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Global spectra of plant litter carbon, nitrogen and phosphorus concentrations and returning amounts
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Yuan, Ji (Fujian Normal University. School of Geographical Sciences) ;
Wu, Fuzhong (Fujian Normal University. School of Geographical Sciences) ;
Peng, Changhui (University of Quebec. Institute of Environment Sciences) ;
Peñuelas, Josep (Centre de Recerca Ecològica i d'Aplicacions Forestals) ;
Vallicrosa Pou, Helena (Centre de Recerca Ecològica i d'Aplicacions Forestals) ;
Sardans i Galobart, Jordi (Centre de Recerca Ecològica i d'Aplicacions Forestals) ;
Peng, Yan (Fujian Normal University. School of Geographical Sciences) ;
Wu, Qiqian (Zhejiang A & F University. State Key Laboratory of Subtropical Silviculture) ;
Li, Zimin (Université catholique de Louvain. Earth and Life Institute) ;
Heděnec, Petr (University Malaysia Terengganu. Institute of Tropical Biodiversity and Sustainable Development) ;
Li, Zhijie (Forschungszentrum Jülich GmbH. Institute of Bio- and Geosciences) ;
Tan, Siyi (Fujian Normal University. School of Geographical Sciences) ;
Yuan, Chaoxiang (Fujian Normal University. School of Geographical Sciences) ;
Ni, Xiangyin (Fujian Normal University. School of Geographical Sciences) ;
Yue, Kai (Fujian Normal University. School of Geographical Sciences)
Litter decomposition is a key ecological process that determines carbon (C) and nutrient cycling in terrestrial ecosystems. The initial concentrations of C and nutrients in litter play a critical role in this process, yet the global patterns of litter initial concentrations of C, nitrogen (N) and phosphorus (P) are poorly understood. [...]
2024 -  10.1111/1365-2745.14250
Journal of Ecology, Vol. 112, issue 4 (April 2024) , p. 717-729
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10 p, 859.5 KB |
Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks
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Zhang, Y. (University of Oxford) ;
Ghose, U. (University of Oxford) ;
Buckley, N.J. (University of Oxford) ;
Engelborghs, S. (Vrije Universiteit Brussel) ;
Sleegers, K. (University of Antwerp) ;
Frisoni, G.B. (Department of Psychiatry. University of Geneva) ;
Wallin, A. (University of Gothenburg) ;
Lleó, Alberto (Institut d'Investigació Biomèdica Sant Pau) ;
Popp, J. (University of Zürich) ;
Martinez-Lage, P. (CITA-Alzheimer Foundation) ;
Legido-Quigley, C. (Steno Diabetes Center) ;
Barkhof, F. (University College London) ;
Zetterberg, H. (Kong Kong Center for Neurodegenerative Diseases) ;
Visser, P.J. (VU University Medical Center) ;
Bertram, L. (University of Oslo) ;
Lovestone, S. (Janssen RD) ;
Nevado-Holgado, Alejo (University of Oxford) ;
Shi, L. (University of Oxford) ;
Universitat Autònoma de Barcelona
Background and objective: Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. [...]
2022 - 10.3389/fnagi.2022.1040001
Frontiers in aging neuroscience, Vol. 14 (29 2022) , p. 1040001
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9 p, 484.1 KB |
Classification of suicidal thoughts and behaviour in children : results from penalised logistic regression analyses in the Adolescent Brain Cognitive Development study
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Van Velzen, L.S. (University of Melbourne) ;
Toenders, Y.J. (Orygen) ;
Avila-Parcet, Aina (Institut d'Investigació Biomèdica Sant Pau) ;
Dinga, R. (Radboud University) ;
Rabinowitz, J.A. (Johns Hopkins University) ;
Campos, A.I. (The University of Queensland) ;
Jahanshad, N. (University of Southern California) ;
Rentería, M.E. (The University of Queensland) ;
Schmaal, L. (Orygen) ;
Universitat Autònoma de Barcelona
Despite efforts to predict suicide risk in children, the ability to reliably identify who will engage in suicide thoughts or behaviours has remained unsuccessful. Aims We apply a novel machine-learning approach and examine whether children with suicide thoughts or behaviours could be differentiated from children without suicide thoughts or behaviours based on a combination of traditional (sociodemographic, physical health, social-environmental, clinical psychiatric) risk factors, but also more novel risk factors (cognitive, neuroimaging and genetic characteristics). [...]
2022 - 10.1192/bjp.2022.7
The British journal of psychiatry, Vol. 220 Núm. 4 (february 2022) , p. 210-218
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16 p, 876.9 KB |
Business Partner Portal
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Ferraz Robles, Raúl ;
Talló Sendra, Marc, dir. (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació) ;
Universitat Autònoma de Barcelona.
Escola d'Enginyeria
Business Partner Portal es una iniciativa por parte de la empresa Lakmé para mejorar todo el proceso de compra y recepción de pedidos en las instalaciones. La aplicación estará totalmente conectada al sistema SAP de la empresa, y comenzará registrando todos los pedidos creados por el departamento de compras a proveedores. [...]
Business Partner Portal is an initiative by the company Lakmé to improve the whole process of purchasing and receiving orders on site. The application will be fully connected to the company's SAP system, and will start by recording all orders created by the purchasing department from suppliers. [...]
Business Partner Portal és una iniciativa per part de l'empresa Lakmé per a millorar tot el procés de compra i recepció de comandes en les instal·lacions. L'aplicació estarà totalment connectada al sistema SAP de l'empresa, i començarà registrant totes les comandes creades pel departament de compres a proveïdors. [...]
2024
Enginyeria Informàtica [958]
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16 p, 1.2 MB |
The problem of institutional fit : uncovering patterns with boosted decision trees
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Epstein, Graham (University of Waterloo. School of Environment, Resources and Sustainability) ;
Apetrei, Cristina I. (Leuphana University, Faculty of Sustainability) ;
Baggio, Jacopo (University of Central Florida. School of Politics, Security and International Affairs) ;
Chawla, Sivee (James Cook University. ARC Centre of Excellence for Coral Reef Studies) ;
Cumming, Graeme S. (James Cook University. ARC Centre of Excellence for Coral Reef Studies) ;
Gurney, Georgina (James Cook University. ARC Centre of Excellence for Coral Reef Studies) ;
Morrison, Tiffany (James Cook University. ARC Centre of Excellence for Coral Reef Studies) ;
Unnikrishnan, Hita (Sheffield University. Urban Institute) ;
Villamayor Tomás, Sergio (Universitat Autònoma de Barcelona. Institut de Ciència i Tecnologia Ambientals)
Complex social-ecological contexts play an important role in shaping the types of institutions that groups use to manage resources, and the effectiveness of those institutions in achieving social and environmental objectives. [...]
2024 - 10.5334/ijc.1226
International Journal of the Commons, Vol. 18, issue 1 (2024) , p. 1-16
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Machine Learning Models for Predicting Personalized Tacrolimus Stable Dosages in Pediatric Renal Transplant Patients
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Sánchez-Herrero, Sergio (Universitat Oberta de Catalunya. Departament d'Informàtica, Multimèdia i Telecomunicació.) ;
Calvet Liñan, Laura (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes) ;
Juan, Ángel A (Universitat Politècnica de València. Centre de Recerca en Gestió i Enginyeria de la Producció)
Tacrolimus, characterized by a narrow therapeutic index, significant toxicity, adverse effects, and interindividual variability, necessitates frequent therapeutic drug monitoring and dose adjustments in renal transplant recipients. [...]
2023 - 10.3390/biomedinformatics3040057
BioMedInformatics, Vol. 3, Issue 4 (December 2023) , p. 926-947
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Enhancing Carsharing Experiences for Barcelona Citizens with Data Analytics and Intelligent Algorithms
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Herrera, Erika M. (Universitat Oberta de Catalunya. Departament d'Informàtica) ;
Calvet Liñan, Laura (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes) ;
Ghorbani, Elnaz (Universitat Oberta de Catalunya. Departament d'Informàtica) ;
Panadero, Javier (Universitat Politècnica de Catalunya. Departament de Gestió) ;
Juan, Ángel A (Euncet Business School. Departament de Gestió)
Carsharing practices are spreading across many cities in the world. This paper analyzes real-life data obtained from a private carsharing company operating in the city of Barcelona, Spain. After describing the main trends in the data, machine learning and time-series analysis methods are employed to better understand citizens' needs and behavior, as well as to make predictions about the evolution of their demand for this service. [...]
2023 - 10.3390/computers12020033
Computers, Vol. 12, Issue 2 (February 2023) , art. 33
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Local interpretation of machine learning models in remote sensing with SHAP : the case of global climate constraints on photosynthesis phenology
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Descals, Adrià (Centre de Recerca Ecològica i d'Aplicacions Forestals) ;
Verger, Aleixandre (Centre de Recerca Ecològica i d'Aplicacions Forestals) ;
Yin, Gaofei (Southwest Jiaotong University. Faculty of Geosciences and Environmental Engineering) ;
Filella, Iolanda (Centre de Recerca Ecològica i d'Aplicacions Forestals) ;
Peñuelas, Josep (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Data-driven models using machine learning have been widely used in remote-sensing applications such as the retrieval of biophysical variables and land cover classification. However, these models behave as a 'black box', meaning that the relationships between the input and predicted variables are hard to interpret. [...]
2023 - 10.1080/01431161.2023.2217982
International Journal of Remote Sensing, Vol. 44, issue 10 (2023) , p. 3160-3173
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55 p, 707.1 KB |
Advances in the Use of Deep Learning for the Analysis of Magnetic Resonance Image in Neuro-Oncology
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Pitarch, Carla (Universitat Politècnica de Catalunya. Departament d'Informàtica) ;
Ungan, Gulnur Semahat (Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular) ;
Julià Sapé, Ma. Margarita (Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí") ;
Vellido, Alfredo (Universitat Politècnica de Catalunya. Departament d'Informàtica)
Machine Learning is entering a phase of maturity, but its medical applications still lag behind in terms of practical use. The field of oncological radiology (and neuro-oncology in particular) is at the forefront of these developments, now boosted by the success of Deep-Learning methods for the analysis of medical images. [...]
2024 - 10.3390/cancers16020300
Cancers, Vol. 16, Issue 2 (January 2024) , art. 300
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