Quantitative monitoring of surface movements on active landslides by multi-temporal, high-resolution X-Band SAR amplitude information: Preliminary results

Multi-temporal image cross-correlation is a method for tracking moving features and can there-fore be used for quantitative assessments of surface displacements. Accuracies of up to 1/8th of the original image geometric resolution can be achieved. We present the results of an analysis car- ried out on Corvara landslide located in the Italian Dolomites. Image offset-tracking was applied to CosmoSky-Med amplitude images acquired between October 2013 and August 2015. The presence of a validation dataset consisting of periodical GPS surveys carried out on 16 benchmarks represents an ideal opportunity to test the applicability of SAR-based image cross-correlation for landslide moni- toring. Despite the relative low accuracy of the results amplitude-based offset-tracking proved to be beneficial due to the ability of this method to capture large displacements. In particular the results evidence its complementarity with respect to multi-temporal interferometry that is confined to slow displacements along E-W directions

Combined microbiological test to assess changes in an organic matrix used to avoid agricultural soil contamination, exposed to an insecticide

Combined microbiological test (Biolog Ecoplate, denaturing gradient gel electrophoresis (DGGE) and Real Time PCR (qPCR)) were developed to evaluate the impact of repeated diazinon (DZN) applications at high concentration (40 mg kg-1) on microbial communities in a microcosm simulating the organic matrix (straw (50%): peat (25%): soil (25%) vv-1) of an pesticide biopurification system (PBS). Moreover, pesticide dissipation was also evaluated. After three successive exposition of DZN, dissipation efficiency was high; achieved 87%, 93% and 96% after each application, respectively showing a clear accelerated dissipation of this pesticide in the organic matrix. The results obtained with Biolog Ecoplate showed that community level physiological profiles were no affected by the addition of DZN. On the other hand, molecular assays (DGGE and QPCR) demonstrated that the microbial structure (bacteria and fungi) remained relatively stable over time with high DZN doses compared to control. Therefore, the results of the present study, clearly, demonstrate the high dissipation capacity of this biomixture and highlight the microbiological robustness of this biological system.Fil: Tortella, G. R.. Universidad de la Frontera. Nucleo Cientifico y Tecnologico En Recursos Naturales (bioren-ufro). Departamento de Ciencias Quimicas y Recursos Naturales; ChileFil: Salgado, E.. Universidad de la Frontera. Nucleo Cientifico y Tecnológico En Recursos Naturales; ChileFil: Cuozzo, Sergio Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán. Planta Piloto de Procesos Industriales Microbiológicos (i); ArgentinaFil: Mella Herrera, R. A.. Universidad de la Frontera. Nucleo Cientifico y Tecnológico En Recursos Naturales; ChileFil: Parra, L.. Universidad de la Frontera. Núcleo Científico y Tecnológico en Recursos Naturales; ChileFil: Diez, M. C.. Universidad de la Frontera. Nucleo Cientifico y Tecnológico En Recursos Naturales; ChileFil: Rubilar, O.. Universidad de la Frontera. Nucleo Cientifico y Tecnológico En Recursos Naturales; Chil

Characterization of Orthogonal Chirp Division Multiplexing and Performance Evaluation at THz Frequencies in the Presence of Phase Noise

Due to its superior performance, Orthogonal Chirp Division Multiplexing (OCDM) has recently gained attention as a potential replacement for Orthogonal Frequency Division Multiplexing (OFDM) in beyond-5G systems. In this paper, we provide an analytical characterization of OCDM signals, elucidating the theoretical principles that enable their numerical generation through the Inverse Discrete Fresnel Transform (IDFnT), despite the presence of severe frequency-domain aliasing that substantially distorts the signal at the transmitter output. Furthermore, in light of the proposed utilization of the THz band in beyond-5G systems, we investigate the performance of OCDM in this frequency range in the presence of thermal, molecular, and phase noise. To model the latter, which is expected to be a significant challenge at THz frequencies, we take as a reference an actual Phase Locked Loop (PLL) oscillator operating at 237.7 GHz. The numerical results reveal the achievable performance of OCDM as a function of several key factors, including the modulation order, the bandwidth, the number of chirps constituting the signal, the oscillator parameters, the channel model, and the use of techniques aimed at mitigating the impact of phase noise. The findings are compared with those of OFDM, which is regarded as a benchmark due to its adoption in 4G and 5G systems, and demonstrate the superior performance of OCDM also in the presence of significant phase noise

OCDMA: a MAC Protocol for Industrial Intra-machine TeraHertz Network

This paper considers an industrial machine, where wireless sensor nodes (denoted as tags or nodes) support control applications. This scenario poses very challenging communication requirements: hundreds of tags per cubic meter can provide an overall offered throughput of tens of Gbit/s; at the same time, control applications require a latency of less than 0.1 ms. To fulfill them, this work proposes an Orthogonal Chirp Division Multiple Access (OCDMA) scheme to be used in the TeraHertz (THz) frequency band. With THz communications, even at short distances, propagation delays can be of the same order of magnitude as the packet transmission time. This requires proper consideration of such delays in the protocol design and performance evaluation. This paper mathematically derives network throughput and latency of the proposed protocol, comparing it to benchmarks; two scenarios are considered, where tags are in fixed positions or move. Results show that OCDMA outperforms the two benchmark protocols, Aloha and Polling, for static and crowded networks, and the performance is compatible with the communication requirements of industrial control applications

A 2.4 GHz LoRa-Based Protocol for Communication and Energy Harvesting on Industry Machines

The fourth industrial revolution is paving the way for Industrial Internet of Things applications where large number of wireless nodes, equipped with sensors and actuators, monitor the production cycle of industrial goods. This paper proposes and analyses LoRaIN, a network architecture and MAC-layer protocol thought for on-demand monitoring of industrial machines. Our proprietary system is an energy-efficient, reliable and scalable solution, where the protocol is built on top of LoRa at 2.4 GHz. Indeed, the low-power characteristics of LoRa allow to reduce energy consumption, while Wireless Power Transfer is used to recharge batteries, avoiding periodic battery replacement. High reliability is obtained through the joint use of Frequency and Time Division Multiple Access. A dynamic LoRaIN scheduler manages the communication and recharging phases depending on the tasks assigned to the nodes, as well as the number of monitoring devices. Performance is measured in terms of network throughput, energy consumption and latency. Results demonstrate that the proposed solution is suitable for monitoring applications of industry machines

On the Support of the 2.4 GHz Band in the LoRaWAN Standard

The introduction of LoRa chipsets operating in the 2.4 GHz band paves the way to unprecedented performance enhancements compared to their sub GHz counterparts, attributed to factors such as the absence of duty cycle constraints and higher data rates. Despite its potential benefits for Internet of Thing (IoT) applications, the LoRa Alliance has not yet proposed the integration of this new frequency spectrum into the LoRaWAN standard. Addressing this gap, this article proposes a roadmap for the evolution of the LoRaWAN standard, outlining three stages for seamless integration of the 2.4 GHz LoRa version. These stages are sequenced based on implementation complexity, starting from the current LoRaWAN standard (Stage 0), moving to the coexistence of two separate LoRaWAN networks (Stage 1), and ending with a single LoRaWAN network capable of supporting both sub GHz and 2.4 GHz bands (Stage 2). Additionally, the document enumerates all possible implementation options for each stage and outlines the main modifications required in the documents of the LoRaWAN standard. Through LoRaWAN-compliant simulation results, we demonstrate the performance advantages of the proposed multi-band approach over the existing LoRaWAN standard for the first stage of the suggested roadmap. Finally, the article discusses the challenges associated with the proposed roadmap and identifies corresponding research gaps to be addressed in the future

Tomato: a crop species amenable to improvement by cellular and molecular methods

Tomato is a crop plant with a relatively small DNA content per haploid genome and a well developed genetics. Plant regeneration from explants and protoplasts is feasable which led to the development of efficient transformation procedures. In view of the current data, the isolation of useful mutants at the cellular level probably will be of limited value in the genetic improvement of tomato. Protoplast fusion may lead to novel combinations of organelle and nuclear DNA (cybrids), whereas this technique also provides a means of introducing genetic information from alien species into tomato. Important developments have come from molecular approaches. Following the construction of an RFLP map, these RFLP markers can be used in tomato to tag quantitative traits bred in from related species. Both RFLP's and transposons are in the process of being used to clone desired genes for which no gene products are known. Cloned genes can be introduced and potentially improve specific properties of tomato especially those controlled by single genes. Recent results suggest that, in principle, phenotypic mutants can be created for cloned and characterized genes and will prove their value in further improving the cultivated tomato.

Factors Associated to the Onset of Mental Illness Among Hospitalized Migrants to Italy: A Chart Review

Migration is a complex phenomenon and mental illness among immigrants remains a major matter of concern in Italy and worldwide. 243 medical and pharmacy records of patients admitted to University of Foggia hospital between 2004 and 2018 were retrospectively screened and included in the study. Socio-demographic data and clinical characteristics of inpatients were compared in those with and without first-episode of mental illness (FEMI). Subjects (140 men, 103 women; aged 34.4 ± 10.2 years) represented 6.66 ± 3.73% of all hospitalizations in 15 years. Nearly half of them (48.5%) had emigrated from other European countries. 30.8% were diagnosed with a DSM-IV TR unspecified psychosis. 103 patients (42.3%) were in first-lifetime episodes of mental illness. Factors significantly associated with FEMI were: younger age, sex (men), immigrating from Africa, poor language proficiency, lower amount of prescribed psychotropics. Mental health among immigrants is of major concern in Italy. Our findings report on factors possibly associated to the onset of mental illness among immigrant psychiatric inpatients

Herramienta Integradora para la mejora de la calidad de productos de software desarrollados por equipos de trabajos distribuidos

Fil: Salamon, Alicia G. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Boaglio, Laura. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Cuozzo, José D. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Mira, Natalia. Instituto Universitario Aeronáutico. Facultad de Ingeniería; ArgentinaFil: Boggio, Alejandra. Instituto Universitario Aeronáutico. Facultad de Ingeniería; ArgentinaEn este trabajo se expone la aplicación de una metodología integradora de IO-Soft para abordar la problemática de la definición de estrategias para la gestión de proyectos en los que participan equipos de desarrollo de software distribuidos geográficamente a partir de un entorno de integración continua, identificando factores que tengan un impacto directo en la calidad del producto software.Fil: Salamon, Alicia G. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Boaglio, Laura. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Cuozzo, José D. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Mira, Natalia. Instituto Universitario Aeronáutico. Facultad de Ingeniería; ArgentinaFil: Boggio, Alejandra. Instituto Universitario Aeronáutico. Facultad de Ingeniería; ArgentinaIngeniería de Sistemas y Comunicacione

Optimizing rock glacier activity classification in South Tyrol (northeastern Italy): integrating multisource data with statistical modelling

As a consequence of atmospheric warming, high-altitude periglacial and glacial environments exhibit clear signs of cryosphere degradation, and the Alps serve as a natural laboratory for studying the primary effects on permafrost-related features. Our research in South Tyrol, northeastern Italy, aimed to develop an updated classification system, based on remote sensing data and statistical models, for rock glacier activity, categorizing it as active, transitional, or relict according to the new Rock Glacier Inventories and Kinematic (RGIK) guidelines. While the current regional inventory includes activity attributes based on morphological observations and differential interferometric synthetic aperture radar (DInSAR) coherence, it lacks a comprehensive classification that also considers climatic drivers, displacement rates, and morphometric parameters. To fill this gap, we utilized the Alaska Satellite Facility's interferometric synthetic aperture radar (InSAR) cloud computing, employing the Small Baseline Subset (SBAS) and Miami InSAR time-series software in Python (MintPy) algorithms to extract velocity data for each rock glacier investigated in this study. Additionally, we analysed geomorphological and climatic maps derived from in situ and remote sensing data to obtain descriptive parameters influencing rock glacier development and activity. From a wide range of potential variables, we selected eight key predictors, representing physical (e.g. temperature), morphological (e.g. roughness), and dynamic attributes (e.g. velocity and coherence indicators). These predictors were integrated in a multiclass generalized additive model (GAM) classifier to categorize the mapped landforms. Applying this model to the entire dataset (achieving an area under the curve (AUC) over 0.9) allowed us to address gaps in previous classification methods and provided activity attributes for previously unclassified rock glaciers, along with associated uncertainty values. Our approach enhanced the previous classification, leaving only 3.5 % of features unclassified compared to 13 % in morphological classification and 18.5 % in the DInSAR-based method. The results revealed a predominance of relict features (∼75 %) and a smaller number of active ones (∼10 %). The result of the distribution of active, transitional, and relict classes suggests that the transition from active to relict states is not direct. Instead, an intermediate transitional phase is commonly observed. This comprehensive approach refines the categorization of mapped features and improves our understanding of the factors influencing rock glacier activity in the alpine environment in South Tyrol.</p