An empirical model of fleet modernization: on the relationship between market concentration and innovation adoption in the Brazilian airline industry

The modernization of an airline's fleet can reduce its operating costs, improve the perceived quality of service offered to passengers, and mitigate emissions. The present paper investigates the market incentives that airlines have to adopt technological innovation from manufacturers by acquiring new generation aircraft. We develop an econometric model of fleet modernization in the Brazilian commercial aviation over two decades. We examine the hypothesis of an inverted-U relationship between market concentration and fleet modernization and find evidence that both the extremes of competition and concentration may inhibit innovation adoption by carriers. We find limited evidence associating either hubbing activity or low-cost carriers with the more intense introduction of new types of aircraft models and variants in the industry. Finally, our results suggest that energy cost rises may provoke boosts in fleet modernization in the long term, with carriers possibly targeting more eco-efficient operations up to two years after an upsurge in fuel price

Intake Rate and Nutritive Value of Elephant Grass cv. Napier Subjected to Strategies of Rotational Stocking Management

Several research papers on forage tropical grass species have demonstrated that grazing management interferes with sward structure that, in turn, alters patterns of ingestive and foraging behaviour of the grazing animals. For that reason it has been used as explicative variable for adjustments in intake characteristics like bite mass, bite rate, intake rate and nutritive value of the consumed herbage (Fonseca et al. 2012). Tall tufted growing plants like elephant grass (Pennisetum purpureum Schum.) cv. Napier show a continuous pattern of growth characterised by stem elongation during their vegetative state (Da Silva and Carvalho 2005), causing swards to become too tall and out of reach for grazing animals, generating serious difficulties in executing efficient grazing management, particularly when long regrowth periods are used. In that context, the increase in defoliation frequency has positive effects on herbage intake and nutritive value (Palhano et al. 2007), since it favours leaf elongation relative to stem elongation and senescent material accumulation throughout successive grazing cycles. Against that background, the objective of this experiment was to evaluate the components of the short term herbage intake (intake rate, bite mass and bite rate) and the nutritive value of the consumed herbage from elephant grass cv. Napier subjected to strategies of rotational stocking management defined in terms of pre- and post-grazing management targets

Statistical properties of random matrix product states

We study the set of random matrix product states (RMPS) introduced in arXiv:0908.3877 as a tool to explore foundational aspects of quantum statistical mechanics. In the present work, we provide an accurate numerical and analytical investigation of the properties of RMPS. We calculate the average state of the ensemble in the non-homogeneous case, and numerically check the validity of this result. We also suggest using RMPS as a tool to approximate properties of general quantum random states. The numerical simulations presented here support the accuracy and efficiency of this approximation. These results suggest that any generalized canonical state can be approximated with high probability by the reduced density matrix of a random MPS, if the average MPS coincide with the associated microcanonical ensemble.Comment: 12 pages, 17 figures; published versio

Analysis of Precipitation and Evapotranspiration in Atlantic Rainforest Remnants in Southeastern Brazil from Remote Sensing Data

The Atlantic Rainforest has been intensely devastated since the beginning of the colonization of Brazil, mainly due to wood extraction and urban and rural settlement. Although the Atlantic Rainforest has been reduced and fragmented, its remnants are important sources of heat and water vapor to the atmosphere. The present study aimed to characterize and to analyze the temporal dynamics of precipitation and evapotranspiration in the Atlantic Rainforest remnants in São Paulo state, southeastern Brazil, for the period from January 2000 to December 2010. To achieve this, global precipitation and evapotranspiration data from TRMM satellite and MOD16 algorithm as well as forest remnant maps produced by SOS Mata Atlântica Foundation and Brazilian National Institute for Space Research (INPE) were used. Results found in this study demonstrated that the use of remote sensing was an important tool for analyzing hydrological variables in Atlantic Rainforest remnants, which can contribute to better understand the interaction between tropical forests and the atmosphere, and for generating input data necessary for surface models coupled to atmospheric general circulation models

Effects of land‐cover changes on the partitioning of surface energy and water fluxes in Amazonia using high‐resolution satellite imagery

Spatial variability of surface energy and water fluxes at local scales is strongly controlled by soil and micrometeorological conditions. Thus, the accurate estimation of these fluxes from space at high spatial resolution has the potential to improve prediction of the impact of land‐use changes on the local environment. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Large‐Scale Biosphere‐Atmosphere Experiment in Amazonia (LBA) data were used to examine the partitioning of surface energy and water fluxes over different land‐cover types in one wet year (2004) and one drought year (2005) in eastern Rondonia state, Brazil. The spatial variation of albedo, net radiation (Rn), soil (G) and sensible (H) heat fluxes, evapotranspiration (ET), and evaporative fraction (EF) were primarily related to the lower presence of forest (primary [PF] or secondary [SF]) in the western side of the Ji‐Parana River in comparison with the eastern side, located within the Jaru Biological Reserve protected area. Water limitation in this part of Amazonia tends to affect anthropic (pasture [PA] and agriculture [AG]) ecosystems more than the natural land covers (PF and SF). We found statistically significant differences on the surface fluxes prior to and ~1 year after the deforestation. Rn over forested areas is ~10% greater in comparison with PA and AG. Deforestation and consequent transition to PA or AG increased the total energy (~200–400%) used to heat the soil subsurface and raise air temperatures. These differences in energy partitioning contributed to approximately three times higher ET over forested areas in comparison with nonforested areas. The conversion of PF to AG is likely to have a higher impact in the local climate in this part of Amazonia when compared with the change to PA and SF, respectively. These results illustrate the importance of conserving secondary forest areas in Amazonia.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151879/1/eco2126_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151879/2/eco2126.pd

Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia

In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001–December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance

Methods to Evaluate Land-Atmosphere Exchanges in Amazonia Based on Satellite Imagery and Ground Measurements

During the last three decades, intensive campaigns and experiments have been conducted for acquiring micrometeorological data in the Amazonian ecosystems, which has increased our understanding of the variation, especially seasonally, of the total energy available for the atmospheric heating process by the surface, evapotranspiration and carbon exchanges. However, the measurements obtained by such experiments generally cover small areas and are not representative of the spatial variability of these processes. This chapter aims to discuss several algorithms developed to estimate surface energy and carbon fluxes combining satellite data and micrometeorological observations, highlighting the potentialities and limitations of such models for applications in the Amazon region. We show that the use of these models presents an important role in understanding the spatial and temporal patterns of biophysical surface parameters in a region where most of the information is local. Data generated may be used as inputs in earth system surface models allowing the evaluation of the impact, both in regional as well as global scales, caused by land-use and land-cover changes

Adsorptive potential of Zn–Al and Mg–Fe layered double hydroxides for the removal of 2–nitrophenol from aqueous solutions

Two layered double hydroxides (LDH) of the type Zn–Al and Mg–Fe were synthesized, characterized and used as adsorbents to uptake 2–nitrophenol (2–NP) from aqueous solutions. XRD, FTIR, SEM, EDS, AFM and N2 adsorption/desorption curves were used to characterize the Zn–Al–LDH and Mg–Fe–LDH. The potential of both layered double hydroxides to adsorb 2–NP was investigated by adsorption kinetics, equilibrium, thermodynamics and consecutive adsorption/desorption cycles. The characterization indicated a high crystallinity degree and a well–organized and lamellar structure, confirming the efficiency of the synthesis. Elovich was the better kinetic model to describe the 2–NP adsorption onto Zn–Al–LDH, while Pseudo–second order was the best for Mg–Fe–LDH. For both LDHs, the adsorption equilibrium followed the Freundlich model. The process was endothermic, being the maximum adsorption capacities of 290 and 165 mg g–1 for Zn–Al–LDH and Mg–Fe–LDH, respectively. LDHs can be applied for five adsorption/desorption cycles with excellent adsorption capacities. It can be concluded that Zn–Al–LDH and Mg–Fe–LDH are promising materials to treat waters and wastewaters containing 2–nitropheno

A combined approach for comparative exoproteome analysis of Corynebacterium pseudotuberculosis

Background: Bacterial exported proteins represent key components of the host-pathogen interplay. Hence, we sought to implement a combined approach for characterizing the entire exoproteome of the pathogenic bacterium Corynebacterium pseudotuberculosis, the etiological agent of caseous lymphadenitis (CLA) in sheep and goats. Results: An optimized protocol of three-phase partitioning (TPP) was used to obtain the C. pseudotuberculosis exoproteins, and a newly introduced method of data-independent MS acquisition (LC-MSE) was employed for protein identification and label-free quantification. Additionally, the recently developed tool SurfG+ was used for in silico prediction of sub-cellular localization of the identified proteins. In total, 93 different extracellular proteins of C. pseudotuberculosis were identified with high confidence by this strategy; 44 proteins were commonly identified in two different strains, isolated from distinct hosts, then composing a core C. pseudotuberculosis exoproteome. Analysis with the SurfG+ tool showed that more than 75% (70/93) of the identified proteins could be predicted as containing signals for active exportation. Moreover, evidence could be found for probable non-classical export of most of the remaining proteins. Conclusions: Comparative analyses of the exoproteomes of two C. pseudotuberculosis strains, in addition to comparison with other experimentally determined corynebacterial exoproteomes, were helpful to gain novel insights into the contribution of the exported proteins in the virulence of this bacterium. The results presented here compose the most comprehensive coverage of the exoproteome of a corynebacterial species so far