificial grammar learning (AGL) task, stemming from the motor learning domain and psycholinguistics, respectively. SRTTs measure the difference in response times between a repeatedly presented and random sequences of keyboard pre

Background: Adjunctive pharmacological treatment may improve nerve regeneration. We investigated nerve regeneration processes of PXL01 - a lactoferrin-derived peptide - after repair of the sciatic nerve in healthy Wistar rats. Materials & methods: PXL01, sodium hyaluronate (carrier) or sodium chloride was administered around the repair. After 6 days axonal outgrowth, Schwann cell response, pa

Formal models for the safety validation of autonomous vehicles have become increasingly important. To this end, we present a safety framework for longitudinal automated driving. This framework enables the calculation of minimum safe inter-vehicular distances for arbitrary ego vehicle control policies in a computationally efficient manner. We use this framework to enhance and generalize the Respons

Despite the widely recognized potential of product-as-a-service (PaaS) business models to contribute to the circular economy, many industrial case studies have reported that several systemic factors tend to hinder product manufacturers from effectively designing such solutions. More specifically, factors such as linear value chains, organizational structures, and market and financial conditions te

Declarative approaches to program analysis promise a number of practical advantages over imperative approaches, from eliminating manual worklist management to increasing modularity. Reference Attribute Grammars (RAGs) are one such approach. One particular advantage of RAGs is the automatic generation of on-demand implementations, suitable for query-based interactive tooling as well as for client a

Background: Sex and gender influence many aspects of chronic obstructive pulmonary disease (COPD). Limited data are available on this topic in alpha-1 antitrypsin deficiency (AATD). We therefore aimed to investigate sex issues in the EARCO registry, a prospective, international, observational cohort study. Methods: Baseline data from PiZZ individuals, enrolled in the registry with complete data on

[18F]Flortaucipir is an FDA-approved tau-PET tracer that is increasingly utilized in clinical settings for the diagnosis of Alzheimer’s disease. Still, a large-scale comparison of the in vivo PET uptake to quantitative post-mortem tau pathology and to other co-pathologies is lacking. Here, we examined the correlation between in vivo [18F]flortaucipir PET uptake and quantitative post-mortem tau pat

Introduction: The presence of fibrillatory waves (f-waves) is important in the diagnosis of atrial fibrillation (AF), which has motivated the development of methods for f-wave extraction. We propose a novel approach to benchmarking methods designed for single-lead ECG analysis, building on the hypothesis that better-performing AF classification using features computed from the extracted f-waves im

The medial temporal lobe (MTL) is a hotspot for neuropathology, and measurements of MTL atrophy are often used as a biomarker for cognitive decline associated with neurodegenerative disease. Due to the aggregation of multiple proteinopathies in this region, the specific relationship of MTL atrophy to distinct neuropathologies is not well understood. Here, we develop two quantitative algorithms usi