Il Museo Geofisico di Rocca di Papa: tra divulgazione e ricerca scientifica

The Geophysical Museum of Rocca di Papa is located in an historical, three floor building, of the small town Rocca di Papa, twentyfive kilometres from Rome. The edifice was, until 1931, the place of the Geodynamic Observatory, created in 1889 by the famous seismologist Michele Stefano De Rossi. The museum is due to an agreement between the Town Council of Rocca di Papa and the Istituto Nazionale di Geofisica (INGV, one of the most important European Research Institutions operating in geophysics) signed in 2000. After bureaucratic passages and two years of important restoration the museum was open to the public at 26th February 2005. The main aim of the Geophysical Museum is to illustrate how experimental data and information, accumulated by science in the course of time, led to new hypotheses on the internal structure of the Earth. The target of the educational and of the scientific disciplines of the Museum is mainly school students of all ages, but also local residents, and tourists: since its opening, approximately two years ago, the Museum has been visited by more than eight-thousand people. Posters, movie presentations, plastics, games and interactive experiments explain to visitors the main topics of geophysics and the stages of scientific research which led to the modern concept of the Earth internal model. Seismic instruments and games are easily accessible so that the visitor can interact with them: experimental data are recorded in real time and displayed through different monitors placed throughout the rooms. The museum has also a small cinema for three dimensional projections which allow visitors to experience a virtual tour on the Alban Hills, the seismic zone where the museum is located, and also on some other Italian tectonic belts where earthquakes occurred in past. The article introduces the museum and the seismological characteristics of the area, and describes the activities, the exhibits of the Museum and their methodology

Ridge regression and its applications in genetic studies

With the advancement of technology, analysis of large-scale data of gene expression is feasible and has become very popular in the era of machine learning. This paper develops an improved ridge approach for the genome regression modeling. When multicollinearity exists in the data set with outliers, we consider a robust ridge estimator, namely the rank ridge regression estimator, for parameter estimation and prediction. On the other hand, the efficiency of the rank ridge regression estimator is highly dependent on the ridge parameter. In general, it is difficult to provide a satisfactory answer about the selection for the ridge parameter. Because of the good properties of generalized cross validation (GCV) and its simplicity, we use it to choose the optimum value of the ridge parameter. The GCV function creates a balance between the precision of the estimators and the bias caused by the ridge estimation. It behaves like an improved estimator of risk and can be used when the number of explanatory variables is larger than the sample size in high-dimensional problems. Finally, some numerical illustrations are given to support our findings

Tailoring 3D printed cellulose acetate properties produced via direct ink writing: Densification through over-extrusion and evaporation rate control

In this study, we conducted a comprehensive experimental campaign aimed at controlling the final properties of 3D printed cellulose acetate. We equipped a commercial printer with a peristaltic pump to be able to print in a continuous fashion by means of the Direct Ink Writing technique. We investigated the effect of ink concentration and printing parameters on the density, mechanical and functional properties of printed objects. Furthermore, water absorption tests demonstrated the hygroscopic behavior of cellulose acetate, with higher water content in samples with lower densities. The diffusion of water within the polymer network followed Fickian diffusion, with the diffusion coefficient influenced by the density of samples. Overall, this study highlights the importance of printing conditions in achieving desired properties in 3D printed cellulose acetate. The ability to fine-tune the mechanical properties and water absorbance of 3D printed cellulose acetate makes it promising for applications in plant science and bioengineering. Highlights: Cellulose acetate has been 3D printed via Direct Ink Writing. The shear-thinning behavior allows for shape retention during printing. Density of printed samples is strongly controlled by printing parameters. Density of printed parts influences mechanical properties and water absorption

Muon spin rotation and relaxation in the superconducting ferromagnet UCoGe

We report zero-field muon spin rotation and relaxation measurements on the superconducting ferromagnet UCoGe. Weak itinerant ferromagnetic order is detected by a spontaneous muon spin precession frequency below the Curie temperature $T_C = 3$ K. The $\mu^+$ precession frequency persists below the bulk superconducting transition temperature $T_{sc} = 0.5$ K, where it measures a local magnetic field $B_{loc} = 0.015$ T. The amplitude of the $\mu$SR signal provides unambiguous proof for ferromagnetism present in the whole sample volume. We conclude ferromagnetism coexists with superconductivity on the microscopic scale.Comment: 4 pages, 3 figures, accepted for publication in PR

Statistical analysis driven optimized deep learning system for intrusion detection

Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology systems. The extent of damage an individual hacker can carry out upon infiltrating a system is well understood. A potentially catastrophic scenario can be envisaged where a nation-state intercepting encrypted financial data gets hacked. Thus, intelligent cybersecurity systems have become inevitably important for improved protection against malicious threats. However, as malware attacks continue to dramatically increase in volume and complexity, it has become ever more challenging for traditional analytic tools to detect and mitigate threat. Furthermore, a huge amount of data produced by large networks has made the recognition task even more complicated and challenging. In this work, we propose an innovative statistical analysis driven optimized deep learning system for intrusion detection. The proposed intrusion detection system (IDS) extracts optimized and more correlated features using big data visualization and statistical analysis methods (human-in-the-loop), followed by a deep autoencoder for potential threat detection. Specifically, a pre-processing module eliminates the outliers and converts categorical variables into one-hot-encoded vectors. The feature extraction module discard features with null values and selects the most significant features as input to the deep autoencoder model (trained in a greedy-wise manner). The NSL-KDD dataset from the Canadian Institute for Cybersecurity is used as a benchmark to evaluate the feasibility and effectiveness of the proposed architecture. Simulation results demonstrate the potential of our proposed system and its outperformance as compared to existing state-of-the-art methods and recently published novel approaches. Ongoing work includes further optimization and real-time evaluation of our proposed IDS.Comment: To appear in the 9th International Conference on Brain Inspired Cognitive Systems (BICS 2018

LA RETE SISMICA DELLA PIANA DI GUIDONIA (LAZIO): DATI PRELIMINARI

After the seismic period during 2001-2002 that has interested the Plain of Guidonia, situated about fifteen kilometres NE of Rome, which events greatest resentment reached the V-VI MCS, have been installed a local seismic purchased by Comune of Guidonia-Montecelio (Rm). The seismic network (RLG) consists of three digital seismic stations with distances of each other about 2 kilometers, activated to leave from the June 2004 and equipped with three components 1 Hz sismometer. Subsequently, the RLG has enriched of other four digital stations equipped with three components 5 Hz sismometer This network has like main objective the high quality data that agree a better definition of the seismic local activity. These data, that integrate those of the Seismographic Centralized National Network (SCNN), agreed a better ipocentre location. Network geometriy was chosen so as to give back the RLG an independent structure to carry out reliable seismicity locations that characterizes the plain of Guidonia. Unfortunately, industrial and human activity, increases in considerable manner the seismic noise, giving back difficult the record of small events. For this motive the location of the sites was more times changed, and lately, after a seismic crisis in the northern side of the Mountains Cornicolani, that has presented with the same features of that of 2001 of Guidonia, some stations were moved in the neighboring village of Palombara Sabina (Rm)

Effectiveness of a controlled 5-fu delivery based on fzd10 antibody-conjugated liposomes in colorectal cancer in vitro models

The use of controlled delivery therapy in colorectal cancer (CRC) reduces toxicity and side effects. Recently, we have suggested that the Frizzled 10 (FZD10) protein, a cell surface receptor belonging to the FZD protein family that is overexpressed in CRC cells, is a novel candidate for targeting and treatment of CRC. Here, the anticancer effect of novel immuno-liposomes loaded with 5-Fluorouracil (5-FU), decorated with an antibody against FZD10 (anti-FZD10/5-FU/LPs), was evaluated in vitro on two different CRC cell lines, namely metastatic CoLo-205 and nonmetastatic CaCo-2 cells, that were found to overexpress FZD10. The anti-FZD10/5-FU/LPs obtained were extensively characterized and their preclinical therapeutic efficacy was evaluated with the MTS cell proliferation assay based on reduction of tetrazolium compound, scratch test, Field Emission Scanning Electron Microscopes (FE-SEM) investigation and immunofluorescence analysis. The results highlighted that the cytotoxic activity of 5-FU was enhanced when encapsulated in the anti-FZD10 /5-FU/LPs at the lowest tested concentrations, as compared to the free 5-FU counterparts. The immuno-liposomes proposed herein possess a great potential for selective treatment of CRC because, in future clinical applications, they can be encapsulated in gastro-resistant capsules or suppositories for oral or rectal delivery, thereby successfully reaching the intestinal tract in a minimally invasive manner

Scaling of the superfluid density in superfluid films

We study scaling of the superfluid density with respect to the film thickness by simulating the $x-y$ model on films of size $L \times L \times H$ ($L >> H$) using the cluster Monte Carlo. While periodic boundary conditions where used in the planar ($L$) directions, Dirichlet boundary conditions where used along the film thickness. We find that our results can be scaled on a universal curve by introducing an effective thickness. In the limit of large $H$ our scaling relations reduce to the conventional scaling forms. Using the same idea we find scaling in the experimental results using the same value of $\nu = 0.6705$.Comment: 4 pages, one postscript file replaced by one Latex file and 5 postscript figure