The effects of assimilating a sub-grid-scale sea ice thickness distribution in a new Arctic sea ice data assimilation system

In the past decade groundbreaking new satellite observations of the Arctic sea ice cover have been made, allowing researchers to understand the state of the Arctic sea ice system in greater detail than before. The derived estimates of sea ice thickness are useful but limited in time and space. In this study the first results of a new sea ice data assimilation system are presented. Observations assimilated (in various combinations) are monthly mean sea ice thickness and monthly mean sea ice thickness distribution from CryoSat-2 and NASA daily Bootstrap sea ice concentration. This system couples the Centre for Polar Observation and Modelling's (CPOM) version of the Los Alamos Sea Ice Model (CICE) to the localised ensemble transform Kalman filter (LETKF) from the Parallel Data Assimilation Framework (PDAF) library. The impact of assimilating a sub-grid-scale sea ice thickness distribution is of particular novelty. The sub-grid-scale sea ice thickness distribution is a fundamental component of sea ice models, playing a vital role in the dynamical and thermodynamical processes, yet very little is known of its true state in the Arctic. This study finds that assimilating CryoSat-2 products for the mean thickness and the sub-grid-scale thickness distribution can have significant consequences for the modelled distribution of the ice thickness across the Arctic and particularly in regions of thick multi-year ice. The assimilation of sea ice concentration, mean sea ice thickness and sub-grid-scale sea ice thickness distribution together performed best when compared to a subset of CryoSat-2 observations held back for validation. Regional model biases are reduced: the thickness of the thickest ice in the Canadian Arctic Archipelago (CAA) is decreased, but the thickness of the ice in the central Arctic is increased. When comparing the assimilation of mean thickness with the assimilation of sub-grid-scale thickness distribution, it is found that the latter leads to a significant change in the volume of ice in each category. Estimates of the thickest ice improve significantly with the assimilation of sub-grid-scale thickness distribution alongside mean thickness

Good neurological outcome despite very low regional cerebral oxygen saturation during resuscitation - a prospective preclinical trial in 29 patients

Background Noninvasive regional cerebral oxygen saturation (rSO2) measurement using near-infrared spectroscopy (NIRS) might inform on extent and duration of cerebral hypoxia during cardiopulmonary resuscitation (CPR). This information may be used to guide resuscitation efforts and may carry relevant early prognostic information. Methods We prospectively investigated non-traumatic out-of-hospital cardiac arrest (OHCA) patients on scene. NIRS was started either during CPR or shortly after (<2 min) return of spontaneous circulation (ROSC) by emergency medical service (EMS). Outcome was determined at intensive care unit (ICU) discharge and 6 months after cardiac arrest. Results A total of 29 OHCA patients were included. In 23 patients NIRS was started during CPR and in 6 patients immediately after ROSC. 18 (62.1 %) patients did not reach ROSC. Initial rSO2 during CPR was very low (<50 % in all 23 patients, < 30 % in 19 of 23 patients) with no significant difference between patients achieving ROSC and those who did not. Of five patients with ROSC, in whom NIRS was recorded during CPR, two reached a good six-months outcome (initial rSO2 22 %) and three died during the ICU stay (initial rSO2 15, 16 and 46 %). In six patients with NIRS started immediately after ROSC (<2 min), rSO2 was substantially higher (54–85 %) than in patients during CPR (p = 0.006). Discussion and conclusion Initial frontal brain rSO2 determined by NIRS during CPR was generally very low and recovered rapidly after ROSC. Very low initial rSO2 during CPR was compatible with good neurological outcome in our limited cohort of patients. Further studies are needed to assess in larger cohorts and more detail the implications of very low initial rSO2 during CPR on scene

Effect of virtual reality training on laparoscopic surgery: randomised controlled trial

Objective To assess the effect of virtual reality training on an actual laparoscopic operation

A ‘fuzzy clustering’ approach to conceptual confusion: how to classify natural ecological associations

The concept of the marine ecological community has recently experienced renewed attention, mainly owing to a shift in conservation policies from targeting single and specific objec- tives (e.g. species) towards more integrated approaches. Despite the value of communities as dis- tinct entities, e.g. for conservation purposes, there is still an ongoing debate on the nature of spe- cies associations. They are seen either as communities, cohesive units of non-randomly associated and interacting members, or as assemblages, groups of species that are randomly associated. We investigated such dualism using fuzzy logic applied to a large dataset in the German Bight (south- eastern North Sea). Fuzzy logic provides the flexibility needed to describe complex patterns of natural systems. Assigning objects to more than one class, it enables the depiction of transitions, avoiding the rigid division into communities or assemblages. Therefore we identified areas with either structured or random species associations and mapped boundaries between communities or assemblages in this more natural way. We then described the impact of the chosen sampling design on the community identification. Four communities, their core areas and probability of occurrence were identified in the German Bight: AMPHIURA-FILIFORMIS, BATHYPOREIA-TELLINA, GONIADELLA-SPISULA, and PHORONIS. They were assessed by estimating overlap and compactness and supported by analysis of beta-diversity. Overall, 62% of the study area was characterized by high species turnover and instability. These areas are very relevant for conservation issues, but become undetectable when studies choose sampling designs with little information or at small spatial scales

Historical Newspaper Content Mining: Revisiting the impresso Project's Challenges in Text and Image Processing, Design and Historical Scholarship

impresso. Media Monitoring of the Past is an interdisciplinary research project in which a team of computational linguists, designers and historians collaborate on the datafication of a multilingual corpus of digitised historical newspapers. The primary goals of the project are to improve text mining tools for historical text, to enrich historical newspapers with (semi-) automatically generated data and to integrate such data into historical research workflows by means of a newly developed user interface. In this paper we discuss our efforts to overcome inherent challenges and to integrate text mining and data visualisation applications in general historical research practices which are characterised by search operations as well as the need to create topical collections

The Uppsala APP deletion causes early onset autosomal dominant Alzheimer's disease by altering APP processing and increasing amyloid β fibril formation

Point mutations in the amyloid precursor protein gene (APP) cause familial Alzheimer's disease (AD) by increasing generation or altering conformation of amyloid beta (A beta). Here, we describe the Uppsala APP mutation (Delta 690-695), the first reported deletion causing autosomal dominant AD. Affected individuals have an age at symptom onset in their early forties and suffer from a rapidly progressing disease course. Symptoms and biomarkers are typical of AD, with the exception of normal cerebrospinal fluid (CSF) A beta 42 and only slightly pathological amyloid-positron emission tomography signals. Mass spectrometry and Western blot analyses of patient CSF and media from experimental cell cultures indicate that the Uppsala APP mutation alters APP processing by increasing beta-secretase cleavage and affecting alpha-secretase cleavage. Furthermore, in vitro aggregation studies and analyses of patient brain tissue samples indicate that the longer form of mutated A beta, A beta Upp1-42(Delta 19-24), accelerates the formation of fibrils with unique polymorphs and their deposition into amyloid plaques in the affected brain

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A &lt; AV &gt; V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis

Light Element Depletion in Contracting Brown Dwarfs and Pre--Main-Sequence Stars

We present an analytic calculation of the thermonuclear depletion of the light elements lithium, beryllium, and boron in fully convective, low-mass stars. Under the presumption that the pre--main-sequence star is always fully mixed during contraction, we find that the burning of these rare light elements can be computed analytically, even when the star is degenerate. Using the effective temperature as a free parameter, we constrain the properties of low-mass stars from observational data, independently of the uncertainties associated with modeling their atmospheres and convection. Our analytic solution explains the dependence of the age at a given level of elemental depletion on the stellar effective temperature, nuclear cross sections, and chemical composition. Most importantly, our results allow observers to translate lithium non-detections in young cluster members into a model-independent minimum age for that cluster. Using this procedure, we have found lower limits to the ages of the Pleiades (100 Myr) and Alpha Persei (60 Myr) clusters. Recent experimental work on the low energy resonance in the ^10B(p,\alpha)^7Be reaction has greatly enhanced estimates of the destruction rate of ^10B, making it possible for stars with M>0.1 M_sun to deplete both ^10B and ^11B before reaching the main sequence. Moreover, there is an interesting range of masses, 0.085 M_sun < M < 0.13 M_sun, where boron depletion occurs on the main sequence in less than a Hubble time, providing a potential ``clock'' for dating low-mass stars.Comment: 34 pages, including 6 figures; Accepted to Ap