Large Time Frames Research Articles

Освоение моделирования как элемента подготовки студентов-гуманитариев в условиях развития технологии больших данных

g Data is a qualitatively new information object that requires special methods of analysis and processing. The peculiarity of Big Data is the following: traditional methods of data processing in the case of Big Data may not be effective, since they require very large time frames and computing resources; Big Data, in many ways, loses its discrete structure and approaches its properties to structures of continuity, which complicates the use of traditional methods of discrete analysis. The article discusses approaches to the study of Big Data in humanitarian universities. The sources of the emergence of big data in this area are discussed as an imbalance between the syntactic and semantic aspects of the information object. It is substantiated that in humanitarian universities it is advisable to place emphasis on mastering the modeling methodology, which, in many respects, allows eliminating this imbalance.

The REBURN model: simulating system-level forest succession and wildfire dynamics

BackgroundHistorically, reburn dynamics from cultural and lightning ignitions were central to the ecology of fire in the western United States (wUS), whereby past fire effects limited future fire growth and severity. Over millennia, reburns created heterogenous patchworks of vegetation and fuels that provided avenues and impediments to the flow of future fires, and feedbacks to future fire event sizes and their severity patterns. These dynamics have been significantly altered after more than a century of settler colonization, fire exclusion, and past forest management, now compounded by rapid climatic warming. Under climate change, the area impacted by large and severe wildfires will likely increase — with further implications for self-regulating properties of affected systems. An in-depth understanding of the ecology of reburns and their influence on system-level dynamics provides a baseline for understanding current and future landscape fire-vegetation interactions.ResultsHere, we present a detailed characterization of REBURN — a geospatial modeling framework designed to simulate reburn dynamics over large areas and long time frames. We interpret fire-vegetation dynamics for a large testbed landscape in eastern Washington State, USA. The landscape is comprised of common temperate forest and nonforest vegetation types distributed along broad topo-edaphic gradients. Each pixel in a vegetation type is represented by a pathway group (PWG), which assigns a specific state-transition model (STM) based on that pixel’s biophysical setting. STMs represent daily simulated and annually summarized vegetation and fuel succession, and wildfire effects on forest and nonforest succession. Wildfire dynamics are driven by annual ignitions, fire weather and topographic conditions, and annual vegetation and fuel successional states of burned and unburned pixels.ConclusionsOur simulation study is the first to evaluate how fire exclusion and forest management altered the active fire regime of this landscape, its surface and canopy fuel patterns, forest and nonforest structural conditions, and the dynamics of forest reburning. The REBURN framework is now being used in related studies to evaluate future climate change scenarios and compare the efficacy of fire and fuel management strategies that either enable the return of active fire regimes or depend on fire suppression and wildfire effects on forest burning.

A New Conceptual Framework and Approach to Decision Making in Public Policy

In this conceptual paper, we bring forward a new theoretical proposition in the form of an Integrated Policy-Making Process Framework. This tool arose from the discussion and hypothesis that the main models used to analyse public policies have practical and theoretical limitations and/or are due for an update, especially when it comes to the study of phenomena with many actors involved, vast legislation, large timeframes, and high degrees of complexity. Our original model encompasses the three fundamental stages of the public policy cycle (agenda; decision making; implementation). Our approach can have a wide spectrum of applications and contribute to the field of knowledge of political sciences. Our proposal of using three frameworks in an integrated way enables researchers and users to gain a holistic vision concerning policy processes, and it offers the possibility to compare and rank categories. The Integrated Policy-Making Process Framework is thus proposed as a new tool to tackle research and studies on decision making in public policies and the policy-making cycle.

Lunar thermal mining: Phase change interface movement, production decline and implications for systems engineering

Thermal mining is a promising architecture, which may provide reliable and ‘dirt-simple’ means of production of space-sourced water, oxygen and rocket propellant in the future. It is especially tailored to water ice deposits that exist within lunar Permanently Shadowed Regions, where our quest for riches of the Outer Space might begin.Here, the thermal mining extraction system is simulated and analysed with combined heat and mass transfer FEM modelling. The results exhibited that water extraction on the Moon might follow specific production phases, which closely relate to changes in the sublimation interface movement over large timeframes. The production behaviour on the Moon might have many characteristics of relevant production systems on Earth. This may open door for many well-established terrestrial models and production projections to be refitted to extraterrestrial case.It was found that the required water yields of the thermal mining architecture, which make its case economically and commercially viable, are hard to reach without production optimization and new systems development. The production is projected to be significantly hindered by sublimation lag build-up, which would create thermal insulation for the icy deposits. Sublimation lag removal and other strategies might be the answer to that problem.

Transfer of Technology in Indian Defence Manufacture - Elements and Challenges

Transfer of Technology in Indian Defence Manufacture - Elements and Challenges - JMRA- Print ISSN No: - 2394-2762 Online ISSN No:- 2394-2770 Article DOI No:- 10.18231/j.jmra.2020.003, Journal of Management Research and Analysis-J Manag Res Anal

Scalable Recollections for Continual Lifelong Learning

Given the recent success of Deep Learning applied to a variety of single tasks, it is natural to consider more human-realistic settings. Perhaps the most difficult of these settings is that of continual lifelong learning, where the model must learn online over a continuous stream of non-stationary data. A successful continual lifelong learning system must have three key capabilities: it must learn and adapt over time, it must not forget what it has learned, and it must be efficient in both training time and memory. Recent techniques have focused their efforts primarily on the first two capabilities while questions of efficiency remain largely unexplored. In this paper, we consider the problem of efficient and effective storage of experiences over very large time-frames. In particular we consider the case where typical experiences are O(n) bits and memories are limited to O(k) bits for k

The other side of need: Reverse economic flows ensuring migrants' transnational social protection

AbstractAlthough there has been a significant study of remittances sent by migrants to their origin countries, reverse economic flows originating from sending contexts have so far received little attention. This paper shows that Ecuadorian migrants living in Europe use financial support from their relatives and their own economic resources from their origin country deriving from the renting of their properties, and to a lesser extent other sources. Financial means from Ecuador are used to ensure various transnational social protection needs both in Europe and in Ecuador, mostly by long‐settled economic migrants. Such arrangements emerged for 21 out of the total 63 transnational families considered in our study, investigated through a multi‐sited ethnography with a partially matched sample, conducted in 2015–2016 in Spain, England, and Ecuador. These unusual economic flows reflect an indirect reciprocity system of mutual responsibilities operating over large time frames and sometimes involve emotional discomfort and relational dissonances.

Constraining long‐term fault activity in the brittle domain through in situ dating of hydrothermal monazite

AbstractSIMS Th–Pb dating of hydrothermal fissure‐vein monazite‐(Ce) has the unique potential to date multiple tectonic events under low‐grade metamorphic brittle/ductile conditions over large time frames. Monazites‐(Ce) from brittle fault systems in the Eastern Alps allow us to constrain their Cretaceous activity over 20 Ma within single crystals, recording all major tectonic events. Eo‐Alpine formation of the fluid‐filled fissure‐veins occurred 90 Ma ago at 352 ± 19°C and 342 ± 42 MPa. This corresponds to peak conditions during regional metamorphism of the Cretaceous collisional nappe stacking. Several stages of dissolution–reprecipitation/recrystallization record fault activity between 84 and 70 Ma. Corresponding fluid inclusions indicate conditions of 229 ± 10°C and 143 ± 20 MPa. This correlates with the formation of sedimentary basins during post‐orogenic extension associated with strike‐slip movements. The results strengthen the hypothesis that many large fault systems in the Eastern Alps developed during the Cretaceous orogeny and became reactivated during Neogene Alpine tectonics.

Leveraging healthcare utilization to explore outcomes from musculoskeletal disorders: methodology for defining relevant variables from a health services data repository

BackgroundLarge healthcare databases, with their ability to collect many variables from daily medical practice, greatly enable health services research. These longitudinal databases provide large cohorts and longitudinal time frames, allowing for highly pragmatic assessment of healthcare delivery. The purpose of this paper is to discuss the methodology related to the use of the United States Military Health System Data Repository (MDR) for longitudinal assessment of musculoskeletal clinical outcomes, as well as address challenges of using this data for outcomes research.MethodsThe Military Health System manages care for approximately 10 million beneficiaries worldwide. Multiple data sources pour into the MDR from multiple levels of care (inpatient, outpatient, military or civilian facility, combat theater, etc.) at the individual patient level. To provide meaningful and descriptive coding for longitudinal analysis, specific coding for timing and type of care, procedures, medications, and provider type must be performed. Assumptions often made in clinical trials do not apply to these cohorts, requiring additional steps in data preparation to reduce risk of bias. The MDR has a robust system in place to validate the quality and accuracy of its data, reducing risk of analytic error. Details for making this data suitable for analysis of longitudinal orthopaedic outcomes are provided.ResultsAlthough some limitations exist, proper preparation and understanding of the data can limit bias, and allow for robust and meaningful analyses. There is the potential for strong precision, as well as the ability to collect a wide range of variables in very large groups of patients otherwise not captured in traditional clinical trials. This approach contributes to the improved understanding of the accessibility, quality, and cost of care for those with orthopaedic conditions.ConclusionThe MDR provides a robust pool of longitudinal healthcare data at the person-level. The benefits of using the MDR database appear to outweigh the limitations.

Does a Crossover Age Effect Exist for African American and Hispanic Binge Drinkers? Findings from the 2010 to 2013 National Study on Drug Use and Health.

Among general population studies, lower rates of binge drinking tend to be found among African Americans and Hispanics compared to Whites. However, among older adult populations, minority groups have been shown to be at higher risk for binge drinking, suggesting the presence of a crossover effect from low to high risk as a function of age. To date, limited research has examined the crossover effect among African American and Hispanic populations compared to non-Hispanic Whites across large developmental time frames or explored variation in risk based on income or gender. This study aimed to fill these gaps in the literature. Data were compiled from the 2010 to 2013 National Survey on Drug Use and Health surveys, which provide annual, nationally representative data on substance use behaviors among individuals aged 12 and older. Hispanic, non-Hispanic African American, and non-Hispanic White respondents were included (N=205,198) in the analyses. A crossover effect was found for African American males and females among the lowest income level (i.e., incomes less than $20,000). Specifically, after controlling for education and marital status, compared to Whites, risk for binge drinking was lower for African American males at ages 18 to 24 and for females at ages 18 to 34, but higher for both African American males and females at ages 50 to 64. No crossover effect was found for Hispanic respondents. Although African Americans are generally at lower risk for binge drinking, risk appears to increase disproportionately with age among those who are impoverished. Explanatory factors, such as social determinants of health prevalent within low-income African American communities (e.g., lower education, violence exposure, housing insecurity) and potential areas for intervention programming are discussed.

Simulation of Maxwell's Equations on GPU Using a High-Order Error-Minimized Scheme

AbstractIn this study an explicit Finite Difference Method (FDM) based scheme is developed to solve the Maxwell's equations in time domain for a lossless medium. This manuscript focuses on two unique aspects – the three dimensional time-accurate discretization of the hyperbolic system of Maxwell equations in three-point non-staggered grid stencil and it's application to parallel computing through the use of Graphics Processing Units (GPU). The proposed temporal scheme is symplectic, thus permitting conservation of all Hamiltonians in the Maxwell equation. Moreover, to enable accurate predictions over large time frames, a phase velocity preserving scheme is developed for treatment of the spatial derivative terms. As a result, the chosen time increment and grid spacing can be optimally coupled. An additional theoretical investigation into this pairing is also shown. Finally, the application of the proposed scheme to parallel computing using one Nvidia K20 Tesla GPU card is demonstrated. For the benchmarks performed, the parallel speedup when compared to a single core of an Intel i7-4820K CPU is approximately 190x.

Treatability Testing for Weathered Hydrocarbons in Soils: Bioremediation, Soil Washing, Chemical Oxidation, and Thermal Desorption

Soils previously treated with landfarming to reduce petroleum hydrocarbon concentrations are often left with a less biodegradable residual fraction that can present challenges for additional treatment. Four possible polishing technologies were tested on the bench scale for weathered hydrocarbons present in fine-grain soils obtained from a previously landfarmed area at an active oil refinery. The technologies included additional bioremediation (both biostimulation and bioaugmentation tested), soil washing, chemical oxidation, and low-temperature thermal desorption. Multiple parameters were tested separately for each technology to identify possible factors that were relevant across technologies. Extractable hydrocarbons comprised only approximately 35% of the organic carbon in the soils, and this component was considerably less affected by biological, surfactant, and oxidant treatment than organic materials that are not quantified by the TEH analysis. Treatment testing of thermal desorption indicated removal of large quantities of extractable hydrocarbons despite the presence of high organic matter. The additional demand to the system would likely result in considerably large timeframes (biological treatment), reagent quantities (soil washing and oxidation), or energy input (thermal desorption) for treatment of target hydrocarbons on a full scale.

EcoVeg: a new approach to vegetation description and classification

A vegetation classification approach is needed that can describe the diversity of terrestrial ecosystems and their transformations over large time frames, span the full range of spatial and geographic scales across the globe, and provide knowledge of reference conditions and current states of ecosystems required to make decisions about conservation and resource management. We summarize the scientific basis for EcoVeg, a physiognomic‐floristic‐ecological classification approach that applies to existing vegetation, both cultural (planted and dominated by human processes) and natural (spontaneously formed and dominated by nonhuman ecological processes). The classification is based on a set of vegetation criteria, including physiognomy (growth forms, structure) and floristics (compositional similarity and characteristic species combinations), in conjunction with ecological characteristics, including site factors, disturbance, bioclimate, and biogeography. For natural vegetation, the rationale for the upper levels (formation types) is based on the relation between global‐scale vegetation patterns and macroclimate, hydrology, and substrate. The rationale for the middle levels is based on scaling from regional formations (divisions) to regional floristic‐physiognomic types (macrogroup and group) that respond to meso‐scale biogeographic, climatic, disturbance, and site factors. Finally, the lower levels (alliance and association) are defined by detailed floristic composition that responds to local to regional topo‐edaphic and disturbance gradients. For cultural vegetation, the rationale is similar, but types are based on distinctive vegetation physiognomy and floristics that reflect human activities. The hierarchy provides a structure that organizes regional/continental vegetation patterns in the context of global patterns. A formal nomenclature is provided, along with a descriptive template that provides the differentiating criteria for each type at all levels of the hierarchy. Formation types have been described for the globe; divisions and macrogroups for North America, Latin America and Africa; groups, alliances and associations for the United States, parts of Canada, Latin America and, in partnership with other classifications that share these levels, many other parts of the globe.

Dynamic thermal sensor for biofilm monitoring

A novel sensor principle to continuously monitor biofilm formation by Enterococcus faecalis is presented. The sensor consists of a small heater and a temperature probe (thermistor); both are located on a thermally insulating, silicon nitride membrane. Biofilm is allowed to develop in M17-medium at 37°C on the surface of the membrane. Electrical current applied to the heater produces a steady sinusoidal power signal at 40Hz. The resulting temperature oscillations are captured by the temperature probe. Their amplitude and phase shift are influenced by the thickness and composition of the biofilm. Results show that the sensor system is able to monitor the evolution of biofilms for large time frames (hours). It also features very stable baseline measurements that outperform other types of sensor systems. A proof-of-concept by means of an antibiotics-growth-inhibition test is achieved.

Terpenes Tell Different Tales at Different Scales: Glimpses into the Chemical Ecology of Conifer - Bark Beetle - Microbial Interactions

Chemical signaling mediates nearly all aspects of species interactions. Our knowledge of these signals has progressed dramatically, and now includes good characterizations of the bioactivities, modes of action, biosynthesis, and genetic programming of numerous compounds affecting a wide range of species. A major challenge now is to integrate this information so as to better understand actual selective pressures under natural conditions, make meaningful predictions about how organisms and ecosystems will respond to a changing environment, and provide useful guidance to managers who must contend with difficult trade-offs among competing socioeconomic values. One approach is to place stronger emphasis on cross-scale interactions, an understanding of which can help us better connect pattern with process, and improve our ability to make mechanistically grounded predictions over large areas and time frames. The opportunity to achieve such progress has been heightened by the rapid development of new scientific and technological tools. There are significant difficulties, however: Attempts to extend arrays of lower-scale processes into higher scale functioning can generate overly diffuse patterns. Conversely, attempts to infer process from pattern can miss critically important lower-scale drivers in systems where their biological and statistical significance is negated after critical thresholds are breached. Chemical signaling in bark beetle - conifer interactions has been explored for several decades, including by the two pioneers after whom this award is named. The strong knowledge base developed by many researchers, the importance of bark beetles in ecosystem functioning, and the socioeconomic challenges they pose, establish these insects as an ideal model for studying chemical signaling within a cross-scale context. This report describes our recent work at three levels of scale: interactions of bacteria with host plant compounds and symbiotic fungi (tree level, biochemical time), relationships among inducible and constitutive defenses, population dynamics, and plastic host-selection behavior (stand level, ecological time), and climate-driven range expansion of a native eruptive species into semi-naïve and potentially naïve habitats (geographical level, evolutionary time). I approach this problem by focusing primarily on one chemical group, terpenes, by emphasizing the curvilinear and threshold-structured basis of most underlying relationships, and by focusing on the system's feedback structure, which can either buffer or amplify relationships across scales.

Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to derive trajectories of aboveground forest biomass for study locations in Arizona and Minnesota. We compared three statistical techniques (Reduced Major Axis regression, Gradient Nearest Neighbor imputation, and Random Forests regression trees) for modeling biomass to better understand how the choice of model type affected predictions of biomass dynamics. Models from each technique were applied across the 20+ year Landsat time-series to derive biomass trajectories, to which a curve-fitting algorithm was applied to leverage the temporal information contained within the time-series itself and to minimize error associated with exogenous effects such as biomass measurements, phenology, sun angle, and other sources. The effect of curve-fitting was an improvement in predictions of biomass change when validated against observed biomass change from repeat FIA inventories. Maps of biomass dynamics were integrated with maps depicting the location and timing of forest disturbance and regrowth to assess the biomass consequences of these processes over large areas and long time frames. The application of these techniques to a large sample of Landsat scenes across North America will facilitate spatial and temporal estimation of biomass dynamics associated with forest disturbance and regrowth, and aid in national-level estimates of biomass change in support of the North American Carbon Program.

Spacecraft Large Attitude Estimation Using a Navigation Sensor

In this paper we assume that we have measurements of a first difference of a typical satellite navigation carrier phase differential, which is a homogeneous quadratic function of the components of the attitude quaternion. We illustrate the determination of large or sustained attitudes using a dedicated unscented Kalman filter. The unscented Kalman filter structure was chosen for the dedicated filter because of its derivative free nature and other advantages. When a Gaussian distributed vector random variable is transformed to an equivalent quaternion it does not continue to be Gaussian distributed. For this reason, a new predictor-corrector form of the unscented Kalman filter is proposed to maintain the normalization of the unscented mean quaternion estimate in the presence of additive disturbances. The results from our realistic simulations indicate that the large attitude of a spacecraft can be estimated to within 0·1% accuracy over large time frames. The filter is particularly useful for autonomous operations of spacecraft as well as in other applications where the process model is bilinear or second order in the states.

Digging deep: Exploring college students' knowledge of macroevolutionary time

AbstractSome ability to comprehend deep time is a prerequisite for understanding macroevolution. This study examines students' knowledge of deep time in the context of seven major historical and evolutionary events (e.g., the age of the Earth, the emergence of life, the appearance of a pre‐modern human, Homo habilis). The subjects were 126 students recruited from psychology, education, and biology classes at two universities. They were assigned to stronger and weaker background groups based on their college‐level biology coursework. Subjects provided startlingly large time ranges for all questions, ranging over several orders of magnitude (e.g., from 1,000 to 600 billion years ago for when most dinosaurs became extinct), coupled with the strong tendency to underestimate how long ago the events occurred. Converting absolute time estimates to relative time estimates allowed subjects' knowledge of the spacing of the events to be examined and also provided a clearer picture of their patterns of over and underestimation. The results of this study suggest that many students are without an effective conceptual framework to make sense of very large time frames. Although there were no consistent differences in the accuracy of students' responses as a function of their biology background, the weaker background students showed greater variability, providing more time estimates at both the low and high extremes. We describe a pedagogical strategy that uses a relative approach presenting major evolutionary events as they unfolded in time and advocate a tool from professional practice to depict events in time and space. © 2009 Wiley Periodicals, Inc. J Res Sci Teach 46: 311–332, 2009

Indicators to assess biological diversity: Weyerhaeuser's coastal British Columbia forest project

Adaptive management is a key component of a forest project being implemented across all of Weyerhaeuser's coastal forest tenures. This project uses two main tools to accomplish the British Columbia (BC) Coastal Group's ecological and socio-economic goals: variable retention (VR) harvesting and broad zoning of the land base. The adaptive management program was designed to examine the effectiveness of retention systems and zoning in maintaining those forest attributes necessary to sustain biological richness and essential ecosystem functions, such as nutrient transfer, energy flow, decomposition, and dispersal of seeds, spores, and animals. The program is grounded on three biological indicators evaluated in both operational and experimental contexts: 1) representation of habitat types in a relatively unmanaged state to ensure that little-known species are retained; 2) structure of stands and landscapes to ensure that key elements are present through time; and 3) indicator organisms to track whether retaining structures and patterns, while addressing representation, will maintain species and populations whose life needs are well understood. Representation of ecosystems in unmanaged conditions has been examined. Habitat structure is being assessed in VR blocks and in unmanaged blocks. Studies on several organisms (breeding birds, owls, gastropods, amphibians, bryophytes, lichen, squirrels, mycorrhizae, and carabid beetles) have been underway for various lengths of time. These studies collected baseline information to begin comparisons of the effectiveness of the various types of VR for maintaining biological richness. The current focus in the adaptive management program is refining the lists of specific elements to monitor and beginning to create tools to help extrapolate relationships and findings over large areas and long time frames, with the expectation of operational implementation in 2003. The first two years of pilot work are also being used to examine how the results will link to management practices to strengthen areas that most need improvement. This paper describes three indicators used in Weyerhaeuser's adaptive management program. Key words: adaptive management, variable retention harvesting, indicators for monitoring forests

Two-phase flow and transport in a single fracture-porous medium system

The prognosis for the remediation of contaminated fractured media is much worse than that for more homogeneous units. Fractures act as conduits for the flow of dense non-aqueous phase liquids (DNAPLs), while diffusion is responsible for the storage of dissolved mass in the surrounding matrix. A numerical model incorporating aqueous phase transport in a variable-aperture fracture and its surrounding matrix is developed and coupled with an existing two-phase flow model. The processes of transient two-phase flow, non-equilibrium dissolution, advective–dispersive transport in the fracture, and three-dimensional matrix diffusion are included in the model. Results from various investigations show that the DNAPL distribution is very sensitive to variations in aperture within a single fracture. Diffusion-controlled mass removal from both the matrix and from the hydraulically inaccessible zones within the fracture itself result in extremely large time frames for significant mass removal from these systems. Success in aqueous phase mass removal from the matrix is very sensitive to the effective fracture spacing. The hydraulic gradient in the fracture only affects the amount of water removed from the system, and does not greatly affect the amount of time required to remove the contaminant mass from the matrix. The ability to remove mass is somewhat sensitive to the porosity and effective matrix diffusion coefficient over the range of expected values.