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La promoción de Cadenas Cortas de Suministro de Alimentos (Short Food Supply Chains, SFSC) es un reto que las instituciones públicas y de investigación están abordando con el fin de desarrollar cadenas de suministro agroalimentarias más sostenibles y empoderar a los pequeños agricultores. Esta investigación analiza la cadena de valor del tomate en la provincia de Barcelona con los objetivos de: 1) conocer los canales de distribución y precios, 2) detectar las limitaciones y oportunidades de la cadena, y 3) determinar la disposición de los agricultores a adoptar las SFSC como alternativa complementaria a la distribución convencional. Para ello, se han encuestado 48 agricultores. Los resultados muestran que las SFSC ofrecen un precio un 40% más alto que el de los mayoristas, pero suponen menos de la mitad del volumen de mercado. Así, aunque un 87% de los agricultores muestren interés en las SFSC, es una opción limitada por los costes elevados y otras barreras asociadas. Finalmente, se señala que las SFSC son un elemento clave para conseguir cadenas de valor más justas y sostenibles y se propone la mejora de la logística y la cooperación entre stakeholders como acciones imprescindibles para su promoción., Peer Reviewed, Postprint (published version)

This study describes a novel combination of methods to remove spurious spectral peaks, or “spurs,” from Doppler spectra produced by a vertically pointing, S-band radar. The University of Massachusetts S-band frequency-modulated, continuous-wave radar (UMass FMCW) was deployed to monitor the growth of the CBL over northern Alabama during the VORTEX–Southeast field campaign in 2016. The Doppler spectra contained spurs caused by high-voltage switching power supplies in the traveling wave tube amplifier. In the original data processing scheme for this radar, a median filtering method was used to eliminate most of the spurs, but the largest ones persisted, which significantly degraded the quality of derived radar moments (e.g., reflectivity, Doppler velocity, and spectrum width) and hindered further analysis of these data (e.g., hydrometeor classification and boundary layer height tracking). Our technique for removing the spurs consists of three steps: (i) a Laplacian filter identifies and masks peaks in the spectra that are characteristic of the spurs in shape and amplitude, (ii) an in-painting method then fills in the masked area based on surrounding data, and (iii) the moments data (e.g., reflectivity, Doppler velocity, and spectrum width) are then recomputed using a coherent power technique. This combination of techniques was more effective than the median filter at removing the largest spurs from the Doppler spectra, and preserved more of the underlying Doppler spectral structure of the scatterers. Performance of both the median-filter and the in-painting methods are assessed through statistical analysis of the spectral power differences. Downstream products, such as boundary layer height detection, are more easily derived from the recomputed moments., This work was funded by NOAA grants NA18OAR4590313 and NA19OAR4590209. Dr. Stanley H. Chan and Dr. Andrew Pazmany advised us on the in-painting and CP techniques, respectively. The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the NOAA or the U.S. Department of Commerce. Dr. Rocadenbosch contributed the CBL detection algorithm via project PID2021-126436OB-C21 funded by Ministerio de Ciencia e Investigación (MCIN)/ Agencia Estatal de Investigación (AEI)/ 10.13039/501100011033 and EU project H2020 ATMO-ACCESS (GA-101008004)., Peer Reviewed, Postprint (author's final draft)

The Barcelona Expert Center (BEC) has become an international reference in the generation of high resolution soil moisture (SM) maps using disaggregation algorithms. More than a decade ago, a semi-empirical approach was developed to produce Soil Moisture and Ocean Salinity (SMOS) SM at 1 km. This method has been refined over the years to obtain cloud free maps, and modified to further improve the spatial resolution up to 300 m. More recently, a machine-learning approach has been developed to derive European Space Agency (ESA)’s Climate Change Initiative (CCI) SM at 60 m.Thanks to the multi-spectral information added during the disaggregation process, the downscaled SM maps have an overall accuracy similar to the coarse ones, but provide additional information about the SM spatial variability. In this regard, three different applications over the north of Africa are presented here to exemplify the added-value of SM data at high resolution., This research was supported by the Spanish Ministry of Science, Innovation and Universities (MCIN/AEI/10.13039/501100011033) through the project INTERACT (PID2020-114623RB-C32) and by the Institute of Space Studies of Catalonia (IEEC)., Peer Reviewed, Postprint (author's final draft)

This study delineates the curriculum covering the instruction of photovoltaic (PV) solar energy within the Electronic Telecommunications Engineering Bachelor's Degree at the Barcelona School of Telecommunications Engineering (ETSETB), part of the Polytechnic University of Catalonia (UPC). This program commenced during the academic year 2018-2019 at the ETSETB. The curriculum comprises three courses dedicated to the study of PV solar energy within the program. A compulsory course: Electric Power Processing (6 ECTS), and two elective courses: Photovoltaic devices (6 ECTS) and Photovoltaic Solar Energy (2 ECTS)., This work has received funding from the Spanish Ministry of Science and Innovation under the MATER-ONE project (PID2020-116719RB-C41)., Peer Reviewed, Postprint (published version)

From 1980 to 2021, earthquakes have caused more than 846 000 casualties and about US$ 661 billion in economic losses. At present, there are no reliable earthquake precursors to generate alerts. Currently, the link between earthquakes and total electron content variations measured by global navigation satellite systems (GNSSs) monitoring ground stations has been studied. However, GNSS ground-based monitoring stations are irregularly disseminated around the globe with significant gaps, particularly in the ocean's regions. In this article, we analyze ionospheric intensity scintillation anomalies as potential proxies of earthquakes. NASA CYGNSS GNSS-R (reflectometry) acquired by CYGNSS/delay Doppler mapping instrument from 2017 to 2021 has been used to calculate and analyze the anomalies in the S 4 parameter over ocean areas affected by earthquakes. More than 30 000 ocean earthquakes within ±40° in latitude and with a magnitude larger than M4 have been examined. The daily planetary geomagnetic index Kp was used to discard data that may be disturbed due to space weather conditions. In addition, a daily sea wind speed mask was used to eliminate sea states that impact the signal reflectivity. The standard deviation and the interquartile time series methods have been used to detect these S 4 anomalies. The confusion matrix, the receiver operating curve, and some other figures of merit have been used for the first time to evaluate and improve the performance of the prediction parameters and identify the optimum configuration to be used as a potential proxy of earthquake occurrence. As a result, a small, but detectable positive S 4 anomaly was detected between 1 and 7 days before the earthquakes under study., The work of Badr-Eddine Boudriki Semlali was supported by an FI Grant: 2021 FI_B 00471 from FI AGAUR 2021. This work was supported in part by the Grant GENESIS, PID2021-126436OB-C21 from the Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia, del Plan Estatal de Investigación Científica, Técnica y de Innovación 2021–2023 (Spain) and in part by the European Social Fund, Grant RYC-2016-2018 financed by MCIN/AEI/10.13039/501100011033., Peer Reviewed, Postprint (published version)

Every year, earthquakes cause numerous casualties and billions of dollars in economic damages, and so far, it is impossible to pre-dict them. Many researchers have studied the land surface tem-perature (LST) anomalies as promising potential earthquake precursors. In this work, more than 30,000 land earthquakes with a Magnitude (Mw) larger than 4 have been studied from 2010 to 2021. Global LST nighttime (0–6 am) data from Meteosat Second Generation (MSG), Himawari-8, and the Geostationary Operational Environmental Satellite (GOES) satellites have been used to evalu-ate the LST anomalies in the zones affected by earthquakes with spatial resolutions of 1, 2, and 4 km, respectively. The time series moving standard deviation (STD) and Interquartile (IQT) have been used to estimate the LST anomalies. The Confusion Matrix (CM), the receiver operating curve (ROC), and some other figures of merit are computed to assess the goodness of positive LST anomalies and detection thresholds as potential proxies of earth-quake occurrence. A positive LST anomaly is typically observed a few days [1–7d] before the earthquake’s occurrence, followed by a negative LST anomaly afterwards [1–3d]., This work was supported in part by the grant PID2021-126436OB-C21 from the Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia, del Plan Estatal de Investigación Científica, Técnica y de Innovación 2021–2023 (Spain) and in part by the European Social Fund (ESF), Grant RYC-2016-2018 financed by MCIN/AEI/10.13039/ 501100011033. Badr-Eddine Boudriki Semlali received support from an FI grant: 2021 FI_B 00471 from FI AGAUR 2021 and MCIN/AEI /10.13039/501100011033; Spanish National Plan for Scientific and Technical Research and Innovation., Peer Reviewed, Postprint (published version)

Electromagnetic waves propagation through the ionosphere is subject to several effects including refraction, absorption, signal delay, or Faraday rotation. A ray tracer propagator that simulates these effects is an important tool for all satellite missions relying on trans-ionospheric communications and Earth observation. This study presents an update to the 1975 Jones & Stephenson IONORT's code by implementing the use of up-to-date ionospheric, atmospheric, and geomagnetic models (IRI or NeQuick, NRLMSISE-00, IGRF), and a new 3-D model for equatorial plasma bubbles (EPBs). The developed code is part of the Ionosphere Modular Software Package (IMSP) in the context of the European Space Agency (ESA) project SIMIONO. HF radar sounders, Synthetic Aperture Radars (SAR), and GNSS Reflectometry (GNSS-R) missions constitute the main application of this software. The ray tracer has been validated with respect to the original software and by comparing real vs. simulated vertical ionograms in different locations and dates., This work was supported in part by the grant GENESIS PID2021-126436OB-C21 from the Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia, del Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023 (Spain) and in part by the European Social Fund (ESF), Grant RYC-2016-2018 financed by MCIN/AEI /10.13039/501100011033., Peer Reviewed, Postprint (published version)

Soil Moisture (SM) is one of the Essential Climate Variables (ECVs) needed to better understand the water cycle, to assess climate change, and it is crucial to monitor floods and droughts, in agriculture, etc. SM mapping at large scale is only feasible using remote sensing sensors for Earth observation. In this paper, the different soil moisture mapping techniques are first revised, then SM mapping using L-band microwave radiometers and GNSS-Reflectometers are presented using UPC-developed techniques and airborne and spaceborne instruments. Downscaled SM mapping techniques are described in detail in the companion paper by Pablos et al. titled "Two disaggregation algorithms to estimate soil moisture at moderate (1 km and 300 m) and at high (60 m) resolution: Applications over the North of Africa" presented also at this conference., This research was supported by the Spanish Ministry of Science, Innovation and Universities (MCIN/AEI/10.13039/501100011033) through projects GENESIS (PID2021-126436OB-C21), AI4WATER (TED2021-131877B-I00), and INTERACT (PID2020- 114623RB-C32)., Peer Reviewed, Postprint (author's final draft)

Scattering information extraction is crucial for enhanced target characterization. While numerous parameters have been introduced to describe scattering from targets using full-polarimetric SAR data, the challenge lies in obtaining such scattering-type information from dual-polarimetric SAR data. This study presents an ingenious approach to address this challenge. We propose a novel index for characterizing surface scattering by leveraging dual-polarimetric Sentinel-1 SLC as well as GRD SAR data. Our method uniquely utilizes a Stokes vector component to effectively distinguish “surface-like” scattering from targets. Notably, the results from our proposed index competently align with similar scattering-type parameters derived from full-polarimetric SAR data., Peer Reviewed, Postprint (author's final draft)

Hyperspectral imaging is a key tool in numerous remote sensing applications. Images with tens or even hundreds of spectral bands contain a wealth of information to retrieve multiple geophysical parameters, to perform target detection, or land classification with unbeatable high accuracies. In addition, hyperspectral sensors are becoming smaller, and today they even fit in CubeSats. However, the amount of data they generate is so large that satellite communication systems have severe limitations to download it, especially in SmallSats. It is therefore becoming urgent to develop efficient automated algorithms that can be executed in the limited capabilities of the onboard computers of these satellites, so as to reduce the amount of data to be stored and downloaded, while keeping as much information as possible for a given scene. In this work a band selection algorithm has been designed to deal with this problem. The proposed algorithm consists of the sequential selection of the spectral bands ranked using the amount of information provided by each band, and also the correlation of these bands with the previously selected ones. The algorithm performance is assessed by means of a suite of classification tests with hyperspectral datasets from different sensors. Results show comparable or even better performance than other existing Band Selection algorithms, while outperforming in terms of computational complexity, which makes it more suitable for SmallSats with limited computing resources., This work was supported by the project GENESIS: GNSS Environmental and Societal Missions, grant PID2021-126436OB-C21, and by a FPU fellowship from the Spanish Ministry of Education. Part of this work has also been possible thanks to the Italian Space Agency (ASI) that granted access to its PRISMA database (http://prisma.asi.it/)., Peer Reviewed, Postprint (published version)

This paper presents a novel planar filtering antenna (filtenna) with simple layout based on tightly-coupled different-length monopoles. Its design methodology is based on an even-mode/odd-mode decomposition of the monopole currents, and the combination of both modes in a multimodal circuit model that facilitates the design and tuning of the antenna and the accompanying feeding network, since most of the process is performed using fast circuit simulations. The circuit model casts light into the interaction between conducting and radiating modes in the bulk of the antenna, and on how this interaction can be used to propose feedback loops that increase and define the radiation band. Using these modal tools, a filtenna was designed and fabricated to fully cover the new 5G frequency bands (n77, n78 and n79) from 3 to 5 GHz that are currently being adopted by many countries for high-capacity data transmission. It features a 62.9% FWB, dipole-like radiation patterns, good out-of-band rejection up to 10 GHz, and a very good trade-off between design/structural-simplicity and bandwidth., This work was supported in part by Ministerio de Ciencia, Innovación y Universidades, Spain under Grant PID2022-136869NBC31 financed by MCIN/AEI/10.13039/501100011033/FEDER, UE and PID2022-136869NB-C33 financed by MCIN/AEI/10.13039/501100 011033/FEDER, UE., Peer Reviewed, Postprint (published version)

The animal production systems are one of the most contributing sectors to the Green Houses Gases emissions. This research analyzes the Spanish consumers’ perceptions and willingness to pay towards sustainable chicken meat, eggs and pork by introducing insect meal in animal feeding. The Contingent Valuation, using the single-bounded dichotomous choice and the payment card elicitation format, was used under different information contexts (Video, written-information + video, and No-information). Data was collected from 1.218 consumers that have purchased pork, chicken and eggs in the last three months. The “cheap talk” and “Solemn oath” scripts were used as an ex-ante method to reduce hypothetical bias. Results showed that the information context influences consumers’ preferences. Surprisingly, the highest premium was obtained when No-information is provided. High heterogeneity levels were found according to the main characteristics of consumers. Results may play an important role to promote sustainable animal feeding and market segmentations., Postprint (published version)

For the first time, geometrical, optical and radiative properties of cirrus clouds, measured with a Polarized Micro Pulse Lidar (P-MPL) in Barcelona, have been analysed. For this purpose, the identification of cirrus scenes and the application of the two-way transmittance method have been applied to P-MPL products, published in the website of Micro Pulse Lidar NETwork (MPLNET), along with radiosondes from 2019-2021. The radiative properties of cirrus scenes have been determined through the use of an ensemble scattering model for cirrus clouds and their radiative effects have been calculated with GAME (Global Atmospheric ModEl) model. The results show that the highest occurrence of cirrus is in spring, the cirrus being in 81% of the cases either visible or opaque. Most cirrus have a COD between 0.1-0.2 (49%), LR around 30 sr (53%), linear cloud depolarization ratio between 0.3-0.5 (50%) and IWC lower than 0.01g/m3 (80%). Also, the net radiative effects of 4 selected cirrus case studies were found to be positive at both daytime and nighttime., Peer Reviewed, Postprint (published version)

Band selection is a key strategy to address the challenges of managing large hyperspectral datasets and reduce the dimensionality problem associated with the simultaneous analysis of hundreds of spectral bands. However, the computational complexity of traditional methods makes the algorithms difficult to be deployed on board satellites. This is especially true for Small Satellites with limited computational and power resources. Moreover, existing band selection techniques often require the hypercube to be processed at least at Level-1B product, i.e., the bands need to be finely aligned before selecting them, demanding more computational resources for the on-board computer. This study presents a novel neural network-based approach for on-board band selection using data with coarse band-to-band aligned. This methodology not only simplifies the pre-processing requirements, but also opens new possibilities for efficient hyperspectral imaging from space on-board Small Satellites, such as classification, change and target detection., This project was part of the project "GENESIS: GNSS Environmental and Societal Missions – Subproject UPC", Grant PID2021-126436OB-C21 funded by the Ministerio de Ciencia e Investigación (MCIN)/Agencia Estatal de Investigación (AEI)/10.13039/501100011033 and EU FEDER “Una manera de hacer Europa”, and by a FPU fellowship from the Spanish Ministry of Education. Part of this work has also been possible thanks to the Italian Space Agency (ASI) that granted access to its PRISMA database (http://prisma.asi.it/)., Peer Reviewed, Postprint (published version)

Effectively implementing innovations in agri-food supply chains (AFSCs) is contingent upon stakeholders’ preferences. Using the analytic hierarchy process (AHP), the objective of this research was to ascertain the degree of willingness among farmers, consumers, and various stakeholders (including processing companies, restaurants, and retailers) in the tomato supply chain of Catalonia (Spain) to shorten the chain and promote local procurement. Based on a set of social, economic, and environmental criteria encompassing sustainability in AFSCs, the results showed that economic factors, particularly profitability and affordability, were the key driving factors in the decisions of stakeholders. However, the considerable importance placed on strategic attributes, including local production, environmental sustainability, and product quality, particularly among consumers, seemed to present a chance to advocate for sustainable alternatives, such as short food supply chains (SFSCs). The AHP methodology facilitates differentiation with respect to the criteria of the decision-making process and serves as a valuable instrument for evaluating the reception of innovations within the AFSC and categorizing the stakeholders who exhibit the greatest interest in them. In order to improve the sustainability of agri-food systems, our findings may be incorporated into strategic plans developed by policymakers., This study belongs to the project Lab4Supply, “Multi-agent agri-food living labs for new supply chain Mediterranean systems. Towards more sustainable and competitive farming addressing consumers’ preferences and market changes”, funded under the PRIMA—Partnership for Research and Innovation in the Mediterranean Area—programme-Section 2, Call 2020, Thematic Area Agri-food Value Chain. PRIMA Lab4supply received funding from participating National Research Agencies: in Spain, by “Ministerio de Ciencia e Innovación” (MCIN)—“Agencia Estatal de Investigación” (AEI) (DOI 10.13039/501100011033) and European Union—NextGenerationEU/PRTR, under grant agreement PCI2021-121923. The content of this paper reflects only the author’s view, and the funding agencies are not responsible for any use that may be made of the information it contains., Peer Reviewed, Postprint (published version)

During the atmospheric entry phase, the high levels of ionization on the plasma layer around a spacecraft can cause disruption of the communications, leading to a radio blackout phenomenon. This work, as part of the Horizon 2020 Magnetohydrodynamics Enhanced Entry System for Space Transportation (MEESST) project, presents experimental measurements of radio signal propagation through stagnant flows of air and CO2 plasmas, representative of Earth and Mars entry flows, to characterize the effect of the flow on the radio wave signal propagation. The measurements are conducted at the VKI plasma wind tunnel, the Plasmatron facility, using conical horn antennas in the Ka-band transmitting inside an optimally designed probe. The design and characterization of the probe, conducted at the UPC anechoic chamber, are also detailed. The measurements at the plasma wind tunnel show that the signal propagates almost undisturbed for low electric powers (and plasma frequencies), being its magnitude attenuated and its polarization rotated consecutively for higher electric powers. The dependency with pressure in air is seen to comply with experimental measurements of electron number densities in the facility found in literature. Similar behaviours for air and CO2 plasmas are observed., Diana Luís research is funcled by a doctoral fellowship (2021.04930.BD) granted by Fundaçao para a Ciencia e Tecnologia (FCT Portugal). The MEESST project is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No 899298., Peer Reviewed, Postprint (author's final draft)

© 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM., In some contexts, like geriatric hospitals, the number of patients requiring assistance with feeding is very high and robots may be an effective tool for caregivers to provide better assistance. This article introduces NYAM, a robot designed to aid in the feeding process for individuals. Our robot is equipped with a mechanism to effectively recapture the person's attention whenever necessary. The mechanism is easily adjustable by the caregivers, allowing the straightforward customisation of the feeding service. The approach was evaluated, within a geriatric hospital, with 9 patients who used the robot for 5 consecutive days. We argue that incorporating enhanced social aspects into the robot is imperative to enhance the effectiveness and acceptance of this solution. © 2024 Copyright held by the owner/author(s), This work was supported by the project ROB-IN PLEC2021-007859 funded by MCIN/ AEI /10.13039/501100011033 and by the "European Union NextGenerationEU/PRTR"; project CHLOE-GRAPH PID2020-118649RB-I00 funded by MCIN/ AEI /10.13039/501100011033; and project PIONEER from PSPV., Peer Reviewed, Postprint (published version)

Aleppo Pine forests provide several ecosystem services for the local population as well as for the society in Tunisia. Knowing the citizens’ preferences is crucial to guide forest management strategies. This study aims to determine the social demand for key benefits provided by forests using the choice experiment modelling. Results show a high social awareness of the benefits derived from forests suggesting that citizens are willing to support forest management activities, especially for promoting the local economy., The research leading to these results has received funding from International Foundation for Science under Grant Agreement No. I-3-S-6234-1., Preprint

Large vertical cylindrical structure is an important type of structure in polarimetric synthetic aperture radar (PolSAR) images. Objects with this structure, such as oil tanks, granaries and rotor sails, attract much attention in multiple fields. Before detecting these targets with these structures, scattering mechanism analysis and feature extraction are necessary prerequisite steps. However, due to the lack of scattering mechanism analysis and characterization for such structures, traditional feature extraction methods, like polarimetric decomposition methods, usually fail to distinguish these targets. In this letter, according to high frequency approximation theory, the scattering mechanism of large vertical cylindrical structure with finite radius and height is analyzed. The coherency matrix of this structure with multiple pixels is derived further for scattering characterization. The model is called vertical cylindrical scattering model (VCDM), which is further introduced into a polarimetric decomposition method for feature extraction. Experiments prove that the model can describe the scattering mechanism of large vertical cylindrical structure accurately. Besides, the feature extraction method can effectively extract features for large vertical cylindrical structures in PolSAR images, which helps detect targets with this kind of structures., This work was supported in part by the National Natural Science Foundation of China under Grant 62271172 and Grant 61871158 and in part by the Aeronautical Science Foundation of China under Grant 20182077008., Peer Reviewed, Postprint (author's final draft)

A compact photonically-driven wireless emitter based on a Uni-Traveling-Carrier photodiode (UTC-PD) which directly connects to a short asymmetrical inductive dipole (SAID) antenna is presented. The design exploits the dependence of the UTC-PD output impedance with the reverse bias voltage to provide maximum power transfer via conjugate impedance matching at different operative frequencies within the Ka band (26.5–40 GHz) with 6 dB antenna directivity and 1 GHz 10 dB return loss channel width. Electro-optical transmission measurements confirm that the photodiode responsivity is maintained throughout the whole voltage swing used for reconfigurability., Peer Reviewed, Postprint (published version)

Accurate land cover information is pivotal in numerous planning and management activities. Synthetic Aperture Radar (SAR) data has emerged as a valuable resource for land cover assessment. Extracting scattering power components from Polarimetric SAR (PolSAR) data provides essential insights into the characteristics of land cover targets, aiding in their detailed characterization. Various techniques in radar polarimetry have been introduced to obtain scattering power components and explore their significance in land cover applications, typically leveraging full-polarimetric (full-pol) SAR data. However, applying these methods directly to dual-polarimetric (dual-pol) HH-HV or VV-VH data presents challenges due to the limited polarimetric information available compared to full-pol SAR data. Distinguishing between the scattering mechanisms of dihedral (or double-bounce) targets and trihedral (or surface) targets based solely on conventional polarimetric information is particularly challenging in dual-pol data compared to its full-pol counterpart. To address this limitation, our study introduces two indices (DpRBI and DpRSI) designed to characterize scattering from “dihedral-like” (e.g., buildings, bridges) and “surface-like” (e.g., water bodies, bare fields) targets in dual-pol SAR data. These indices, measuring the similarity of a given pixel to either a “dihedral-like” or a “surface-like” target, are then used in the Scattering Power Factorization Framework (SPFF) to derive the proposed scattering power components. The SPFF discerns the primary scattering power contribution within a resolution cell by factorizing the total power, employing the two indices. Our method applies to both Single Look Complex (SLC) and Ground Range Detected (GRD) dual-pol SAR data from operational platforms such as Sentinel-1 and the upcoming NISAR missions. We assess the proposed methodology using Sentinel-1 SLC and GRD SAR data for two scenarios. (1) Spatial variation in the scattering pow, Peer Reviewed, Postprint (author's final draft)

Towards supporting a myriad of new services and applications under highly heterogeneous operating conditions, while dynamically adapting to capacity and quality-of-service (QoS) demands, the sixth generation (6G) communication systems are required to undergo significant advances. Along with the proliferation of devices, a multitude of challenges remain towards aspired performance, versatility, security, and cost-effectiveness of next generation networks. The aim of this work is to identify said challenges and promising approaches, within the scenario of dense and complex urban deployments enabled by optical-wireless coexistence. Towards enabling such operation scenario, our 6G vision focuses on various aspects of four main innovation paradigms. First, as future systems target network capacities beyond the capabilities of current technologies, the scientific trend of pursuing radio frequencies edging towards the THz domain continues. To ensure reliable and efficient deployment and mobility under the cell densification paradigm, particularly in complex urban environments, novel approaches are required to address the challenges as latency, signal blockages, and unreliable handovers. Second, towards enabling efficient operation under the heterogeneous scenario, we highlight the cooperative coexistence paradigm as a key feature of the underlying physical layer architecture. Third, joint and holistic resource optimization is required towards dynamically optimized support of mm-wave and sub-THz operation while retaining legacy coexistence, where we consider features that may benefit from the research paths proposed within the second paradigm. Fourth, network security is identified as critical towards the market adoption of technologies proposed within the first paradigm, where we highlight aspects unique to our scenario and network vision. We provide a comprehensive overview of promising state-of-the-art approaches and identify relevant research gaps while holistically add, This work was supported by the European Union’s Horizon Europe research and innovation program under the Marie Skłodowska-Curie grant agreement No. 101073265 (EWOC), and the UKRI (UK Research and Innovation) Horizon Europe Guarantee Scheme with grant no: EP/X030342/1 (EWOC). Zoran Vujicic also thanks the research and innovation program under the Marie Skłodowska-Curie grant agreement No. 872897 (EXPLOR)., Peer Reviewed, Postprint (published version)

Currently, the greatest losses in the agricultural sector are caused by fungal diseases. One of the fungal diseases that has the greatest impact on a wide variety of crops, including grapes, is that caused by Botrytis cinerea. There is a growing demand for effective and, above all, sustainable solutions, with technology that incorporates only natural compounds from renewable resources as an alternative or complement to phytosanitary and synthetic treatments based on compounds that are potentially harmful to the environment. In this line of research, and with the aim of reducing the use of chemical additives in the food industry, the development of an extract of natural origin for post-harvest application on Muscat of Alexandria grapes has been proposed as the functional bioactive part of the edible coating. The extraction of thyme with distilled water at room temperature for 4 hours has been determined as the simplest and most efficient methodology possible in terms of in vivo growth of Botrytis cinerea on grapes. Additionally, the total antioxidant activity was determined by two different methodologies, FRAP and ABTS +, and values of 8308.05 ¿M ferrous sulphate/g thyme extract and 6222.25 ¿M Trolox/g thyme extract were obtained, respectively. When evaluating the physico-chemical parameters of grapes with thyme extract, it has been concluded that thyme extract reduces the percentage of weight loss, improves the overall appearance, brightness and colour of the grapes for 13 days. The sensory evaluation (overall appearance, colour, taste and purchase intention) was significantly better for the grapes with thyme extract. In addition, no considerable changes were observed with respect to the control grapes in parameters such as moisture, total solids, soluble solids and pH., Actualment les pèrdues més importants en el sector agrícola procedeixen de patologies causades per fongs. Una de les malalties fúngiques que té més repercussió sobre una àmplia varietat de cultius, entre elles el raïm, és la causada per Botrytis cinerea. Hi ha una creixent demanda de solucions eficaces i sobretot sostenibles, amb una tecnologia que incorpori únicament compostos naturals procedents de recursos renovables com a alternativa o complement als tractaments fitosanitaris i de síntesi a base de compostos potencialment perjudicials per al medi ambient. En aquesta línia de recerca, i amb l'objectiu de reduir l'ús d'additius químics a la indústria alimentària, s'ha plantejat el desenvolupament d'un extracte d'origen natural per aplicació en raïms Moscatell d'Alexandria postcollita que constitueixi la part bioactiva funcional del recobriment comestible. S'ha determinat l'extracció de farigola amb aigua destil·lada a temperatura ambient durant 4 hores com la metodologia més senzilla i eficient possible quant al creixement in vivo de Botrytis cinerea sobre el raïm. Addicionalment s'ha determinat de l'activitat antioxidant total per dues metodologies diferents, FRAP i ABTS+, i s'han obtingut valors de 8308.05 ¿M sulfat ferrós/g d'extracte de farigola i 6222,25 ¿M Trolox/g d'extracte de farigola respectivament. En avaluar els paràmetres fisicoquímics del raïm amb l'extracte de farigola, s'ha conclòs que l'extracte de farigola redueix el percentatge de pèrdua de pes, millora l'aparença general, la brillantor i el color del raïm durant 13 dies. L'avaluació sensorial (aparença general, color, sabor i intenció de compra) ha estat significativament millor per al raïm amb l'extracte de farigola. A més, no s'han apreciat canvis considerables respecte del raïm control en paràmetres com la humitat, els sòlids totals, els sòlids solubles i el pH., Actualmente las mayores pérdidas en el sector agrícola proceden de patologías causadas por hongos. Una de las enfermedades fúngicas que tiene mayor repercusión sobre una amplia variedad de cultivos, entre ellas la uva, es la causada por Botrytis cinerea. Hay una creciente demanda de soluciones eficaces y sobre todo sostenibles, con una tecnología que incorpore únicamente compuestos naturales procedentes de recursos renovables como alternativa o complemento a los tratamientos fitosanitarios y de síntesis a base de compuestos potencialmente dañinos para el medio ambiente. En esta línea de investigación, y con el objetivo de reducir el uso de aditivos químicos en la industria alimentaria, se ha planteado el desarrollo de un extracto de origen natural para aplicación en uvas Moscatel de Alejandría postcosecha que constituya la parte bioactiva funcional del recubrimiento comestible. Se ha determinado la extracción de tomillo con agua destilada a temperatura ambiente durante 4 horas como la metodología más sencilla y eficiente posible en cuanto al crecimiento in vivo de Botrytis cinerea sobre uva. Adicionalmente se ha determinado de la actividad antioxidante total por dos metodologías diferentes, FRAP y ABTS +, y se han obtenido valores de 8308.05 ¿M sulfato ferroso/g de extracto de tomillo y 6222,25 ¿M Trolox/g de extracto de tomillo respectivamente. Al evaluar los parámetros físico-químicos de la uva con el extracto de tomillo, se ha concluido que el extracto de tomillo reduce el porcentaje de pérdida de peso, mejora la apariencia general, el brillo y el color de la uva durante 13 días. La evaluación sensorial (apariencia general, color, sabor e intención de compra) ha sido significativamente mejor para la uva con el extracto de tomillo. Además, no se han apreciado cambios considerables respecto a las uvas control en parámetros como la humedad, sólidos totales, sólidos solubles y pH., Objectius de Desenvolupament Sostenible::12 - Producció i Consum Responsables, Objectius de Desenvolupament Sostenible::13 - Acció per al Clima

This work presents the first results of canopy height mapping with L -Band SAOCOM data by means of Polarimetric SAR Interferometry (PolInSAR). For this study case, a colocated temporal series of SAOCOM fully polarimetric images covering the year 2021 was acquired, with a temporal baseline of 8 to 16 days between each acquisition. The study area corresponds to managed forests in Corrientes, Argentina, one of the main forest production regions in the country. Field measurements provided by forest owners were available in order to validate the obtained results, along with canopy height measurements from the Global Ecosystem Dynamics Investigation mission. A multi-baseline PolInSAR approach was adopted, following the methodology proposed by previous works. The results show that this multi-baseline selection approach is more appropriate than a single-baseline one, given the high variability that SAOCOM presents in the spatial baseline between acquisitions, and the lack of orbital control over this parameter. The height maps obtained over a validation site yielded an average R2 of 0.72 and a mean RMSE of 2.35 m., in agreement with the figures obtained in similar studies. This study presents, for the first time, canopy height maps of 8 and 16-day temporal baselines, L -band, orbital interferograms. The conclusions yielded by this research represent a qualitative and quantitative evaluation of SAOCOM PolInSAR capabilities for forest height mapping. It is also relevant to assess the suitability of the RVoG model to characterize the structure of these forests with L-band data retrieved by the Argentinean constellation., This work was supported by the Spanish MCIN/AEI/10.13039/501100011033 under the Project INTERACTPID2020-114623RB-C32., Peer Reviewed, Postprint (published version)

This paper aims to analyze the scientific evolution and research trends concerning the water–energy–food (WEF) nexus, as well as its development within scientific databases. To achieve this, a bibliometric analysis has been conducted using publications sourced from Scopus and Web of science databases. This study examined key aspects such as primary journals, prominent authors, affiliated institutions, countries of origin, subject areas, and notable keywords. Furthermore, there is a dedicated section that delves into research and innovation gaps within publications related to the WEF nexus. Results reveal that research on the WEF nexus has experienced exponential growth over the past decade, with the majority of publications emerging between 2017 and 2023. The United States leads in this field, with engineering and environmental science being the predominant research categories, with Spain and Italy being the prominent countries in Europe. The WEF nexus concept in the agriculture sector is notably underdeveloped, particularly in its ties with the Sustainable Development Goals and the science–policy–society interface. The study stresses the importance of integrating health considerations into the WEF Nexus to understand the interconnections and their implications on public health, thereby enriching the Nexus approach with a critical dimension of human well-being. This situation underscores the urgent need to create a nexus community that bridges science and practice, and to incorporate this specialized discipline into university curricula., Peer Reviewed, Postprint (published version)

Dihedral is a common structure in polarimetric SAR images and can be found on many man-made targets. Many researchers have proposed different dihedral models, but the accuracy of these models is limited. In this case, the feature extraction methods based on these models are also not effective enough, which affects the subsequent applications such as target detection. Therefore, it is necessary to propose a new and accurate scattering model, which can be applied to dihedral with different orientation angles for feature extraction and target detection. In this paper, a general scattering model called modified oriented dihedral scattering model (MODM) is proposed based on physical optics (PO) and geometric optics (GO) of high-frequency approximation techniques. By analyzing the propagation and reflection of electromagnetic wave, MODM can accurately describe the scattering characteristic of dihedral for all observation conditions. In order to apply the model to real PolSAR images, MODM is introduced into a new feature extraction method, which is called five-scattering component polarimetric decomposition method (MODM-5SD). Feature extraction and target detection experiments of buildings with various oriented dihedral structures are performed using different data sets, which show that dihedral scattering components from oriented dihedral structures can be more effectively extracted by MODM-5SD. In addition, more buildings with oriented dihedral structures can be detected with the features from MODM-5SD. The experimental results show that MODM can more accurately describe the scattering characteristic of dihedral, which can be further applied for scattering characterization and feature extraction of targets with typical dihedral structures., This work was supported in part by the National Natural Science Foundation of China under Grant 62271172 and Grant 61871158, and in part by Aeronautical Science Foundation of China under Grant 20182077008., Peer Reviewed, Postprint (published version)

The ability to utilize resources to meet the need of growing diversity of communication services and user behavior marks the future of cognitive wireless communication systems. Cognitive wireless technologies for vehicular communications, in combination with Orbital Angular Momentum (OAM) modes aim at extending Non-Line-Of-Sight (NLOS) short-distance communications for smart mobility. In this regard, OAM antenna frameworks need to be developed to support these technologies. In this work, we describe a magnetoelectric dipole antenna framework supporting OAM modes. The framework is derived from moment tensors of specific vector spherical harmonic functions synthesized from dipoles. The antenna framework is discussed in terms of OAM generation, and it is validated numerically and experimentally for l = 1 OAM mode, achieving more than 500MHz operation bandwidth at the frequency of operation of 3.5GHz. Also, for l = 1 OAM mode, the null aligns precisely with the anticipated dimensions numerically computed., This work was financially supported by PDR-2014-2022/56-30157-2021-2A, 2021 SGR 01415 Q0818003F and Metropolis PLEC2021-007609 grants of the Generalitat de Catalunya and European Regional Development Fund (FEDER), by CICYT PID2019-107885GB-C31, PID2022-136869NB-C31 and Prueba de Concepto PDC2022-133091-I00 grants of the Agencia Estatal de Investigación (Spain) and Next Generation EU., Peer Reviewed, Postprint (author's final draft)

Synchronizing the local oscillators in multibeam satellites with the objective of coherent communications is still an open challenge. It has to be addressed to implement full-frequency reuse approaches, such as precoding techniques using the already deployed multibeam satellites. This article addresses the required phase synchronization to enable precoding techniques in multibeam satellite systems. It contains the detailed design of a frequency and phase compensation loop based on the proportional-integral controller, which deals with the phase drift introduced by the hardware components. Specifically, the phase noise of the local oscillators used for up and down conversion at each system element (gateway, satellite, and user terminals). The implementation of the two-state phase noise model used to emulate this phase drift is included in the article. Besides, a comparative analysis of several methods to combine the frequency and phase measurements obtained from the user terminals is also included. Finally, the performance of the proposed closed-loop synchronization method is validated through simulations using our in-house developed MIMO end-to-end satellite emulator based on SDR platforms., This research was funded by the Luxembourg National Research Fund (FNR) under the CORE project COHESAT: Cognitive Cohesive Networks of Distributed Units for Active and Passive Space Applications, grant reference [FNR11689919] and the project DISBuS: Dynamic Beam Forming and In-band Signalling for Next Generation Satellite Systems, grant reference [FNR13778945]. For the purpose of open access, the author has applied a Creative Commons Attribution 4.0 International (CCBY4.0) license to any Author Accepted Manuscript version arising from this submission. Additionally, this work has been supported by the European Space Agency under project number 4000122451/18/NL/NR ”Live Satellite Precoding Demonstration - CCN: MEO case (LiveSatPreDem).”, Peer Reviewed, Postprint (published version)

The Global Navigation Satellite Systems (GNSS), including the US’s GPS, China’s BDS, the European Union’s Galileo, and Russia’s GLONASS, offer real-time, all-weather, any-time, anywhere and high precision observations by transmitting L band signals continuously, which have been widely used for positioning, navigation and timing. With the development of GNSS technology, it has been found that GNSS-reflected signals can be used to detect Earth’s surface characteristics together with other signals of opportunity. In this paper, the current status and latest advances are presented on Global Navigation Satellite System-Reflectometry (GNSS-R) in theory, methods, techniques and observations. New developments and progresses in GNSS-R instruments, theoretical modeling, and signal processing, ground and space-/air-borne experiments, parameters retrieval (e.g. wind speed, sea surface height, soil moisture, ice thickness), sea surface altimetry and applications in the atmosphere, oceans, land, vegetation, and cryosphere are given and reviewed in details. Meanwhile, the challenges in the GNSS-R development of each field are also given. Finally, the future applications and prospects of GNSS-R are discussed, including multi-GNSS reflectometry, new GNSS-R receivers, GNSS-R missions, and emerging applications, such as mesoscale ocean eddies, ocean phytoplankton blooms, microplastics detection, target recognition, river flow, desert studies, natural hazards and landslides monitoring., This work was supported by the Henan International Science and Technology Cooperation Key Project (Grant No. 241111520700) and Strategic Priority Research Program Project of the Chinese Academy of Sciences (Grant No. XDA23040100)., Peer Reviewed, Postprint (published version)

In this paper a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. First, a review of the literature on the two-way transmittance method is presented. This method is a well-known lidar inversion method used to retrieve the optical properties of an aerosol–cloud layer between two molecular (i.e. aerosol and cloud-free) regions below and above, without the need to make any a priori assumptions about their optical and/or microphysical properties. Second, a simple mathematical expression of the two-way transmittance method is proposed for both ground-based and spaceborne lidar systems. This approach of the method allows the retrieval of the cloud optical depth, the cloud column lidar ratio and the vertical profile of the cloud backscatter coefficient. The method is illustrated for a cirrus cloud using measurements from the ground-based MPL and from the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Third, the database is then filtered with a cirrus identification criterion based on (and compared to) the literature using only lidar and radiosonde data. During the period from November 2018 to September 2022, 367 high-altitude cirrus clouds were identified at 00:00 and 12:00 UTC, of which 203 were successfully inverted with the two-way transmittance method. The statistical results of these 203 high-altitude cirrus clouds show that the cloud thickness is 1.8 ± 1.1 km, the mid-cloud temperature is −51 ± 8 ∘C and the linear cloud depolarization ratio is 0.32 ± 0.13. The application of the transmittance method yields an average cloud optical depth (COD) of 0.36 ± 0.45 and a mean effective column lidar ratio of 30 ± 19 sr. Statistical results of the errors associated with the two-way transmittance method retrievals are also provided. The highest occurrence of cirrus is observed in spring and the majority of cirrus clou, This research has been partly funded by the Spanish Agencia Estatal de Investigación (grant no. PID2019103886RB-I00) and the European Commission through the Horizon 2020 Programme (project ACTRIS IMP, grant agreement no. 871115; ATMO-ACCESS, grant agreement no. 101008004; GRASP-ACE, grant agreement no. 778349) and through the Horizon Europe Programme (project REALISTIC, grant agreement no. 101086690)., Peer Reviewed, Postprint (published version)

This study determined consumers' attitudes towards physical and mental wellness related to red meat consumption and their willingness to pay (WTP) more for the meat. In 2019, two online surveys of red meat eaters were conducted in the USA (n = 1000) and Australia (n = 523) using commercial platforms. Results showed that over 90% of respondents indicated interest in purchasing red meat to improve their wellness status. Additionally, about 85% indicated their WTP more for red meat for its wellness benefits, with Americans indicating stronger willingness than Australian respondents. The potential of meat consumption to improve overall wellness among red meat eaters was a dominant factor influencing consumers' WTP more. Other factors that increased WTP included frequency of meat consumption, physical exercise, sleep quality, number of children in a household, partnership status, and economic position. Outcomes from this study highlight a unique opportunity for the meat industry to position meat on its qualities that include wellness improvement if backed up with robust scientific evidence., This research was co-funded by Meat & Livestock Australia Donor Company and AgResearch Ltd. Strategic Science Investment Fund, SSIF-A25692 (Consumer Experience: Delivering Customized Food Attributes), Postprint (updated version)

In May–June 2019, smoke plumes from wildfires in Alberta, Canada, were advected all the way to Europe. To analyze the evolution of the plumes and to estimate the amount of smoke aerosols transported to Europe, retrievals from the spaceborne lidar CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) were used. The plumes were located with the help of a trajectory analysis, and the masses of smoke aerosols were retrieved from the CALIOP observations. The accuracy of the CALIOP mass retrievals was compared with the accuracy of ground-based lidars/ceilometer near the source in North America and after the long-range transport in Europe. Overall, CALIOP and the ground-based lidars/ceilometer produced comparable results. Over North America the CALIOP layer mean mass was 30¿% smaller than the ground-based estimates, whereas over southern Europe that difference varied between 12¿% and 43¿%. Finally, the CALIOP mass retrievals were compared with simulated aerosol concentrations from two reanalysis models: MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) and CAMS (Copernicus Atmospheric Monitoring System). The simulated total column aerosol optical depths (AODs) and the total column mass concentration of smoke agreed quite well with CALIOP observations, but the comparison of the layer mass concentration of smoke showed significant discrepancies. The amount of smoke aerosols in the model simulations was consistently smaller than in the CALIOP retrievals. These results highlight the limitations of such models and more specifically their limitation to reproduce properly the smoke vertical distribution. They indicate that CALIOP is a useful tool monitoring smoke plumes over secluded areas, whereas reanalysis models have difficulties in representing the aerosol mass in these plumes. This study shows the advantages of spaceborne aerosol lidars, e.g., being of paramount importance to monitor smoke plumes, and reveals the urgent need of future, This research has been supported by the Academy of Finland (grant nos. 339885 and 337552), the European Union (grant no. 101079201), the Hellenic Foundation for Research and Innovation (grant nos. 3995 and 07222), Horizon Europe (grant no. 101086690), Agencia Estatal de Investigación (grant no. PID2019-103886RB-I00), H2020 Environment (grant nos. 871115 and 101008004), and H2020 Excellent Science (grant no. 778349)., Peer Reviewed, Postprint (published version)

Mathematical modeling of neuronal dynamics has experienced a fast growth in the last decades thanks to the biophysical formalism introduced by Hodgkin and Huxley in the 1950s. Other types of models (for instance, integrate and fire models), although less realistic, have also contributed to understand neuronal dynamics. However, there is still a vast volume of data that have not been associated with a mathematical model, mainly because data are acquired more rapidly than they can be analyzed or because it is difficult to analyze (for instance, if the number of ionic channels involved is huge). Therefore, developing new methodologies to obtain mathematical or computational models associated with data (even without previous knowledge of the source) can be helpful to make future predictions. Here, we explore the capability of a wavelet neural network to identify neuronal (single-cell) dynamics. We present an optimized computational scheme that trains the ANN with biologically plausible input currents. We obtain successful identification for data generated from four different neuron models when using all variables as inputs of the network. We also show that the empiric model obtained is able to generalize and predict the neuronal dynamics generated by variable input currents different from those used to train the artificial network. In the more realistic situation of using only the voltage and the injected current as input data to train the network, we lose predictive ability but, for low-dimensional models, the results are still satisfactory. We understand our contribution as a first step toward obtaining empiric models from experimental voltage traces., DA has been funded by the Collaboration in University Departments AGAUR Grant (COLAB 2020). AG and EF have been partially funded by the MINECO-FEDER-UE-MTM Grant RTI2018-093860-B-C21, the Generalitat de Catalunya-AGAUR projects 2021SGR01039 (AG) and 2021SGR00376 (EF), the Grants PID-2021-122954NB-I00 and PID2022-137708NB-I00 funded by MCIN/ AEI/ 10.13039/ 501100011033 and by ERDF ‘A way of making Europe’ (AG) and the Severo Ochoa and María de Maeztu Program for Centers and Units of Excellence in R &D (CEX2020-001084-M) (AG). We are grateful to the Institut d’Organització i Control (IOC-UPC) for the access to its high-performance computing facilities to perform all the computations of this work., Postprint (published version)

The 2-D frequency-based omega-K method is known to be a suitable algorithm for fully focused SAR (FF-SAR) radar altimeter processors, as its computational efficiency is much higher than equivalent time-based alternatives without much performance degradation. In this article, we provide a closed-form description of a 2-D frequency-domain omega-K algorithm specific for instruments such as Poseidon-4 onboard Sentinel-6. The processor is validated with real data from point targets and over the open ocean. Applications such as ocean swell retrieval and lead detection are demonstrated, showing the potentiality of the processor for future operational global-scale products., This work was supported by the Industrial Doctorates Plan from the Secretary of Universities and Research of the Department of Business and Knowledge of the Government of Catalonia through Project SA.45217 with Expedient Number 094 under Grant Doctorats Industrials 2020., Peer Reviewed, Postprint (published version)

This document is the partial result of an ongoing satellite research activity carried out by Universitat Politècnica de Catalunya NanoSat Lab and i2CAT Foundation, submitted to the Horizon Europe Program in 2022., Thousands of rockets, spaceships, and satellites have been launched, resulting in a steady increase in the number of space debris notably in Low Earth Orbit (LEO) and Geostationary Orbit (GEO). Among the objects comprising space debris, defunct satellites are commonly found, which may have been abandoned in space due to various anomalies. While these satellite failures may not be catastrophic, certain subsystems could still be repurposed for alternative uses beyond their initial design. This study aims to assess the feasibility of “recycling” partially failed satellites, also known as “Zombie Satellites”, by statistically evaluating the severity of their anomalies and quantifying their remaining capabilities and limitations. By conducting a comprehensive statistical analysis, the anomalies have been categorized based on subsystem, orbit type, occurrence date during the satellite’s lifespan, and severity. Additionally, an analysis is presented to identify failed satellites from some of the current large constellations., This work was sponsored in part by the I+D+i project of UPC GENESIS project PID 2021-1264360B-C21 financed by MCIN/AEI. Additionally, this work was supported by the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union–NextGeneration EU , in the framework of the Recovery Plan, Transformation and Resilience (PRTR) (Call UNICO I+D 5G 2021, ref. number TSI-063000-2021-8-6GSatNet-SeS)., Peer Reviewed, Postprint (published version)

Livestock farming has a detrimental effect on the environment since it generates a lot of gas emissions. In pig farming, the use of feed is among the substantial sources of animal farm emissions among the European Union. Nevertheless, the use of Low Dietary Crude Protein (LCP) may reduce the environmental impacts of pig farming and provide diverse ecosystem services (ESs). Concurrently, these pig diets alternatives may result more expensive than the conventional ones, which may negatively affect farmers' intention to adopt these alternatives. Citizens’ payment for ESs may be a viable strategy to motivate farmers to implement more sustainable pig diets. The primary objective of this study is to assess the extent to which citizens of Catalonia (Spain) are willing to pay for the ESs generated by the implementation of a LCP diet in pig production. In pursuit of this goal, we conducted an online survey among 501 citizens, including a Discrete Choice Experiment. Participants evaluated three feed scenarios, and their choices were scrutinized using conditional logit model. Results revealed that citizens prefer the new pig diets, including both LCP and Very LCP (VLCP) diets, over the conventional pig diet. However, there is a clear preference toward the VLCP diet justified by their willingness to pay (WTP) of €67/year/adult., The authors gratefully acknowledge the financial support of this study from Metex-Noovistago., Postprint (updated version)

Monitoring vegetation moisture conditions is paramount to better understand and assess drought impacts on vegetation, enhance crop yield predictions, and improve ecosystem models. Passive microwave remote sensing allows retrievals of the vegetation optical depth (VOD; [unitless]), which is directly proportional to the vegetation water content (VWC; in units of water mass per unit area [kg/m2]). However, VWC is largely dependent on the dry biomass and structure imprints on the VOD signal. Previously, statistical models have been used to isolate the water component from the biomass and structure components. Physically-based approaches have not yet been proposed for this goal. In this study, we present a multi-sensor semi-physical approach to retrieve the vegetation moisture from the VOD and express it as Live Fuel Moisture Content (LFMC [%]; the percentage of water mass per dry biomass unit). The study is performed in the western United States for the period April 2015 – December 2018. There, in situ LFMC samples are available for assessment. We rely on a VOD model based on vegetation height data from GEDI/Sentinel-2 and radar backscatter from Sentinel-1, which account for the biomass and structure components. Vegetation moisture is retrieved at L-, X- and Ku-bands by minimizing the difference between the modeled VOD and the VOD estimates from SMAP (L-band) and AMSR-2 (X- and Ku-band) satellites. Results show that the LFMC retrievals are independent of canopy height, land cover, and radar backscatter, demonstrating the capability of the proposed algorithm to separate water dynamics from the biomass/structure component in VOD. LFMC estimates at X- and Ku-bands reproduce well the expected spatio-temporal dynamics of in situ LFMC. Results show good agreement with in situ at a regional scale, with Pearson's correlations (r) between in situ LFMC samples and LFMC estimates of 0.64 (Ku-band), 0.60 (X-band) and 0.47 (L-band). Similar results are obtained independently for shr, The work of D. Chaparro was supported by the XXXIII Ramón Areces Postdoctoral Fellowship and by MIT and the “la Caixa” Foundation (ID 100010434) under Grant LCF/ PR/MIT19/51840001 (MIT-Spain Seed Fund; D. Entekhabi, D. Chaparro). M. Piles thanks the support of Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital through the project AI4CS CIPROM/2021/56. M. Vall-llossera acknowledges funding from the Grant PID2020-114623RB-C32, funded by MCIN/AEI/10.13039/ 501100011033, and from the ERDF under Grant RTI2018-096765-A- 100. Also, the authors are grateful to MIT for supporting this research with the MIT-Germany Seed Fund (D. Entekhabi, T. Jagdhuber) and with the MIT-Belgium Seed Fund (D. Entekhabi, F. Jonard). A.F. Feldman was supported by both the ECOSTRESS science team and by a NASA Terrestrial Ecology scoping study for a dryland field campaign., Peer Reviewed, Postprint (author's final draft)

The multi-temporal polarimetric SAR (PolSAR) data contains the scattering change information during the growth of crops. However, the current classification methods usually directly use the addition of features extracted at single-temporal or use the temporal and spatial variations of certain features, not really exploring the complete scattering variation information. The specific data representation models for multi-temporal PolSAR data should combine time with polarimetry to characterize the scattering variations. However, the characterization and utilization of such kind of models are inadequate. In this article, we construct data representation model based on the power form of coherence matrix to comprehensively represent all kinds of scattering mechanism variation, which is full-rank positive semi-definite Hermitian matrix. We extract new time-variant scattering features and design vision transformer classifier accordingly for crop classification. Experiment results on RADARSAT-2 datasets show that the proposed power representation model outperforms other models., Peer Reviewed, Postprint (published version)

Stakeholders’ preferences are a key element for the successful introduction of innovations in agri-food value chains. In this research we use of the Analytic Hierarchy Process (AHP) as a multi-criteria decision-making tool to analyse the preferences of farmers, consumers, and other stakeholders such as retailers, restaurants and processing companies in the tomato agri-food value chain in Catalonia. From an array of several social, economic, and environmental criteria and attributes, results showed that the economic aspects are the main driver factors in the stakeholders’ decisions, although certain opportunities related to product quality and sustainability are detected, especially among consumers. The AHP methodology allowed to discriminate among the different analysed factors and found to be a useful tool to assess the innovations acceptance in the agri-food supply chain., Postprint (published version)

Frailty is a crucial indicator in determining the well-being of older adults in terms of their health. With the growing number of elderly people, the demand for geriatricians is increasing, which means that they have less time to spend with each patient. The current methods for frailty assessment use simple tests that are time-consuming and do not require specific medical expertise. To address this issue, this paper proposes the use of social robots to assess frailty autonomously. It presents a practical proposal that defines the robot’s behavior and explains the design and implementation concepts. Finally, it discusses some of the challenges that may arise from introducing social robots as frailty evaluators., This work was supported by the project ROB-IN PLEC2021-007859 funded by MCIN/ AEI /10.13039/501100011033 and by the "European Union NextGenerationEU/PRTR"; project CHLOE-GRAPH PID2020-118649RB-I00 funded by MCIN/AEI /10.13039/501100011033; and the 23S06141-001 FRAILWATCH project funded by Barcelona Ciencia 2020-2023 Plan., Peer Reviewed, Postprint (published version)

In this paper, we assess the role of emotions in choices. We elicited emotions using an innovative facial expression analysis approach, comparing the results to those from a traditional hedonic liking scale. To this end, we conduct an experiment combing surveys and actual wine tasting. The results show a positive and significant relationship between positive emotions (joy), positive experiences (valence), and wine choices, especially in the case of wines with credence attributes (organic and selected vintage organic wines). Moreover, we conclude that facial recognition mechanisms can be useful to elicit evoked emotions and provide complementary information to the traditional liking scales to better understand decision making., Postprint (updated version)

This study proposes a new method for the detection of facial expressions of pain using a 3D profiler that combines a multiple-input-multiple-output (MIMO) radar system with a machine learning (ML) model (ML-MIMO radar profiler). It offers a solution for pain detection of facial expressions in a non-invasive, non-intrusive, and cost-effective manner. The ML-MIMO radar profiler employs six radars behind a lens to monitor changes in six facial regions and build a 3D facial profile with real-time facial activity information. A dielectric lens was used to ensure an optimal beam size to effectively illuminate each facial region. Signal processing is performed using dynamic time deformation to determine the longitudinal distance and a discrete stationary wavelet transform to filter the signal and improve accuracy. The information from the 3D profiler was compared with the facial action coding system (FACS) to determine actual facial expressions. A machine learning algorithm was trained to learn action units from the FACS and compare them with the information provided by the ML-MIMO radar profiler, thereby performing facial expression classification. In this study, we analyzed four facial expressions: hapiness, sadness, anger, and pain. Identification and classification were performed using a machine-learning model based on multilayer perceptrons. The results revealed 92% accuracy of the system for pain expression, whereas expressions of happiness, sadness, and anger were detected with 88, 86, and 87% accuracy, respectively., This work was supported in part by the Spanish ‘‘Comision Interministerial de Ciencia y Tecnologia’’ (CICYT) under Project PID2019-107885GB-C31, Project PID2022-136869NB-C31, and Project MDM2016-0600; in part by Metropolis under Grant PLEC2021-007609; in part by the Catalan Research Group, Centre Específic de Recerca en Comunicació i Detecció-UPC (CommSensLab-UPC), under Grant 2021 SGR 01415; and in part by the ‘‘Secretaría Nacional de Educación Superior, Ciencia, Tecnología e Innovación’’ (SENESCYT) from the Ecuadorian Government., Peer Reviewed, Postprint (published version)

Adopting genome editing with the trait of pest resistance contributes to sustainable development by reducing pesticide use. Developed by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology, CRISPR rice is resistant to two of its most destructive insect pests. However, there exists a trade-off between pest resistance and lower potential yield. In the presence of uncertainty of pest severity, adopting CRISPR rice demonstrates positive environmental benefits at its optimal planting ratio, estimated based on a microeconomic model extended with environmental externalities of rice cultivation. We estimate the optimal planting ratio to be 37%, with the environmental benefit of co-planting CRISPR rice to be 560 million US dollars annually in China. The environmental benefit accounts for 4–22% of the total value of co-planting CRISPR rice in the Monte Carlo simulations. Regional heterogeneity regarding optimal planting ratio and environmental benefit is studied for 12 major rice-cultivating provinces in China. We conclude with policy implications that policymakers need to consider the vast environmental benefit of CRISPR rice adoption to have a more comprehensive view of its economic and environmental market potential, contributing to the heated debate on regulating CRISPR technology in China and worldwide., Postprint (published version)

Microwaves have proven their imaging capabilities to visualize the body composition for medical applications, thanks to their penetration inside biological structures. In this context, this article presents a novel methodology that aims to extract not just the internal morphology, but also the brain’s functional activity using the UWB pulse amplitude modulation (PAM) technique to have simultaneously functional monitoring and imaging capability and apply it to monitor the Parkinson’s disease (PD). The radio-frequency system is composed of two orthogonal sets of double UWB probes operating in the frequency range of 0.5–1.5 GHz. An experimental setup has been devised that avoids complex in vivo testing, albeit allows a system proof-of-concept validation. A bio-tag (BT) consisting of an optically modulated photodiode is used to emulate local medium changes associated with cell activity. The proposed system is used to first extract the modeled brain action potential (AP) to validate the performance of the BT and then to monitor the PD based on the beta frequency band character within basal ganglia–thalamocortical (BGTC) which is a key marker for the PD. The results show a good capability of locating and differentiating the signals generated within the phantom by the BT, alternatively emulating the healthy and PD’s state, based on the frequency. The obtained results of the functional monitoring technique on distinguishing the healthy from nonhealthy brain model activity, as well as in the phantom mimicking the average proprieties of a human head, will serve as a basis for detecting functional diseases in the future., This work was supported in part by Comision Interministerial de Ciencia y Tecnologia (CICYT) PID2019-107885GB-C31, PID2022-136869NB-C31, Catalan Research Group 2021 SGR 01415, Metropolis PLEC2021-007609, (FI-SDUR) under Grant 2021 FISDU 00195; in part by the PDR-2014-2022/56-30157-2021-2A grant of the Generalitat de Catalunya; and in part by the Prueba de Concepto PDC2022-133091-I00 grants of the Ministerio de Ciencia, Innovación y Universidades (Spain)., Peer Reviewed, Postprint (published version)