Performance Analysis of Tomographic Methods against Experimental Contactless Multistatic Ground Penetrating Radar

Ground-penetrating radar (GPR) technology for underground exploration consists of the transmission of an electromagnetic signal in the ground for sensing the presence of buried objects. While monostatic or bistatic configurations are usually adopted, a limited number of multistatic GPR systems have been proposed in the scientific literature. In this article, we investigate the recovery performance of a specific and unconventional contactless multistatic GPR system, designed at the Georgia Institute of Technology for the subsurface imaging of antitank and antipersonnel plastic mines. In particular, for the first time, tomographic approaches are tested against this experimental multistatic GPR system, while most GPR processing in the scientific literature processes multimonostatic experimental data sets. First, by mimicking the system at hand, an accurate theoretical as well as numerical analysis is performed in order to estimate the data information content and the performance achievable. Two different tomographic linear approaches are adopted, i.e., the linear sampling method and the Born approximation (BA) method, this latter enhanced by means of the compressive sensing (CS) theoretical framework. Then, the experimental data provided by the Georgia Institute of Technology are processed by means of a multifrequency CS- and BA-based method, thus generating very accurate 3D maps of the investigated underground scenario

Shorter cyclone clusters modulate changes in European wintertime precipitation extremes

Wintertime extreme precipitation from cyclone clusters, i.e. consecutive cyclones moving across the same region, can lead to flooding and devastating socio-economic impacts in Europe. Previous studies have suggested that the future direction of the changes in these events are uncertain across climate models. By employing an impact-based metric of accumulated precipitation extremes, we show that projections of cyclone clusters are instead broadly robust, i.e. consistent in sign, across models. A novel physical diagnostic shows that accumulated precipitation extremes are projected to grow by only +1.0%/K on average across Europe, although the mean precipitation per cyclone increases by +4.7%/K. This results from a decreased number of clustered cyclones, associated with decreased wintertime storminess, the extent of which varies from northern to southern Europe and depends on the future storyline of atmospheric circulation change. Neglecting the changes in the number of clustered cyclones, i.e. assuming that accumulated precipitation extremes would change as the mean precipitation per cyclone, would lead to overestimating the population affected by increased accumulated wintertime precipitation extremes by 130-490 million across Europe

Network structure indexes to forecast epidemic spreading in real-world complex networks

Complex networks are the preferential framework to model spreading dynamics in several real-world complex systems. Complex networks can describe the contacts between infectious individuals, responsible for disease spreading in real-world systems. Understanding how the network structure affects an epidemic outbreak is therefore of great importance to evaluate the vulnerability of a network and optimize disease control. Here we argue that the best network structure indexes (NSIs) to predict the disease spreading extent in real-world networks are based on the notion of network node distance rather than on network connectivity as commonly believed. We numerically simulated, via a type-SIR model, epidemic outbreaks spreading on 50 real-world networks. We then tested which NSIs, among 40, could a priori better predict the disease fate. We found that the “average normalized node closeness” and the “average node distance” are the best predictors of the initial spreading pace, whereas indexes of “topological complexity” of the network, are the best predictors of both the value of the epidemic peak and the final extent of the spreading. Furthermore, most of the commonly used NSIs are not reliable predictors of the disease spreading extent in real-world networks

Field and Temperature Shaping for Microwave Hyperthermia: Recent Treatment Planning Tools to Enhance SAR-Based Procedures

The aim of the article is to provide a summary of the work carried out in the framework of a research project funded by the Italian Ministry of Research. The main goal of the activity was to introduce multiple tools for reliable, affordable, and high-performance microwave hyperthermia for cancer therapy. The proposed methodologies and approaches target microwave diagnostics, accurate in vivo electromagnetic parameters estimation, and improvement in treatment planning using a single device. This article provides an overview of the proposed and tested techniques and shows their complementarity and interconnection. To highlight the approach, we also present a novel combination of specific absorption rate optimization via convex programming with a temperature-based refinement method implemented to mitigate the effect of thermal boundary conditions on the final temperature map. To this purpose, numerical tests were carried out for both simple and anatomically detailed 3D scenarios for the head and neck region. These preliminary results show the potential of the combined technique and improvements in the temperature coverage of the tumor target with respect to the case wherein no refinement is adopted

Performance Analysis of Tomographic Methods Against Experimental Contactless Multistatic Ground Penetrating Radar

Ground-penetrating radar (GPR) technology for underground exploration consists of the transmission of an electromagnetic signal in the ground for sensing the presence of buried objects. While monostatic or bistatic configurations are usually adopted, a limited number of multistatic GPR systems have been proposed in the scientific literature. In this article, we investigate the recovery performance of a specific and unconventional contactless multistatic GPR system, designed at the Georgia Institute of Technology for the subsurface imaging of antitank and antipersonnel plastic mines. In particular, for the first time, tomographic approaches are tested against this experimental multistatic GPR system, while most GPR processing in the scientific literature processes multimonostatic experimental data sets. First, by mimicking the system at hand, an accurate theoretical as well as numerical analysis is performed in order to estimate the data information content and the performance achievable. Two different tomographic linear approaches are adopted, i.e., the linear sampling method and the Born approximation (BA) method, this latter enhanced by means of the compressive sensing (CS) theoretical framework. Then, the experimental data provided by the Georgia Institute of Technology are processed by means of a multifrequency CS- and BA-based method, thus generating very accurate 3D maps of the investigated underground scenario

Considering weights in real social networks: A review

Network science offers powerful tools to model complex social systems. Most social network science research focuses on topological networks by simply considering the binary state of the links, i.e., their presence or absence. Nonetheless, complex social systems present heterogeneity in link interactions (link weight), and accounting for this heterogeneity, it is mandatory to design reliable social network models. Here, we revisit the topic of weighted social networks (WSNs). By summarizing the main notions, findings, and applications in the field of WSNs, we outline how WSN methodology may improve the modeling of several real problems in social sciences. We are convinced that WSNs may furnish ideas and insights to open interesting lines of new research in the social sciences

Simple gene transfer technique based on I-SceI meganuclease and cytoplasmic injection in IVF bovine embryos

Although transgenic methods in mammals are inefficient, an easy and highly efficient transgenesis systemusing I-SceI meganuclease (intron-encoded endonuclease fromS. cerevisiae)was recently described in Xenopus. The method consisted of injection into fertilized eggs of an I-SceI reaction mixture with a plasmid DNA carrying the transgene, flanked by the meganuclease recognition sites (pIS). In the present study, the effects of I-SceI on gene transfer were tested apparently for the first time in mammals, in particular, in cattle. Various conditions were evaluated, including three concentrations of the plasmid pIS Pax6egfp, carrying I-SceI recognition sites flanking egfp under Pax6 promoter and two injection times (before IVM and after IVF) of pIS CAGegfp, carrying I-SceI sites fanking egfp under CAG promoter. In addition, the quantity of transgenewasmeasured using quantitative polymerase chain reaction, and presence of transgene signals was evaluated using fluorescence in situ hybridization analysis. Transgene expression rateswere higher (P< 0.05) for groups treated after IVF (79.1%, 91/115 and 63.0%, 75/ 119) than before IVM (32.6%, 31/95 and 34.7%, 33/95), with and without I-SceI, respectively. Interestingly, injectionwith pIS plus I-SceI after IVF increased frequency (P<0.05) of nonmosaic transgene-expressing embryos (58.3%, 42/72 vs. 29.7%, 25/84) for pIS plus I-SceI and pIS alone. Based on fluorescence in situ hybridization analysis, injectionwith I-SceI increased (P<0.05) the proportion of embryos with transgene signals in all blastomeres compared with pIS alone (44.0%,11/25 vs. 6.9%, 2/29) for pIS plus I-SceI and pIS alone. In addition, transgene copy number was numerically higher for the group treated with pIS plus I-SceI compared with pIS alone. In conclusion, I-SceI gene transfer increased transgene signals in bovine embryos.Fil: Bevacqua, Romina Jimena. Universidad de Buenos Aires. Facultad de Agronomía. Pabellón de Zootecnica. Laboratorio de Biotecnología Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; ArgentinaFil: Canel, Natalia Gabriela. Universidad de Buenos Aires. Facultad de Agronomía. Pabellón de Zootecnica. Laboratorio de Biotecnología Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; ArgentinaFil: Hiriart, María Inés. Universidad de Buenos Aires. Facultad de Agronomía. Pabellón de Zootecnica. Laboratorio de Biotecnología Animal; ArgentinaFil: Sipowicz, P.. Universidad Nacional de San Martín. Laboratorio de Neuro y Citogenética Molecular; ArgentinaFil: Rozenblum, G. T.. Universidad Maimónides. Area de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; ArgentinaFil: Vitullo, Alfredo Daniel. Universidad Maimónides. Area de Investigaciones Biomédicas y Biotecnológicas. Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y de Diagnóstico; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; ArgentinaFil: Radrizzani Helguera, Martin. Universidad Nacional de San Martín. Laboratorio de Neuro y Citogenética Molecular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; ArgentinaFil: Fernández y Martín, Rafael. Universidad de Buenos Aires. Facultad de Agronomía. Pabellón de Zootecnica. Laboratorio de Biotecnología Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; ArgentinaFil: Salamone, Daniel Felipe. Universidad de Buenos Aires. Facultad de Agronomía. Pabellón de Zootecnica. Laboratorio de Biotecnología Animal; Argentin

Predicting Head Pose in Dyadic Conversation

Natural movement plays a significant role in realistic speech animation. Numerous studies have demonstrated the contribution visual cues make to the degree we, as human observers, find an animation acceptable. Rigid head motion is one visual mode that universally co-occurs with speech, and so it is a reasonable strategy to seek features from the speech mode to predict the head pose. Several previous authors have shown that prediction is possible, but experiments are typically confined to rigidly produced dialogue. Expressive, emotive and prosodic speech exhibit motion patterns that are far more difficult to predict with considerable variation in expected head pose. People involved in dyadic conversation adapt speech and head motion in response to the others’ speech and head motion. Using Deep Bi-Directional Long Short Term Memory (BLSTM) neural networks, we demonstrate that it is possible to predict not just the head motion of the speaker, but also the head motion of the listener from the speech signal