86 research outputs found
‘Dinosaur-bird’ macroevolution, locomotor modules and the origins of flight
S.M.N. is supported by a FPI-UAM 2019 predoctoral grant from the Autonomous University of Madrid. This research was partially funded by project CGL2013-42643P from MINECO (Spain) and PGC2018-094955-A100 from MICIU (Spain). This work is a contribution of the CIPb-UAM research group and the PMMV team (Paleoclimatology, Macroecology and Macroevolution of Vertebrates) as part of the UCM-910607 research group. We thank to all the organizing committee of the 4th International Meeting of Early-stage Researchers in Palaeontology for inviting us to participate in the Special Issue “Young Solutions to Old Issues: Discoveries in Palaeontology Research”. Funding Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Natu
In Vivo Reprogramming Ameliorates Aging Features in Dentate Gyrus Cells and Improves Memory in Mice
Post-translational epigenetic modifications take place in mouse neurons of the dentate gyrus (DG) with age. Here, we report that age-dependent reduction in H3K9 trimethylation (H3K9me3) is prevented by cyclic induction of the Yamanaka factors used for cell reprogramming. Interestingly, Yamanaka factors elevated the levels of migrating cells containing the neurogenic markers doublecortin and calretinin, and the levels of the NMDA receptor subunit GluN2B. These changes could result in an increase in the survival of newborn DG neurons during their maturation and higher synaptic plasticity in mature neurons. Importantly, these cellular changes were accompanied by an improvement in mouse performance in the object recognition test over long time. We conclude that transient cyclic reprogramming in vivo in the central nervous system could be an effective strategy to ameliorate aging of the central nervous system and neurodegenerative diseases
Solar multiple optimization of a DSG linear Fresnel power plant
Linear Fresnel power plants are currently one of the most promising concentrating solar power plants. However there are only a few commercial projects. These power plants have a lower efficiency than parabolic trough collector plants and are still expensive. To increase the efficiency of these plants, the utilization of water/steam in the receivers (direct steam generation, DSG) and thermal storage (TES) have been considered.
As case study, a 50 MWe solar-only linear Fresnel power plant located in Seville, Spain is considered. The effects of the solar field size and the thermal storage size on the annual production of the plant are analyzed: Nine different solar field sizes and up to eight thermal storage sizes have been compared.
An economic optimization is presented in order to determine which plant has lowest Levelized Cost of Electricity (LCOE). It has been found that for the power plants with no-storage the optimum solar multiple (SM) is 1.7, whereas for the cases with thermal storage, the optimum configuration is a larger solar field (SM = 2), with a thermal storage of 2 h
Carbon dioxide and acetone mixtures as refrigerants for industry heat pumps to supply temperature in the range 150-220 ºC
Industry decarbonization is a key a challenge towards the transition to climate neutrality. Indeed, there is a need to satisfy heat at temperatures higher than 150 °C in relevant industrial sectors by upgrading lower temperature heat flows, such as heat from renewable heat sources, ambient heat or industrial waste heat. High temperature heat pumps (HTHP) can upgrade such heat flows enabling great savings in carbon emissions. New refrigerants are needed to develop HTHPs achieving high performances at high temperatures. This paper proposes the use of a new zeotropic mixture composed of carbon dioxide and acetone as the refrigerant of HTHPs working in the temperature range of 150-220 °C. The new fluid is compared with existing pure refrigerants currently used. The thermodynamic characterization of the CO2/acetone mixtures shows temperature glides below 50 K for CO2 mass fractions up to 10%. The best HTHP performance is shown for the mixture 5% CO2/95% acetone in mass fraction. For instance, such a mixture obtains a COP of 5.63 when the target outlet sink temperature is 200 °C and the temperature difference between the outlet heat sink and the inlet heat source is 70 K, showing an improvement of 46% compared to pure acetone.This work has been supported by the Madrid Government (Comunidad
de Madrid-Spain) under the Multiannual Agreement with UC3M
in the line of Excellence of University Professors (EPUC3M22), and in
the context of the V PRICIT (Regional Programme of Research and
Technological Innovation).Publicad
A survey of artificial neural network in wind energy systems
© 2018 Elsevier Ltd Wind energy has become one of the most important forms of renewable energy. Wind energy conversion systems are more sophisticated and new approaches are required based on advance analytics. This paper presents an exhaustive review of artificial neural networks used in wind energy systems, identifying the methods most employed for different applications and demonstrating that Artificial Neural Networks can be an alternative to conventional methods in many cases. More than 85% of the 190 references employed in this paper have been published in the last 5 years. The methods are classified and analysed into four groups according to the application: forecasting and predictions; design optimization; fault detection and diagnosis; and optimal control. A statistical analysis of the current state and future trends in this field is carried out. An analysis of each application group about the strengths and weaknesses of each ANN structure is carried out. A quantitative analysis of the main references is carried out showing new statistical results of the current state and future trends of the topic. The paper describes the main challenges and technological gaps concerning the application of ANN to wind turbines, according to the literature review. An overall table is provided to summarize the most important references according to the application groups and case studies
Vaccination with transgenic Eimeria tenella expressing Eimeria maxima AMA1 and IMP1 confers partial protection against high level E. maxima challenge in a broiler model of coccidiosis.
Poultry coccidiosis is a parasitic enteric disease with a highly negative impact on chicken production. In-feed chemoprophylaxis remains the primary method of control, but the increasing ineffectiveness of anticoccidial drugs, and potential future restrictions on their use has encouraged the use of commercial live vaccines. Availability of such formulations is constrained by their production, which relies on the use of live chickens. Several experimental approaches have been taken to explore ways to reduce the complexity and cost of current anticoccidial vaccines including the use of live vectors expressing relevant Eimeria proteins. We and others have shown that vaccination with transgenic Eimeria tenella parasites expressing E. maxima Apical Membrane Antigen-1 or Immune Mapped Protein-1 (EmAMA1 and EmIMP1) partially reduces parasite replication after challenge with a low dose of E. maxima oocysts. In the present work we have reassessed the efficacy of these experimental vaccines using commercial birds reared at high stocking densities and challenged with both low and high doses of E. maxima to evaluate how well they protect chickens against the negative impacts of disease on production parameters
A Novel Whole Yeast-Based Subunit Oral Vaccine Against Eimeria tenella in Chickens
Cheap, easy-to-produce oral vaccines are needed for control of coccidiosis in chickens to reduce the impact of this disease on welfare and economic performance. Saccharomyces cerevisiae yeast expressing three Eimeria tenella antigens were developed and delivered as heat-killed, freeze-dried whole yeast oral vaccines to chickens in four separate studies. After vaccination, E. tenella replication was reduced following low dose challenge (250 oocysts) in Hy-Line Brown layer chickens (p<0.01). Similarly, caecal lesion score was reduced in Hy-Line Brown layer chickens vaccinated using a mixture of S. cerevisiae expressing EtAMA1, EtIMP1 and EtMIC3 following pathogenic-level challenge (4,000 E. tenella oocysts; p<0.01). Mean body weight gain post-challenge with 15,000 E. tenella oocysts was significantly increased in vaccinated Cobb500 broiler chickens compared to mock-vaccinated controls (p<0.01). Thus, inactivated recombinant yeast vaccines offer cost-effective and scalable opportunities for control of coccidiosis, with relevance to broiler production and chickens reared in low-and middle-income countries (LMICs)
A Survey of Artificial Neural Network in Wind Energy Systems
Wind energy has become one of the most important forms of renewable energy. Wind energy conversion systems are more sophisticated and new approaches are required based on advance analytics. This paper presents an exhaustive review of artificial neural networks used in wind energy systems, identifying the methods most employed for different applications and demonstrating that Artificial Neural Networks can be an alternative to conventional methods in many cases. More than 85% of the 190 references employed in this paper have been published in the last 5 years. The methods are classified and analysed into four groups according to the application: forecasting and predictions; design optimization; fault detection and diagnosis; and optimal control. A statistical analysis of the current state and future trends in this field is carried out. An analysis of each application group about the strengths and weaknesses of each ANN structure is carried out. A quantitative analysis of the main references is carried out showing new statistical results of the current state and future trends of the topic. The paper describes the main challenges and technological gaps concerning the application of ANN to wind turbines, according to the literature review. An overall table is provided to summarize the most important references according to the application groups and case studies
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