Miracle-dz/UniFAR-FTUs huggingface dataset:
Does spatial resolution matter? A multi-scale comparison of object-based and pixel-based methods for detecting change associated with gas well drilling operations

An implicit assumption of the geographic object-based image analysis (GEOBIA) literature is that GEOBIA is more accurate than pixel-based methods for high spatial resolution image classification, but that the benefits of using GEOBIA are likely to be lower when moderate resolution data are employed. This study investigates this assumption within the context of a case study of mapping forest clearings associated with drilling for natural gas. The forest clearings varied from 0.2 to 9.2 ha, with an average size of 0.9 ha. National Aerial Imagery Program data from 2004 to 2010, with 1 m pixel size, were resampled through pixel aggregation to generate imagery with 2, 5, 15, and 30 m pixel sizes. The imagery for each date and at each of the five spatial resolutions was classified into Forest and Non-forest classes, using both maximum likelihood and GEOBIA. Change maps were generated through overlay of the classified images. Accuracy evaluation was carried out using a random sampling approach. The 1 m GEOBIA classification was found to be significantly more accurate than the GEOBIA and per-pixel classifications with either 15 or 30 m resolution. However, at any one particular pixel size (e.g. 1 m), the pixel-based classification was not statistically different from the GEOBIA classification. In addition, for the specific class of forest clearings, accuracy varied with the spatial resolution of the imagery. As the pixel size coarsened from 1 to 30 m, accuracy for the per-pixel method increased from 59% to 80%, but decreased from 71% to 58% for the GEOBIA classification. In summary, for studying the impact of forest clearing associated with gas extraction, GEOBIA is more accurate than pixel-based methods, but only at the very finest resolution of 1 m. For coarser spatial resolutions, per-pixel methods are not statistically different from GEOBIA.
Cropping System Effects on NO3-N Loss with Subsurface Drainage Water

An appropriate combination of tillage and nitrogen management practices will be necessary to develop sustainable farming practices. A six–year (1993–1998) field study was conducted on subsurface–drained Clyde–Kenyon–Floyd soils to quantify the impact of two tillage systems (chisel plow vs. no tillage) and two N fertilizer management practices (preplant single application vs. late–spring soil test based application) on nitrate–nitrogen (NO3–N) leaching loss with subsurface drain discharge from corn (Zea mays L.) soybean (Glycine max L.) rotation plots. Preplant injected urea ammonium nitrate solution (UAN) fertilizer was applied at the rate of 110 kg ha–1 to chisel plow and no–till corn plots, while the late–spring N application rate averaged 179 and 156 kg ha–1 for the no–till and chisel plow corn plots, respectively. Data on subsurface drainage flow volume, NO3–N concentrations in subsurface drainage water, NO3–N loss with subsurface drainage flow, and crop yield were collected and analyzed using a randomized complete block design. Differences in subsurface drainage flow volume due to annual variations in rainfall significantly (P = 0.05) affected the NO3–N loss with subsurface drainage flows. High correlation (R2 = 0.89) between annual subsurface drainage flow volume and the annual NO3–N leaching loss with subsurface drainage water was observed. The flow–weighted average annual NO3–N concentrations varied from a low of 6.8 mg L–1 in 1994 to a high of 13.9 mg L–1 in 1996. Results of this study indicated that NO3–N losses from the chisel plow plots were 16% (16 vs. 19 kg–N ha–1) lower in comparison with no–till plots, while corn grain yield was 11% higher in the chisel plow plots (8.3 vs. 7.5 Mg ha–1). Late–spring N application applied as a sidedress resulted in 25% lower NO3–N leaching losses with subsurface drainage water in comparison with preplant single N application and also significantly (P = 0.5) higher corn grain yield by 13% (8.4 vs. 7.4 Mg ha–1). These results clearly demonstrate that chisel plow tillage with late–spring soil test based N application for corn after soybean can be a sustainable farming practice for the northeast part of Iowa.
Tracking Branches in Trees - A Propositional Encoding for Solving Partially-Ordered HTN Planning Problems

Planning via SAT has proven to be an efficient and versatile planning technique. Its declarative nature allows for an easy integration of additional constraints and can harness the progress made in the SAT community without the need to adapt the planner. However, there has been only little attention to SAT planning for hierarchical domains. To ease encoding, existing approaches for HTN planning require additional assumptions, like non-recursiveness or totally-ordered methods. Both limit the expressiveness of HTN planning severely. We propose the first propositional encodings which are able to solve general, i.e., partially-ordered, HTN planning problems, based on a previous encoding for totally-ordered problems. The empirical evaluation of our encoding shows that it outperforms existing HTN planners significantly.
THE DISTRIBUTION OF Cr BETWEEN BASALTIC MELT AND CHROMIAN SPINEL AS AN OXYGEN GEOBAROMETER

A thermodynamic model of Cr distribution between chromian spinel and basaltic melt has been developed using the [Sack & Ghiorso (1991)][1] thermodynamic model for chromian spinel and an equation analogous to that of [Sack et al. (1980)][2] to calculate the Cr oxidation state in the melt. The model has been calibrated using published experimental data on the composition of coexisting chromian spinel and basaltic melt. The model can be used either to calculate the oxygen fugacity, f (O2), of magmas saturated with chromian spinel, to predict the Cr content of the melt, or to calculate the oxidation state of Cr in the melt. The f (O2) values calculated for a set of natural lavas (primitive MORB and a Hawaiian pumice) using the method show good agreement with f (O2) values calculated from measured values of Fe3+/Fe2+ in the melt. An EXCEL spreadsheet for calculating log f (O2) using composition of glass and chromian spinel is available from the authors upon request. [1]: #ref-23 [2]: #ref-22
The Impact of Perceptions in Averting‐Decision Models: An Application of the Special Regressor Method to Drinking Water Choices

Individuals are commonly surveyed about their perception or assessment of risk and these variables are often used to explain individuals’ actions to protect themselves against these risks. Perceptions appear as endogenous variables in traditional theoretical averting-decision models but, quite surprisingly, endogeneity of perceived risk is not always controlled for in empirical studies. In this article, we present different models that can be useful to the practitioner when estimating binary averting-decision models featuring an endogenous discrete variable (such as risk perception). In particular we compare the traditional bivariate probit model with the special regressor model, which is less well known and relies on a different set of assumptions. In the empirical illustration using household data from Australia, Canada, and France, we study how the perceived health impacts of tap water affect a household’s decision to drink water from the tap. Individuals’ perceptions are found to be endogenous and significant for all models, but the estimated marginal effect is sensitive to the model and underlying assumptions. The special regressor appears to be a valuable alternative to the more common bivariate probit model.
An Analysis of Drivers Affecting Green Supply Chain Management Implementation in Electronics Industry in Thailand

Manufacturers attention now focuses on green supply chain (GSCM) due to pressure from the government and environmental consciousness among customers. However, implementation of GSCM is not easy, so it is necessary to study about the key to success from the successful companies. In this research, electronics industry is depicted. The electronics industry plays a significant role in Thailand due to high exporting to international market. This industry also generates harmful wastes to the environment and makes social environmental problems. Therefore, this study aimed to identify factors that are critical for the implementation of the GSCM strategy of the electronic industry in Thailand in order to help the newcomer in electronic industry who wants to implement GSCM successfully. This study can be used as a guide for other industrial sectors. Data are collected through a questionnaire-based survey, and analyzed using analytic hierarchy process (AHP). Then, the main drivers those affect GSCM on the electronics industry in Thailand are ranked. We have found that regulatory is one of the most critical factors. Moreover, supporting for top management, market/consumer and organization strategy are also important drivers for implementing GSCM.
Effect of Proprioceptive Training on Static Balance and Dynamic Balance of Junior Hockey Players

Proprioceptive training is important and an essential training tool for elite athletes to the everyday person. To achieve this purpose, 40 junior hockey players were selected randomly as subjects for this present study. The subjects selected (N=40), were assigned randomly into two groups namely experimental group-1and control group, consisting of 20 each. Thus they were named experimental group-1 as Proprioceptive Training Group (PTG), and Control Group (CG). Their age was fixed in the range of 14 – 16 years. PTG underwent proprioceptive training programme for three days a week for about twelve weeks. Subjects in the control group were not engaged in any activity. Before and after the training period data will be taken to all the subjects. The collected data were processed with Paired t-test was used. The obtained result was tested at 0.05 level of significance. The results of the study show that experimental group shows better improvement on static balance and dynamic balance when compared to control group.
Sharks in nearshore environments: models, importance, and consequences

Theoretical models of coastal shark populations have remained largely unchanged since the 1960s despite limitations in applicability to many species. Smaller bodied coastal species are poorly represented by the current models. A new theoretical model is proposed to represent those species that spend most or all of their life within nearshore waters but do not show use of discrete nursery areas. Description of this new model outlines the importance of nearshore areas to these smaller species. While all coastal shark populations are susceptible to environmental and anthropogenic impacts, species that fit the new model are more vulnerable to varying coastal processes, habitat degradation, and fishing pressure than are species that use nearshore areas for only part of their life-span. The dynamic nature of nearshore areas and their proximity to human populations present all sharks that occur in them with a range of advantages and disadvantages. This paper reviews how different species utilise nearshore areas and how they overcome the challenges they face in inhabiting these areas. Improving and expanding theoretical models of coastal shark populations will provide a better understanding of how sharks use nearshore environments and assist in making conservation and management decisions for these regions.
Toddler-Inspired Visual Object Learning

Real-world learning systems have practical limitations on the quality and quantity of the training datasets that they can collect and consider. How should a system go about choosing a subset of the possible training examples that still allows for learning accurate, generalizable models? To help address this question, we draw inspiration from a highly efficient practical learning system: the human child. Using head-mounted cameras, eye gaze trackers, and a model of foveated vision, we collected first-person (egocentric) images that represents a highly accurate approximation of the "training data" that toddlers' visual systems collect in everyday, naturalistic learning contexts. We used state-of-the-art computer vision learning models (convolutional neural networks) to help characterize the structure of these data, and found that child data produce significantly better object models than egocentric data experienced by adults in exactly the same environment. By using the CNNs as a modeling tool to investigate the properties of the child data that may enable this rapid learning, we found that child data exhibit a unique combination of quality and diversity, with not only many similar large, high-quality object views but also a greater number and diversity of rare views. This novel methodology of analyzing the visual "training data" used by children may not only reveal insights to improve machine learning, but also may suggest new experimental tools to better understand infant learning in developmental psychology.
Estimating model error covariances using particle filters

A method is presented for estimating the error covariance of the errors in the model equations in observation space. Estimating model errors in this systematic way opens up the possibility to use data assimilation for systematic model improvement at the level of the model equations, which would be a huge step forward. This model error covariance is perhaps the hardest covariance matrix to estimate. It represents how the missing physics and errors in parametrizations manifest themselves at the scales the model can resolve.
Measuring and monitoring soil organic carbon stocks in agricultural lands for climate mitigation

Policies that encourage greenhouse-gas emitters to mitigate emissions through terrestrial carbon (C) offsets – C sequestration in soils or biomass – will promote practices that reduce erosion and build soil fertility, while fostering adaptation to climate change, agricultural development, and rehabilitation of degraded soils. However, none of these benefits will be possible until changes in C stocks can be documented accurately and cost-effectively. This is particularly challenging when dealing with changes in soil organic C (SOC) stocks. Precise methods for measuring C in soil samples are well established, but spatial variability in the factors that determine SOC stocks makes it difficult to document change. Widespread interest in the benefits of SOC sequestration has brought this issue to the fore in the development of US and international climate policy. Here, we review the challenges to documenting changes in SOC stocks, how policy decisions influence offset documentation requirements, and the benefit.
Patient's Satisfaction: Insight into Access to Service, Interpersonal Communication and Quality of Care Issues

Objective: To assess patient satisfaction and expectations from the family medicine department at a newly established public sector hospital in Riyadh. Methodology: A cross sectional study. Pre tested, pre designed, well structured questionnaire written in English with Arabic translation was administered to randomly selected volunteer patients, who presented to family medicine clinics of a tertiary care hospital from February to March 2014. A total of 148 anonymously completed questionnaires were returned to the investigator. Data were analyzed using SPSS-21 and the results expressed as counts and percentages. Results: The overall level of patient satisfaction on a Likert scale from 1 to 5 was indicated by a mean score of 3.84 ± 1.27 for pre-consultation process and 4.63 ± 0.75 for process of consultation by family physicians. The highest satisfaction was with family physicians who clearly explained what is wrong before giving any treatment (4.72 mean points) and the lowest for availability of reading material in the waiting room (2.93 mean points). Conclusion: Consultation by family physicians followed by nursing services were highly satisfactory whereas the satisfaction score and written comments of some of the participants reflected a need to improve some infrastructure and administrative aspects.
Snow grain-size profiles deduced from microwave snow emissivities in Antarctica

Abstract Spaceborne microwave radiometers are an attractive tool for observing Antarctic climate because their measurements are related to the snow temperature. However, the conversion from microwave emission to snow temperature is not simple and strongly depends on the emissivity through snow properties. This difficulty in predicting the snow property profile for Antarctic conditions is the main bottleneck in the retrieval of accurate climate information from microwave radiometers. We attempt to explain the vertically polarized emissivity at 19.3 and 37 GHz derived from brightness temperatures acquired by the Special Sensor Microwave/Imager (SSM/I) and physical temperature from the ERA-40 re-analysis. In Antarctica the snow emissivities at 19.3 and 37 GHz are nearly equal, although a decrease with frequency is expected. To explain this, we consider various profiles of snow grain size and density and predict their emissivity using a dense-medium radiative transfer (DMRT) model. The results show that the emissivities cannot be explained by constant profiles of grain size and density. Heterogeneous snowpacks need to be considered. We first test random variations of snow density and grain radius with depth and then monotonic and continuous variations in the snow grain radius. In both cases, we show that an overall increase of the snow grain radius with depth is required to match the observed emissivity in Antarctica. In addition, two parameters characterizing the snow grain profiles are retrieved and compared with (1) in situ measurements of grain size at various locations in East Antarctica, (2) grain size estimated using visible spaceborne radiometers and (3) a semi-empirical relationship for grain growth.
Simulating Dynamic Stall in a 2D VAWT: Modeling strategy, verification and validation with Particle Image Velocimetry data

The implementation of wind energy conversion systems in the built environment renewed the interest and the research on Vertical Axis Wind Turbines (VAWT), which in this application present several advantages over Horizontal Axis Wind Turbines (HAWT). The VAWT has an inherent unsteady aerodynamic behavior due to the variation of angle of attack with the angle of rotation, perceived velocity and consequentially Reynolds number. The phenomenon of dynamic stall is then an intrinsic effect of the operation of a Vertical Axis Wind Turbine at low tip speed ratios, having a significant impact in both loads and power. The complexity of the unsteady aerodynamics of the VAWT makes it extremely attractive to be analyzed using Computational Fluid Dynamics (CFD) models, where an approximation of the continuity and momentum equations of the Navier-Stokes equations set is solved. The complexity of the problem and the need for new design approaches for VAWT for the built environment has driven the authors of this work to focus the research of CFD modeling of VAWT on: •comparing the results between commonly used turbulence models: URANS (Spalart-Allmaras and k-ϵ) and large eddy models (Large Eddy Simulation and Detached Eddy Simulation) •verifying the sensitivity of the model to its grid refinement (space and time), •evaluating the suitability of using Particle Image Velocimetry (PIV) experimental data for model validation. The 2D model created represents the middle section of a single bladed VAWT with infinite aspect ratio. The model simulates the experimental work of flow field measurement using Particle Image Velocimetry by Simão Ferreira et al for a single bladed VAWT. The results show the suitability of the PIV data for the validation of the model, the need for accurate simulation of the large eddies and the sensitivity of the model to grid refinement.
Intrinsic low-frequency variability of the Gulf Stream

In this paper a process study aimed at analyzing the low-frequency variability of intrinsically oceanic origin of the Gulf Stream (GS) and GS extension (GSE) is pre- sented. An eddy-permitting reduced-gravity nonlinear shal- low water model is implemented in an idealized North At- lantic Ocean, with schematic boundaries including the es- sential geometric features of the coastline and a realistic zonal basin width at all latitudes. The forcing is provided by a time-independent climatological surface wind stress ob- tained from 41 years of monthly ECMWF fields. The model response yields strong intrinsic low-frequency fluctuations on the interannual to decadal time scales. The modelled time- averaged GS/GSE flows are found to exhibit several features that can also be deduced from satellite altimeter data, such as the Florida Current seaward deflection, the GS separation at Cape Hatteras, and the overall structure of the GSE. The intrinsic low-frequency variability yields two preferred states of the GSE differing in latitudinal location that also have their counterpart in the altimeter data. A preliminary analysis of the variability in terms of dynamical systems theory is carried out by using the lateral eddy viscosity as the control param- eter. A complex transition sequence from a steady state to irregular low-frequency variability emerges, in which Hopf and global bifurcations can be identified.
NASA EM Drive via E-Infinity Cantorian-Fractal Space-Time Theory

In the present short Letter we follow El Naschie in advancing the thesis that EM drive is in principle not only possible but more than that. To show that nothing is simpler than appealing to the Hartle-Hawking universe wave function theory as used in a few recent publications by El Naschie concerned with ordinary cosmic energy density and dark cosmic energy density [4-29]. The first, in the meantime well known, is the energy density of the quantum particle which amounts to 4.5% of the total while the rest of 95.5% is related to the quantum wave side of the universe [10,11]. This gradient is sufficient to support a fuelless EM drive enabling interstellar navigation from anywhere to infinity. In fact we need an engine for navigation only, the thrust comes naturally from the local form of one sided Casimir effect of space-time as discussed sometime ago by El Naschie [11-13]. There is a simple picture associated with the energy density gradient from 4.5% to 95.5% which we will attempt to explain in what follows in general terms while detailed mathematical equations are given in the Appendix [4,11,13]. This picture is based on the quantum E-infinity fact that the quantum wave surrounds and guides the quantum particle [7-29]. Applying all that to the entire universe we see that a point inside the universe could be thought of as 4.5% quantum particle energy density location while any point at the hyperbolic horizon and the holographic boundary of the universe may be regarded as the 95.5% quantum wave energy density [4,7,11]. The same idea is expressed in a different language when one invokes Dvoretzky‟s theorem as done by El Naschie and reason that 95.5% of the volume of the higher dimensional (i.e. a five dimensional KaluzaKlein space-time) universe of our real existence lies at a thin layer of the surface [12,13]. Consequently one expects that any spacecraft will be pulled from any point of the interior of the universe towards the hyperbolic boundary of the universe so that a skilful navigation technique could get it from anywhere to any destination and practically without fuel except for navigation. This conclusion is reinforced completely by Dvoretzky‟s theorem [12,13]. That is essentially all that we need for the theoretical justification of EM drive. We stress once more that El Naschie‟s theory goes as far as saying that the thrust is inbuilt into the geometry and topology of the five dimensional vacuum of a fractal space-time so that the motion of the spacecraft is in principle possible with or without an engine. In his formal and ABSTRACT