Estimating the effects of water-induced shallow landslides on soil erosion

Rainfall induced landslides and soil erosion are part of a complex system of multiple interacting processes, and both are capable of significantly affecting sediment budgets. These sediment mass movements also have the potential to significantly impact on a broad network of ecosystems health, functionality and the services they provide. To support the integrated assessment of these processes it is necessary to develop reliable modelling architectures. This paper proposes a semi-quantitative integrated methodology for a robust assessment of soil erosion rates in data poor regions affected by landslide activity. It combines heuristic, empirical and probabilistic approaches. This proposed methodology is based on the geospatial semantic array programming paradigm and has been implemented on a catchment scale methodology using Geographic Information Systems (GIS) spatial analysis tools and GNU Octave. The integrated data-transformation model relies on a modular architecture, where the information flow among modules is constrained by semantic checks. In order to improve computational reproducibility, the geospatial data transformations implemented in ESRI ArcGis are made available in the free software GRASS GIS. The proposed modelling architecture is flexible enough for future transdisciplinary scenario analysis to be more easily designed. In particular, the architecture might contribute as a novel component to simplify future integrated analyses of the potential impact of wildfires or vegetation types and distributions, on sediment transport from water induced landslides and erosion.Comment: 14 pages, 4 figures, 1 table, published in IEEE Earthzine 2014 Vol. 7 Issue 2, 910137+ 2nd quarter theme. Geospatial Semantic Array Programming. Available: http://www.earthzine.org/?p=91013

Semantic array programming in data-poor environments: assessing the interactions of shallow landslides and soil erosion

This research was conducted with the main objective to better integrate and quantify the role of water-induced shallow landslides within soil erosion processes, with a particular focus on data-poor conditions. To fulfil the objectives, catchment-scale studies on soil erosion by water and shallow landslides were conducted. A semi-quantitative method that combines heuristic, deterministic and probabilistic approaches is here proposed for a robust catchment-scale assessment of landslide susceptibility when available data are scarce. A set of different susceptibility-zonation maps was aggregated exploiting a modelling ensemble. Each susceptibility zonation has been obtained by applying heterogeneous statistical techniques such as logistic regression (LR), relative distance similarity (RDS), artificial neural network (ANN), and two different landslide-susceptibility techniques based on the infinite slope stability model. The good performance of the ensemble model, when compared with the single techniques, make this method suitable to be applied in data-poor areas where the lack of proper calibration and validation data can affect the application of physically based or conceptual models. A new modelling architecture to support the integrated assessment of soil erosion, by incorporating rainfall induced shallow landslides processes in data-poor conditions, was developed and tested in the study area. This proposed methodology is based on the geospatial semantic array programming paradigm. The integrated data-transformation model relies on a modular architecture, where the information flow among modules is constrained by semantic checks. By analysing modelling results within the study catchment, each year, on average, mass movements are responsible for a mean increase in the total soil erosion rate between 22 and 26% over the pre-failure estimate. The post-failure soil erosion rate in areas where landslides occurred is, on average, around 3.5 times the pre-failure value. These results confirm the importance to integrate landslide contribution into soil erosion modelling. Because the estimation of the changes in soil erosion from landslide activity is largely dependent on the quality of available datasets, this methodology broadens the possibility of a quantitative assessment of these effects in data-poor regions

Architecture of a pan-European framework for Integrated Soil Water Erosion Assessment

Soil erosion implications on future food security are gaining global attention because in many areas worldwide there is an imbalance between soil loss and its subsequent deposition. Soil erosion is a complex phenomenon affected by many factors such as climate, topography and land cover (in particular forest resources, natural vegetation and agriculture) while directly influencing water sediment transport, the quality of water resources and water storage loss. A modeling architecture, based on the Revised Universal Soil Loss Equation, is proposed and applied to evaluate and validate at regional scale potential and actual soil water erosion, enabling it to be linked to other involved natural resources. The methodology benefits from the array programming paradigm with semantic constraints (lightweight array behavioural contracts provided by the Mastrave library) to concisely implement models as composition of interoperable modules and to process heterogeneous data.JRC.H.3-Forest Resources and Climat

The histone deacetylase inhibitor JAHA down-regulates pERK and global DNA methylation in MDA-MB231 breast cancer cells

The histone deacetylase inhibitor N1-(ferrocenyl)-N8-hydroxyoctanediamide (JAHA) down-regulates extracellular-signal-regulated kinase (ERK) and its activated form in triple-negative MDA-MB231 breast cancer cells after 18 h and up to 30 h of treatment, and to a lesser extent AKT and phospho-AKT after 30 h and up to 48 h of treatment. Also, DNA methyltransferase 1 (DNMT1), 3b and, to a lesser extent, 3a, downstream ERK targets, were down-regulated already at 18 h with an increase up to 48 h of exposure. Methylation-sensitive restriction arbitrarily-primed (MeSAP) polymerase chain reaction (PCR) analysis confirmed the ability of JAHA to induce genome-wide DNA hypomethylation at 48 h of exposure. Collective data suggest that JAHA, by down-regulating phospho-ERK, impairs DNMT1 and 3b expression and ultimately DNA methylation extent, which may be related to its cytotoxic effect on this cancer cytotype

Interplay Between Grip and Vision in the Monkey Medial Parietal Lobe

We aimed at understanding the relative contribution of visual information and hand shaping to the neuronal activity of medial posterior parietal area V6A, a newly added area in the monkey cortical grasping circuit. Two Macaca fascicularis performed a Reach-to-Grasp task in the dark and in the light, grasping objects of different shapes. We found that V6A contains Visual cells, activated only during grasping in the light; Motor neurons, equally activated during grasping in the dark and in the light; Visuomotor cells, differently activated while grasping in the dark and in the light. Visual, Motor, and Visuomotor neurons were moderately or highly selective during grasping, whereas they reduced their selectivity during object observation without performing grasping. The use of the same experimental design employed in the dorsolateral grasping area AIP by other authors allowed us to compare the grasp-related properties of V6A and AIP. From these data and from the literature a frame emerges with many similarities between medial grasping area V6A and lateral grasping area AIP: both areas update and control prehension, with V6A less sensitive than AIP to fine visual details of the objects to be grasped, but more involved in coordinating reaching and grasping

The "Alzheimer's disease signature": potential perspectives for novel biomarkers

Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neurodegeneration. Biomarkers discovery and validation are considered the key aspects to support clinical diagnosis and provide discriminatory power between different stages of the disorder. A considerable challenge is to integrate different types of data from new potent approach to reach a common interpretation and replicate the findings across studies and populations. Furthermore, long-term clinical follow-up and combined analysis of several biomarkers are among the most promising perspectives to diagnose and manage the disease. The present review will focus on the recent published data providing an updated overview of the main achievements in the genetic and biochemical research of the Alzheimer's disease. We also discuss the latest and most significant results that will help to define a specific disease signature whose validity might be clinically relevant for future AD diagnosis

Targeted sequencing of BRAF by MinION in archival Formalin-Fixed Paraffin-Embedded specimens allows to discriminate between Hairy Cell Leukemia and Hair Cell Leukemia Variant

Targeted sequencing of BRAF by MinION in archival Formalin-Fixed Paraffin-Embedded specimens allows to discriminate between Hairy Cell Leukemia and Hair Cell Leukemia Varian

The BciAi4SLA Project: Towards a User-Centered BCI

The brain–computer interfaces (BCI) are interfaces that put the user in communication with an electronic device based on signals originating from the brain. In this paper, we describe a proof of concept that took place within the context of BciAi4Sla, a multidisciplinary project involving computer scientists, physiologists, biomedical engineers, neurologists, and psychologists with the aim of designing and developing a BCI system following a user-centered approach, involving domain experts and users since initial prototyping steps in a design–test–redesign development cycle. The project intends to develop a software platform able to restore a communication channel in patients who have compromised their communication possibilities due to illness or accidents. The most common case is the patients with amyotrophic lateral sclerosis (ALS). In this paper, we describe the background and the main development steps of the project, also reporting some initial and promising user evaluation results, including real-time performance classification and a proof-of-concept prototype