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The Role of Chilean Mountain Areas in Time of Drought and Energy Crisis:New Pressures and Challenges for Vulnerable Ecosystems

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Journal of Mountain Science 2012年第4期9卷 451-462页

作者： rafael SáNCHEZ Carla MARCHANT Axel BORSDORF Institute for Geography Pontifical University Catholic of ChileAvenida Vicu a Mackenna 4860MaculSantiago de Chile Institute for Geography University of InnsbruckInnrain 526020 InnsbruckAustria Institute for Mountain Research:Man and Environment Austrian Academy of SciencesTechnikerstr.21a6020 InnsbruckAustria

In the summer of 2010/2011 Chile suffered the third most severe energy and water supply crisis in only one decade. This may be surprising as the Andes which accompany the country along 4,200 km are a water tower and could provide more electricity and water than needed. On top of that, it has to be mentioned that Chile also counts with sunny and windy climates and with excellent geothermal energy resources and thus has a huge potential as far as renewable energies are concerned. After analyzing the existing natural conditions, the infrastructure and the present challenges of climate change, it has to be asked in which way Chile can make use of this potential in the near future, considering the legal and political situation and the technological opportunities. It seems that the resources are still hidden in the Andes, and only the key is missing to realize the country＇s natural potential. This research has been based on the analysis of existing literature, media, quantitative data from government institutions and other antecedents obtained by the authors in field work done in the South of Chile in 2OLO. The added value of this compilation lies in the comprehensive perspective, linking the knowledge of climatologists, hydrologists, mountain researchers and energy experts in order to support a sustainable energy and water supply for the future in Chile. From this present research, it can be concluded that Chile necessarilyhas to adopt new energy-related strategies, particularly those aimed at diminishing the strong dependence on traditional sources of energy and establishing new techniques and technologies for generating electrieity and utilizing the vast potential that the country is ready to offer, such as that provided by the Andes along 4,200 kilometers.

关键词： Mountain region Andes Energy supply Chile

Nylon 6-cellulose composite hosted in a hypodermic needle: Biofluid extraction and analysis by ambient mass spectrometry in a single device

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Journal of Pharmaceutical Analysis 2023年第11期13卷 1346-1352页

作者： Jaime Millan-Santiago rafael Lucena Soledad Cardenas Affordable and Sustainable Sample Preparation(AS2P)Research Group Analytical Chemistry DepartmentChemical Institute for Energy and Environment(IQUEMA)University of CordobaE-14071CordobaSpain

This study proposes a hypodermic needle(HN)as a sorbent holder and an electrospray(ESI)emitter,thus combining extraction and analysis in a single device.A novel nylon 6-cellulose(N6-Cel)composite sorbent is proposed to extract methadone from oral fluid *** cellulosic substrate provides the composite with high porosity,permitting the flow-through of the sample,while the polyamide contributes to the extraction of the *** low price of the devices(considering the holder and the sorbent)contributes to the affordability of the method,and their small size allows easy transportation,opening the door to on-site *** the optimum conditions,the analyte can be determined by high-resolution ambient ionization mass spectrometry at a limit of detection(LOD)as low as 0.3 mg/L and precision(expressed as relative standard deviation,RSD)better than 9.3%.The trueness,expressed as relative recovery(RR),ranged from 90%to 109%.As high-resolution mass spectrometers are not available in many laboratories,the method was also adapted to low-resolution *** this sense,the direct infusion of the eluates in a triple quadrupole-mass spectrometry provided an LOD of 2.2 mg/*** RSD was better than 5.3%,and the RR ranged from 96%to 121%.

关键词： ESI emitter Mass spectrometry Hypodermic needle Composite Methadone

Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning

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npj Computational Materials 2022年第1期8卷 588-597页

作者： James Damewood Daniel Schwalbe-Koda rafael Gómez-Bombarelli Department of Materials Science and Engineering Massachusetts Institute of Technology77 Massachusetts AvenueCambridgeMA02319USA

Calculating thermodynamic potentials and observables efficiently and accurately is key for the application of statistical mechanics simulations to materials ***,naive Monte Carlo approaches,on which such calculations are often dependent,struggle to scale to complex materials in many state-of-the-art disciplines such as the design of high entropy alloys or multi-component *** address this issue,we adapt sampling tools built upon machine learning-based generative modeling to the materials space by transforming them into the semi-grand canonical ***,we show that the resulting models are transferable across wide ranges of thermodynamic conditions and can be implemented with any internal energy model U,allowing integration into many existing materials *** demonstrate the applicability of this approach to the simulation of benchmark systems (AgPd,CuAu) that exhibit diverse thermodynamic behavior in their phase ***,we discuss remaining challenges in model development and promising research directions for future improvements.

关键词： canonical thermodynamic directions

Fuzzy C-means Rule Generation for Fuzzy Entry Temperature Prediction in a Hot Strip Mill

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Journal of Iron and Steel Research International 2016年第2期23卷 116-123页

作者： Jose Angel BARRIOS Cesar VILLANUEVA Alberto CAVAZOS rafael COLAS Mechanical and Electrical Engineering Faculty Autonomous University of Nuevo LeonSan Nicolas de los Garza 66451Nuevo LeonMexico Hot Rolling Department Ternium ChurubuscoMonterrey 64000Nuevo LeonMexico

Variable estimation for finishing mill set-up in hot rolling is greatly affected by measurement uncertainties, variations in the incoming bar conditions and product changes. The fuzzy C-means algorithm was evaluated for rule base generation for fuzzy and fuzzy grey-box temperature estimation. Experimental data were collected from a real- life mill and three different sets were randomly drawn. The first set was used for rule-generation, the second set was used for training those systems with learning capabilities, while the third one was used for validation. The perform- ance of the developed systems was evaluated by five performance measures applied over the prediction error with the validation set and was compared with that of the empirical rule-base fuzzy systems and the physical model used in plant. The results show that the fuzzy C-means generated rule-bases improve temperature estimation; however, the best results are obtained when fuzzy C-means algorithm, grey-box modeling and learning functions are combined. Application of fuzzy C-means rule generation brings improvement on performance of up to 72%.

关键词： gray-box modeling ANFIS hot rolling temperature estimation fuzzy C-means rule base generation

Systemic treatment in EGFR-ALK NSCLC patients:second line therapy and beyond

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Cancer Biology & Medicine 2014年第3期11卷 173-181页

作者： Niki Karachaliou rafael Rosell Translational Research Unit Dr Rosell Oncology InstituteQuirón Dexeus University Hospital08028 BarcelonaSpain Cancer Biology and Precision Medicine Program Catalan Institute of Oncology Hospital Germans Trias i PujolCtra Canyet s/n08916 BadalonaBarcelonaSpain Fundación Molecular Oncology Research (MORe) Sabino Arana 5-1908028 BarcelonaSpain

Lung cancer is the most frequently diagnosed cancer and a leading cause of cancer mortality worldwide, with adenocarcinoma being the most common histological subtype. Deeper understanding of the pathobiology of non-small cell lung cancer(NSCLC) has led to the development of small molecules that target genetic mutations known to play critical roles in progression to metastatic disease and to influence response to targeted therapies. The principle goal of precision medicine is to define those patient populations most likely to respond to targeted therapies. However, the cancer genome landscape is composed of relatively few "mountains" [representing the most commonly mutated genes like KRAS, epidermal growth factor(EGFR), and anaplastic lymphoma kinase(ALK)] and a vast number of "hills"(representing low frequency but potentially actionable mutations). Low-frequency lesions that affect a druggable gene product allow a relatively small population of cancer patients for targeted therapy to be selected.

关键词： Lung cancer epidermal growth factor(EGFR) anaplastic lymphoma kinase fusions(ALK fusions) tyrosine kinase inhibitors(TKIs) TKI resistance

Elastography-based screening for esophageal varices in patients with advanced chronic liver disease

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World Journal of Gastroenterology 2019年第3期25卷 308-329页

作者： rafael Paternostro Thomas Reiberger Theresa Bucsics Department of Medicine Ⅲ Division of Gastroenterology and Hepatology Medical University of Vienna

Elastography-based liver stiffness measurement(LSM) is a non-invasive tool for estimating liver fibrosis but also provides an estimate for the severity of portal hypertension in patients with advanced chronic liver disease(ACLD). The presence of varices and especially of varices needing treatment(VNT) indicates distinct prognostic stages in patients with compensated ACLD(cACLD). The Baveno VI guidelines suggested a simple algorithm based on LSM 150 G/L for ruling-out VNT in patients with cACLD. These(and other) TE-based LSM cut-offs have been evaluated for VNT screening in different liver disease etiologies. Novel point shear-wave elastography(pSWE) and two-dimensional shear wave elastography(2D-SWE) methodologies for LSM have also been evaluated for their ability to screen for "any" varices and for VNT. Finally, the measurement of spleen stiffness(SSM) by elastography(mainly by pSWE and 2D-SWE) may represent another valuable screening tool for varices. Here, we summarize the current literature on elastography-based prediction of "any" varices and VNT. Finally,we have summarized the published LSM and SSM cut-offs in clinically useful scale cards.

关键词： Elastography Liver stiffness Spleen stiffness Shear wave Magnetic resonance elastography Varices Portal hypertension Cirrhosis Advanced chronic liver disease

Disturbance and forest recovery in the Monarch Butterfly Biosphere Reserve,Mexico

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Journal of Forestry Research 2020年第5期31卷 1551-1566页

作者： Jose Lopez-Garcıa rafael M.Navarro-Cerrillo Instituto de Geografıa Universidad Nacional Autonoma de MexicoCiudad UniversitariaC.P.04510 CoyoacanDFMexico Departamento de Ingenierıa Forestal Universidad de CordobaCampus de RabanalesCarretera Nacional IV km 39614014 CordobaSpain

Analysis of the change in forest cover is important to determine stand dynamics and the processes involved in disturbance and *** of the core zone of the Monarch Butterfly Biosphere Reserve were studied using photo interpretation techniques,considering biennial changes between 1999 and 2013 and changes over the whole period of study 1999–*** matrices were elaborated to determine the processes of change involved in both recovery and *** biennial changes for the whole period amounted to 2274 ha;343 ha accounted as degraded in more than one biennial *** total changes in forest cover between 1999 and 2013 involved 4902 ha,out of which,2912 ha were affected by disturbance,and 1990 ha were *** density and 2013 vegetation cover maps,the overall accuracy was 95.6%and 90.2%,*** combining both maps,gradual processes were revealed that were not evident in separate *** methodology is useful for the management and conservation of natural protected areas.

关键词： Illegal logging Forest density change Forest recovery Conifer forests Monarch Butterfly Biosphere Reserve

Artificial intelligence and liver transplantation:Looking for the best donor-recipient pairing

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Hepatobiliary & Pancreatic Diseases International 2022年第4期21卷 347-353页

作者： Javier Briceno rafael Calleja César Hervás Unit of Liver Transplantation Department of General SurgeryHospital Universitario Reina SofíaCórdobaSpain Maimónides Institute of Biomedical Research of Córdoba(IMIBIC) CórdobaSpain Department of Computer Sciences and Numerical Analysis Universidad de CórdobaCórdobaSpain

Decision-making based on artificial intelligence(AI)methodology is increasingly present in all areas of modern *** recent years,models based on deep-learning have begun to be used in organ *** into account the huge number of factors and variables involved in donor-recipient(DR)matching,AI models may be well suited to improve organ ***-based models should provide two solutions:complement decision-making with current metrics based on logistic regression and improve their *** of classifiers could be used to address this ***,not all of them are really useful for D-R ***,in the decision to assign a given donor to a candidate in waiting list,a multitude of variables are handled,including donor,recipient,logistic and perioperative *** these last two,some of them can be inferred indirectly from the team’s previous *** groups of AI models have been used in the D-R matching:artificial neural networks(ANN)and random forest(RF).The former mimics the functional architecture of neurons,with input layers and output *** algorithms can be uni-or *** general,ANNs can be used with large databases,where their generalizability is ***,they are models that are very sensitive to the quality of the databases and,in essence,they are black-box models in which all variables are ***,these models do not allow to know safely the weight of each *** the other hand,RF builds decision trees and works well with small *** addition,they can select top variables as with logistic ***,they are not useful with large databases,due to the extreme number of decision trees that they would generate,making them *** ANN and RF allow a successful donor allocation in over 80%of D-R pairing,a number much higher than that obtained with the best statistical metrics such as model for end-stage liver disease,balance of risk

关键词： Donor-recipient matching Artificial intelligence Deep learning Artificial neural networks Random forest Liver transplantation outcome

Visual analytics tool for the interpretation of hidden states in recurrent neural networks

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Visual Computing for Industry,Biomedicine,and Art 2021年第1期4卷 233-245页

作者： rafael Garcia Tanja Munz Daniel Weiskopf VISUS University of Stuttgart70569 StuttgartGermany

In this paper,we introduce a visual analytics approach aimed at helping machine learning experts analyze the hidden states of layers in recurrent neural *** technique allows the user to interactively inspect how hidden states store and process information throughout the feeding of an input sequence into the *** technique can help answer questions,such as which parts of the input data have a higher impact on the prediction and how the model correlates each hidden state configuration with a certain *** visual analytics approach comprises several components:First,our input visualization shows the input sequence and how it relates to the output(using color coding).In addition,hidden states are visualized through a nonlinear projection into a 2-D visualization space using t-distributed stochastic neighbor embedding to understand the shape of the space of the hidden *** are also employed to show the details of the evolution of the hidden state ***,a time-multi-class heatmap matrix visualizes the evolution of the expected predictions for multi-class classifiers,and a histogram indicates the distances between the hidden states within the original *** different visualizations are shown simultaneously in multiple views and support brushing-and-linking to facilitate the analysis of the classifications and debugging for misclassified input *** demonstrate the capability of our approach,we discuss two typical use cases for long short-term memory models applied to two widely used natural language processing datasets.

关键词： Visual analytics Visualization Machine learning Classification Recurrent neural networks Long shortterm memory Hidden states Interpretability Natural language processing Nonlinear projection