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1.
Raquel Cano Jos L. Prez Liss Angarita Dvila ngel Ortega Yosselin Gmez Nereida Josefina Valero-Cedeo Heliana Parra Alexander Manzano Teresa Isabel Vliz Castro María P. Díaz Albornoz Gabriel Cano Joselyn Rojas-Quintero Maricarmen Chacín Valmore Bermúdez 《International journal of molecular sciences》2021,22(9)
Non-alcoholic fatty liver disease (NAFLD) is considered the most common liver disorder, affecting around 25% of the population worldwide. It is a complex disease spectrum, closely linked with other conditions such as obesity, insulin resistance, type 2 diabetes mellitus, and metabolic syndrome, which may increase liver-related mortality. In light of this, numerous efforts have been carried out in recent years in order to clarify its pathogenesis and create new prevention strategies. Currently, the essential role of environmental pollutants in NAFLD development is recognized. Particularly, endocrine-disrupting chemicals (EDCs) have a notable influence. EDCs can be classified as natural (phytoestrogens, genistein, and coumestrol) or synthetic, and the latter ones can be further subdivided into industrial (dioxins, polychlorinated biphenyls, and alkylphenols), agricultural (pesticides, insecticides, herbicides, and fungicides), residential (phthalates, polybrominated biphenyls, and bisphenol A), and pharmaceutical (parabens). Several experimental models have proposed a mechanism involving this group of substances with the disruption of hepatic metabolism, which promotes NAFLD. These include an imbalance between lipid influx/efflux in the liver, mitochondrial dysfunction, liver inflammation, and epigenetic reprogramming. It can be concluded that exposure to EDCs might play a crucial role in NAFLD initiation and evolution. However, further investigations supporting these effects in humans are required. 相似文献
2.
Maria del Rosario Martínez-Macias Rocio Janeth Aguilar-Ruiz Omar Nateras-Ramírez Dalia Isabel Sánchez-Machado Jaime López-Cervantes Germán Eduardo Dévora-Isiordia Jesús Álvarez-Sánchez Nidia Josefina Ríos-Vázquez 《Journal of the American Oil Chemists' Society》2021,98(10):993-1000
Greenhouse gases emitted into the atmosphere by burning of fossil fuels cause global warming. One option is obtaining biodiesel. Nannochloropsis oculata was cultured under different light intensities and reactors at 25°C for 21 days with f/2 medium to assess their effects on cell density, lipid, and fatty acids (FAs). N. oculata improved cell density on fed-batch glass tubular reactor (7 L) at 200 μmol E m−2 s−1, yielding 3.5 × 108 cells ml−1, followed by fed-batch Erlenmeyer flask (1 L) at 650 μmol E m−2 s−1 with 1.7 × 108 cells ml−1. The highest total lipid contents (% g lipid × g dry biomass−1) were 44.4 ± 0.8% for the reactor (1 L) at 650 μmol E m−2 s−1 and 35.2 ± 0.2% for the tubular reactor (7 L) at 200 μmol E m−2 s−1, until twice as high compared with the control culture (Erlenmeyer flask 1 L, 80 μmol E m−2 s−1) with 21.2 ± 1%. Comparing the total lipid content at 200 μmol E m−2 s−1, tubular reactor (7 L) and reactor 1 L achieved 35.2 ± 0.2% and 28.3 ± 1%, respectively, indicating the effect of shape reactor. The FAs were affected by high light intensity, decreasing SFAs to 2.5%, and increased monounsaturated fatty acids + polyunsaturated fatty acids to 2.5%. PUFAs (20:5n-3) and (20:4n-3) were affected by reactor shape, decreasing by half in the tubular reactor. In the best culture, fed-batch tubular reactor (7 L) at 200 μmol E m−2 s−1 contains major FAs (16:0; 38.06 ± 0.16%), (16:1n-7; 30.74 ± 0.58%), and (18:1n-9; 17.15 ± 0.91%). 相似文献
3.
Juan Manuel González Calleros Josefina Guerrero García Jean Vanderdonckt 《Universal Access in the Information Society》2013,12(4):387-401
The need for accessibility evaluation tools is motivated by several endogenous and exogenous reasons coming from the end user (the designer and the developer) and companies releasing information systems. Existing evaluation tools mainly concentrate on examining the code of Web pages: Web pages more and more frequently contain non-HTML parts that entirely escape from being treated by existing techniques. This is the case of the advanced human–machine interface (AHMI), a piece of software programmed in C/C++, used for controlling the advanced flight management system in the aircraft cockpit. Studying this new user interface (UI) requires a structured approach to evaluate and validate AHMI designs. The goal in this work is to develop an evaluation tool to automate the process of evaluating the AHMI. The method addresses: support of multiple bases of guidelines (accessibility or usability or both) on-demand (partial or total evaluation), with different levels of details (a presentation for developers and for those responsible for certifying accessibility). The method goes a step toward the automatic evaluation of UI containing non-HTML parts. 相似文献
4.
Julien Ah-Pine Marco Bressan Stephane Clinchant Gabriela Csurka Yves Hoppenot Jean-Michel Renders 《Multimedia Tools and Applications》2009,42(1):31-56
This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing
that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media
pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate components, considering
them as a single relevance concept. In our second approach, we define trans-media similarities as an aggregation of monomodal
similarities between the elements of the aggregate and the new multimodal object. We also introduce the monomodal similarity
measures for text and images that serve as basic components for both proposed trans-media similarities. We show how one can
frame a large variety of problem in order to address them with the proposed techniques: image annotation or captioning, text
illustration and multimedia retrieval and clustering. Finally, we present how these methods can be integrated in two applications:
a travel blog assistant system and a tool for browsing the Wikipedia taking into account the multimedia nature of its content.
Dr. Julien Ah-Pine joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities. 相似文献
Gabriela CsurkaEmail: |
Dr. Julien Ah-Pine joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities. 相似文献
5.
Josefina Sierra-Santibáñez 《Annals of Mathematics and Artificial Intelligence》2003,39(1-2):61-100
We study the declarative formalization of reasoning strategies by presenting declarative formalizations of: (1) the SNLP algorithm for nonlinear planning, and (2) a particular algorithm for blocks world nonlinear planning proposed in this paper. The formal models of a heuristic forward chaining planner, which can take advantage of declarative formalizations of action selection strategies, and of a reasoning strategy based planner, which can use declarative formalizations of reasoning strategies, are proposed. The effectiveness of these systems is studied from formal and empirical points of view. Empirical results showing how the use of declarative formalizations of reasoning strategies can reduce the amount of search required for solving planning problems (with respect to state of the art planning systems) are presented. 相似文献
6.
Plaza-Cazón Josefina González Esteban Donati Edgardo Rubén 《Mine Water and the Environment》2021,40(4):994-1002
Mine Water and the Environment - The role of iron- and sulfur- oxidizing microorganisms in the generation of acid mine drainage (AMD) from sulfide ores and tailings is widely recognized. The... 相似文献
7.
Josefina Pérez-Arantegui Judit Molera Angel Larrea Trinitat Pradell Marius Vendrell-Saz Ilaria Borgia Brunetto G. Brunetti Franco Cariati Paola Fermo Marcello Mellini Antonio Sgamellotti Cecilia Viti 《Journal of the American Ceramic Society》2001,84(2):442-46
Luster is a decorative metallic film that was applied on the surface of medieval glazed pottery. It can be obtained via the low-temperature (∼650°C), controlled reduction of copper and silver compounds. In this paper, we show that luster is a thin layered film (200–500 nm thick) that contains metallic spherical nanocrystals dispersed in a silicon-rich matrix and has a metal-free outermost glassy layer that is 10–20 nm thick. Silver nanocrystals seem to be separated from those of copper, forming aggregates 5–100 μm in diameter. This composite structure exhibits optical properties that are dependent on both the particle size and the matrix. Luster is indeed the first reproducible nanostructured thin metallic film that was made by humans. 相似文献
8.
9.
The relative proportion of caseins to total protein is a parameter that can be used to control the protein quality in standardised milk, an increasing tendency in dairy industries. 31P-NMR was used to analyse the casein content of milk, by the quantitation of the area under the resonances belonging to SerP, and using methylenediphosphonic acid as internal standard. This procedure yielded good results, as similar values of caseins were obtained from N Kjeldahl and NMR analysis for slightly heated milk samples. Heating at 95 degrees C for 15 min did not alter the casein content results. Casein content of raw, pasteurised and UHT milks (25.6 +/- 1.4, 26.4 +/- 1.8, 25.5 +/- 1.6 g casein/l milk, respectively), obtained by NMR, were not significantly different, giving an average of 25.8 +/- 1.6 g casein/l for bulk liquid milk. This work concluded that 31P-NMR could be used as an alternative method to determine casein in raw, pasteurised, dry and UHT milks. 相似文献
10.
Effects of dietary supplements of zinc-methionine on milk production,udder health and zinc metabolism in dairy goats 总被引:5,自引:0,他引:5
Salama AA Caja G Albanell E Such X Casals R Plaixats J 《The Journal of dairy research》2003,70(1):9-17
Twenty-two Murciano-Granadina dairy goats were used to investigate the effects of organic Zn supplementation of a diet containing a high level of inorganic Zn. Goats were kept in pens, machine milked once a day throughout lactation and fed a diet based on a dehydrated mixture of whole-plant maize and alfalfa ad libitum, alfalfa pellets, barley grain and a concentrate mixture. Treatments were: (1) control, and (2) supplemented with 1 g/d Zn-Methionine (Zn-Met) included in the concentrate mixture. After parturition, goats were blocked in week 3 and dietary treatments were applied until week 23. From weeks 3-20, feed intake, milk yield, milk composition, milk somatic cell count (SCC), and udder health were measured. In week 21, all goats were injected intraperitoneally with 1 g/d DL-methionine for 5 d to establish the effects of methionine under the conditions of udder stress induced by hand milking on the second day. During weeks 22 and 23, diet digestibility, and N and Zn balance were determined. Dry matter intake, milk yield, and milk contents of total solids, fat, total and true protein, and casein did not differ between treatments, but whey protein and non-protein nitrogen contents were significantly lower for the Zn-Met group. Milk SCC tended to decrease as a result of Zn-Met supplementation but differences between treatments were not significant when halves with persistent infection were excluded. Hand milking increased SCC in both groups, but udders of supplemented goats showed a lower reaction. Apparent absorption of N significantly increased and Zn retention tended to increase in Zn-Met supplemented goats. We conclude that Zn-Met supplementation can enhance resistance to udder stress in dairy goats. Effects were attributed to the organic Zn and not to the methionine component. Zn retention and protein utilization were also improved by the Zn-Met supplement. 相似文献