14,300 research outputs found
ON THE RENTAL PRICE OF CAPITAL AND THE PROFIT RATE: THE PERILS AND PITFALLS OF TOTAL FACTOR PRODUCTIVITY GROWTH
This paper considers the implications of the conceptual difference between the rental price of capital, embedded in the neoclassical cost identity (output equals the cost of labour plus the cost of capital), and used in growth accounting studies; and the profit rate, which can be derived from the national income and product accounts (NIPA). The neoclassical identity is a "virtual" identity in that it depends on a series of assumptions (constant returns to scale and perfectly competitive factor markets). The income side of the NIPA also provides an accounting identity for output as the sum of the wage bill plus the surplus. This identity, however, is a "real" one, in the sense that it does not depend on any assumptions and thus it holds always. It is shown that because the neoclassical cost identity and the income accounting identity according to the NIPA are formally equivalent expressions, estimations of aggregate production functions and growth accounting studies are tautologies. Likewise, the test of the hypothesis of competitive markets using Hall's (1988) framework gives rise to a null hypothesis that cannot be rejected statistically.
Dark matter cores in the Fornax and Sculptor dwarf galaxies: joining halo assembly and detailed star formation histories
We combine the detailed Star Formation Histories of the Fornax and Sculptor
dwarf Spheroidals with the Mass Assembly History of their dark matter (DM) halo
progenitors to estimate if the energy deposited by Supernova type II (SNeII) is
sufficient to create a substantial DM core. Assuming the efficiency of energy
injection of the SNeII into DM particles is , we find
that a single early episode, , that combines the
energy of all SNeII due to explode over 0.5 Gyr, is sufficient to create a core
of several hundred parsecs in both Sculptor and Fornax. Therefore, our results
suggest that it is energetically plausible to form cores in Cold Dark Matter
(CDM) halos via early episodic gas outflows triggered by SNeII. Furthermore,
based on CDM merger rates and phase-space density considerations, we argue that
the probability of a subsequent complete regeneration of the cusp is small for
a substantial fraction of dwarf-size haloes.Comment: ApJL accepted versio
Satellite remote sensing reveals a positive impact of living oyster reefs on microalgal biofilm development
Satellite remote sensing (RS) is routinely used for the large-scale monitoring of microphytobenthos (MPB) biomass in intertidal mudflats and has greatly improved our knowledge of MPB spatio-temporal variability and its potential drivers. Processes operating on smaller scales however, such as the impact of benthic macrofauna on MPB development, to date remain underinvestigated. In this study, we analysed the influence of wild Crassostrea gigas oyster reefs on MPB biofilm development using multispectral RS. A 30-year time series (1985-2015) combining high-resolution (30 m) Landsat and SPOT data was built in order to explore the relationship between C. gigas reefs and MPB spatial distribution and seasonal dynamics, using the normalized difference vegetation index (NDVI). Emphasis was placed on the analysis of a before-after control-impact (BACI) experiment designed to assess the effect of oyster killing on the surrounding MPB biofilms. Our RS data reveal that the presence of oyster reefs positively affects MPB biofilm development. Analysis of the historical time series first showed the presence of persistent, highly concentrated MPB patches around oyster reefs. This observation was supported by the BACI experiment which showed that killing the oysters (while leaving the physical reef structure, i.e. oyster shells, intact) negatively affected both MPB biofilm biomass and spatial stability around the reef. As such, our results are consistent with the hypothesis of nutrient input as an explanation for the MPB growth-promoting effect of oysters, whereby organic and inorganic matter released through oyster excretion and biodeposition stimulates MPB biomass accumulation. MPB also showed marked seasonal variations in biomass and patch shape, size and degree of aggregation around the oyster reefs. Seasonal variations in biomass, with higher NDVI during spring and autumn, were consistent with those observed on broader scales in other European mudflats. Our study provides the first multi-sensor RS satellite evidence of the promoting and structuring effect of oyster reefs on MPB biofilms
CORRECTING FOR BIASES WHEN ESTIMATING PRODUCTION FUNCTIONS: AN ILLUSION OF THE LAWS OF ALGEBRA?
this paper argues that the true cause of the endogeneity bias that allegedly appears when estimating production functions, and which the literature has tried to deal with since the 1940s, is s imply the result of omitted-variable bias due to an incorrect approximation to an accounting identity. As a result we question recent attempts to solve the problem by developing new estimators.
Emerging role of angiogenesis in adaptive and maladaptive right ventricular remodeling in pulmonary hypertension
Right ventricular (RV) function is the primary prognostic factor for both morbidity and mortality in pulmonary hypertension (PH). RV hypertrophy is initially an adaptive physiological response to increased overload; however, with persistent and/or progressive afterload increase, this response frequently transitions to more pathological maladaptive remodeling. The mechanisms and disease processes underlying this transition are mostly unknown. Angiogenesis has recently emerged as a major modifier of RV adaptation in the setting of pressure overload. A novel paradigm has emerged that suggests that angiogenesis and angiogenic signaling are required for RV adaptation to afterload increases and that impaired and/or insufficient angiogenesis is a major driver of RV decompensation. Here, we summarize our current understanding of the concepts of maladaptive and adaptive RV remodeling, discuss the current literature on angiogenesis in the adapted and failing RV, and identify potential therapeutic approaches targeting angiogenesis in RV failure
Erratum: Martins, M.S., et al. Wideband and wIde beam polyvinylidene difluoride (PVDF) acoustic transducer for broadband underwater. Sensors 2019, 19, 3991
The authors wish to make the following erratum to this paper [...].info:eu-repo/semantics/publishedVersio
Characterization of a Mexican halloysitic clay and behavior in dry pressing
A Mexican clay, intended to be used as refractory raw material, was identified. Problems encountered in the characterization of halloysitic clays are discussed and emphasis is made on the use of the electron microscope (scanning or transmission type) as a definite evidence of the existence of halloysite due to its unique morphology within the kaolinite group of clay minerals.
Beneficiation of this particular clay was carried out on a small scale hydrocyclone equipment and the results are discussed.
In an attempt to increase the green density in dry pressing of this halloysitic clay, mixtures with grog were prepared using different additives, grinding and low temperature preheating treatment. The effect of these variables upon green density is given and discussed.
It is believed that an increase in the dry pressing density will be reflected in better after burning properties of bricks made out of clays.
Pressure levels in the dry pressing experiments were made in a range similar to an industrial power press production --Abstract, page ii
Stream Learning in Energy IoT Systems: A Case Study in Combined Cycle Power Plants
The prediction of electrical power produced in combined cycle power plants is a key challenge in the electrical power and energy systems field. This power production can vary depending on environmental variables, such as temperature, pressure, and humidity. Thus, the business problem is how to predict the power production as a function of these environmental conditions, in order to maximize the profit. The research community has solved this problem by applying Machine Learning techniques, and has managed to reduce the computational and time costs in comparison with the traditional thermodynamical analysis. Until now, this challenge has been tackled from a batch learning perspective, in which data is assumed to be at rest, and where models do not continuously integrate new information into already constructed models. We present an approach closer to the Big Data and Internet of Things paradigms, in which data are continuously arriving and where models learn incrementally, achieving significant enhancements in terms of data processing (time, memory and computational costs), and obtaining competitive performances. This work compares and examines the hourly electrical power prediction of several streaming regressors, and discusses about the best technique in terms of time processing and predictive performance to be applied on this streaming scenario.This work has been partially supported by the EU project iDev40. This project has received funding
from the ECSEL Joint Undertaking (JU) under grant agreement No 783163. The JU receives support from the
European Unionâs Horizon 2020 research and innovation programme and Austria, Germany, Belgium, Italy,
Spain, Romania. It has also been supported by the Basque Government (Spain) through the project VIRTUAL
(KK-2018/00096), and by Ministerio de EconomĂa y Competitividad of Spain (Grant Ref. TIN2017-85887-C2-2-P)
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