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Soil organic carbon stocks in native forest of Argentina:a useful surrogate for mitigation and conservation planning under climate variability

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Ecological Processes 2024年第1期13卷 3-24页

作者： Pablo L.Peri juan Gaitán Matías Mastrangelo Marcelo nosetto Pablo E.Villagra Ezequiel Balducci martín Pinazo Roxana P.Eclesia Alejandra Von Wallis Sebastián Villarino Francisco Alaggia Marina González Polo Silvina Manrique Pablo A.Meglioli Julián Rodríguez-Souilla martín Mónaco Jimena E.Chaves Ariel Medina Ignacio Gasparri Eugenio alvarez Arnesi María Paula Barral Axel von Müller norberto M.Pahr Josefina Uribe Echevarria Pedro Fernández Marina Morsucci Dardo López juan manuel Cellini Leandro alvarez Ignacio Barberis Hernán Colomb Ludmila La Manna Sebastián Barbaro Cecilia Blundo Ximena Sirimarco Laura Cavallero Gualberto Zalazar Guillermo martínez Pastur Instituto nacional de Tecnología Agropecuaria (InTA) Universidad nacional de la Patagonia Austral (UnPA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Universidad nacional de Luján Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP) Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científicas y Técnicas(CONICET ) CCT San Luis Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Instituto Argentino de nivología Glaciología y Ciencias Ambientales (IANIGLA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Universidad Nacional de Cuyo Instituto de Investigaciones en Biodiversidad y Medioambiente (InIBIOMA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Instituto de Investigaciones en Energía no Convencional CCT Salta-JujuyConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Laboratorio de Recursos Agroforestales Centro Austral de Investigaciones Científicas (CADIC) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Dirección nacional de Bosques Ministerio de Ambiente y Desarrollo Sostenible de la Nación Instituto de Ecología Regional Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET )Universidad Nacional de Tucumán Universidad nacional de Rosario Instituto de Investigaciones en Ciencias Agrarias de Rosario Centro Científico Tecnológico CONICET Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP) Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Laboratorio de Investigaciones en Maderas (LIMAD) Universidad Nacional de La Plata (UNLP) Administración de Parques nacionales (APn) Parque Nacional Los Alerces Centro de Estudios Ambientales Integrados (CEAI) Universidad Nacional de la Patagonia San Juan Bosco (UNPASJB) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET )

Background The nationally determined contribution（nDC） presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United nations Framework Conven-tion on Climate Change（UnFCCC） on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation（REDD+）. In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon（SOC） stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under cli-mate variability due to a lack of information. The objectives of this study were:（i） to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and（ii） to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate *** We used 1040 forest soil samples（0–30 cm） to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covari-ates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index（EVI） and land surface temperature（LST） images from Landsat *** SOC model（0–30 cm depth） prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C（2.71–2.84 Pg C with a probability of 90%） for a total area of 460,790 km2,

关键词： Soil organic carbon Biodiversity native forest Climate change mitigation Modelling Resilience

Improved organs at risk segmentation based on modified U‐net with self‐attention and consistency regularisation

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 850-865页

作者： Maksym Manko Anton Popov juan manuel Gorriz Javier Ramirez Electronic Engineering Department Igor Sikorsky Kyiv Polytechnic InstituteKyivUkraine Department of Signal Theory Telematics and CommunicationsUniversity of GranadaGranadaSpain

Cancer is one of the leading causes of death in the world,with radiotherapy as one of the treatment *** planning starts with delineating the affected area from healthy organs,called organs at risk(OAR).A new approach to automatic OAR seg-mentation in the chest cavity in Computed Tomography(CT)images is *** proposed approach is based on the modified U‐net architecture with the Resnet‐34 encoder,which is the baseline adopted in this *** new two‐branch CS‐SA U‐net architecture is proposed,which consists of two parallel U‐net models in which self‐attention blocks with cosine similarity as query‐key similarity function(CS‐SA)blocks are inserted between the encoder and decoder,which enabled the use of con-sistency *** proposed solution demonstrates state‐of‐the‐art performance for the problem of OAR segmentation in CT images on the publicly available SegTHOR benchmark dataset in terms of a Dice coefficient(oesophagus-0.8714,heart-0.9516,trachea-0.9286,aorta-0.9510)and Hausdorff distance(oesophagus-0.2541,heart-0.1514,trachea-0.1722,aorta-0.1114)and significantly outperforms the *** current approach is demonstrated to be viable for improving the quality of OAR segmentation for radiotherapy planning.

关键词： 3‐D computer vision deep learning deep neural networks image segmentation medical image processing object segmentation

Guest Editorial:Knowledge‐based deep learning system in bio‐medicine

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 787-789页

作者： Yu‐Dong Zhang juan manuel Górriz University of Leicester LeicesterUK University of Granada GranadaSpain

numerous healthcare procedures can be viewed as medical sector *** the modern era,computers have become indispensable in the realm of medical decision‐***-ever,the common view of computers in the medical field typically extends only to applications that support doctors in diagnosing *** more tightly intertwine computers with the biomedical sciences,professionals are now more frequently utilising knowledge‐driven deep learning systems(KDLS)and their foundational technologies,especially in the domain of neuroimaging(nI).

关键词： learning computer doctor

GAn‐MD:A myocarditis detection using multi‐channel convolutional neural networks and generative adversarial network‐based data augmentation

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 866-878页

作者： Hengame Ahmadi Golilarz Alireza Azadbar Roohallah Alizadehsani juan manuel Gorriz Department of Medical Radiation Engineering Faculty of EngineeringLahijan BranchIslamic Azad UniversityLahijanIran Department of Medical Radiation Engineering Lahijan BranchIslamic Azad UniversityLahijanIran Institute for Intelligent Systems Research and Innovation(IISRI) Deakin UniversityWaurn PondsVictoriaAustralia Data Science and Computational Intelligence Institute University of GranadaGranadaSpain

Myocarditis is a significant public health concern because of its potential to cause heart failure and sudden *** standard invasive diagnostic method,endomyocardial bi-opsy,is typically reserved for cases with severe complications,limiting its widespread ***,non‐invasive cardiac magnetic resonance(CMR)imaging presents a promising alternative for detecting and monitoring myocarditis,because of its high signal contrast that reveals myocardial *** assist medical professionals via artificial intelligence,the authors introduce generative adversarial networks‐multi discriminator(GAn‐MD),a deep learning model that uses binary classification to diagnose myocarditis from CMR *** approach employs a series of convolutional neural networks(Cnns)that extract and combine feature vectors for accurate *** authors suggest a novel technique for improving the classification precision of *** generative adversarial networks(GAns)to create synthetic images for data augmentation,the authors address challenges such as mode collapse and unstable *** a reconstruction loss into the GAn loss function requires the generator to produce images reflecting the discriminator features,thus enhancing the generated images'quality to more accurately replicate authentic data ***,combining this loss function with other reg-ularisation methods,such as gradient penalty,has proven to further improve the perfor-mance of diverse GAn models.A significant challenge in myocarditis diagnosis is the imbalance of classification,where one class dominates over the *** mitigate this,the authors introduce a focal loss‐based training method that effectively trains the model on the minority class *** GAn‐MD approach,evaluated on the Z‐Alizadeh Sani myocarditis dataset,achieves superior results(F‐measure 86.2%;geometric mean 91.0%)compared with other deep learning models and traditional machine learning methods.

关键词： 2‐D 3‐D

Improving the radiological diagnosis of hepatic artery thrombosis after liver transplantation: Current approaches and future challenges

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World Journal of Transplantation 2024年第1期14卷 1-8页

作者： Cristian Lindner Raúl Riquelme Rodrigo San martín Frank Quezada Jorge Valenzuela juan P Maureira martín Einersen Department of Radiology Faculty of MedicineUniversity of ConcepciónConcepción 4030000Chile Department of Radiology Hospital Clínico Regional Guillermo Grant BenaventeConcepción 4030000Chile Department of Statistics Catholic University of MauleTalca 3460000Chile neurovascular Unit Department of RadiologyHospital Clínico Regional Guillermo Grant BenaventeConcepción 4030000Chile

Hepatic artery thrombosis(HAT)is a devastating vascular complication following liver transplantation,requiring prompt diagnosis and rapid revascularization treatment to prevent graft *** present,imaging modalities such as ultrasound,computed tomography,and magnetic resonance play crucial roles in diagnosing *** imaging techniques have improved sensitivity and specificity for HAT diagnosis,they have limitations that hinder the timely diagnosis of this *** this sense,the emergence of artificial intelligence(AI)presents a transformative opportunity to address these diagnostic *** development of machine learning algorithms and deep neural networks has demonstrated the potential to enhance the precision diagnosis of liver transplant complications,enabling quicker and more accurate detection of *** article examines the current landscape of imaging diagnostic techniques for HAT and explores the emerging role of AI in addressing future challenges in the diagnosis of HAT after liver transplant.

关键词： Liver transplantation Postoperative complications Hepatic artery Thrombosis Radiology Artificial intelligence

nickel-based cerium zirconate inorganic complex structures for CO_(2)valorisation via dry reforming of methane

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Journal of Environmental Sciences 2024年第6期140卷 12-23页

作者： juan Luis martín-Espejo Loukia-Pantzechroula Merkouri Jesús Gándara-Loe José Antonio Odriozola Tomas Ramirez Reina Laura Pastor-Pérez Department of Inorganic Chemistry and Material Sciences Institute of Seville University of Seville-CSICSeville 41092Spain Department of Chemical and Process Engineering University of SurreyGuildford GU27XHUnited Kingdom

The increasing anthropogenic emissions of greenhouse gases(GHG)is encouraging extensive research in CO_(2)*** reforming of methane(DRM)depicts a viable strategy to convert both CO_(2)and CH4into syngas,a worthwhile chemical *** the different active phases for DRM,the use of nickel as catalyst is economically favourable,but typically deactivates due to sintering and carbon *** stabilisation of ni at different loadings in cerium zirconate inorganic complex structures is investigated in this work as strategy to develop robust ni-based DRM *** and TPR-H2analyses confirmed the existence of different phases according to the ni loading in these ***,superficial ni is observed as well as the existence of a CeniO_(3)perovskite *** catalytic activity was tested,proving that 10 wt.%ni loading is the optimum which maximises *** catalyst was also tested in long-term stability experiments at 600and 800℃in order to study the potential deactivation issues at two different *** 600℃,carbon formation is the main cause of catalytic deactivation,whereas a robust stability is shown at 800℃,observing no sintering of the active phase evidencing the success of this strategy rendering a new family of economically appealing CO_(2)and biogas mixtures upgrading catalysts.

关键词： CO_(2)conversion Dry reforming of methane nickel catalysts Pyrochlore Cerium zirconate

Promotion of structural plasticity in area V2 of visual cortex prevents against object recognition memory deficits in aging and Alzheimer's disease rodents

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neural Regeneration Research 2024年第8期19卷 1835-1841页

作者： Irene navarro-Lobato Mariam Masmudi-martín manuel F.López-Aranda juan F.López-Téllez Gloria Delgado Pablo Granados-Durán Celia Gaona-Romero marta Carretero-Rey Sinforiano Posadas María E.Quiros-Ortega Zafar U.Khan Laboratory of neurobiology Centro de Investigaciones Médico Sanitarias(CIMES)University of MalagaMalagaSpain Department of Medicine Faculty of MedicineUniversity of MalagaMalagaSpain Centro de Investigación Biomédica en Red de Enfermedades neurodegenerativas(CIBERnED) Institute of Health Carlos IIIMadridSpain the Donders Institute for Brain Cognition and Behaviour Radboud UniversityNijmegenThe Netherlands the Brain Metastasis Group National Cancer Research Centre(CNIO)MadridSpain the Department of neurobiology University of California-Los AngelesLos AngelesCAUSA

Memory deficit,which is often associated with aging and many psychiatric,neurological,and neurodegenerative diseases,has been a challenging issue for *** till now,all potential drug candidates have failed to produce satisfa ctory ***,in the search for a solution,we found that a treatment with the gene corresponding to the RGS14414protein in visual area V2,a brain area connected with brain circuits of the ventral stream and the medial temporal lobe,which is crucial for object recognition memory(ORM),can induce enhancement of *** this study,we demonstrated that the same treatment with RGS14414in visual area V2,which is relatively unaffected in neurodegenerative diseases such as Alzheimer s disease,produced longlasting enhancement of ORM in young animals and prevent ORM deficits in rodent models of aging and Alzheimer’s ***,we found that the prevention of memory deficits was mediated through the upregulation of neuronal arbo rization and spine density,as well as an increase in brain-derived neurotrophic factor(BDnF).A knockdown of BDnF gene in RGS14414-treated aging rats and Alzheimer s disease model mice caused complete loss in the upregulation of neuronal structural plasticity and in the prevention of ORM *** findings suggest that BDnF-mediated neuronal structural plasticity in area V2 is crucial in the prevention of memory deficits in RGS14414-treated rodent models of aging and Alzheimer’s ***,our findings of RGS14414gene-mediated activation of neuronal circuits in visual area V2 have therapeutic relevance in the treatment of memory deficits.

关键词： behavioral performance brain-derived neurotrophic factor cognitive dysfunction episodic memory memory circuit activation memory deficits memory enhancement object recognition memory prevention of memory loss regulator of G protein signaling

Vertical Displacement Measurement in a Slow-Moving Sinkhole Using BOTDA

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Photonic Sensors 2024年第1期14卷 23-39页

作者： Pascual SEVILLAnO Javier PRECIADO-GARBAYO Jorge SEVIL Francisco GUTIERREZ juan JmartinEZ Sonia martin-LOPEZ Miguel GOnZALEZ-HERRAEZ Aragon Institute of Engineering Research(I3A) Universidad de ZaragozaZaragoza 50018Spain Electronic Enginering and Communicaton Dpartment EINAUniversidad de ZaragzaZaragza 50018Spain Aragon Photonics Labs. Zaragoza 50009Spain Department of Earth Sciences Universidad de ZaragozaZaragoza 50009Spain Department of Electronics Escuela Politecnica SuperiorUniversidad de AlcalaMadrid 28805Spain

The effectiveness of monitoring and early-warning systems for ground deformation phenomena,such as sinkholes,depends on their ability to accurately resolve the ongoing ground displacement and detect the subtle deformation preceding catastrophic *** sinkholes with a slow subsidence rate and diffuse edges pose a significant challenge for subsidence monitoring due to the low deformation rates and limited lateral strain *** this work,we satisfactorily illustrate the practicality of the Brillouin optical time domain analysis(BOTDA)to measure the spatial-temporal patterns of the vertical displacement in such challenging slow-moving sagging *** assess the performance of the approach,we compare the strain recorded by the distributed optical fiber sensor with the vertical displacement measured by high-precision *** results show a good spatial correlation with the ability to identify the maximum subsidence *** is also a good temporal correlation with the detection of an acceleration phase in the subsidence associated with a flood event.

关键词： Distributed fiber optic sensing(DFOS) vertical displacement measurement slow subsidence rate sinkhole hazard early-warning system

Taurine: a promising nutraceutic in the prevention of retinal degeneration

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neural Regeneration Research 2024年第3期19卷 606-610页

作者： Diego García-Ayuso Johnny Di Pierdomenico Ana martínez-Vacas manuel Vidal-Sanz Serge Picaud María PVillegas-Pérez Grupo de Investigación Oftalmología Experimental Departamento de OftalmologíaOptometríaOtorrinolaringología y Anatomía PatológicaFacultad de MedicinaUniversidad de MurciaInstituto Murciano de Investigación Biosanitaria(IMIB)Campus de Ciencias de la SaludMurciaEspaña Sorbonne Université INSERMCNRSInstitut de la VisionParisFrance

Taurine is considered a non-essential amino acid because it is synthesized by most ***,dietary intake of taurine may be necessary to achieve the physiological levels required for the development,maintenance,and function of certain *** may be especially important for the *** concentration of taurine in the retina is higher than that in any other tissue in the body and taurine deficiency causes retinal oxidative stress,apoptosis,and degeneration of photoreceptors and retinal ganglion *** plasma taurine levels may also underlie retinal degeneration in humans and therefore,taurine administration could exert retinal neuroprotective *** has antioxidant,anti-apoptotic,immunomodulatory,and calcium homeostasis-regulatory *** review summarizes the role of taurine in retinal health and disease,where it appears that taurine may be a promising nutraceutical.

关键词： amino acid anti-inflammatory antioxidant gamma-aminobutyric acid nutraceutical photoreceptor degeneration retina retinitis pigmentosa taurine