Variability In Space Research Articles

Global well-posedness of the viscous Camassa–Holm equation with gradient noise

We analyse a nonlinear stochastic partial differential equation that corresponds to a viscous shallow water equation (of the Camassa--Holm type) perturbed by a convective, position-dependent noise term. We establish the existence of weak solutions in $H^m$ ($m\in\mathbb{N}$) using Galerkin approximations and the stochastic compactness method. We derive a series of a priori estimates that combine a model-specific energy law with non-standard regularity estimates. We make systematic use of a stochastic Gronwall inequality and also stopping time techniques. The proof of convergence to a solution argues via tightness of the laws of the Galerkin solutions, and Skorokhod--Jakubowski a.s. representations of random variables in quasi-Polish spaces. The spatially dependent noise function constitutes a complication throughout the analysis, repeatedly giving rise to nonlinear terms that "balance" the martingale part of the equation against the second-order Stratonovich-to-It\^{o} correction term. Finally, via pathwise uniqueness, we conclude that the constructed solutions are probabilistically strong. The uniqueness proof is based on a finite-dimensional It\^{o} formula and a DiPerna--Lions type regularisation procedure, where the regularisation errors are controlled by first and second order commutators.

Marine GIS as a Tool to Support Backscatter Data Analysis for Zooplankton Investigations

Echo-sounders and Vessel-Mounted Acoustic Doppler Current Profilers (VM-ADCP) are widely operating onboard research vessels with the aim of providing real-time backscatter and ocean current profiles along the route, while the vessel is moving. Backscatter data are exploited to infer important information about zooplankton presence and distribution. Nevertheless, as these organisms daily vertically migrate even below the depth of the instrument range, the combination of space and time variability make their mapping from a moving vessel quite complex. The objective of this work is to describe a GIS application developed for the management and analysis of these data. The GIS capability as a tool to facilitate zooplankton investigations is assessed by means of a test-case in the area of the Ligurian Sea (Western Mediterranean) by using VM-ADCP backscatter data made available during oceanographic campaigns. The system, which includes a high-resolution bathymetry, environmental parameters, ephemeris, allows to select and visualize data sorted according to all the possible layer combinations. Moreover, different backscatter profiles, characterizing the identified migration phases can be enlightened by means of false color scale representation.

On the use of machine learning methods to improve the estimation of gross primary productivity of maize field with drip irrigation

As an important part of the energy-matter cycle, gross primary productivity (GPP) reflects the ability of plants to absorb carbon dioxide from the atmosphere. The accurate estimation of GPP is critical to understanding the regional carbon cycle. With the development of machine learning (ML) theory, machine learning models are increasingly used to study complex phenomena with high variability in time and space. In this study, three machine learning models (Support vector regression (SVR), artificial neural network (ANN), and long short-term memory networks (LSTM)) were investigated for predicting GPP in northwest China and compared them with the traditional physical models. Carbon flux, various environmental factors, and maize growth indices were measured in the maize field over five years in northwest China. The rigorous analysis which included statistical comparison and cross-validation for the prediction of GPP confirmed that the machine learning models performed better than traditional physical models. And the SVR model performed the best among the considered ML models with the highest nash-efficiency coefficient and the lowest root mean squared error. The machine learning model also outperformed the traditional physical models on cloudy days and after irrigation. The SVR achieved good prediction accuracy and high stability. With different training data sets, the ANN and LSTM were relatively more sensitive to the training data set. When the training data was sufficient, SVR, ANN and LSTM could achieve similar prediction accuracy, but SVR was slightly higher. When the training data was small, the simulation accuracy of SVR was better than ANN and LSTM. The performance of ANN and LSTM was more sensitive to parameter selection, and the relationship between model performance and parameter selection had no obvious regularity. Based on this comprehensive comparison study, it was elicited that the SVR model can be successfully applied to GPP simulation of maize fields, which provided a new perspective for the application of machine learning modeling in GPP simulation.

Environmental and land use controls of microplastic pollution along the gravel-bed Ain River (France) and its “Plastic Valley”

Understanding microplastic particles (MPs) accumulation and transport along rivers represents a major task due to the complexity and heterogeneity of rivers, and their interactions with their wider corridor. The identification of MPs hotspots and their potential sources is especially challenging in coarse-bed rivers transporting a wide range of particle sizes with a high degree of variability in time and space. This research focuses on the gravel-bed Ain River (Rhône River tributary, France) which is managed by means of various dams and also hosts one of the major plastic production centres in Europe (Oyonnax and Bienne Plastic Valleys). In this research, (i) Geographical Information Systems (GIS) were used to locate plastic factories and to characterise the land use of the Ain River watershed. (ii) On the field, sediment samples were extracted from the hyporheic zone (HZ) of mobile gravel bar heads, while hydro-sedimentary settings were measured in order to describe site conditions. Sampling sites were especially established in downwelling areas (i.e. where the surface water entered the hyporheic zone), upstream and downstream of dams and plastic factories. (iii) After density separation and organic matter digestion of sediment, MPs were characterised with a µFTIR device followed by data processing via the siMPle software. This work highlighted the trapping efficiency of alluvial bars for MPs. The highest MPs concentrations were found along the Plastic Valleys (up to 4400 MPs/kg), while the lower river was less contaminated by MPs. After grain-size correction, a significant breakpoint was identified in the area of the main dams, revealing their major influence on MPs distribution. The variability in MPs concentrations and types suggested a local origin for most of MPs. A particular feature was the dominance of polypropylene (PP) which appears as a critical industrial heritage as the studied region is specialised in the manufacturing of hard plastics. Indeed, multivariate analyses also revealed that MPs concentrations and types were mostly driven by the vicinity of plastic factories and urban areas. This relationship between the land use, the presence of dams and MPs characteristics provides key results for the MPs assessment and the improvement of management issues along coarse-bed rivers.

First molecular evidence of hybridization in endosymbiotic ciliates (Protista, Ciliophora).

Hybridization is an important evolutionary process that can fuel diversification via formation of hybrid species or can lead to fusion of previously separated lineages by forming highly diverse species complexes. We provide here the first molecular evidence of hybridization in wild populations of ciliates, a highly diverse group of free-living and symbiotic eukaryotic microbes. The impact of hybridization was studied on the model of Plagiotoma, an obligate endosymbiont of the digestive tube of earthworms, using split decomposition analyses and species networks, 2D modeling of the nuclear rRNA molecules and compensatory base change analyses as well as multidimensional morphometrics. Gene flow slowed down and eventually hampered the diversification of Lumbricus-dwelling plagiotomids, which collapsed into a single highly variable biological entity, the P. lumbrici complex. Disruption of the species boundaries was suggested also by the continuum of morphological variability in the phenotypic space. On the other hand, hybridization conspicuously increased diversity in the nuclear rDNA cistron and somewhat weakened the host structural specificity of the P. lumbrici complex, whose members colonize a variety of phylogenetically closely related anecic and epigeic earthworms. By contrast, another recorded species, P. aporrectodeae sp. n., showed no signs of introgression, no variability in the rDNA cistron, and very high host specificity. These contrasting eco-evolutionary patterns indicate that hybridization might decrease the alpha-diversity by dissolving species boundaries, weaken the structural host specificity by broadening ecological amplitudes, and increase the nuclear rDNA variability by overcoming concerted evolution within the P. lumbrici species complex.

Two-Dimensional Modelling of the Mixing Patterns in a Tropical Semiarid Reservoir

Tropical semi-arid regions suffer with recurrent droughts and uncertain water availability, but a few research studies have been conducted to further understand those complexities and their relationships with reservoir hydrodynamics. This study assessed the hydrodynamic processes of a multiple-use reservoir located in the Brazilian semiarid region. The aim was to apply the CE-QUAL-W2 model to understand the lake’s thermal structure and its variabilities in time and space by using the Richardson’s number (Ri) as a reference. Meteorological patterns were also investigated. Results show that: (1) no significant changes were found by analysing the spatial variabilities of stratification; (2) seasonal changes were relevant as more robust stratification stability was observed in the wet period when water availability may be impacted by poor water quality; (3) from meteorological evaluations, rainfall showed a strong coefficient of determination with Ri (r² of 0.77); and (4) a threshold value of 60 mm in monthly precipitation was found as an indication of a stable stratification in the water column. Wind speed and water level partly influenced Ri’s variabilities, while low impact was noted for air temperature and inflow. These results can promote an improvement in water-resources management by linking rainfall regime and reservoir hydrodynamics.

The World Ocean Wave Fields Discerned From ERA‐Interim Spectra

AbstractA wave field is a spatial expanse of the ocean surface in which waves of a single meteorological event are generated and propagate until their energy dissipates and disperses to the point where they are not detectable any further. Since water as a transport medium allows the superposition of waves of different sizes traveling in different directions, the typical sea surface is composed of several coexisting and overlapping fields. Historically, the methods for describing waves were based on bulk parameters (e.g., Hs, Tz), but the modern methods based on the wave spectrum, provide us with all the information necessary to distinguish individual wave fields out of the composed set. Weather prediction centers archive nowadays point spectra time series with global coverage and spanning long periods of time. The statistical characterization of such data shows that long‐term spectral patterns are few and well defined at each location, and they can be associated with a specific meteorological forcing (e.g., distant swells, trade‐winds, local jets). The objective of this work is to consolidate the local point information as to obtain spatially coherent wave fields, discerning them from each other to determine their characteristics. Individual wave fields can be regarded as a new source of information, useful for a wide range of applications such as data assimilation, sediment transport, biomass productivity, among others. For climate‐related purposes time and space variability can be analyzed, identifying trends, anomalies, and tele‐connections. These climate aspects are explored here through an illustrative example focused on the southern trade‐winds' field.

Longitudinal distribution of seeds under the action of different conductor tubes and sowing speeds

The objective of this study was to evaluate the distribution of longitudinal soybean seeds under the action of different sowing velocities and conductor tubes. The test was carried out on a sticky belt test, equipped with a seed meter, Selenium model, adjusted for seeding of 12 seeds m-1, submitted to four different tubes and three sowing speeds at 5, 7 and 9 km h-1, resulting in a completely randomized experimental design in a factorial scheme. Spacings between seeds were selected, classified as acceptable, misses and multiples, in addition to spacing variations coefficient. The data obtained were submitted to analysis of variance and the averages of the Tukey test levels of 5% error probability. The sowing speed only showed statistical differences for the spacing variables and the average deviation values ??while the conductor tubes showed distinct performance, with the Selenium tube being the one with the highest percentage of average spacings acceptable (98.5%) and smaller average values of ??spacing misses, multiples and coefficient of variation (Cve): 0.67; 0.68 and 18.4% respectively.

Estimation of Transfer Time from Multimodal Transit Services in the Paris Region

A reliable public transport system is beneficial for people traveling in the metropolitan area. Transfer time in multimodal transit networks has been highlighted as one of the measures of public transport service quality. In this paper, we propose a novel method to estimate the passengers’ transfer time between the transit modes (i.e., train, metro, and bus) based on the 2018 Household Travel Survey in the Paris region, France. The transit trips with a single transit leg are primarily studied, wherein average wait time and mode speeds are estimated through an integrated linear regression model. Based on these inferences, transfer time is deduced within the trips of multiple transit legs. The decomposition procedure of journey time facilitates the estimation of the time components, and reveals the transfer variability in mode, time, and space. From the results, we find that the transfer to the railway modes, especially to the metro, costs less time on average than the transfer to the bus in the study area. The transfer patterns in the morning and evening peak hours are different regarding the transfer duration and locations. Lastly, the results’ reliability, method scalability, and potential applications are discussed in detail.

Projectional Editing of Software Product Lines Using Multi-variant Model Editors

Model-driven software engineering (MDSE) as well as software product line engineering (SPLE) achieve productivity gains by raising the level of abstraction and fostering organized reuse. Consequently, the integrating discipline model-driven software product line engineering (MDSPLE) aims at combining the best of both worlds by creating multi-variant models which are (automatically) configured into single-variant models which are in turn adapted further (if required). Inherently complex multi-variant models call for urgently needed tools providing support for editing multi-variant models. In this paper, we present a framework for projectional multi-variant editors which make complexity manageable using a user-friendly representation. At all times, a domain engineer is aware of editing a multi-variant model which is necessary to assess the impact of changes on all model variants. Supporting a clear separation of product space (domain model) and variant space (variability annotations), our projectional multi-variant editors provide a novel approach to representing variability information which is displayed non-intrusively. Furthermore, the domain engineer may employ a projectional multi-variant editor to adapt the representation of the multi-variant domain model in a flexible way, according to the current focus of interest.

On the Birth of the Universe and Time

A theory of the initial state of the universe is proposed within the framework of the Euclidean quantum theory of gravity. The theory is based on a quantum representation in which the action functional is implemented as an operator on the space of wave functionals depending on the 4D space metric and matter fields. The initial construction object is the eigenvalue of the action operator in the area of the origin of the universe with the given values of the 3D metric and matter fields on the boundary. The wave function of the initial state is plotted as an exponential of this eigenvalue, after a Wick rotation in the complex plane of the radial variable of the Euclidean 4D space. An estimate of the initial radius of the universe is proposed.

Posture dependent factors influence movement variability when reaching to nearby virtual objects.

Reaching movements are subject to noise arising during the sensing, planning and execution phases of movement production, which contributes to movement variability. When vision of the moving hand is available, reach endpoint variability appears to be strongly influenced by internal noise associated with the specification and/or online updating of movement plans in visual coordinates. In contrast, without hand vision, endpoint variability appears more dependent upon movement direction, suggesting a greater influence of execution noise. Given that execution noise acts in part at the muscular level, we hypothesized that reaching variability should depend not only on movement direction but initial arm posture as well. Moreover, given that the effects of execution noise are more apparent when hand vision is unavailable, we reasoned that postural effects would be more evident when visual feedback was withheld. To test these hypotheses, participants planned memory-guided reaching movements to three frontal plane targets using one of two initial arm postures ("adducted" or "abducted"), attained by rotating the arm about the shoulder-hand axis. In this way, variability was examined for two sets of movements that were largely identical in endpoint coordinates but different in joint/muscle-based coordinates. We found that patterns of reaching variability differed in several respects when movements were initiated with different arm postures. These postural effects were evident shortly after movement onset, near the midpoints of the movements, and again at the endpoints. At the endpoints, posture dependent effects interacted with effects of visual feedback to determine some aspects of variability. These results suggest that posture dependent execution noise interacts with feedback control mechanisms and biomechanical factors to determine patterns of reach endpoint variability in 3D space.

Emission estimates and air quality simulation on Lombardy during lockdown.

This paper illustrates the study carried out by ARPA Lombardia to quantify the variation in daily emissions of the main pollutants and their impacts on air quality in Lombardy during the anti-COVID-19 lockdown between the end of February and the end of May 2020. A methodology for emission estimates was developed over Lombardy for this purpose and later was extended to larger areas: the Po-basin, (LIFE PREPAIR 2020) and the entire Italy (PULVIRUS 2021). In this study, the daily emissions estimates were derived by combining data from air emission inventory of Lombardy and a set of indicators that allowed to update the estimates and describe the temporal and spatial variations of the emission sources. The calculation of emission variation was conducted for all the main pollutants (PM10, NH3, NOx, SO2, NMVOC) and the greenhouse gases; then, the impact on air quality concentrations was simulated by the chemical and transport model FARM, that also allows to track secondary particulate and its variability in time and space on the basis of nonlinear processes and weather conditions. The estimated emission reduction, compared to the expected average value in the absence of anti-COVID-19 measures, daily varies depending on pollutants and is mainly affected by reductions in road traffic emissions and an estimated increase in domestic heating emissions. Simulations confirm strong reductions of NO2 atmospheric average concentrations, slightly variations of PM10 averages and a potential growth of tropospheric ozone.

Insights into the Spatial and Temporal Variability of Soil Attributes in Irrigated Farm Fields and Correlations with Management Practices: A Multivariate Statistical Approach

The evaluation of the spatial and temporal variability of soil properties can be valuable to improve crop productivity and soil health. A study of soil properties was carried out in southern Portugal, in three farm fields with irrigated annual crops (layers 0–20 cm and 20–40 cm), over three years. Factor Analysis (FA) and Discriminant Analysis (DA) were used to analyze the data. With FA, the observed variables were grouped into a smaller number of latent variables related to soil attributes. Discriminant Analysis was used to classify and identify the most dominant attributes and indicators for the time and space variability of soil parameters. The FA performed for the surface layer included factors related to texture, water and nutrient retention capacity, chemical composition, and soil fertility. In the sub-surface layer, the factor structure was similar, with four factors related to texture, chemical composition, nutrient availability, and soil fertility. The most influential factors and variables in temporal discrimination (sampling dates) in both layers were those related to chemical composition, with electric conductivity as the preponderant indicator. As for the spatial differentiation (fields), the dominant factor in the surface layer was texture, and in the sub-surface layer, nutrient availability. The most important discriminant indicators of spatial variability were fine sand proportion and available potassium, respectively, for the surface and sub-surface layers. The results obtained showed potential for the multidimensional and integrated assessment of patterns of temporal and spatial variation of soil functions from agricultural practices or soil degradation processes.

Acoustic Imaging Observes Predator–Prey Interactions between Bull Trout and Migrating Sockeye Salmon Smolts

AbstractAnnual migrations by juvenile Pacific salmon Oncorhynchus spp. smolts are predictable, presenting opportunities for predators to exploit these seasonal prey pulses. Directly observing predator–prey interactions to understand factors affecting predation may be possible via dual‐frequency identification sonar (DIDSON) acoustic imaging. Within Chilko Lake, British Columbia, prior telemetry and stomach content analyses suggested that the out‐migration of Sockeye Salmon Oncorhynchus nerka smolts influences the movements and aggregations of Bull Trout Salvelinus confluentus that feed extensively on smolts during their out‐migration. Bull Trout captured at a government‐installed counting fence exhibited high consumption of smolts, but it is only assumed that feeding occurred directly at the fence. We used DIDSON to assess fine‐scale predator–prey interactions between Sockeye Salmon smolts and Bull Trout over 10 d during the 2016 smolt out‐migration. We found that smolt–Bull Trout interactions were correlated with smolt densities at the counting fence, consistent with the prior diet studies in the system. Predator–prey interactions were also coupled with nocturnal migratory behaviors of Sockeye Salmon smolts, presumably to minimize predation risk. These results demonstrate that DIDSON technology can record interactions between predators and migrating prey at a resolution that can identify variability in space and time and provide insight on the role of anthropogenic structures (e.g., counting fences) in mediating such interactions.

A Generalized Framework for Risk-Based Extreme Load Analysis in Offshore System Design

Abstract The primary aim of this research is to consider the correlation among environmental factors in calculating 100 and 1000 years of extreme load design criteria. This is done by considering load as energy transferred from external environment to the offshore system. Also, incorporating spatial and temporal dependence of environmental variables in the context of offshore design. A bivariate extreme value distribution and a conditional joint return level function are developed using the Gumbel–Hougaard copula. The offshore design risk criteria are developed for the finer grid locations (0.1 deg × 0.1 deg latitude/longitude grid) considering joint extreme wind and wave energy. The developed approach is tested using data for the Flemish Pass basin off the east coast of Canada. Along with the primary aim, the impact of climate change is investigated (time and space variability) by implementing the proposed methodology in two cases: the periods from 1959 to 1988 and 1989 to 2018. This study observed that climate change has caused 30% less correlation between wind speed and wave height in recent years (1989–2018) compared to the period of 1959–1988. The proposed extreme design wind speed is 39.7 m/s, and significant wave height is 16.4 m; their joint exceeding probability is 5.80 × 10−5 over an annual basis for a scenario of 100-year.

Leveraging Embodied Intelligence for Dexterous Robotic Manipulators Through Iterative Co-design

The role of embodied intelligence (EI) has the potential to overcome current limitations in the fabrication, control, and resulting behavior to create robust and effective dexterous robotic manipulators. To develop hands that truly exploit EI, we must design hands by considering the entire system: the physical body, sensory systems, and the brain (the controller). However, we lack clear approaches and methods that enable this system level design for hands. We introduce an iterative approach for co-design which seeks to utilize simulation and real world evaluation to maximize the performance by distributing EI across the different elements of the system. To achieve this vision we require hands that can be rapidly fabricated with variability in the design space. Thus, to further the development of robotic hands that utilize EI we need streamlined fabrication pipelines which incorporate spatially distributed sensors, complex geometries and materials, and control distributed at the sensory-motor and high task planning domains.

Assessment of Urban Green Space Dynamics Influencing the Surface Urban Heat Stress Using Advanced Geospatial Techniques

Urban areas are mostly heterogeneous due to settlements and vegetation including forests, water bodies and many other land use and land cover (LULC) classes. Due to the overwhelming population pressure, urbanization, industrial works and transportation systems, urban areas have been suffering from a deficiency of green spaces, which leads to an increase in the variation of temperature in urban areas. This study investigates the conceptual framework design towards urban green space (UGS) and thermal variability over Kolkata and Howrah city using advanced remote sensing (RS) and geospatial methods. The low green space is located in the highly built-up area, which is influenced by thermal variations. Therefore, the heat stress index showed a high area located within the central, north, northwestern and some parts of the southern areas. The vegetated areas decreased by 8.62% during the ten years studied and the other land uses increased by 11.23%. The relationship between land surface temperature (LST) and the normalized difference vegetation index (NDVI) showed significant changes with R2 values between 0.48 (2010) and 0.23 (2020), respectively. The correlation among the LST and the normalized difference built-up index (NDBI) showed a notable level of change with R2 values between 0.38 (2010) and 0.61 (2020), respectively. The results are expected to contribute significantly towards urban development and planning, policymaking and support for key stakeholders responsible for the sustainable urban planning procedures and processes.

OPTIMIZATION OF THE DESIGN PROCESS OF HIGH-RISE BUILDINGS WITH INTEGRATED SOLAR SYSTEMS

The relevance of the tasks of integrating solar energy into the energy system of high-rise buildings is associated with their high level of energy consumption compared to lower-rise buildings. In the course of the analysis of scientific research carried out in the article, factors were noted that complicate the use of solar energy, primarily its variability in space and time. Therefore, the aim of the study was to optimize the formation of design solutions for high-rise buildings to improve the efficiency of solar energy systems integrated into them.
 In the article, the initial provisions for the design of heliosystems in high-rise buildings are investigated, the factors influencing the design process are established, and the design levels of modeling are highlighted. It is shown that the realization of the advantages of solar energy when integrated into high-rise buildings should be based on integrated design, taking into account the natural-climatic, urban planning, space-planning, structural and technological levels of design analysis. The available technologies for the use of solar energy are analyzed. The conditions under which the implementation of the principle of "permissible interference" will be carried out, when one or another task of integrating solar systems into a high-rise building can be correctly implemented as a fragment of the corresponding design stage.
 It has been determined that the effectiveness of design solutions for the integration of solar renewable energy into high-rise buildings is provided taking into account numerous connections and influences, which requires an appropriate system analysis for their optimization.

포스트코로나 시대 노후아파트 리모델링 계획을 위한 거주자 의견 조사

Background/Objectives: Apartment dwellers had various problems such as hygiene and quarantine in their residential space, lack of area, privacy and noise during the pandemic. The purpose of this study was to identify the direction of the remodeling plan reflecting their opinions by classifying the deteriorated apartment residents in the metropolitan area by family life cycle during the pandemic. Methods: The survey method of this study was conducted with 201 apartment dwellers living in deteriorated apartments over 15 years old in the metropolitan area in South Korea. Results: The results of the study are as follows. First, in terms of unit planning, variable space planning that can be used for multiple purposes in all family life cycles and space planning for exercise and hobbies were derived as important items. Second, all family life cycles showed a high preference for safety and hygiene of common spaces in apartments. Third, in terms of complexes and communities, all family life cycles showed high preference for hygiene and functionality of community facilities. Conclusion/Implications: These results imply that when planning apartment remodeling in the post-corona era, it is necessary to consider the variability of space for unit households, the sanitary condition of the main building, and the diversity of community facilities.