Earthquake-induced landslide-susceptibility mapping using an artificial neural network

The purpose of this study was to apply and verify landslide-susceptibility analysis techniques using an artificial neural network and a Geographic Information System (GIS) applied to Baguio City, Philippines. The 16 July 1990 earthquake-induced landslides were studied. Landslide locations were identified from interpretation of aerial photographs and field survey, and a spatial database was constructed from topographic maps, geology, land cover and terrain mapping units. Factors that influence landslide occurrence, such as slope, aspect, curvature and distance from drainage were calculated from the topographic database. Lithology and distance from faults were derived from the geology database. Land cover was identified from the topographic database. Terrain map units were interpreted from aerial photographs. These factors were used with an artificial neural network to analyze landslide susceptibility. Each factor weight was determined by a back-propagation exercise. Landslide-susceptibility indices were calculated using the back-propagation weights, and susceptibility maps were constructed from GIS data. The susceptibility map was compared with known landslide locations and verified. The demonstrated prediction accuracy was 93.20%

A green prospective for learned post-processing in sparse-view tomographic reconstruction

Deep Learning is developing interesting tools that are of great interest for inverse imaging applications. In this work, we consider a medical imaging reconstruction task from subsampled measurements, which is an active research field where Convolutional Neural Networks have already revealed their great potential. However, the commonly used architectures are very deep and, hence, prone to overfitting and unfeasible for clinical usages. Inspired by the ideas of the green AI literature, we propose a shallow neural network to perform efficient Learned Post-Processing on images roughly reconstructed by the filtered backprojection algorithm. The results show that the proposed inexpensive network computes images of comparable (or even higher) quality in about one-fourth of time and is more robust than the widely used and very deep ResUNet for tomographic reconstructions from sparse-view protocols

Wave Celerity in Hydraulic Transients Computation for CIPP-Rehabilitated Pipes

[Abstract] Most of the water pipe infrastructure is outdated; therefore, frequent maintenance and repair works are required. To speed up the rehabilitation work and to have a more sustainable and efficient approach, trenchless methodologies have been developed in the last decades. One of the most cost-effective trenchless methods is the so-called Cured in Place Pipeline (CIPP) method, in which a resin-impregnated liner is pulled or inverted inside the host pipe and, when cured, it restores the old pipe structural and mechanical integrity. The aim of this study is to analyse the effects of the presence of a CIPP liner in a deteriorated pipe during unsteady flow for compressible fluids. In particular, the paper deals with a new formulation to compute the celerity of the wave which produces the overpressures, when the pipe wall is composed of both the host (old) pipe and the new liner, whose thickness depends on the required mechanical characteristics. The problem is strictly dependent on the mechanical properties of the liner. In order to obtain the new formula for celerity, the linear elastic problem for multi-layered pipes has been solved. The theoretical results have been validated by performing numerical simulation analysis using a Boundary Element model, with the software BEASY™. The resulting circumferential strain is integrated in the continuity equation, deriving the new formula to compute the wave celerity. The values of the celerity are dependent on the thickness and on the elastic properties of the liner. The behaviour of several combinations of thickness of the liner and Young’s modulus values has been studied and the results have been critically shown in the paper

Does initial spacing influence crown and hydraulic architecture of Eucalyptus marginata?

Long-term declines in rainfall in south-western Australia have resulted in increased interest in the hydraulic characteristics of jarrah (Eucalyptus marginata Donn ex Smith) forest established in the region's drinking water catchments on rehabilitated bauxite mining sites. We hypothesized that in jarrah forest established on rehabilitated mine sites: (1) leaf area index (L) is independent of initial tree spacing; and (2) more densely planted trees have less leaf area for the same leaf mass, or the same sapwood area, and have denser sapwood. Initial stand densities ranged from about 600 to 9000 stems ha -1, and trees were 18 years old at the time of sampling. Leaf area index was unaffected by initial stand density, except in the most sparsely stocked stands where L was 1.2 compared with 2.0-2.5 in stands at other spacings. The ratio of leaf area to sapwood area (Al:As) was unaffected by tree spacing or tree size and was 0.2 at 1.3 m height and 0.25 at the crown base. There were small increases in sapwood density and decreases in leaf specific area with increased spacing. Tree diameter or basal area was a better predictor of leaf area than sapwood area. At the stand scale, basal area was a good predictor of L (r2 = 0.98, n = 15) except in the densest stands. We conclude that the hydraulic attributes of this forest type are largely independent of initial tree spacing, thus simplifying parameterization of stand and catchment water balance models. © 2008 Heron Publishing

Dynamic association between perfusion and white matter integrity across time since injury in Veterans with history of TBI.

ObjectiveCerebral blood flow (CBF) plays a critical role in the maintenance of neuronal integrity, and CBF alterations have been linked to deleterious white matter changes. Although both CBF and white matter microstructural alterations have been observed within the context of traumatic brain injury (TBI), the degree to which these pathological changes relate to one another and whether this association is altered by time since injury have not been examined. The current study therefore sought to clarify associations between resting CBF and white matter microstructure post-TBI.Methods37 veterans with history of mild or moderate TBI (mmTBI) underwent neuroimaging and completed health and psychiatric symptom questionnaires. Resting CBF was measured with multiphase pseudocontinuous arterial spin labeling (MPPCASL), and white matter microstructural integrity was measured with diffusion tensor imaging (DTI). The cingulate cortex and cingulum bundle were selected as a priori regions of interest for the ASL and DTI data, respectively, given the known vulnerability of these regions to TBI.ResultsRegression analyses controlling for age, sex, and posttraumatic stress disorder (PTSD) symptoms revealed a significant time since injury × resting CBF interaction for the left cingulum (p < 0.005). Decreased CBF was significantly associated with reduced cingulum fractional anisotropy (FA) in the chronic phase; however, no such association was observed for participants with less remote TBI.ConclusionsOur results showed that reduced CBF was associated with poorer white matter integrity in those who were further removed from their brain injury. Findings provide preliminary evidence of a possible dynamic association between CBF and white matter microstructure that warrants additional consideration within the context of the negative long-term clinical outcomes frequently observed in those with history of TBI. Additional cross-disciplinary studies integrating multiple imaging modalities (e.g., DTI, ASL) and refined neuropsychiatric assessment are needed to better understand the nature, temporal course, and dynamic association between brain changes and clinical outcomes post-injury

Towards Designing a Knowledge Sharing System for Higher Learning Institutions in the UAE Based on the Social Feature Framework

Numerous ICT instruments, such as communication tools, social media platforms, and collaborative software, bolster and facilitate knowledge sharing activities. Determining the vital success factors for knowledge sharing within its unique context is argued to be essential before implementing it. Therefore, it is imperative to define domain-specific critical success factors when envisioning the design of a knowledge sharing system. This research paper introduces the blueprint for an Academic Knowledge Sharing System (AKSS), rooted in an essential success framework tailored to knowledge sharing to deploy within an academic institution. In this regard, an extensive exploration of the relevant literature led to the formulation of the research hypothesis that guided the construction of a questionnaire targeting university students through the online platform Pollfish, utilizing a quantitative approach to investigate, while the data collected was analyzed using SPSS version 22. The study unveils critical factors, including encouragement, acknowledgment, a reward system, fostering a knowledge sharing culture, and leading by example, contributing to developing the knowledge sharing framework. Furthermore, the study illustrates how this framework seamlessly integrated into the design, implementation, and execution of the Academic Knowledge Sharing System (AKSS)