Miracle-dz/UniFAR-FTUs huggingface dataset:
Collation of earth resources data collected by ERIM airborne sensors

Earth resources imagery from nine years of data collection with developmental airborne sensors is cataloged for reference. The imaging sensors include single and multiband line scanners and side-looking radars. The operating wavelengths of the sensors include ultraviolet, visible and infrared band scanners, and X- and L-band radar. Imagery from all bands (radar and scanner) were collected at some sites and many sites had repeated coverage. The multiband scanner data was radiometrically calibrated. Illustrations show how the data can be used in earth resource investigations. References are made to published reports which have made use of the data in completed investigations. Data collection sponsors are identified and a procedure described for gaining access to the data.
A Computable General Equilibrium Analysis of the Relative Price Sensitivity Required to Induce Rebound Effects in Response to an Improvement in Energy Efficiency in the UK Economy

In recent years there has been extensive debate in the energy economics and policy literature on the likely impacts of improvements in energy efficiency. This debate has focussed on the notion of rebound effects. Rebound effects occur when improvements in energy efficiency actually stimulate the direct and indirect demand for energy in production and/or consumption. This phenomenon occurs through the impact of the increased efficiency on the effective, or implicit, price of energy. If demand is stimulated in this way, the anticipated reduction in energy use, and the consequent environmental benefits, will be partially or possibly even more than wholly (in the case of A¢â‚¬EœbackfireA¢â‚¬â„¢ effects) offset. A recent report published by the UK House of Lords identifies rebound effects as a plausible explanation as to why recent improvements in energy efficiency in the UK have not translated to reductions in energy demand at the macroeconomic level, but calls for empirical investigation of the factors that govern the extent of such effects.Undoubtedly the single most important conclusion of recent analysis in the UK, led by the UK Energy Research Centre (UKERC) is that the extent of rebound and backfire effects is always and everywhere an empirical issue. It is simply not possible to determine the degree of rebound and backfire from theoretical considerations alone, notwithstanding the claims of some contributors to the debate. In particular, theoretical analysis cannot rule out backfire. Nor, strictly, can theoretical considerations alone rule out the other limiting case, of zero rebound, that a narrow engineering approach would imply. In this paper we use a computable general equilibrium (CGE) framework to investigate the conditions under which rebound effects may occur in the Scottish regional and UK national economies. Previous work has suggested that rebound effects will occur even where key elasticities of substitution in production are set close to zero. Here, we carry out a systematic sensitivity analysis, where we gradually introduce relative price sensitivity into the system, focusing in particular on elasticities of substitution in production and trade parameters, in order to determine conditions under which rebound effects become a likely outcome. We find that, while there is positive pressure for rebound effects even where (direct and indirect) demand for energy is very price inelastic, this may be partially or wholly offset by negative income and disinvestment effects, which also occur in response to falling energy prices.
Revista Brasileira de Paleontologia

This paper presents descriptions, and taxonomic and ecological data by the angiosperm pollen grains recovered from Quaternary sediments of the Gruta do Urso Cave, Tocantins State, Northern Brazil. Among recovered assemblage, 44 types of angiosperm pollen were identified. Most of the pollen types described here are related to the modern aboreal-shrub and herbaceous-subshrub taxa currently present in the plant communities of the Cerrado biome: (i) forest formations (Annonaceae, Aspidosperma, Ilex, Celtis, Trema, Tournefortia, Protium, Combretaceae-Melastomataceae type, Croton-type, Moraceae-Urticaceae type, cf. Bauhinia brevipes, Cassia, Pithecellobium, Peixotoa, and Cedrela); (ii) savannah formations (Anacardium, Astronium, Asteraceae Tribu Eupatorieae, Caryocar, Cyperaceae, Eriotheca-type, Ludwigia, Pseudobombax spp., Ouratea, Qualea, and Utricularia), and (iii) grasslands (Poaceae). Regarding the diversity of pollen types registered, the most representative botanical families were: Fabaceae (8), Malvaceae (4), Euphorbiaceae (3), Anacardiaceae (3), Apocynaceae (2), Cannabaceae (2), Sapindaceae (2) and Poaceae (2), which also occur in the Cerrado-Caatinga transition. Pollen data show paleovegetation during the Last Glacial Maximum and Holocene times out of the cave, and provides a reliable source for paleoecological, paleoenvironmental and paleoclimatic investigations.
Revista Brasileira de Paleontologia

The goals of this study were to establish patterns in a silicified wood assemblage to depict the evolution patterns of the Triassic paleoclimate in southern Brazilian Gondwana during an interval of global arid to semi-arid climatic context, and the taphonomic process that led to the preservation of the so-called “Petrified Forest”, which is preserved in the central area of the state of Rio Grande do Sul. Analyses were developed with an assemblage of 13 permineralized conifer wood, using standard thin sections, whose anatomical details were studied in transmitted light. Ground-Penetrating Radar was used to obtain information about the depositional characteristics of the site. Main results are: true growth rings are absent in all samples, and the boundaries of the interruption zones are marked by an abrupt decline in cell diameter, but they are not accompanied by a reduction of cell wall thickness. The subsequent reversion to normal tracheid diameter is also abrupt, revealing the return of the previous growing conditions. Ground-penetrating Radar analyses confirmed that the Mata Sequence deposits correspond to a river. The identification of growth interruption zones in a Late Triassic wood assemblage in southernmost Brazilian Gondwana (Paleobotanic Garden of the city of Mata, RS) indicates the presence of tropical, temporarily dry climate conditions, characterized by irregular, short-term environmental disturbances to growth. The taphonomic process was related to a river-channel infilling depositional process, under the influence of high-energy flood events that dragged and buried the trees.
Unsupervised Authorship Analysis of Phishing Webpages

—Authorship analysis on phishing websites enables the investigation of phishing attacks, beyond basic analysis. In authorship analysis, salient features from documents are used to determine properties about the author, such as which of a set of candidate authors wrote a given document. In unsupervised authorship analysis, the aim is to group documents such that all documents by one author are grouped together. Applying this to cyber-attacks shows the size and scope of attacks from speciﬁc groups. This in turn allows investigators to focus their attention on speciﬁc attacking groups rather than trying to proﬁle multiple independent attackers. In this paper, we analyse phishing websites using the current state of the art unsupervised authorship analysis method, called NUANCE. The results indicate that the application produces clusters which correlate strongly to authorship, evaluated using expert knowledge and external information as well as showing an improvement over a previous approach with known ﬂaws.
Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.
PAPIERS DE RECHERCHE WORKING PAPERS

Abstract This paper, constructed as pedagogical notes, serves two complementary targets. On the one hand, it belongs to the initial part of a global applied research that should bring new arguments to the recurrent results obtained by previous studies, i.e. the observation that almost invariably, American corporations, multinationals and large companies have been found to have more sophisticated and advanced approaches to project evaluation than non-US, small-sized and country -focused (as opposed to international) ones. 1 On the other hand, the authors are concerned about the current disparity of academic opinion on the evolution of decision tools for project evaluation. Some scholars believe in an increasing sophistication a nd others dont. Therefore, such a paper should be considered as an invitation to keep up with the latest academic theory and tools used by organisations to evaluate projects. Material that is taught to our readers today will surely be complemented through the decades to come, just as it was in the past. An original chronological approach has been chosen in order to
Trident Fuzzy Aggregation Operators on Right and Left Apex-Base Angles in Parallel Computing

In this paper, a new concept called Trident Fuzzy Aggregation Operators in which the operation is made by the grouping of numerous Trapezoidal Trident Fuzzy Numbers (TTriFN) to become a solitary trapezoidal trident fuzzy numeral for parallel computing application is introduced. This proposed operator in computing architecture is applicable in the development of fuzzy networking and ranking concepts. Also, the geometric mean over ‘n’ TTriFN on the left-side apex-base angles and right-side apex-base angles are introduced in the architecture development process.
Eiffel: The Language

Introduction Basic Conventions Classes, Universes, and Systems: The Architecture of Eiffel Software Storing Class Texts Classes Features Inheritance Clients and Exports Types Conformance Routines and Instructions Assertions, Specifications, and Correctness Control Structures Exceptions Attributes Objects, Values, Expressions, and Entities Object Creation Re-attachment Feature Call Expressions and Constants Universal Features Persistance and Environments Arrays and Strings Input and Output Interfacing with Other Languages Appendix A. An Introduction to Eiffel Appendix B. Style Guidelines Appendix C. Reserved Words and Special Symbols Appendix D. Syntax Summary Appendix E. Syntax in Alphabetical Order Index
Integrating Portal Based Support Tools to Foster Learning Communities in University Courses

This paper identifies four criteria for systems that aim at supporting learning communities in university courses, and describes the web-based environment iPAL (internet Portal to Augment Learning) that addresses these criteria in an integrated manner. The iPAL environment extends a freely available content management system through some self-developed components. Practical experiences with the system are outlined, and a first evaluation is given.
Innovative models for analysis of survival data

In this paper, innovative models for analysis of survival data, indexed by two shape parameters, which encompasses a wide range of situations are discussed. These models are called hypertabastic survival models. The models are shown to provide different shaped hazard rates. One of the unique strengths of the hypertabastic models is the flexibility of the hazard function that permits the data to determine the nature of the hazard function without its being inadvertently imposed through the selection of improper models. The consideration of the different hazard shapes explains the different mechanisms of the outcome behavior. This helps researchers understand the outcome status over time.
Global Research Unit Working Paper #2016-008 Reserve Requirements and the Bank Lending Channel in China

This paper examines how reserve requirements influence the transmission of monetary policy through the bank lending channel in China while also taking into account the role of bank ownership. The implementation of Chinese monetary policy is characterized by the reliance on the reserve requirements as a regular policy tool with frequent adjustments. Using a large dataset of 170 Chinese banks for the period 2004–2013, we analyze the reaction of loan supply to changes in reserve requirements. We find no evidence of the bank lending channel through the use of reserve requirements. We observe, nonetheless, that changes in reserve requirements influence loan growth of banks. The same findings hold true for other monetary policy instruments. Further, we show that the bank ownership format influences transmission of monetary policy.
Massively-Parallel Proximity Queries for Point Clouds

We present a novel massively-parallel algorithm that allows real-time distance computations between arbitrary 3D objects and unstructured point cloud data. Our main application scenario is collision avoidance for robots in highly dynamic environments that are recorded via a Kinect, but our algorithm can be easily generalized for other applications such as virtual reality. Basically, we represent the 3D object by a bounding volume hierarchy, therefore we adopted the Inner Sphere Trees data structure, and we process all points of the point cloud in parallel using GPU optimized traversal algorithms. Additionally, all parallel threads share a common upper bound in the minimum distance, this leads to a very high culling efficiency. We implemented our algorithm using CUDA and the results show a real-time performance for online captured point clouds. Our algorithm outperforms previous CPU-based approaches by more than an order of magnitude.
Lean Thinking: An Overview

The lean manufacturing is a popular means of continuous improvement that has reshaped manufacturing processes, practices, and principles globally. Originating from the automobile industry, the approach has been used extensively in the manufacturing sector since the 1990s. Basically, lean manufacturing centered around the philosophy of continuously improving performances by systematically eliminating wastes in the manufacturing floor. Lean thinking was introduced to extend the concept from the manufacturing floor to a business operation level. This paper is intended to provide an overview on the concept of lean thinking, discuss in details the five key principles constituting the concept.
Factors Affecting Blood Pressure Control among Hypertensive Patients Attending Primary Healthcare Facilities in Western Jamaica View Edit

Objective: To identify patient-related factors that act as barriers to hypertension control. Methods: A cross-sectional study of 365 patients who were diagnosed with primary hypertension and attended primary healthcare facilities in western Jamaica was carried out. A pretested questionnaire was administered, and the patients’ blood pressure and body mass index were taken and calculated. Inferential statistics were used to interpret the data. Chi-square and Fischer’s exact tests were used to analyse the differences in dichotomous variables. A p-value of ≤ 0.05 was regarded as statistically significant. Two focus group discussions and 10 in-depth interviews provided qualitative data. Results: Of the 365 participants, only 30.1% had blood pressure readings within normal limits. The blood pressure was statistically significantly higher in those who last smoked under one year (p = 0.018), those who consumed alcohol (p = 0.021), those who reported high stress levels (p = 0.020) and those with a weak support system (p = 0.012; Spearman’s rank correlation coefficient = 0.131). Knowledge deficit was also statistically significant where 55.1% believed that hypertension could be cured or were unsure and 27.5% denied personal responsibility in achieving control. Patients who had been diagnosed 11 years or more were more likely to be uncontrolled (p = 0.010). Medication adherence (p = 0.056), alternative medicine (p = 0.476), diet (p = 0.108), exercise (p = 0.568) and obesity (p = 0.941) showed no statistically significant relationship. Conclusion: Smoking, alcohol consumption, stress, level of awareness and support system were significant modifiable determinants of blood pressure control. Clinicians often place much emphasis on medication adherence, diet and exercise. However, these modifiable contributing factors are often overlooked in the management of hypertension. Addressing these issues could result in a significant improvement in blood pressure control.
NATIONAL HIGH MAGENTIC FIELD LABORATORY FEL INJECTOR DESIGN CONSIDERATION

A Numerical study of beam dynamics was performed for two injector systems for the proposed National High Magnetic Field Laboratory at the Florida State University (FSU) Free Electron Laser (FEL) facility. The first considered a system consisting of a thermionic DC gun, two buncher cavities operated at 260 MHz and 1.3 GHz and two TESLA type cavities, and is very similar to the injector of the ELBE Radiation Source. The second system we studied uses a DC photogun (a copy of JLab FEL electron gun), one buncher cavity operated at 1.3 GHz and two TESLA type cavities. The study is based on PARMELA simulations and takes into account operational experience of both the JLab FEL and the Radiation Source ELBE. The simulations predict the second system will have a much smaller longitudinal emittance. For this reason the DC photo gun based injector is preferred for the proposed FSU FEL facility.
Class of framing the war on drugs in the media of northern Mexico: the cases of Bar Sabino Gordo and Casino Royale

The purpose of this article is to describe how and to what extent the attacks on Bar Sabino Gordo and Casino Royale were framed by the northern Mexican media: El Norte and Milenio Diario. Framing theory is used to contextualize and discuss how these events were represented. Discourse and content analysis of 224 news items produced immediately after the attacks and subsequently carried out. The results suggest the idea of class distinction as a backdrop to the drug war phenomenon in Mexico. While the event at Casino Royale was intensely discussed by the news and the amount of images was greatly increased, news about Bar Sabino Gordo was mainly published on the front pages of the newspapers in question. The victims at the Casino Royale were hardly mentioned, attention was focused on the appropriation of the site, while the people killed and wounded at Bar Sabino Gordo were framed as victims of their own decisions to be there.
Implementation of Scale-Dependent Background-Error Covariance Localization in the Canadian Global Deterministic Prediction System

: The approach of applying different amounts of horizontal localization to different ranges of background-error covariance horizontal scales as proposed by Buehner and Shlyaeva was recently implemented in the four-dimensional ensemble – variational (4DEnVar) data assimilation scheme of the global deterministic prediction system (GDPS) at Environment and Climate Change Canada operations. To maximize the bene ﬁ ts from this approach to reduce the sampling noise in the ensemble-derived background-error covariances, it was necessary to adopt a new weighting between the clima-tological and ﬂ ow-dependent covariances that increases signi ﬁ cantly the role of the latter. Thus, in December 2021 the GDPS became the ﬁ rst operational global deterministic medium-range weather forecasting system to rely completely on ﬂ ow-dependent covariances in the troposphere and the lower stratosphere. The experiments that led to the adoption of these two related changes and their impacts on the forecasts up to 7 days for various regions of the globe during the boreal summer of 2019 and winter of 2020 are presented here. It is also illustrated that relying more on ensemble-derived cova-riances ampli ﬁ es the positive impacts on the GDPS when the background ensemble generation strategy is improved.
the allocation of output between

: For a typical developing country, this paper shows that once inter-sectoral linkages are taken into account, closing the productivity gap in a number of services gives bigger gains in aggregate productivity than closing it in agriculture or in manufacturing. This is performed in the context of an input-output economy and general equilibrium. Also, the importance of sector-specific distortions that produce cross-sector misallocation is addressed. I compute the effect of the removal of these distortions on aggregate productivity using the input-output model and find that this could increase productivity up to 68%, depending on whether the rents from distortions stay in the economy or not.
Numerical Modelling of Turbulent Coastal Processes

A numerical model HYDROTAM-3, is developed that simulates turbulent coastal transport processes due to tidal or nontidal forcing. Model includes four sub model components; hydrodynamic, turbulence, salinity and temperature transport, suspended sediment transport. The only simplifying assumption used in the model is Boussinesq approximation, i.e. the density differences are neglected unless the differences are multiplied by the gravity. It is a composite finite difference finite element model. Model has been applied to Fethiye Bay located at the Mediterrenean Sea. At three Stations in the Bay, continuous measurements of velocity throughout the water depth and water level, were taken for 27 days. Model well simulates the measurements.