Dynamic changes of intramural hematoma in patients with acute spontaneous internal carotid artery dissection.

BACKGROUND We prospectively investigated temporal and spatial evolution of intramural hematomas in patients with acute spontaneous internal carotid artery dissection using repeated magnetic resonance imaging over six-months. AIM The aim of the present study was to assess dynamic changes of intramural hematoma in patients with acute spontaneous internal carotid artery dissection at multiple follow-up time-points with T1w, PD/T2w, and magnetic resonance angiography. METHODS We performed serial multiparametric magnetic resonance imaging in 10 patients with spontaneous internal carotid artery dissection on admission, at days 1, 3, 7-14 and at months 1·5, 3, and 6. We calculated the volume and extension of the hyperintense intramural hematoma using T1w and PD/T2w fat suppressed sequences and assessed the degree of stenosis due to the hematoma using magnetic resonance angiography. RESULTS Mean interval from symptom onset to first magnetic resonance imaging was two-days (SD 2·7). Two patients presented with ischemic stroke, three with transient ischemic attacks, and five with pain and local symptoms only. Nine patients had a transient increase of the intramural hematoma volume, mainly up to day 10 after symptom onset. Fifty percent had a transient increase in the degree of the internal carotid artery stenosis on MRA, one resulting in a temporary occlusion. Lesions older than one-week were predominantly characterized by a shift from iso- to hyperintese signal on T2w images. At three-month follow-up, intramural hematoma was no longer detectable in 80% of patients and had completely resolved in all patients after six-months. CONCLUSIONS Spatial and temporal dynamics of intramural hematomas after spontaneous internal carotid artery dissection showed an early volume increase with concomitant progression of the internal carotid artery stenosis in 5 of 10 patients. Although spontaneous internal carotid artery dissection overall carries a good prognosis with spontaneous hematoma resorption in all our patients, early follow-up imaging may be considered, especially in case of new clinical symptoms.

Computational Tools for Stereo and Light Field Photography

This thesis covers a broad part of the field of computational photography, including video stabilization and image warping techniques, introductions to light field photography and the conversion of monocular images and videos into stereoscopic 3D content. We present a user assisted technique for stereoscopic 3D conversion from 2D images. Our approach exploits the geometric structure of perspective images including vanishing points. We allow a user to indicate lines, planes, and vanishing points in the input image, and directly employ these as guides of an image warp that produces a stereo image pair. Our method is most suitable for scenes with large scale structures such as buildings and is able to skip the step of constructing a depth map. Further, we propose a method to acquire 3D light fields using a hand-held camera, and describe several computational photography applications facilitated by our approach. As the input we take an image sequence from a camera translating along an approximately linear path with limited camera rotations. Users can acquire such data easily in a few seconds by moving a hand-held camera. We convert the input into a regularly sampled 3D light field by resampling and aligning them in the spatio-temporal domain. We also present a novel technique for high-quality disparity estimation from light fields. Finally, we show applications including digital refocusing and synthetic aperture blur, foreground removal, selective colorization, and others.

Linking livelihood strategies with a regional level landscape mosaic to explore trade-offs between forest conservation and human wellbeing in a Madagascar biodiversity hotspot

The north-eastern escarpment of Madagascar contains the island’s last remaining large-scale humid forest massifs surrounded by diverse small-scale agricultural mosaics. There is high deforestation mainly caused by shifting cultivation practiced by local land users to produce upland rice for subsistence. Today, large protected areas restrict land users’ access to forests to collect wood and other forest products. Moreover, they are no more able to expand their cultivated land, which leads to shorter shifting cultivation cycles and decreasing plot sizes for irrigated rice and cash crop cultivation. Cash crop production of clove and vanilla is exposed to risks such as extreme inter-annual price fluctuations, pests and cyclones. In the absence of work opportunities, agricultural extension services and micro-finance schemes people are stuck in a poverty trap. New development strategies are needed to mitigate the trade-offs between forest conservation and human well-being. As landscape composition and livelihood strategies vary across the region, these strategies need to be spatially differentiated to avoid implementing generic solutions, which do not fit the local context. However, up to date, little is known about the spatial patterns of shifting cultivation and other land use systems at the regional level. This is mainly due to the high spatial and temporal dynamics inherent to shifting cultivation, which makes it difficult to monitor the dynamics of this land use system with remote sensing methods. Furthermore, knowledge about land users’ livelihood strategies and the risks and opportunities they face stems from very few local case studies. To overcome this challenge, firstly, we used remote sensing data and a landscape mosaic approach to delineate the main landscape types at the regional level. Secondly, we developed a land user typology based on socio-ecological data from household surveys in 45 villages spread throughout the region. Combining the land user typology with the landscape mosaic map allowed us to reveal spatial patterns of the interaction between landscapes and people and to better understand the trade-offs between forest conservation and local wellbeing. While shifting cultivation systems are being transformed into more intensive permanent agricultural systems in many countries around the globe, Madagascar seems to be an exception to this trend. Linking land cover information to human-environmental interactions over large areas is crucial to designing policies and to inform decision making for a more sustainable development of this resource-rich but poverty-prone context.

Soil and land information: How to support decision-making?

Soils are fundamental to ensuring water, energy and food security. Within the context of sus- tainable food production, it is important to share knowledge on existing and emerging tech- nologies that support land and soil monitoring. Technologies, such as remote sensing, mobile soil testing, and digital soil mapping, have the potential to identify degraded and non- /little-responsive soils, and may also provide a basis for programmes targeting the protection and rehabilitation of soils. In the absence of such information, crop production assessments are often not based on the spatio-temporal variability in soil characteristics. In addition, uncertain- ties in soil information systems are notable and build up when predictions are used for monitor- ing soil properties or biophysical modelling. Consequently, interpretations of model-based results have to be done cautiously. As such they provide a scientific, but not always manage- able, basis for farmers and/or policymakers. In general, the key incentives for stakeholders to aim for sustainable management of soils and more resilient food systems are complex at farm as well as higher levels. The same is true of drivers of soil degradation. The decision- making process aimed at sustainable soil management, be that at farm or higher level, also in- volves other goals and objectives valued by stakeholders, e.g. land governance, improved envi- ronmental quality, climate change adaptation and mitigation etc. In this dialogue session we will share ideas on recent developments in the discourse on soils, their functions and the role of soil and land information in enhancing food system resilience.

Challenges in the participatory assessment of sustainable management practices in dryland ecosystems under regime shifts

Regime shifts, defined as a radical and persistent reconfiguration of an ecosystem following a disturbance, have been acknowledged by scientists as a very important aspect of the dynamic of ecosystems. However, their consideration in land management planning remains marginal and limited to specific processes and systems. Current research focuses on mathematical modeling and statistical analysis of spatio-temporal data for specific environmental variables. These methods do not fulfill the needs of land managers, who are confronted with a multitude of processes and pressure types and require clear and simple strategies to prevent regime shift or to increase the resilience of their environment. The EU-FP7 CASCADE project is looking at regime shifts of dryland ecosystems in southern Europe and specifically focuses on rangeland and forest systems which are prone to various land degradation threats. One of the aims of the project is to evaluate the impact of different management practices on the dynamic of the environment in a participatory manner, including a multi-stakeholder evaluation of the state of the environment and of the management potential. To achieve this objective we have organized several stakeholder meetings and we have compiled a review of management practices using the WOCAT methodology, which enables merging scientific and land users knowledge. We highlight here the main challenges we have encountered in applying the notion of regime shift to real world socio-ecological systems and in translating related concepts such as tipping points, stable states, hysteresis and resilience to land managers, using concrete examples from CASCADE study sites. Secondly, we explore the advantages of including land users’ knowledge in the scientific understanding of regime shifts. Moreover, we discuss useful alternative concepts and lessons learnt that will allow us to build a participatory method for the assessment of resilient management practices in specific socio-ecological systems and to foster adaptive dryland management.

When looking back to nothing goes back to nothing

Previous research showed that the eyes revisit the location in which the stimulus has been encoded when visual or verbal information is retrieved from memory. A recent study showed that this behavior still occurs 1 week after encoding, suggesting that visual, spatial and linguistic information is tightly associated with the oculomotor trace and stored as an integrated memory representation. However, it is yet unclear whether looking behavior simply remains stable between encoding and recall or whether it changes over time in a more fine-tuned manner. Here, we investigate the time course of looking behavior during recall in multiple sessions across 1 week. Participants encoded visual objects presented in one of the four locations on the computer screen. In five sessions during the week after encoding, they performed on a visual memory recall task. During retrieval, participants looked back to the encoding location, but only in the recall sessions within 1 day of encoding. We discuss different explanations for the temporal dynamics of looking behavior during recall, searching for the role of eye movements in memory.

European summer temperatures since Roman times

The spatial context is critical when assessing present-day climate anomalies, attributing them to potential forcings and making statements regarding their frequency and severity in a long-term perspective. Recent international initiatives have expanded the number of high-quality proxy-records and developed new statistical reconstruction methods. These advances allow more rigorous regional past temperature reconstructions and, in turn, the possibility of evaluating climate models on policy-relevant, spatio-temporal scales. Here we provide a new proxy-based, annually-resolved, spatial reconstruction of the European summer (June–August) temperature fields back to 755 CE based on Bayesian hierarchical modelling (BHM), together with estimates of the European mean temperature variation since 138 BCE based on BHM and composite-plus-scaling (CPS). Our reconstructions compare well with independent instrumental and proxy-based temperature estimates, but suggest a larger amplitude in summer temperature variability than previously reported. Both CPS and BHM reconstructions indicate that the mean 20th century European summer temperature was not significantly different from some earlier centuries, including the 1st, 2nd, 8th and 10th centuries CE. The 1st century (in BHM also the 10th century) may even have been slightly warmer than the 20th century, but the difference is not statistically significant. Comparing each 50 yr period with the 1951–2000 period reveals a similar pattern. Recent summers, however, have been unusually warm in the context of the last two millennia and there are no 30 yr periods in either reconstruction that exceed the mean average European summer temperature of the last 3 decades (1986–2015 CE). A comparison with an ensemble of climate model simulations suggests that the reconstructed European summer temperature variability over the period 850–2000 CE reflects changes in both internal variability and external forcing on multi-decadal time-scales. For pan-European temperatures we find slightly better agreement between the reconstruction and the model simulations with high-end estimates for total solar irradiance. Temperature differences between the medieval period, the recent period and the Little Ice Age are larger in the reconstructions than the simulations. This may indicate inflated variability of the reconstructions, a lack of sensitivity and processes to changes in external forcing on the simulated European climate and/or an underestimation of internal variability on centennial and longer time scales.

Sediment mobilization deposits from episodic subsurface fluid flow—A new tool to reveal long-term earthquake records?

Subsurface fluid flow can be affected by earthquakes; increased spring activity, mud vol- cano eruptions, groundwater fluctuations, changes in geyser frequency, and other forms of altered subsurface fluid flow have been documented during, after, or even prior to seismic shaking. Recently discovered giant pockmarks on the bottom of Lake Neuchâtel, Switzerland, are the lake-floor expression of subsurface fluid flow. They discharge groundwater from the Jura Mountains karstic aquifers and experience episodically increased subsurface fluid flow documented by subsurface sediment mobilization deposits at the levees of the pockmarks. In this study, we present the spatio-temporal distribution of event deposits from these phases of sediment expulsion and of multiple time-correlative mass-transport deposits. We report five striking instances of concurrent multiple subsurface sediment deposits and multiple mass- transport deposits since late glacial times, for which we propose past earthquakes as a trigger. Comparison of this new event catalogue with historic earthquakes and other independent paleoseismic records suggests that initiation of sediment expulsion requires a minimum mac- roseismic intensity of VII. Thus, our study presents for the first time sedimentary deposits resulting from increased subsurface fluid flow as a paleoseismic proxy.

Temporally Coherent Disparity Maps Using CRFs with Fast 4D Filtering

State of the art methods for disparity estimation achieve good results for single stereo frames, but temporal coherence in stereo videos is often neglected. In this paper we present a method to compute temporally coherent disparity maps. We define an energy over whole stereo sequences and optimize their Conditional Random Field (CRF) distributions using mean-field approximation. We introduce novel terms for smoothness and consistency between the left and right views, and perform CRF optimization by fast, iterative spatio-temporal filtering with linear complexity in the total number of pixels. Our results rank among the state of the art while having significantly less flickering artifacts in stereo sequences.

Space-time clustering of childhood cancers in Switzerland: A nationwide study.

The aetiology of childhood cancers remains largely unknown. It has been hypothesized that infections may be involved and that mini-epidemics thereof could result in space-time clustering of incident cases. Most previous studies support spatio-temporal clustering for leukaemia, while results for other diagnostic groups remain mixed. Few studies have corrected for uneven regional population shifts which can lead to spurious detection of clustering. We examined whether there is space-time clustering of childhood cancers in Switzerland identifying cases diagnosed at age <16 years between 1985 and 2010 from the Swiss Childhood Cancer Registry. Knox tests were performed on geocoded residence at birth and diagnosis separately for leukaemia, acute lymphoid leukaemia (ALL), lymphomas, tumours of the central nervous system, neuroblastomas and soft tissue sarcomas. We used Baker's Max statistic to correct for multiple testing and randomly sampled time-, sex- and age-matched controls from the resident population to correct for uneven regional population shifts. We observed space-time clustering of childhood leukaemia at birth (Baker's Max p = 0.045) but not at diagnosis (p = 0.98). Clustering was strongest for a spatial lag of <1 km and a temporal lag of <2 years (Observed/expected close pairs: 124/98; p Knox test = 0.003). A similar clustering pattern was observed for ALL though overall evidence was weaker (Baker's Max p = 0.13). Little evidence of clustering was found for other diagnostic groups (p > 0.2). Our study suggests that childhood leukaemia tends to cluster in space-time due to an etiologic factor present in early life.

Lake-effect snow as the dominant control of mesic-forest distribution in Michigan, USA

1Recent studies demonstrated the sensitivity of northern forest ecosystems to changes in the amount and duration of snow cover at annual to decadal time scales. However, the consequences of snowfall variability remain uncertain for ecological variables operating at longer time scales, especially the distributions of forest communities. 2The Great Lakes region of North America offers a unique setting to examine the long-term effects of variable snowfall on forest communities. Lake-effect snow produces a three-fold gradient in annual snowfall over tens of kilometres, and dramatic edaphic variations occur among landform types resulting from Quaternary glaciations. We tested the hypothesis that these factors interact to control the distributions of mesic (dominated by Acer saccharum, Tsuga canadensis and Fagus grandifolia) and xeric forests (dominated by Pinus and Quercus spp.) in northern Lower Michigan. 3We compiled pre-European-settlement vegetation data and overlaid these data with records of climate, water balance and soil, onto Landtype Association polygons in a geographical information system. We then used multivariate adaptive regression splines to model the abundance of mesic vegetation in relation to environmental controls. 4Snowfall is the most predictive among five variables retained by our model, and it affects model performance 29% more than soil texture, the second most important variable. The abundance of mesic trees is high on fine-textured soils regardless of snowfall, but it increases with snowfall on coarse-textured substrates. Lake-effect snowfall also determines the species composition within mesic forests. The weighted importance of A. saccharum is significantly greater than of T. canadensis or F. grandifolia within the lake-effect snowbelt, whereas T. canadensis is more plentiful outside the snowbelt. These patterns are probably driven by the influence of snowfall on soil moisture, nutrient availability and fire return intervals. 5Our results imply that a key factor dictating the spatio-temporal patterns of forest communities in the vast region around the Great Lakes is how the lake-effect snowfall regime responds to global change. Snowfall reductions will probably cause a major decrease in the abundance of ecologically and economically important species, such as A. saccharum.