262 research outputs found
A política de habitação rural e o desenvolvimento da agricultura familiar.
Este artigo analisa a contribuição do Programa Nacional de Habitação Rural (PNHR) para o desenvolvimento de territórios predominantemente rurais. A partir do estudo de sua implementação na região Oeste Catarinense, ponder sobre os avanços e as restrições desta política social. Para as análises realizadas procedeu-se a uma revisão de literatura, à busca de documentação sobre a política e sua implementação na região estudada, bem como a entrevistas com lideranças e agricultores demandantes e beneficiados por uma casa nova ou reforma. Verificou-se que o PNHR cria uma oportunidade para as famílias rurais descapitalizadas construírem ou reformarem sua casa, apesar de ser ainda restrita a sua abrangência para o conjunto dessas famílias. A reformulação do programa, reduzindo exigências financeiras e para operação dos créditos, pode oportunizar que maior número de famílias dele se beneficie, com impacto social positivo no desenvolvimento regional
Generalizable semi-supervised learning method to estimate mass from sparsely annotated images
Mass flow estimation is of great importance to several industries, and it can
be quite challenging to obtain accurate estimates due to limitation in expense
or general infeasibility. In the context of agricultural applications, yield
monitoring is a key component to precision agriculture and mass flow is the
critical factor to measure. Measuring mass flow allows for field productivity
analysis, cost minimization, and adjustments to machine efficiency. Methods
such as volume or force-impact have been used to measure mass flow; however,
these methods are limited in application and accuracy. In this work, we use
deep learning to develop and test a vision system that can accurately estimate
the mass of sugarcane while running in real-time on a sugarcane harvester
during operation. The deep learning algorithm that is used to estimate mass
flow is trained using very sparsely annotated images (semi-supervised) using
only final load weights (aggregated weights over a certain period of time). The
deep neural network (DNN) succeeds in capturing the mass of sugarcane
accurately and surpasses older volumetric-based methods, despite highly varying
lighting and material colors in the images. The deep neural network is
initially trained to predict mass on laboratory data (bamboo) and then transfer
learning is utilized to apply the same methods to estimate mass of sugarcane.
Using a vision system with a relatively lightweight deep neural network we are
able to estimate mass of bamboo with an average error of 4.5% and 5.9% for a
select season of sugarcane.Comment: 22 pages, 21 figures, Computers and Electronics in Agriculture. arXiv
admin note: text overlap with arXiv:1908.0438
Volumetric based mass flow estimation on sugarcane harvesters
Yield monitors on harvesters are a key component of precision agriculture.
Mass flow estimation is the critical factor to measure, and having this allows
for field productivity analysis, adjustments to machine efficiency, and cost
minimization by ensuring trucks are filled maximally without exceeding weight
limits. Several common technologies used on grain harvesters, including impact
plate sensors, are accurate enough on combines to be valuable but suffer from
issues such as drift. Sugarcane is composed of a mixture of billets and trash,
which is a very dispersed material with much less consistency than grains. In
this study, a 3d point cloud approach is used to estimate volume, from which a
calibration factor is derived [density] to translate to mass. The system was
proved in concept in a controlled environment using bamboo, achieving an R2 of
97.4% when fitting average volume flow per test against average mass flow after
correcting for bulk density changes with volume. The system was also tested on
field data, which was collected from nearly 1700 wagon loads from the southern
U.S. and Brazil over the course of 3 seasons in both green and burnt cane.
Results indicated that the concept is very robust with good accuracy, having
seasonal CVs for density values ranging from 6.9% to 16.2%. The camera concept
proves relatively robust to environmental conditions. The same approach could
be used in sugar beets, potatoes or other sparse/non-flowing crops with highly
varying material properties, where traditional mass flow sensors do not work.Comment: 14 pages, 6 figures, computers and electronics in agriculture journa
Um olhar sobre a ação re-territorializadora do manejo de castanhais nativos no Acre.
O sistema de produção da castanha-da-amazônia (Bertholletia excelsa) apresenta importante valor para a manutenção dos meios de vida de comunidades extrativistas no Acre. Este sistema produtivo tem sua herança nos povos originários, mas sua exploração econômica está associada às mudanças de uso do espaço-floresta amazônica a partir de um novo ciclo de extrativismo o qual ocorreu após a decadência do ciclo da borracha. Sob a perspectiva de análise de ?territórios construídos? o presente artigo buscou analisar o processo de territorialização a partir de fatores e componentes associados ao setor produtivo da castanha-da-amazônia no contexto acreano. O trabalho fornece informações sobre conceitos de território e territorialidade e aborda um histórico da dinâmica da atividade produtiva vinculada a castanha-da-amazônia, incluindo o papel dos agentes sociais no processo estudado. Por seu grande valor de uso, este setor produtivo passou por muitas mudanças na última década, motivadas por uma sequência de políticas públicas empreendidas pelo estado e pela estruturação de uma cooperativa central de produtores. O estudo demonstra a existência de uma ação territorializadora resultante do sistema produtivo da castanha-da-amazônia no Acre, principalmente pelas características particulares encontradas em: i) espaço-lugar considerado aqui como a base natural ou florestas com ocorrência de castanhais nativos especificamente em uma determinada parte do estado e ii) pelo espaço-território construído a partir das relações socias estabelecidas ao longo do tempo para que a atividade extrativista se consolidasse em um setor econômico-produtivo. The production system of Brazil nut (Bertholletia excelsa) presents important value for the maintenance of the livelihoods of extractive communities in Acre. This productive system has its inheritance in the original peoples, but its economic exploitation is associated with the changes of use of the Amazonian forest space in a new cycle of extractivism which occurred after the decay of the rubber cycle. From the perspective of "constructed territories", the present article sought to analyze the territorialization process based on factors and components associated with the productive sector of the Brazil nuts in the Acrean context. The paper provides information on the concepts of territory and territoriality and discusses the history of the productive activity dynamics linked to Brazil nuts, including the role of social agents in the process studied. Due to its great value in use, this productive sector underwent many changes in the last decade, motivated by a sequence of public policies undertaken by the state and by the structuring of a central cooperative of producers. The study demonstrates the existence of a territorializing action resulting from the Brazil nut production system in Acre, mainly due to the particular characteristics found in: i) space-place considered here as the natural base or forests with native Brazil nut tree that occur specifically in a certain part of the state and ii) by the space-territory constructed from the social relations established over time so that the extractive activity was consolidated in an economic-productive sector
Beta receptor-mediated modulation of the late positive potential in humans
RATIONALE
Electrophysiological studies have identified a scalp potential, the late positive potential (LPP), which is modulated by the emotional intensity of observed stimuli. Previous work has shown that the LPP reflects the modulation of activity in extrastriate visual cortical structures, but little is known about the source of that modulation.
OBJECTIVES
The present study investigated whether beta-adrenergic receptors are involved in the generation of the LPP.
METHODS
We used a genetic individual differences approach (experiment 1) and a pharmacological manipulation (experiment 2) to test the hypothesis that the LPP is modulated by the activation of β-adrenergic receptors.
RESULTS
In experiment 1, we found that LPP amplitude depends on allelic variation in the β1-receptor gene polymorphism. In experiment 2, we found that LPP amplitude was modulated by the β-blocker propranolol in a direction dependent on subjects' level of trait anxiety: In participants with lower trait anxiety, propranolol led to a (nonsignificant) decrease in the LPP modulation; in participants with higher trait anxiety, propranolol increased the emotion-related LPP modulation.
CONCLUSIONS
These results provide initial support for the hypothesis that the LPP reflects the downstream effects, in visual cortical areas, of β-receptor-mediated activation of the amygdala.Stress-related psychiatric disorders across the life spa
Evolution of Broader Impacts
This work is supported by the National Science Foundation under grant number OIA-1810732 and MCB-1940655, the Kavli Foundation and the Burroughs Wellcome Fund. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, the Kavli Foundation or Burroughs Wellcome Fund
Hydrocarbon Liquid Production via Catalytic Hydroprocessing of Phenolic Oils Fractionated from Fast Pyrolysis of Red Oak and Corn Stover
Phenolic oils were produced from fast pyrolysis of two different biomass feedstocks, red oak and corn stover, and evaluated in hydroprocessing tests for production of liquid hydrocarbon products. The phenolic oils were produced with a bio-oil fractionating process in combination with a simple water wash of the heavy ends from the fractionating process. Phenolic oils derived from the pyrolysis of red oak and corn stover were recovered with yields (wet biomass basis) of 28.7 and 14.9 wt %, respectively, and 54.3% and 60.0% on a carbon basis. Both precious metal catalysts and sulfided base metal catalyst were evaluated for hydrotreating the phenolic oils, as an extrapolation from whole bio-oil hydrotreatment. They were effective in removing heteroatoms with carbon yields as high as 81% (unadjusted for the 90% carbon balance). There was substantial heteroatom removal with residual O of only 0.4% to 5%, while N and S were reduced to less than 0.05%. Use of the precious metal catalysts resulted in more saturated products less completely hydrotreated compared to the sulfided base metal catalyst, which was operated at higher temperature. The liquid product was 42–52% gasoline range molecules and about 43% diesel range molecules. Particulate matter in the phenolic oils complicated operation of the reactors, causing plugging in the fixed-beds especially for the corn stover phenolic oil. This difficulty contrasts with the catalyst bed fouling and plugging, which is typically seen with hydrotreatment of whole bio-oil. This problem was substantially alleviated by filtering the phenolic oils before hydrotreating. More thorough washing of the phenolic oils during their preparation from the heavy ends of bio-oil or online filtration of pyrolysis vapors to remove particulate matter before condensation of the bio-oil fractions is recommended.Reprinted with permission from ACS Sustainable Chem. Eng., 2015, 3 (5), pp 892–902. Copyright 2015 American Chemical Society.</p
Implications For The Origin Of GRB 051103 From LIGO Observations
We present the results of a LIGO search for gravitational waves (GWs)
associated with GRB 051103, a short-duration hard-spectrum gamma-ray burst
(GRB) whose electromagnetically determined sky position is coincident with the
spiral galaxy M81, which is 3.6 Mpc from Earth. Possible progenitors for
short-hard GRBs include compact object mergers and soft gamma repeater (SGR)
giant flares. A merger progenitor would produce a characteristic GW signal that
should be detectable at the distance of M81, while GW emission from an SGR is
not expected to be detectable at that distance. We found no evidence of a GW
signal associated with GRB 051103. Assuming weakly beamed gamma-ray emission
with a jet semi-angle of 30 deg we exclude a binary neutron star merger in M81
as the progenitor with a confidence of 98%. Neutron star-black hole mergers are
excluded with > 99% confidence. If the event occurred in M81 our findings
support the the hypothesis that GRB 051103 was due to an SGR giant flare,
making it the most distant extragalactic magnetar observed to date.Comment: 8 pages, 3 figures. For a repository of data used in the publication,
go to: https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=15166 . Also see
the announcement for this paper on ligo.org at:
http://www.ligo.org/science/Publication-GRB051103/index.ph
Search for Gravitational Wave Bursts from Six Magnetars
Soft gamma repeaters (SGRs) and anomalous X-ray pulsars (AXPs) are thought to be magnetars: neutron stars powered by extreme magnetic fields. These rare objects are characterized by repeated and sometimes spectacular gamma-ray bursts. The burst mechanism might involve crustal fractures and excitation of non-radial modes which would emit gravitational waves (GWs). We present the results of a search for GW bursts from six galactic magnetars that is sensitive to neutron star f-modes, thought to be the most efficient GW emitting oscillatory modes in compact stars. One of them, SGR 0501+4516, is likely similar to 1 kpc from Earth, an order of magnitude closer than magnetars targeted in previous GW searches. A second, AXP 1E 1547.0-5408, gave a burst with an estimated isotropic energy >10(44) erg which is comparable to the giant flares. We find no evidence of GWs associated with a sample of 1279 electromagnetic triggers from six magnetars occurring between 2006 November and 2009 June, in GW data from the LIGO, Virgo, and GEO600 detectors. Our lowest model-dependent GW emission energy upper limits for band-and time-limited white noise bursts in the detector sensitive band, and for f-mode ringdowns (at 1090 Hz), are 3.0 x 10(44)d(1)(2) erg and 1.4 x 10(47)d(1)(2) erg, respectively, where d(1) = d(0501)/1 kpc and d(0501) is the distance to SGR 0501+4516. These limits on GW emission from f-modes are an order of magnitude lower than any previous, and approach the range of electromagnetic energies seen in SGR giant flares for the first time.United States National Science FoundationScience and Technology Facilities Council of the United KingdomMax-Planck-SocietyState of Niedersachsen/GermanyItalian Istituto Nazionale di Fisica NucleareFrench Centre National de la Recherche ScientifiqueAustralian Research CouncilCouncil of Scientific and Industrial Research of IndiaIstituto Nazionale di Fisica Nucleare of ItalySpanish Ministerio de Educacion y CienciaConselleria d'Economia Hisenda i Innovacio of the Govern de les Illes BalearsFoundation for Fundamental Research on Matter supported by the Netherlands Organisation for Scientific ResearchPolish Ministry of Science and Higher EducationFoundation for Polish ScienceRoyal SocietyScottish Funding CouncilScottish Universities Physics AllianceNational Aeronautics and Space Administration NNH07ZDA001-GLASTCarnegie TrustLeverhulme TrustDavid and Lucile Packard FoundationResearch CorporationAlfred P. Sloan FoundationRussian Space AgencyRFBR 09-02-00166aIPN JPL Y503559 (Odyssey), NASA NNG06GH00G, NASA NNX07AM42G, NASA NNX08AC89G (INTEGRAL), NASA NNG06GI896, NASA NNX07AJ65G, NASA NNX08AN23G (Swift), NASA NNX07AR71G (MESSENGER), NASA NNX06AI36G, NASA NNX08AB84G, NASA NNX08AZ85G (Suzaku), NASA NNX09AU03G (Fermi)Astronom
Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project
The Numerical INJection Analysis (NINJA) project is a collaborative effort
between members of the numerical relativity and gravitational-wave data
analysis communities. The purpose of NINJA is to study the sensitivity of
existing gravitational-wave search algorithms using numerically generated
waveforms and to foster closer collaboration between the numerical relativity
and data analysis communities. We describe the results of the first NINJA
analysis which focused on gravitational waveforms from binary black hole
coalescence. Ten numerical relativity groups contributed numerical data which
were used to generate a set of gravitational-wave signals. These signals were
injected into a simulated data set, designed to mimic the response of the
Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this
data using search and parameter-estimation pipelines. Matched filter
algorithms, un-modelled-burst searches and Bayesian parameter-estimation and
model-selection algorithms were applied to the data. We report the efficiency
of these search methods in detecting the numerical waveforms and measuring
their parameters. We describe preliminary comparisons between the different
search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ
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