Ltc1 is an ER-localized sterol transporter and a component of ER-mitochondria and ER-vacuole contacts.

Organelle contact sites perform fundamental functions in cells, including lipid and ion homeostasis, membrane dynamics, and signaling. Using a forward proteomics approach in yeast, we identified new ER-mitochondria and ER-vacuole contacts specified by an uncharacterized protein, Ylr072w. Ylr072w is a conserved protein with GRAM and VASt domains that selectively transports sterols and is thus termed Ltc1, for Lipid transfer at contact site 1. Ltc1 localized to ER-mitochondria and ER-vacuole contacts via the mitochondrial import receptors Tom70/71 and the vacuolar protein Vac8, respectively. At mitochondria, Ltc1 was required for cell viability in the absence of Mdm34, a subunit of the ER-mitochondria encounter structure. At vacuoles, Ltc1 was required for sterol-enriched membrane domain formation in response to stress. Increasing the proportion of Ltc1 at vacuoles was sufficient to induce sterol-enriched vacuolar domains without stress. Thus, our data support a model in which Ltc1 is a sterol-dependent regulator of organelle and cellular homeostasis via its dual localization to ER-mitochondria and ER-vacuole contact sites

3D MODELING WITH PHOTOGRAMMETRY BY UAVS AND MODEL QUALITY VERIFICATION

This paper deals with a test lead by Geomatics laboratory (DICEAM, Mediterranea University of Reggio Calabria), concerning the application of UAV photogrammetry for survey, monitoring and checking. The study case relies with the surroundings of the Department of Agriculture Sciences. In the last years, such area was interested by landslides and survey activities carried out to take the phenomenon under control. For this purpose, a set of digital images were acquired through a UAV equipped with a digital camera and GPS. Successively, the processing for the production of a 3D georeferenced model was performed by using the commercial software Agisoft PhotoScan. Similarly, the use of a terrestrial laser scanning technique allowed to product dense cloud and 3D models of the same area. To assess the accuracy of the UAV-derived 3D models, a comparison between image and range-based methods was performed

UAV AND COMPUTER VISION, DETECTION OF INFRASTRUCTURE LOSSES AND 3D MODELING

The degradation of buildings, or rather the decline of their initial performances following external agents both natural (cold-thaw, earthquake, salt, etc.) and artificial (industrial field, urban setting, etc.), in the years lead to the necessity of developing Non-Destructive Testing (NDT) intended to give useful information for an explanation of a potential deterioration without damaging the state of buildings. An accurate examination of damages, of the repeat of cracks in condition of similar stress, indicate the existence of principles that control the creation of these events. There is no doubt that a precise visual analysis is at the bottom of a correct evaluation of the building. This paper deals with the creation of 3D models based on the capture of digital images, through autopilot flight UAV, for civil buildings situated on the area of Reggio Calabria. The following elaboration is done thanks to the use of commercial software, based on specific algorithms of the Structure from Motion (SfM) technique. SfM represents an important progress in the aerial and terrestrial survey field obtaining results, in terms of time and quality, comparable to those achievable through more traditional data capture methodologies

Sterol transporters at membrane contact sites regulate TORC1 and TORC2 signaling.

Membrane contact sites (MCSs) function to facilitate the formation of membrane domains composed of specialized lipids, proteins, and nucleic acids. In cells, membrane domains regulate membrane dynamics and biochemical and signaling pathways. We and others identified a highly conserved family of sterol transport proteins (Ltc/Lam) localized at diverse MCSs. In this study, we describe data indicating that the yeast family members Ltc1 and Ltc3/4 function at the vacuole and plasma membrane, respectively, to create membrane domains that partition upstream regulators of the TORC1 and TORC2 signaling pathways to coordinate cellular stress responses with sterol homeostasis

Triggering mechanisms of static stress on Mount Etna volcano. An application of the boundary element method

In the last thirty years, numerous eruptions and associated deformation episodes have occurred at Mt. Etna volcano. Datasets recorded by continuous monitoring of these episodes provide a unique opportunity to study the relationships between volcanism, flank instability and faulting activity. We have investigated the stress triggering mechanism between magmatic reservoir inflation, intrusive episodes and flank dynamics. Using three-dimensional numerical Boundary Elements Models we simulated volcano-tectonic events and calculated Coulomb stress changes. Using this modeling approach, we analyzed four realistic scenarios that are representative of recent kinematics occurring at Mt. Etna. The main results obtained highlight how (1) the inflation of a deep spherical magma source transfers elastic stress to a sliding plane and faults (2) the opening of the NE Rift and S Rift (to a less efficient extent) favor movements of the instable sector and may encourage seismicity on the eastern flank faults, and (3) flank instability may trigger the uprising of magma. Defining the effects of the elastic stress transfer and relationships among the main forces acting on volcano, may help to forecast possible eruption scenarios during future episodes of unrest at Mount Etna and provide an important tool for decision makers during volcanic emergencies involving the highly populated areas of the volcano

LASER SCANNER TECHNOLOGY, GROUND-PENETRATING RADAR AND AUGMENTED REALITY FOR THE SURVEY AND RECOVERY OF ARTISTIC, ARCHAEOLOGICAL AND CULTURAL HERITAGE

In this study, using technologies such as laser scanner and GPR it was desired to see their potential in the cultural heritage. Also with regard to the processing part we are compared the results obtained by the various commercial software and algorithms developed and implemented in Matlab. Moreover, Virtual Reality and Augmented Reality allow integrating the real world with historical-artistic information, laser scanners and georadar (GPR) data and virtual objects, virtually enriching it with multimedia elements, graphic and textual information accessible through smartphones and tablets

fem and ann combined approach for predicting pressure source parameters at etna volcano

Abstract. A hybrid approach for forward and inverse geophysical modeling, based on Artificial Neural Networks (ANN) and Finite Element Method (FEM), is proposed in order to properly identify the parameters of volcanic pressure sources from geophysical observations at ground surface. The neural network is trained and tested with a set of patterns obtained by the solutions of numerical models based on FEM. The geophysical changes caused by magmatic pressure sources were computed developing a 3-D FEM model with the aim to include the effects of topography and medium heterogeneities at Etna volcano. ANNs are used to interpolate the complex non linear relation between geophysical observations and source parameters both for forward and inverse modeling. The results show that the combination of neural networks and FEM is a powerful tool for a straightforward and accurate estimation of source parameters in volcanic regions

LASER SCANNER TECHNOLOGY, GROUND-PENETRATING RADAR AND AUGMENTED REALITY FOR THE SURVEY AND RECOVERY OF ARTISTIC, ARCHAEOLOGICAL AND CULTURAL HERITAGE

In this study, using technologies such as laser scanner and GPR it was desired to see their potential in the cultural heritage. Also with regard to the processing part we are compared the results obtained by the various commercial software and algorithms developed and implemented in Matlab. Moreover, Virtual Reality and Augmented Reality allow integrating the real world with historical-artistic information, laser scanners and georadar (GPR) data and virtual objects, virtually enriching it with multimedia elements, graphic and textual information accessible through smartphones and tablets

FEM and ANN combined approach for predicting pressure source

A hybrid approach for forward and inverse geophysical modeling, based on Artificial Neural Networks (ANN) and Finite Element Method (FEM), is proposed in order to properly identify the parameters of volcanic pressure sources from geophysical observations at ground surface. The neural network is trained and tested with a set of patterns obtained by the solutions of numerical models based on FEM. The geophysical changes caused by magmatic pressure sources were computed developing a 3-D FEM model with the aim to include the effects of topography and medium heterogeneities at Etna volcano. ANNs are used to interpolate the complex non linear relation between geophysical observations and source parameters both for forward and inverse modeling. The results show that the combination of neural networks and FEM is a powerful tool for a straightforward and accurate estimation of source parameters in volcanic regions

Automatic Classification of eruptive events by the VAMOS system

An automatic system named VAMOS (Volcanic Activity MOnitoring System) for monitoring volcanic activity at Mt. Etna and Stromboli volcanoes, is at the present under test at the data collection center at IIV (Istituto Internazionale di Vulcanologia, CNR, Catania). This system allows automatic recognition of volcanic activity by on-line processing of images collected by the surveillance cameras positioned close to the summit crater of two above mentioned volcanoes which are worldwide known to be characterized by a persistent eruptive activity. Based on this automatic system, a new software tool to extract quantitative information from collected images is now under developing. Several tasks have been planned to solve by using this tool such as the automatic classification of recorded events and the computation of relaxed energy based on stereo-vision and thermal images. One of the first result of the undertaken research activity has been the automatic classification of the type of volcanic events and the localization of the eruptive event