Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices

Neurons cultured in vitro on MicroElectrode Array (MEA) devices connect to each other, forming a network. To study electrophysiological activity and long term plasticity effects, long period recording and spike sorter methods are needed. Therefore, on-line and real time analysis, optimization of memory use and data transmission rate improvement become necessary. We developed an algorithm for amplitude-threshold spikes detection, whose performances were verified with (a) statistical analysis on both simulated and real signal and (b) Big O Notation. Moreover, we developed a PCA-hierarchical classifier, evaluated on simulated and real signal. Finally we proposed a spike detection hardware design on FPGA, whose feasibility was verified in terms of CLBs number, memory occupation and temporal requirements; once realized, it will be able to execute on-line detection and real time waveform analysis, reducing data storage problems

The Overlooked Potential of Generalized Linear Models in Astronomy - I: Binomial Regression

Revealing hidden patterns in astronomical data is often the path to fundamental scientific breakthroughs; meanwhile the complexity of scientific inquiry increases as more subtle relationships are sought. Contemporary data analysis problems often elude the capabilities of classical statistical techniques, suggesting the use of cutting edge statistical methods. In this light, astronomers have overlooked a whole family of statistical techniques for exploratory data analysis and robust regression, the so-called Generalized Linear Models (GLMs). In this paper -- the first in a series aimed at illustrating the power of these methods in astronomical applications -- we elucidate the potential of a particular class of GLMs for handling binary/binomial data, the so-called logit and probit regression techniques, from both a maximum likelihood and a Bayesian perspective. As a case in point, we present the use of these GLMs to explore the conditions of star formation activity and metal enrichment in primordial minihaloes from cosmological hydro-simulations including detailed chemistry, gas physics, and stellar feedback. We predict that for a dark mini-halo with metallicity $\approx 1.3 \times 10^{-4} Z_{\bigodot}$, an increase of $1.2 \times 10^{-2}$ in the gas molecular fraction, increases the probability of star formation occurrence by a factor of 75%. Finally, we highlight the use of receiver operating characteristic curves as a diagnostic for binary classifiers, and ultimately we use these to demonstrate the competitive predictive performance of GLMs against the popular technique of artificial neural networks.Comment: 20 pages, 10 figures, 3 tables, accepted for publication in Astronomy and Computin

Cool Core Clusters from Cosmological Simulations

We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our simulations include the effects of stellar and AGN feedback and are based on an improved version of the smoothed particle hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, the primary diagnostic we used to classify the degree of cool-coreness of clusters, and on the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of cool-core systems, to nearly flat core isentropic profiles, characteristic of non-cool-core systems. Using observational criteria to distinguish between the two classes of objects, we find that they occur in similar proportions in both simulations and in observations. Furthermore, we also find that simulated cool-core clusters have profiles of iron abundance that are steeper than those of NCC clusters, which is also in agreement with observational results. We show that the capability of our simulations to generate a realistic cool-core structure in the cluster population is due to AGN feedback and artificial thermal diffusion: their combined action allows us to naturally distribute the energy extracted from super-massive black holes and to compensate for the radiative losses of low-entropy gas with short cooling time residing in the cluster core.Comment: 6 pages, 4 figures, accepted in ApJL, v2 contains some modifications on the text (results unchanged

5kWe+5kWt reformer-PEMFC energy generator from bioethanol first data on the fuel processor from a demonstrative project

A power unit constituted by a reformer section, a H 2 purification section and a fuel cell stack is being tested c/o the Dept. of Physical Chemistry and Electrochemistry of Universit\ue0 degli Studi di Milano, on the basis of a collaboration with HELBIO S.A. Hydrogen and Energy Production Systems, Patras (Greece), supplier of the unit, and some sponsors (Linea Energia S.p.A., Parco Tecnologico Padano and Provincia di Lodi, Italy). The system size allows to co-generate 5 kW e (220 V, 50 Hz a.c.) + 5 kW t (hot water at 65\ub0C) as peak output. Bioethanol, obtainable by different non-food-competitive biomass, is transformed into syngas by a pre-reforming and reforming reactors couple and the reformate is purified from CO to a concentration below 20 ppmv, suitable to feed a proton exchange membrane fuel cell (PEMFC) stack that will be integrated in the fuel processor in a second step of the experimentation. This result is achieved by feeding the reformate to two water gas shift reactors, connected in series and operating at high and low temperature, respectively. CO concentration in the outcoming gas is ca. 0.4 vol% and the final CO removal to meet the specifications is accomplished by two methanation reactors in series. The second methanation step acts merely as a guard, since ca. 15 ppmv of CO are obtained already after the first reactor. The goals of the present project are to test the integrated fuel processor, to check the effectiveness of the proposed technology and to suggest possible adequate improvements

Investigation of TiCr Hydrogen Storage Alloy

A new reversible hydrogen storage material, based on TiCr metal alloy, is proposed. Cr and Ti were mixed and melted in a final atomic ratio of 1,78. Chemical-physical characterisations, in terms of XRD and SEM-EDX, were performed. The quantification of Laves phases was performed through Rietveld refinements. The atomic Cr/Ti ratio was determined by EDX analysis and 1,71 was obtained. The H2 sorption/desorption measurements by Sievert apparatus were carried out. After different tests varying temperature and pressure, a protocol measurement was established; and a H2 sorption value of 0,4 wt% at 200 °C/10 bar with a fast kinetic at 5 bar (Dwt% of about 0,3 wt%) were obtained. Hydrogen desorption measurements performed in the same conditions of T confirmed a totally reversible trend. A confirm of metal hydride formation was recorded by XRD, in fact, comparing X-Ray patterns before and after volumetric tests a notable difference was recorded

Design, simulation, and fabrication of a three-dimensional printed pump mimicking the left ventricle motion

The development of accurate replicas of the circulatory and cardiac system is fundamental for a deeper understanding of cardiovascular diseases and the testing of new devices. Although numerous works concerning mock circulatory loops are present in the current state of the art, still some limitations are present. In particular, a pumping system able to reproduce the left ventricle motion and completely compatible with the magnetic resonance environment to permit the four-dimensional flow monitoring is still missing. The aim of this work was to evaluate the feasibility of an actuator suitable for cardiovascular mock circuits. Particular attention was given to the ability to mimic the left ventricle dynamics including both compression and twisting with the magnetic resonance compatibility. In our study, a left ventricle model to be actuated through vacuum was designed. The realization of the system was evaluated with finite element analysis of different design solutions. After the in silico evaluation phase, the most suitable design in terms of physiological values reproduction was fabricated through three-dimensional printing for in vitro validation. A pneumatic experimental setup was developed to evaluate the pump performances in terms of actuation, in particular ventricle radial and longitudinal displacement, twist rotation, and ejection fraction. The study demonstrated the feasibility of a custom pneumatic pump for mock circulatory loops able to reproduce the physiological ventricle movement and completely suitable for the magnetic resonance environment

Cosmological hydrodynamical simulations of galaxy clusters: X-ray scaling relations and their evolution

We analyse cosmological hydrodynamical simulations of galaxy clusters to study the X-ray scaling relations between total masses and observable quantities such as X-ray luminosity, gas mass, X-ray temperature, and $Y_{X}$. Three sets of simulations are performed with an improved version of the smoothed particle hydrodynamics GADGET-3 code. These consider the following: non-radiative gas, star formation and stellar feedback, and the addition of feedback by active galactic nuclei (AGN). We select clusters with $M_{500} > 10^{14} M_{\odot} E(z)^{-1}$, mimicking the typical selection of Sunyaev-Zeldovich samples. This permits to have a mass range large enough to enable robust fitting of the relations even at $z \sim 2$. The results of the analysis show a general agreement with observations. The values of the slope of the mass-gas mass and mass-temperature relations at $z=2$ are 10 per cent lower with respect to $z=0$ due to the applied mass selection, in the former case, and to the effect of early merger in the latter. We investigate the impact of the slope variation on the study of the evolution of the normalization. We conclude that cosmological studies through scaling relations should be limited to the redshift range $z=0-1$, where we find that the slope, the scatter, and the covariance matrix of the relations are stable. The scaling between mass and $Y_X$ is confirmed to be the most robust relation, being almost independent of the gas physics. At higher redshifts, the scaling relations are sensitive to the inclusion of AGNs which influences low-mass systems. The detailed study of these objects will be crucial to evaluate the AGN effect on the ICM.Comment: 24 pages, 11 figures, 5 tables, replaced to match accepted versio

In vivo biodistribution and lifetime analysis of cy5.5-conjugated rituximab in mice bearing lymphoid tumor xenograft using time-domain near-infrared optical imaging

Rituximab is a chimeric monoclonal antibody directed against human CD20 antigen, which is expressed on B-cell lymphocytes and on the majority of B-cell lymphoid malignancies. Herein we report the conjugate of rituximab with the near-infrared (NIR) fluorophore Cy5.5 (RI-Cy5.5) as a tool for in vitro, in vivo, and ex vivo NIR time-domain (TD) optical imaging. In vitro, RI-Cy5.5 retained biologic activity and led to elevated cell-associated fluorescence on tumor cells. In vivo, TD optical imaging analysis of RI-Cy5.5 injected into lymphoma-bearing mice revealed a slow tumor uptake and a specific long-lasting persistence of the probe within the tumor. Biodistribution studies after intraperitoneal and endovenous administration were undertaken to evaluate differences in the tumor uptake. RI-Cy5.5 concentration in the organs after intraperitoneal injection was not as high as after endovenous injection. Ex vivo analysis of biologic tissues and organs by both TD optical imaging and immunohistochemistry confirmed the probe distribution, as demonstrated by imaging experiment in vivo, showing that RI-Cy5.5 selectively accumulated in the tumor tissue and major excretion organs. In summary, the study indicates that NIR TD optical imaging is a powerful tool for rituximab-targeting investigation, furthering understanding of its administration outcome in lymphoma treatment

Deep learning cardiac motion analysis for human survival prediction

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors. This dense motion model formed the input to a supervised denoising autoencoder (4Dsurvival), which is a hybrid network consisting of an autoencoder that learns a task-specific latent code representation trained on observed outcome data, yielding a latent representation optimised for survival prediction. To handle right-censored survival outcomes, our network used a Cox partial likelihood loss function. In a study of 302 patients the predictive accuracy (quantified by Harrell's C-index) was significantly higher (p < .0001) for our model C=0.73 (95$\%$ CI: 0.68 - 0.78) than the human benchmark of C=0.59 (95$\%$ CI: 0.53 - 0.65). This work demonstrates how a complex computer vision task using high-dimensional medical image data can efficiently predict human survival