Multi-source composite kernels for urban image classification

This letter presents advanced classification methods for very high resolution images. Efficient multisource information, both spectral and spatial, is exploited through the use of composite kernels in support vector machines. Weighted summations of kernels accounting for separate sources of spectral and spatial information are analyzed and compared to classical approaches such as pure spectral classification or stacked approaches using all the features in a single vector. Model selection problems are addressed, as well as the importance of the different kernels in the weighted summation.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Cellular mechanisms underlying the regulation of dendritic development by hepatocyte growth factor.

Acquisition of a mature dendritic morphology is critical for neural information processing. In particular, hepatocyte growth factor (HGF) controls dendritic arborization during brain development. However, the cellular mechanisms underlying the effects of HGF on dendritic growth remain elusive. Here, we show that HGF increases dendritic length and branching of rat cortical neurons through activation of the mitogen-activated protein kinase (MAPK) signaling pathway. Activation of MAPK by HGF leads to the rapid and transient phosphorylation of cAMP response element-binding protein (CREB), a key step necessary for the control of dendritic development by HGF. In addition to CREB phosphorylation, regulation of dendritic growth by HGF requires the interaction between CREB and CREB-regulated transcription coactivator 1 (CRTC1), as expression of a mutated form of CREB unable to bind CRTC1 completely abolished the effects of HGF on dendritic morphology. Treatment of cortical neurons with HGF in combination with brain-derived neurotrophic factor (BDNF), a member of the neurotrophin family that regulates dendritic development via similar mechanisms, showed additive effects on MAPK activation, CREB phosphorylation and dendritic growth. Collectively, these results support the conclusion that regulation of cortical dendritic morphology by HGF is mediated by activation of the MAPK pathway, phosphorylation of CREB and interaction of CREB with CRTC1.

Multi-slice three-dimensional myocardial strain tensor quantification using zHARP.

In this article we propose a novel method for calculating cardiac 3-D strain. The method requires the acquisition of myocardial short-axis (SA) slices only and produces the 3-D strain tensor at every point within every pair of slices. Three-dimensional displacement is calculated from SA slices using zHARP which is then used for calculating the local displacement gradient and thus the local strain tensor. There are three main advantages of this method. First, the 3-D strain tensor is calculated for every pixel without interpolation; this is unprecedented in cardiac MR imaging. Second, this method is fast, in part because there is no need to acquire long-axis (LA) slices. Third, the method is accurate because the 3-D displacement components are acquired simultaneously and therefore reduces motion artifacts without the need for registration. This article presents the theory of computing 3-D strain from two slices using zHARP, the imaging protocol, and both phantom and in-vivo validation.

Education and Training in Forensic Intelligence: a New Challenge

From recent calls for positioning forensic scientists within the criminal justice system, but also policing and intelligence missions, this paper emphasizes the need for the development of educational and training programs in the area of forensic intelligence, It is argued that an imbalance exists between perceived and actual understanding of forensic intelligence by police and forensic science managers, and that this imbalance can only be overcome through education. The challenge for forensic intelligence education and training is therefore to devise programs that increase forensic intelligence awareness, firstly for managers to help prevent poor decisions on how to develop information processing. Two recent European courses are presented as examples of education offerings, along with lessons learned and suggested paths forward. It is concluded that the new focus on forensic intelligence could restore a pro-active approach to forensic science, better quantify its efficiency and let it get more involved in investigative and managerial decisions. A new educational challenge is opened to forensic science university programs around the world: to refocus criminal trace analysis on a more holistic security problem solving approach.

Structured sparsity for spatially coherent fibre orientation estimation in diffusion MRI.

We propose a novel formulation to solve the problem of intra-voxel reconstruction of the fibre orientation distribution function (FOD) in each voxel of the white matter of the brain from diffusion MRI data. The majority of the state-of-the-art methods in the field perform the reconstruction on a voxel-by-voxel level, promoting sparsity of the orientation distribution. Recent methods have proposed a global denoising of the diffusion data using spatial information prior to reconstruction, while others promote spatial regularisation through an additional empirical prior on the diffusion image at each q-space point. Our approach reconciles voxelwise sparsity and spatial regularisation and defines a spatially structured FOD sparsity prior, where the structure originates from the spatial coherence of the fibre orientation between neighbour voxels. The method is shown, through both simulated and real data, to enable accurate FOD reconstruction from a much lower number of q-space samples than the state of the art, typically 15 samples, even for quite adverse noise conditions.

Functional importance of cardiac enhancer-associated noncoding RNAs in heart development and disease.

The key information processing units within gene regulatory networks are enhancers. Enhancer activity is associated with the production of tissue-specific noncoding RNAs, yet the existence of such transcripts during cardiac development has not been established. Using an integrated genomic approach, we demonstrate that fetal cardiac enhancers generate long noncoding RNAs (lncRNAs) during cardiac differentiation and morphogenesis. Enhancer expression correlates with the emergence of active enhancer chromatin states, the initiation of RNA polymerase II at enhancer loci and expression of target genes. Orthologous human sequences are also transcribed in fetal human hearts and cardiac progenitor cells. Through a systematic bioinformatic analysis, we identified and characterized, for the first time, a catalog of lncRNAs that are expressed during embryonic stem cell differentiation into cardiomyocytes and associated with active cardiac enhancer sequences. RNA-sequencing demonstrates that many of these transcripts are polyadenylated, multi-exonic long noncoding RNAs. Moreover, knockdown of two enhancer-associated lncRNAs resulted in the specific downregulation of their predicted target genes. Interestingly, the reactivation of the fetal gene program, a hallmark of the stress response in the adult heart, is accompanied by increased expression of fetal cardiac enhancer transcripts. Altogether, these findings demonstrate that the activity of cardiac enhancers and expression of their target genes are associated with the production of enhancer-derived lncRNAs.

Pom1 gradient buffering through intermolecular auto-phosphorylation.

Concentration gradients provide spatial information for tissue patterning and cell organization, and their robustness under natural fluctuations is an evolutionary advantage. In rod-shaped Schizosaccharomyces pombe cells, the DYRK-family kinase Pom1 gradients control cell division timing and placement. Upon dephosphorylation by a Tea4-phosphatase complex, Pom1 associates with the plasma membrane at cell poles, where it diffuses and detaches upon auto-phosphorylation. Here, we demonstrate that Pom1 auto-phosphorylates intermolecularly, both in vitro and in vivo, which confers robustness to the gradient. Quantitative imaging reveals this robustness through two system's properties: The Pom1 gradient amplitude is inversely correlated with its decay length and is buffered against fluctuations in Tea4 levels. A theoretical model of Pom1 gradient formation through intermolecular auto-phosphorylation predicts both properties qualitatively and quantitatively. This provides a telling example where gradient robustness through super-linear decay, a principle hypothesized a decade ago, is achieved through autocatalysis. Concentration-dependent autocatalysis may be a widely used simple feedback to buffer biological activities.

Call for uniform neuropsychological assessment after aneurysmal subarachnoid hemorrhage: Swiss recommendations.

BACKGROUND: In a high proportion of patients with favorable outcome after aneurysmal subarachnoid hemorrhage (aSAH), neuropsychological deficits, depression, anxiety, and fatigue are responsible for the inability to return to their regular premorbid life and pursue their professional careers. These problems often remain unrecognized, as no recommendations concerning a standardized comprehensive assessment have yet found entry into clinical routines. METHODS: To establish a nationwide standard concerning a comprehensive assessment after aSAH, representatives of all neuropsychological and neurosurgical departments of those eight Swiss centers treating acute aSAH have agreed on a common protocol. In addition, a battery of questionnaires and neuropsychological tests was selected, optimally suited to the deficits found most prevalent in aSAH patients that was available in different languages and standardized. RESULTS: We propose a baseline inpatient neuropsychological screening using the Montreal Cognitive Assessment (MoCA) between days 14 and 28 after aSAH. In an outpatient setting at 3 and 12 months after bleeding, we recommend a neuropsychological examination, testing all relevant domains including attention, speed of information processing, executive functions, verbal and visual learning/memory, language, visuo-perceptual abilities, and premorbid intelligence. In addition, a detailed assessment capturing anxiety, depression, fatigue, symptoms of frontal lobe affection, and quality of life should be performed. CONCLUSIONS: This standardized neuropsychological assessment will lead to a more comprehensive assessment of the patient, facilitate the detection and subsequent treatment of previously unrecognized but relevant impairments, and help to determine the incidence, characteristics, modifiable risk factors, and the clinical course of these impairments after aSAH.

The empirical assessment of agency accountability: A regime approach and an application to the German Bundesnetzagentur

Regulation has in many cases been delegated to independent agencies, which has led to the question of how democratic accountability of these agencies is ensured. There are few empirical approaches to agency accountability. We offer such an approach, resting upon three propositions. First, we scrutinize agency accountability both de jure (accountability is ensured by formal rights of accountability 'fora' to receive information and impose consequences) and de facto (the capability of fora to use these rights depends on resources and decision costs that affect the credibility of their sanctioning capacity). Second, accountability must be evaluated separately at political, operational and managerial levels. And third, at each level accountability is enacted by a system of several (partially) interdependent fora, forming together an accountability regime. The proposed framework is applied to the case of the German Bundesnetzagentur's accountability regime, which shows its suitability for empirical purposes. Regulatory agencies are often considered as independent, yet accountable. This article provides a realistic framework for the study of accountability 'regimes' in which they are embedded. It emphasizes the need to identify the various actors (accountability fora) to which agencies are formally accountable (parliamentary committees, auditing bodies, courts, and so on) and to consider possible relationships between them. It argues that formal accountability 'on paper', as defined in official documents, does not fully account for de facto accountability, which depends on the resources possessed by the fora (mainly information-processing and decision-making capacities) and the credibility of their sanctioning capacities. The article applies this framework to the German Bundesnetzagentur.

Rockfall detection from LIDAR point clouds: A clustering approach using R

The analysis of rockfall characteristics and spatial distribution is fundamental to understand and model the main factors that predispose to failure. In our study we analysed LiDAR point clouds aiming to: (1) detect and characterise single rockfalls; (2) investigate their spatial distribution. To this end, different cluster algorithms were applied: 1a) Nearest Neighbour Clutter Removal (NNCR) in combination with the Expectation?Maximization (EM) in order to separate feature points from clutter; 1b) a density based algorithm (DBSCAN) was applied to isolate the single clusters (i.e. the rockfall events); 2) finally we computed the Ripley's K-function to investigate the global spatial pattern of the extracted rockfalls. The method allowed proper identification and characterization of more than 600 rockfalls occurred on a cliff located in Puigcercos (Catalonia, Spain) during a time span of six months. The spatial distribution of these events proved that rockfall were clustered distributed at a welldefined distance-range. Computations were carried out using R free software for statistical computing and graphics. The understanding of the spatial distribution of precursory rockfalls may shed light on the forecasting of future failures.

Maturation and Functional Integration of New Granule Cells into the Adult Hippocampus.

The adult hippocampus generates functional dentate granule cells (GCs) that release glutamate onto target cells in the hilus and cornus ammonis (CA)3 region, and receive glutamatergic and γ-aminobutyric acid (GABA)ergic inputs that tightly control their spiking activity. The slow and sequential development of their excitatory and inhibitory inputs makes them particularly relevant for information processing. Although they are still immature, new neurons are recruited by afferent activity and display increased excitability, enhanced activity-dependent plasticity of their input and output connections, and a high rate of synaptogenesis. Once fully mature, new GCs show all the hallmarks of neurons generated during development. In this review, we focus on how developing neurons remodel the adult dentate gyrus and discuss key aspects that illustrate the potential of neurogenesis as a mechanism for circuit plasticity and function.