260 research outputs found
Recurrent Neural Networks Applied to GNSS Time Series for Denoising and Prediction
Global Navigation Satellite Systems (GNSS) are systems that continuously acquire data and provide position time series. Many monitoring applications are based on GNSS data and their efficiency depends on the capability in the time series analysis to characterize the signal content and/or to predict incoming coordinates. In this work we propose a suitable Network Architecture, based on Long Short Term Memory Recurrent Neural Networks, to solve two main tasks in GNSS time series analysis: denoising and prediction. We carry out an analysis on a synthetic time series, then we inspect two real different case studies and evaluate the results. We develop a non-deep network that removes almost the 50% of scattering from real GNSS time series and achieves a coordinate prediction with 1.1 millimeters of Mean Squared Error
Empirical Evidence of Nonminimally Coupled Dark Matter in the Dynamics of Local Spiral Galaxies?
We look for empirical evidence of a nonminimal coupling (NMC) between dark matter (DM) and gravity in the
dynamics of local spiral galaxies. In particular, we consider a theoretically motivated NMC that may arise
dynamically from the collective behavior of the coarse-grained DM field (e.g., via Bose–Einstein condensation)
with averaging/coherence length L. In the Newtonian limit, this NMC amounts to modify the Poisson equation by
a term L2∇2ρ proportional to the Laplacian of the DM density itself. We show that such a term, when acting as a
perturbation over the standard Navarro–Frenk–White profile of cold DM particles, can substantially alter the
dynamical properties of galaxies, in terms of their total radial acceleration within the disk and rotation velocity.
Specifically, we find that this NMC model can properly fit the stacked rotation curves (RCs) of local spiral galaxies
with different velocities at the optical radius, including dwarfs and low-surface-brightness systems, at a level of
precision comparable to, and in some instances even better than, the phenomenological Burkert profile. Finally, we
show that by extrapolating down to smaller masses the scaling of L versus halo mass found from the above RC
analysis, the NMC model can adequately reproduce the radial acceleration relation in shape and normalization
down to the dwarf spheroidal galaxy range, a task which constitutes a serious challenge for alternative DM models
even inclusive of baryonic effects
Climate change awareness, perceived impacts, and adaptation from farmers’ experience and behavior: a triple-loop review
Individuals and communities socially construct risk, and societies with greater risk perception may be more apt to mobilize or adapt to emergent threats like climate change. Increasing climate change awareness is often considered necessary in the first stages of the adaptation process to manage its impacts and reduce overall vulnerability. Since agriculture is affected by climate change in several ways, farmers can provide first-hand observations of climate change impacts and adaptation options. This paper aims to identify the current research trends and set the future research agenda on climate change awareness, perceived impacts, and adaptive capacity from farmers’ experiences and behavior. We analyzed a portfolio of 435 articles collected from WoS and Scopus databases between 2010 and 2020 using bibliometrics. From the original portfolio, we select 108 articles for a more comprehensive and systematic review. Publication trends and content analysis have been employed to identify influential work, delineate the mental structure of farmers’ beliefs and concerns, and identify main research gaps. The comprehensive analysis reported (1) farmers’ socio-demographic characteristics influencing farmers’ perceptions; (2) awareness and changing climate evidence due to human activity; (3) the main perceived effects (rising temperatures, changing rainfall patterns, and extreme events); (4) the most relevant adaptation measures (crop changing and soil/water conservation techniques); and (5) factors and barriers limiting adaptation (lack of information, credit, and expertness). The review outlines the main gaps and their drivers to help future researchers, managers, and decision-makers to prioritize their actions according to farmers’ concerns and their adaptive capacity to reduce farming vulnerability
How do irrigation district managers deal with climate change risks? Considering experiences, tipping points, and risk normalization in northern Italy
Agriculture is one of the most sensitive and vulnerable activities to climate variations; climate change impacts crop yield, soil processes, water availability, and pest dynamic. Farmers are on the front lines of climate change-induced stressors, shifts, and shocks, having to provide solutions as planners, performers, and innovators working under challenging and uncertain risk conditions. Extensive research has been carried out to deepen farmers’ behavior on risks posed by climate change. However, less attention was paid to irrigation district managers, even though their essential role in guaranteeing hydraulic safety, ensuring water supply, even as on-site observers of farmers’ behavior. This paper seeks to uncover the attitudes and actions of irrigation districts managers towards climate change, and their ability to gather significant information on the climate experiences of farmers in the Lombardy region, Italy. Employing a mix of semi-structured interviews and questionnaires, the exploratory approach gathered insights from the managers of the 12 public irrigation districts tasked with governing irrigation development and water management in the region. The study reveals that managers are cognizant of the shifting climate caused by warmer temperatures and extreme weather events, implementing both hard (e.g. water infrastructure maintenance, water storage) and soft (climate and weather services) adaptation countermeasures. Through their own experiences, managers brought to light the driving factors behind farmers’ willingness to adopt water-saving techniques or adapt their crops, despite facing obstacles (e.g. financial investment, institutional support). In addition, the identification of tipping points related to water scarcity and security is coupled with managers and farmers’ trust in technological solutions to partially counteract risk normalization. In line with the findings, suggestions were put forth to enhance managers’ adaptive capacity
+The phenology of species in a swamp forest in Bauru, SP / + A fenologia das espécies em uma floresta pântica em Bauru, SP
The way both phenophase and periodicity occur is crucial to define phenological patterns of species and communities. These studies are of great importance in order to understand the behavior of such communities in relation to climate variability, the measurement of the amount of fruit and the best time for seed collection. Thus, this work has the objective to describe the phenological patterns of the twelve most important species within their phytosociological structure from an arboreal shrub community in a swamp forest in the municipality of Bauru, SP. We have noticed that most of the species, the anthesis, occurred in the beginning and in the end of the dry season. For fruiting phenophase, the pattern has presented a greater variation from one year to another, meaning that in the first year, 75% of the individuals bore fruit during the dry season. On the other hand, lower fructification has been noticed throughout the same period (June to October) of the following year. Thus, we could get to the conclusion that anthesis phenophase has a strong correlation with the changing seasons. Fruiting phenophases have not shown to have a clear pattern. We could notice that fructification is strongly related with precipitation variability index, and it can be explained since there was a significant increase of rainfall and a decrease of fructification in the second year
Astroparticle Constraints from the Cosmic Star Formation Rate Density at High Redshift: Current Status and Forecasts for JWST
We exploit the recent determination of cosmic star formation rate (SFR)
density at redshifts to derive astroparticle constraints on three
common dark matter scenarios alternative to standard cold dark matter (CDM):
warm dark matter (WDM), fuzzy dark matter (DM) and self-interacting dark
matter (SIDM). Our analysis relies on the UV luminosity functions measured by
the Hubble Space Telescope out to and down to UV magnitudes
. We extrapolate these to fainter yet unexplored
magnitude ranges, and perform abundance matching with the halo mass functions
in a given DM scenario, so obtaining a relationship between the UV magnitude
and the halo mass. We then compute the cosmic SFR density by integrating the
extrapolated UV luminosity functions down to a faint magnitude limit , which is determined via the above abundance matching
relationship by two free parameters: the minimum threshold halo mass for galaxy formation, and the astroparticle quantity
characterizing each DM scenario (namely, particle mass for WDM and DM,
and kinetic temperature at decoupling for SIDM). We perform Bayesian
inference on such parameters via a MCMC technique by comparing the cosmic SFR
density from our approach to the current observational estimates at , constraining the WDM particle mass to keV, the DM particle mass to
eV, and the
SIDM temperature to keV at
() confidence level. We then forecast how such constraints will be
strengthened by upcoming refined estimates of the cosmic SFR density, if the
early data on the UV luminosity function at from JWST will be
confirmed down to ultra-faint magnitudes.Comment: 18 pages, accepted in MDPI Universe. arXiv admin note: text overlap
with arXiv:2205.0947
Phylogenetic and biogeographic history of brook lampreys (Lampetra: Petromyzontidae) in the river basins of the Adriatic Sea based on DNA barcode data.
The Adriatic brook lamprey, Lampetra zanandreai Vladykov 1955, was described from northeastern Italy. Its distribution is thought to include left tributaries of the River Po and the river basins of the Adriatic Sea from the River Po to the River Isonzo/Soča in Italy, Switzerland and Slovenia. It also shows a geographically isolated distribution in the Potenza River on the Adriatic slope in Central Italy. Lampetra from the Neretva River system in Croatia and Bosnia and Herzegovina and the Morača River system in Montenegro that were previously identified as L. zanandreai were recently described as a new species Lampetra soljani Tutman, Freyhof, Dulčić, Glamuzina & Geiger 2017 based on morphological data and a genetic distance between the two species of roughly 2.5% in the DNA barcoding gene cytochrome oxidase I (COI). Since DNA barcodes for L. zanandreai are only available for one population from the upper Po River in northwestern Italy, we generated additional COI nucleotide sequence data of this species from Switzerland, northeastern and central Italy comprising near topotypic material and obtained GenBank sequences of the species from Slovenia to better assess the evolutionary history of the two brook lamprey species in the river basins of the Adriatic Sea. Our data show a low sequence divergence of <1% between L. zanandreai from Switzerland, northeastern and central Italy and Slovenia and the Balkan species L. soljani. However, members of the population previously identified as 'L. zanandreai' from northwest Italy are genetically highly divergent from those of L. zanandreai and likely belong to an undescribed species, L. sp. 'upper Po'. The presence of a unique and highly divergent brook lamprey lineage in the upper Po River suggests that L. zanandreai and Lampetra sp. 'upper Po' may have evolved in separate paleo drainages during the formation of the modern Po Valley subsequent to marine inundations in the Pliocene
Esox flaviae: population genomics revealed entangled origin and differentiation of the Italian populations
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