Miracle-dz/UniFAR-FTUs huggingface dataset:
Eddy Formation and Shedding in a Separating Boundary Current

Abstract This study deals with the separation of western boundary currents within a reduced-gravity framework, and it analyzes the formation of eddies in the separation region and the conditions of their shedding into the open ocean. It shows that the separation point of the current oscillates along the coast so that the retroflected eastward current develops meanders. These meanders grow, drift westward under the influence of β, and finally hit the coastal current, which leads to the periodic formation of eddies. This study also highlights the impact by the geometrical configurations of the flow and coastline upon the existence or lack of a subsequent shedding of these eddies: a shedding occurs when no obstacle hinders the β-induced westward drift of the eddies. This happens when either (i) the current retroflects far enough beyond the tip of the coast so that, because of β, the eddies can propagate westward without being blocked, or (ii) the tilt of the coast is small enough so that the alongshore compo.
RELATIONSHIP BETWEEN COLLEGIATE TRACK RUNNERS' ACHIEVEMENT GOAL ORIENTATIONS AND PERCEPTIONS OF MOTIVATIONAL CLIMATE

of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Exercise and Sport Sciences RELATIONSHIP BETWEEN COLLEGIATE TRACK RUNNERS’ ACHIEVEMENT GOAL ORIENTATIONS AND PERCEPTIONS OF MOTIVATIONAL CLIMATE By Sean P. McManus December 2004 Chair: John R. Todorovich Major Department: Health Education and Behavior The purpose of this study was to investigate the achievement goal orientations and perceptions of motivational climate exhibited by intercollegiate athletes competing in track’s two running disciplines—sprinting and distance running—and then to examine the relationship between the athletes’ goal orientations and perceptions of motivational climate. Previous research in motivation in sport failed to make the distinction between these two different event groups within the sport of track. This failure to recognize track as being composed of two distinctly different event groups may have confounded the results of studies utilizing track athletes in examinations of motivation in sport across age, gender, time of season, and other variables. Data collection relied upon two questionnaires, the Task and Ego in Sport Questionnaire (TEOSQ) and the Perceived Motivational Climate in Sport Questionnaire (PMCSQ). From these, sprinters and distance runners were assigned group means for task
35. XRF ANALYSES OF VOLCANIC ROCKS FROM LEG 152 BY LABORATORIES IN EDINBURGH AND COPENHAGEN: IMPLICATIONS FOR THE MOBILITY OF YTTRIUM AND OTHER ELEMENTS DURING ALTERATION 1

Neighboring (parallel) samples from 72 lava flows, splits of identical samples from five lava flows, and splits of 10 shipboard powders from Ocean Drilling Program Leg 152 were analyzed by X-ray fluorescence (XRF) in both Edinburgh and Copenhagen. The agreement between the two data sets is very good, although systematic differences are apparent in some cases. Correlation between the results for the identical powders is very high. Correlation between the results for the parallel samples is somewhat lower, mainly because of element redistribution during secondary alteration, but also due to primary lava inhomogeneity. The elements show differences in the degree of scatter due to alteration, with K, Rb, and Ba being the most mobile, and Si, Sc, Al, Fe, Zn, V, and Nb the least mobile. Y is immobile in the Site 917 lavas but distinctly mobile in the Si te 918 lavas where it is both leached and precipitated locally. The mobility of Y is related to secondary breakdown of clinopyroxene at Site 918, in contrast to Site 917 where the clinopyroxene is generally fresh. The hydrothermal alteration conditions at the two sites appear to have been different.
Controlling Tiltrotors Unmanned Aerial Vehicles (UAVs) with Deep Reinforcement Learning

Unmanned Aerial Vehicles (UAVs) have gained significant attention in various domains due to their versatility and potential applications. Effective control of UAVs is crucial for achieving desired flight behaviors and optimizing their performance. This paper presents a comprehensive exploration of learning-based approaches for controlling UAVs with fixed-rotors and tiltrotors, specifically focusing on the Proximal Policy Optimization (PPO) and Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithms. The study aims to compare and evaluate the efficacy of these two state-of-the-art reinforcement learning algorithms in controlling UAVs with varying designs and control complexities. By utilizing PPO and TD3, we address the challenges associated with maneuvering UAVs in dynamic environments and achieving precise control under different flight conditions. We conducted extensive simulations to assess the performance of PPO and TD3 algorithms in diverse UAV scenarios, considering multiple design configurations and control requirements. The evaluation criteria encompassed stability, robustness, trajectory tracking accuracy, and control efficiency. Results demonstrate the suitability and effectiveness of both PPO and TD3 in controlling UAVs.
Greece's current account drivers and forecasts An empirical study Preface

The present study employs cointegration techniques and a vector correction model (VECM) to identify and analyze the main drivers of Greece’s current account in recent decades and, especially, in the years following the euro adoption. Our econometric results provide broad-based support to the key findings of a number of earlier empirical studies on the determinants of the current account. In more detail, the trend deterioration in the country’s external imbalance in 1999-2008 can be traced back to a number of developments related to: a) the EU convergence process and closer integration in world goods and financial markets; b) domestic authorities’ response to policy challenges arising from participation in the single currency area; and c) the structural characteristics and idiosyncrasies of the Greek economy. At the Eurozone level, the initial years following the adoption of the single currency saw most countries in the so-called euro area periphery running large current account deficits, with core member states in the richer north featuring significant external surpluses. Despite these large divergences across member states, the outbreak of the global financial crisis found the euro area running a broadlybalanced external position vis-à-vis the rest of the world. The scale and dispersion of current account imbalances across euro area countries in the initial years following the introduction of the single currency raise credible concerns as to whether such unprecedented imbalances were justified on the basis of underlying macro fundamentals. It also supports the notion that these imbalances were, to a certain extent, overlooked by euro area policy makers.
Flexible, scalable, and robust architecture for industrial automation applications with real-time requirements

With the outbreak of the fourth industrial revolution, industrial automation applications demand a more flexible, scalable, and robust architecture than the one proposed in the ISA-95 standard. In addition, the high availability demanded by industrial processes hinders maintenance and updating tasks that go against information security policies. To address these challenges, some frameworks supported by virtualization and information distribution technologies have been generated for industrial automation systems. However, these proposals lack the means to implement real-time task scheduling algorithms, so it is difficult to migrate developments already implemented under these requirements. In this work, we present a microservices-based architecture that integrates virtualization technologies, a robust middleware for the communication layer, and a priority-based task scheduler. It also describes the implementation of this architecture using low-cost hardware components and free software, to be subsequently tested on a pressure control process in a laboratory setting. The obtained results confirm the effectiveness of the proposed architecture and meeting of real-time requirements, which enables supporting the diverse current industrial automation applications requirements, addressing the challenges of migration to Industry 4.0, and incorporating new functionalities.
Early intervention for children with autism

267 Autism is a neurobehavioural disorder characterized by impairment of social relatedness, delayed and disordered communication, and restricted, perseverative and stereotypic behaviour patterns occurring in young children. It has a major impact on the lives of children and their families. The manifestations of this disorder vary between children and within an individual child over time. The current understanding of this disorder is of an autism spectrum with degrees of involvement from mild to severe. From a conservative analysis of existing data, the prevalence of autism spectrum disorder is reported at 27.5/10,000. This is comprised of a prevalence of 10/10,000 for autism, 15/10,000 for pervasive developmental disorder – not otherwise specified (PDD-NOS) and 2.5/10,000 for Asperger syndrome (1). These prevalence figures are higher than those reported 30 years ago. Current epidemiological data are insufficient to determine whether factors other than a broadening of the definition and better public awareness of autism disorders are responsible for this increase (1). The studies reviewed in this statement involve primarily children with autism, with four studies (2-5) involving children with autism and PDDNOS. Autism or autism spectrum disorder is a disorder of abnormal brain development, the basis of which is largely genetic (6). The evidence does not suggest a causal association with measles-mumps-rubella vaccination (7). Treatment for autism has become an important public policy issue, with parents advocating for funding of comprehensive treatment programs and challenging governments through the courts. Funding agencies and policy-makers should critically appraise the literature on early intensive teaching and behavioural programs for children with autism to make informed decisions about service provision.
MATHEMATICAL EXPRESSION OF ELUVIATION-ILLUVIATION PROCESSES AND THE COMPUTATION OF THE EFFECTS OF CLAY MIGRATION IN HOMOGENEOUS SOIL PARENT MATERIALS

Summary Clay movement and its effect on the differences in texture between the A and B horizons are expressed by mathematical equations. The factors which are considered are the actual amount of clay which has moved (l), the ratio of the thick nesses of the horizons (N), and the original clay content (C). Parent materials are assumed to be homogeneous. Knowing the clay contents of the A and B horizons, it is possible to calculate for given N ratios the theoretical amount of clay which has moved in order to achieve the observed textural difference. The theoretical clay content C'of the parent material can also be computed. All computations assume homogeneous parent materials and closed profiles, i.e. materials that do not collapse, shrink, or swell, and consider all other clay transformations non-operative. An eluviations index k, which indicates the proportion of the original clay that has been translocated, is proposed for evaluating the intensity of clay migration. Examples of practical applications are given: i.e. the required difference in clay content between A and B in the definition of the argillic horizon should not be kept constant in soils which have variable initial clay contents; graphs illustrate the effects of clay migration for constant C and k values (isoparentic and isoluvic lines). All computations can be made by desk calculators provided with an extended memory for storage of data and programmes.
Dropout, School Performance, and Working while in School

We develop an econometric model where the determinants of working while in school, academic performance, and the decision to drop out are set in the context of two types of high school students: those who prefer schooling and those who are more likely to join the labor market. The likelihood function of this model with heterogeneous preferences for schooling is composed of 48 individual contributions of a standard quadrivariate normal function. Exploiting a unique Canadian microdata set of high school students and school dropouts, we show that being a female student, attending a private school, and living with educated parents are linked to having a strong preference for schooling over the labor market. We also find that working fewer than fifteen hours per week while in school is not necessarily detrimental to success in school. Our results indicate that the decision to drop out is affected by the legal age to access the labor market, high minimum wages, and low unemployment rates. Several policies that aim at reducing the number of high school dropouts are identified.
Transient Energy Function and Oscillation Analysis of PMSG with Wind Speed Variation

In order to investigate the impacts of WS(wind shear) and TS(tower shadow) on the PMSG. Firstly, we derive the transient energy function of the PMSG considering the effect of wind speed; then, we analyze the power output characteristics of PMSG with different wind speeds under strong damping and weak damping respectively; finally, we build a single infinity system including wind speed model, pitch angle variation and maximum power tracking in PSCAD/EMTDC and simulate it. The results show that the low-frequency oscillation components generated by WS and TS effect cause unit oscillation when passing through the strongly damped PMSG; when passing through the negatively damped PMSG, they are coupled with the free oscillation generated by the unit, causing a significant increase in the unit output energy, and the unit output power contains both low-frequency oscillation and sub-synchronous oscillation.
Bubble‐mediated aerosol production as a consequence of wave breaking in supersaturated (hyperoxic) seawater

The influence of changes in the degree of saturation of the surface waters, with respect to the major atmospheric gases, on the aerosol productivity of an individual whitecap has now been inferred from results recently obtained using the University of Connecticut's Whitecap Simulation Tank IV. As the level of dissolved oxygen increased from 100% saturation to 130%, i.e., to a significant degree of supersaturation, the production of aerosol droplets by the whitecap generated by a standard laboratory breaking wave was found to increase by a factor of 2.4 in the case of submicron radius droplets, while the generation of larger droplets (r > 2.5 μm) was observed to increase by at least a factor of 4.0. As a consequence of these findings, a multiplier, defined in terms of the degree of gas saturation, has been introduced as a term in the various sea surface aerosol generation models.
An objective ocean temperature and salinity analysis using covariances from a global climate model

[1] Covariances are crucial for propagating information from data-rich to data-sparse regions, but owing to the sparsity of observations, previous analyses of subsurface ocean temperature and salinity have employed fairly crude parameterizations of covariances defined at resolutions much coarser than the required analysis. Here we investigate the use of covariances computed directly from a realistic coupled global climate model, HadCM3. We demonstrate that 50 to 80% of the monthly variance of both temperature and salinity at 300 m for the period 1950 to 2004 could potentially be captured by analyses based on perfect covariances. However, because of errors in the HadCM3 covariances, we estimate that our analysis captures on average 40% and 25% of the variance of temperature and salinity anomalies in the upper 300 m for this period, although we project both these percentages to increase to about 70% for future analyses benefiting from the full ARGO array. Assessed against tide gauge and altimeter data, our analysis is comparable to that of Ishii et al. (2003) (I03). However, the simple average of our analysis and I03 provides a clear improvement over I03. This improvement probably arises partly from additional observations and partly because errors in covariances will be reduced by taking the mean of an ensemble which samples their uncertainty. We recommend sampling all sources of uncertainty in future ensemble analyses, and anticipate that statistics from future more realistic climate models will become increasingly important to such an ensemble.
Multimetallic contamination from Zn-ore smelter: solid speciation and potential mobility in riverine floodbank soils of the upper Lot River (SW France)

The former Zn-ore smelting activity in Viviez (Aveyron, France) resulted in multimetallic contamination of the upper Lot River system (SW France). This study addresses for the first time the metals/metalloids mobility in impacted riverside fluvial soils due to reducing conditions during long-term flooding events. Six impacted riverside fluvio-soils were sampled along the Riou Mort and Lot rivers. Their levels of contamination decrease with the distance from the contamination source. Higher enrichment factors (EF) relative to French average soil metallic content occur 1 km far from the contamination source and vary from 3 for Sn, to 5 for As, 9 for Sb, 27 for Pb, 40 for Zn and 63 for Cd. At 20 km downstream from the contamination source, EF still reach a value of 3 for Cd and Zn. A micro-physical mineralogical characterisation of contaminated soils revealed a variety of metal-bearing phases: metallic compounds, oxides and sulphides, Fe oxides, glass and silicates as well as coke. Sequential chemical extraction experiments were conducted on the most contaminated soil in order to identify which mineral phases were the best candidates to release metals/metalloids. At the end of experiments more than 70 % of total Cd and As, 55 % of Zn and Sb, and 40 % of Pb and Sn were extracted from the soil. Only Cd appeared as readily mobilised, with 33 % of its total amount being extracted in the first steps of experiments. Under reducing conditions, iron oxyhydroxides, franklinite and multimetallic oxides are the best candidates, in decreasing order of importance, for metals/metalloids release from the soil.
Street Generation for City Modelling

In this paper, we present a complete solution for automatically retrieving the street graph of an urban model. Given a set of 2-5D polygons representing the buildings footprints and their heights, the algorithm constructs a graph that represent the street network (a node for a crossing, an edge a street, each associated with a set of surrounding buildings) along with geometric information such as the width of the streets. We demonstrate how this graph can be used to analyze the city structure and give an example of its use with an automatic geometric modeler for city streets.
Stratospheric effects of energetic particle precipitation in 2003–2004

Upper stratospheric enhancements in NOx (NO and NO2) were observed at high northern latitudes from March through at least July of 2004. Multi‐satellite data analysis is used to examine the temporal evolution of the enhancements, to place them in historical context, and to investigate their origin. The enhancements were a factor of 4 higher than nominal at some locations, and are unprecedented in the northern hemisphere since at least 1985. They were accompanied by reductions in O3 of more than 60% in some cases. The analysis suggests that energetic particle precipitation led to substantial NOx production in the upper atmosphere beginning with the remarkable solar storms in late October 2003 and possibly persisting through January. Downward transport of the excess NOx, facilitated by unique meteorological conditions in 2004 that led to an unusually strong upper stratospheric vortex from late January through March, caused the enhancements.
Semi-Supervised Bootstrapped Syntax-Semantics-Based Approach for Agriculture Relation Extraction for Knowledge Graph Creation and Reasoning

We propose a novel approach that uses semi-supervised learning to extract triplets from domain-specific texts and create a Knowledge Graph (KG), with a focus on the agricultural domain. Building domain specific knowledge graphs can be challenging due to several factors such as domain specific vocabulary, data integration challenges, dynamic data, and the need for domain expertise. Our approach primarily focuses on triplet extraction for the creation of knowledge graph. We employ dependency parsing techniques to extract relationships between entities, and utilize an extended version of BERT, combined with Latent Dirichlet Allocation (LDA) for Named Entity Recognition (NER). The proposed Agriculture knowledge graph covers significant areas of the agricultural domain by focusing on six major entities: soil, place, disease, pathogen, pesticide, and crops, along with their intra and inter-relationships. There is no benchmark dataset in the agriculture domain encompassing all the major entities. Hence we create our own corpus comprises 30k sentences sourced from reputable agriculture websites. To evaluate the effectiveness of our triplet extraction model, we utilized a test corpus containing 3500 agriculture triplets. Based on the experimental results, we were able to achieve an average macro F-score of 87% for relation extraction, indicating the efficacy of our approach. Additionally, we created an Agriculture knowledge graph using a triplet corpus of 6236 triplets. We also analyzed various knowledge graph reasoning models that improve the discovery of implicit knowledge that is not explicitly represented in the knowledge graph. Experimental results indicate that our approach is effective in creating triplets and reasoning knowledge graphs for the agricultural domain.
Habitat modeling for rustic bunting (Emberiza rustica) territories in boreal Sweden

The rustic bunting (Emberiza rustica) is a bird breeding in swampy boreal forests of Russia and Fennoscandia. In the last decades, populations in Norway, Sweden and Finland have declined drastically. The factors behind this decline are not fully understood and, among other things, there is a lack of quantitative habitat data from the breeding territories. In this study, 19 habitat variables are used to model presence of rustic bunting. Swampy forests in boreal Sweden were surveyed using playback and habitat variables were measured at both presence points and randomly generated points. The data were analyzed by generating all possible GLMs with one or two variables and ranking these models according to their AICc value. The individual variables were ranked using Akaike weights. The variables broadleaf trees 3-5m tall and water surface coverage stood out as the most important: they were both included in the top model and received top scores in the Akaike weights. This study is the first to analyze rustic bunting habitat in a quantitative manner and offers a starting point for making spatial predictions of rustic bunting habitat, which is important to further understand the situation at breeding grounds.