Are We Using Autoencoders in a Wrong Way?

Autoencoders are certainly among the most studied and used Deep Learning models: the idea behind them is to train a model in order to reconstruct the same input data. The peculiarity of these models is to compress the information through a bottleneck, creating what is called Latent Space. Autoencoders are generally used for dimensionality reduction, anomaly detection and feature extraction. These models have been extensively studied and updated, given their high simplicity and power. Examples are (i) the Denoising Autoencoder, where the model is trained to reconstruct an image from a noisy one; (ii) Sparse Autoencoder, where the bottleneck is created by a regularization term in the loss function; (iii) Variational Autoencoder, where the latent space is used to generate new consistent data. In this article, we revisited the standard training for the undercomplete Autoencoder modifying the shape of the latent space without using any explicit regularization term in the loss function. We forced the model to reconstruct not the same observation in input, but another one sampled from the same class distribution. We also explored the behaviour of the latent space in the case of reconstruction of a random sample from the whole dataset

Seismic response of the geologically complex alluvial valley at the "Europarco Business Park" (Rome - Italy) through instrumental records and numerical modelling

The analysis of the local seismic response in the “Europarco Business Park”, a recently urbanized district of Rome (Italy) developed over the alluvial valley of the “Fosso di Vallerano” stream, is here presented. A high-resolution geological model, reconstructed over 250 borehole log-stratigraphies, shows a complex and heterogeneous setting of both the local Plio- Pleistocene substratum and the Holocene alluvia. The local seismo-stratigraphy is derived by a calibration process performed through 1D numerical modelling, accounting for: i) 55 noise measurements, ii) 10 weak motion records obtained through a temporary velocimetric array during the August 2009 L’Aquila- Gran Sasso seismic sequence and iii) one cross-hole test available from technical report. Based on the reconstructed seismo- stratigraphy, the local seismic bedrock is placed at the top of a gravel layer that is part of the Pleistocene deposits and it does not correspond to the local geological bedrock represented by Plio-Pleistocene marine deposits. 1D amplification functions were derived via numerical modelling along three representative sections that show how in the Fosso di Vallerano area two valleys converge into a single one moving from SE toward NW. The obtained results reveal a main resonance at low frequency (about 0.8 Hz) and several higher resonance modes, related to the local geological setting. Nonlinear effects are also modelled by using strong motion inputs from the official regional dataset and pointed out a general down-shift (up to 0.5 Hz) of the principal modes of resonance as well as an amplitude reduction of the amplification function at frequencies higher than 7 Hz

Molecular typing of Staphylococcus pseudintermedius canine strains by three commonly used techniques

Staphylococcus pseudintermedius is a newly described species of Staphylococcus regarded as the main causative agent of canine pyoderma [1]. S. pseudintermedius infection was recently described in humans. An important feature of this pathogen is the high genetic identity with two other species of staphylococci, namely S. intermedius and S. delphini, which are included all together in the Staphylococcus Intermedius Group (SIG) [2]. This scenario seriously hampers phenotypic differentiation of these three pathogens. Despite this, only in 2008 was described the first molecular protocol for diagnostic identification of   S. pseudintermedius [3]. The aim of this work was to investigate the presence of different biotypes of S. pseudintermedius obtained from clinically relevant cases of pyoderma in dogs using three molecular methods commonly used to type bacteria: the Ribosomal Spacers Amplification (RSA), the Random Amplification of Polymorphic DNA (RAPD) and the Restriction Fragment Length Polymorphism (RFLP). A total of 46 different strains were included in this work. The application of the RSA technique, which was applied here for the first time, identified the presence of S. pseudintermedius, although it did not allow any differentiation between biotypes. The RAPD assay showed a single cluster that assembles all the interested strains that are grouped in three different sub-clusters (Fig. 1). The RFLP technique showed the most discriminative power, providing the opportunity to clearly identify this bacterium. In conclusion, the use of these three different techniques allows to clearly identify S. pseudintermedius and to observe the presence of different biotypes. In future it could be interesting to couple these results with the determination of the antibiotic resistance in order to verify if certain Multi Drug Resistant strains have particular RSA and RAPD profiles

Automation in 3D cellular system in Live-Imaging with Microfluidic Technology CELLviewer®

Differences observed when comparing cell cultures in 2D and 3D is morphological dissimilarity and their evolution over time. Cells grown in a monolayer tend to flatten on the bottom of the plate by adhering and spreading on the horizontal plane without expanding into the vertical dimension; § Mitochondria are involved in crucial cellular tasks controlling the cell cycle and growth such as cell signaling, differentiation, and death. Damage to and subsequent dysfunction of mitochondria play a role in various diseases like diabetes, myopathy and other systemic disorders; § CELLviewer® enables the simultaneous 3D cell culture and live cell imaging as well, featuring microfluidics and time-lapse multicolour epifluorescence microscopy; § Single cell tracking in 3D space is now possible and is combined with subsequent biochemical analyses of individually tracked cells, keeping their identity traceable with CELLviewer® system; q Jurkat (ATCC) Cells grown at 37°C and 5% CO2; q Medium RPMI 1640 soil (Gibco, Life Technologies, Thermo Fisher Scientific), with 2 mM of L-glutamine, 10% FBS, 100 units/mL of penicillin and 100 mg/mL of streptomycin; q MitoGreen (PromoKine, PromoCell) incubated for 20 minutes in the dark at 37°C with MitoGreen 200 mM; q The sample is then piped inside a 50ml Falcon tube closed with a 50ml CELLviewer® DOCK and flowed inside the cartridge chamber; q CELLviewer® automatically captures sample images in Brightfield channel and GFP channel; q ImageJ software was used for image analysis using the Measure function to calculate the diameter of a single cell; q 3D surface plot plug-in to display in 3D the distribution of the intensity of spatial fluorescence; Staining of mitochondria with fluorescent dyes, antibodies or fluorescent molecules can greatly facilitate studies of their function and distribution and the viability of cells in healthy and diseased individuals. The preliminary experience conducted with CELLviewer indicates that this equipment responds to the needs of individual operators as it consists of a synthesis of different integrated tools, which works both with manual and automated control. A microfluidic system has been developed and demonstrated that the 3D model can locate the 3D model spatially, it's possible to carry out experiments in direct time in terms of physiology, toxicology and clinical pharmacology. The entire automated system allows full autonomy and protocol management thanks to the software making the operator free to conduct other work, thus increasing the productivity of his project. In summary, the proposed microfluidic technology can serve as a new platform approach, which has the potential to advance studies at the cellular level. Single-cell Jurkat cells was isolated and imaged for 4 and 7 hours respectively and intensified labelling of the mitochondria and fluidic transport were observed over time. CELLviewer® can obtain detailed images of current cellular morphology with resolution and high-quality data; employing time-lapse imaging can be achieved, the evolution of cells and their 3D morphology

Earthquake-triggered landslide susceptibility in Italy by means of Artificial Neural Network

The use of Artificial Neural Network (ANN) approaches has gained a significant role over the last decade in the field of predicting the distribution of effects triggered by natural forcing, this being particularly relevant for the development of adequate risk mitigation strategies. Among the most critical features of these approaches, there are the accurate geolocation of the available data as well as their numerosity and spatial distribution. The use of an ANN has never been tested at a national scale in Italy, especially in estimating earthquake-triggered landslides susceptibility. The CEDIT catalogue, the most up-to-date national inventory of earthquake-induced ground effects, was adopted to evaluate the efficiency of an ANN to explain the distribution of landslides over the Italian territory. An ex-post evaluation of the ANN-based susceptibility model was also performed, using a sub-dataset of historical data with lower geolocation precision. The ANN training highly performed in terms of spatial prediction, by partitioning the Italian landscape into slope units. The obtained results returned a distribution of potentially unstable slope units with maximum concentrations primarily distributed in the central Apennines and secondarily in the southern and northern Apennines. Moreover, the Alpine sector clearly appeared to be divided into two areas, a western one with relatively low susceptibility to earthquake-triggered landslides and the eastern sector with higher susceptibility. Our work clearly demonstrates that if funds for risk mitigation were allocated only on the basis of rainfall-induced landslide distribution, large areas highly susceptible to earthquake-triggered landslides would be completely ignored by mitigation plans.</p

Разработка агрегатора данных о погоде и прогнозов погоды

Nowadays we frequently can't say which clothes weshould wear tomorrow. The problem is that there is no weather forecast service which can provide us exact weather forecast even for tomorrow, needless to say about further future. Main purpose of this work is to design system that will predict which weather forecast service should be used today to know weather for tomorrow. Authors suggest to evaluate forecasting value of temperature relying on statistics. They describe steps which they need to pass to achieve the purpose. As a result authors want to develop software which can provide weather forecast with higher probability than all existing services

MICROFLUIDIC LIVE-IMAGING WITH CELLVIEWER TECHNOLOGY TO PERFORM BIOTECHNOLOGICAL TASKS

Cells grown in a monolayer tend to flatten in the lower part of the plate adhering to and spreading in the horizontal plane without expanding in the vertical dimension. The result is that cells grown in 2D have a forced apex-basal polarity. Microfluidic Live-Imaging with CellViewer technology is an ideal solution to observe the maintenance of a cell in excellent health, trying to bridge the gap between the 2D and 3D model. In this work we propose to test the system on a single isolated Jurkat cell in the microfluidic cartridge and record the timelapse for 4 hours. After adaptive autofocus, when sliding inside the cartridge chamber, the single cell is tracked under the action of the optics and the 3D rotation was experimentally successfully achieved. Then a single cell viability assessment was used using MitoGreen-dye a fluorescence marker selectively permeable to live cells. ImageJ software was used to: calculate the diameter of a single cell, create fluorescence intensity graphs along a straight line passing through the cell, visualize spatial fluorescence intensity distribution in 3D

Bacteriophage-Host Association in the Phytoplasma Insect Vector Euscelidius variegatus

Insect vectors transmit viruses and bacteria that can cause severe diseases in plants and economic losses due to a decrease in crop production. Insect vectors, like all other organisms, are colonized by a community of various microorganisms, which can influence their physiology, ecology, evolution, and also their competence as vectors. The important ecological meaning of bacteriophages in various ecosystems and their role in microbial communities has emerged in the past decade. However, only a few phages have been described so far in insect microbiomes. The leafhopper Euscelidius variegatus is a laboratory vector of the phytoplasma causing Flavescence dorée, a severe grapevine disease that threatens viticulture in Europe. Here, the presence of a temperate bacteriophage in E. variegatus (named Euscelidius variegatus phage 1, EVP-1) was revealed through both insect transcriptome analyses and electron microscopic observations. The bacterial host was isolated in axenic culture and identified as the bacterial endosymbiont of E. variegatus (BEV), recently assigned to the genus Candidatus Symbiopectobacterium. BEV harbors multiple prophages that become active in culture, suggesting that different environments can trigger different mechanisms, finely regulating the interactions among phages. Understanding the complex relationships within insect vector microbiomes may help in revealing possible microbe influences on pathogen transmission, and it is a crucial step toward innovative sustainable strategies for disease management in agriculture