Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the Economics of Ethanol

The ethanol industry has experienced booms and busts throughout its nearly 200year history. Currently the industry is booming with production due to market sentiment and enacted policies. However, sentiment has begun to shift against corn ethanol due to increasing food costs and increased government expenditures propping up the industry. Despite the record increase in gasoline prices ethanol has struggled with its own rising costs of production and market turmoil. This masters project assesses the economics of corn-based ethanol production in the United States through the development of three models. The Ethanol Supply Curve Model constructs an ethanol supply curve based on user defined commodity prices. The model compares the marginal cost of ethanol production to the wholesale price of gasoline in order to determine the ability of ethanol to compete with gasoline and whether a fuel subsidy or renewable fuel standard is required to promote ethanol production. The Ethanol Profit Model solves for a facility’s profit margin under user defined commodity conditions. The Ethanol Variable Subsidy Model calculates the price-contingent subsidy required for ethanol to compete with gasoline on a price basis. A reference case is developed using commodity prices from U.S. government forecasts for 2008. Due to the volatile state of commodity markets, several sensitivity analyses are completed to provide insight about the potential health of the ethanol industry under different conditions. The results from the reference case indicate the ethanol industry is facing a treacherous production environment. The reference case scenario finds profit margins of $-0.1116/gallon for dry-mill ethanol producers, and $0.0498/gallon for wet-mill producers. Ethanol producers require a 33% increase in the ethanol subsidy from $0.51/gallon to $0.6796/gallon in order to break-even with gasoline prices. The Ethanol Supply Curve Model also shows that the market currently values ethanol on a gasolineenergy equivalent basis rather than a volumetric basis. Several ethanol producers recently disclosed financial troubles, included the recent bankruptcy filing by VeraSun, one of the largest ethanol producers in the U.S. If production conditions persist, more ethanol producers are at risk for bankruptcy. The risk of bankruptcy is exacerbated given the current state of the credit markets and investor aversion to low-margin industries. Further government support may be necessary to maintain production levels or to meet federal production requirements. A key issue in 2009 will be the reduction of the blender’s tax credit from $0.51/gal to $0.45/gal. Production growth is likely to be constrained, and the U.S. may have to relax production standards or consider other options to buoy the industry such as promoting ethanol pipeline infrastructure.
Beat and meter extraction using gaussified onsets

Rhythm, beat and meter are key concepts of music in general. Many efforts had been made in the last years to automatically extract beat and meter from a piece of music given either in audio or symbolical representation (see e.g. [11] for an overview). In this paper we propose a new method for extracting beat, meter and phase information from a list of unquantized onset times. The procedure relies on a novel method called ’Gaussification’ and adopts correlation techniques combined with findings from music psychology for parameter settings.
Measurement of lower extremity kinematics during level walking

A simple external marker system and algorithms for computing lower extremity joint angle motion during level walking were developed and implemented on a computer‐aided video motion analysis system (VICON). The concept of embedded axes and Euler rotation angles was used to define the three‐dimensional joint angle motion based on a set of body surface markers. Gait analysis was peformed on 40 normal young adults three times on three different test days at least 1 Week apart using the marker system. Angular motion of the hip, knee, and ankle joints and of the pelvis were obtained throughout a gait cycle utilizing the three‐dimensional trajectories of markers. The effect of uncertainties in defining the embedded axis on joint angles was demonstrated using sensitivity analysis. The errors in the estimation of joint angle motion were quantified with respect to the degree of error in the construction of embedded axes. The limitations of the model and the marker system in evaluating pathologic gait are discussed. The relatively small number of body surface markers used in the system render it easy to implement for use in routine clinical gait evaluations. Additionally, data presented in this paper should be a useful reference for describing and comparing pathologic gait patterns.
Robust Control Of Air-Flow In Air-Heating Set

The paper deals with the robust control of air-flow in air-heating set. The identification is perrfomred using step responses and approximation via second order system. The controller is designed using the structured singular value (SSV or μ) and algebraic approach. Since the cost function is nonconvex the optimization cannot be done using standard tools. Hence an evolutionary algorithm Differential Migration (DM) is employed yielding good results in this case. The functionality of the comtroller is verified though experiments on the real plant.
An Architecture Description Language for Massively Parallel Processor Architectures

In this paper, we introduce an architecture description language for modeling, simulation, and evaluation of massively parallel processor architectures that are designed for special purpose applications from the domain of embedded systems. The architectural description of the processor system is supposed to be done according to two abstraction levels. Architectural parameters of processor elements are characterized on processor level and the interaction between processors (i.e., interconnect topology, positioning of the processors, etc.) is described on the array level. Key features, semantic, and technical innovations of the proposed architecture description language are demonstrated in this paper.
Local Elections and Representation in the United States

In recent years, there has been a surge in the study of representation and elections in local politics. Scholars have made progress on many of the empirical barriers that stymied earlier researchers. As a result, the study of representation and elections in local politics has moved squarely into the center of American politics. The findings of recent research show that local politics in the modern, polarized era is much more similar to other areas of American politics than previously believed. Scholars have shown that partisanship and ideology play important roles in local politics. Due to the growing ideological divergence between Democrats and Republicans, Democratic elected officials increasingly take more liberal positions, and enact more liberal policies, than Republican ones. As a result, despite the multitude of constraints on local governments, local policies in the modern era tend to largely reflect the partisan and ideological composition of their electorates.
Simulation Control in General Game Playing Agents

The aim of General Game Playing (GGP) is to create intelligent agents that can automatically learn how to play many different games at an expert level without any human intervention. One of the main challenges such agents face is to automatically learn knowledge-based heuristics in realtime, whether for evaluating game positions or for search guidance. In recent years, GGP agents that use Monte-Carlo simulations to reason about their actions have become increasingly more popular. For competitive play such an approach requires an effective search-control mechanism for guiding the simulation playouts. In here we introduce several schemes for automatically learning search guidance, as well as comparing them empirically. We show that by combining schemes one can improve upon the current state-of-the-art of simulation-based search-control in GGP.
Multiple sclerosis : Correlation of neuropsychological tests with EEG coherence analysis and MRI findings

The purpose of the current study was to evaluate the type and severity of cognitive affection in MS patients and its correlations with clinical, MRI findings, and EEG interhemispheric coherence analysis. We selected 24 patients with clinically definite MS patients with relapsingremitting course and 20 age and sex matched subjects as a control group. The patients were examined with eight neuropsycological tests, MRI and EEG coherence analysis. The degree of disability was rated using EDSS scale. Cognitive impairment was detected in 11 (45.8%) patients and was compatible with the subcortical dementia where the most affected cognitive domain was memory either visual or visuospatial as well as sustained attention. However, conceptual reasoning and information processing were also affected, whereas lingustic test was the least to be affected. Digit span, Benton visual retention, Story recall, Circle connection and Digit symbol were the most sensitive tests that could be used to evaluate cognitive impairment in our patients. EDSS score was correlated positively with GCI and SC lesion in MRI whereas no correlation was demonstrated between EDSS and EEG coherence. Compared to control, patients with MS has statistically significant reduction of interhemispheric coherence of both  and  bands especially over central and frontotemporal regions. Furthermore, there were significant correlations between  and -band coherence and neuropsychological tests except for Digit symbol, CCT and Benton VRT tests (tests need motor ability). EEG interhemispheric coherence analysis has the advantage of its independency on physical disabilities than the neuropsychological tests. A significant correlations were detected between  and  band coherence and both total and SC lesions in MRI. Neither GCI nor coherence correlated with duration of disease whereas a significant correlation was detected between GCI and both SC lesion in MRI and  and  band coherence. These findings support the hypothesis that cognitive impairment in MS is mostly dependent on involvement of cortico-cortical connection related to demyelination and axonal loss within white matter areas. (Egypt J. Neurol. Psychiat. Neurosurg., 2004, 41(1): 79-94).
Knowledge of Indonesian University Students on the Sustainable Management of Natural Resources

Graduates of university programs addressing sustainable resource management are likely to shape strategies for natural resource use in the future. Their academic training needs to foster student knowledge of the multiple dimensions of natural resource management. This paper investigates university student understanding of such challenges. We differentiated situational, conceptual, and procedural types of knowledge, and three domains of knowledge (ecological, socio-economic and institutional knowledge), and sampled beginners (third semester) and seniors (seventh semester) of seven natural resource related programs at the leading Indonesian institution of higher education in the field of natural resource management (IPB Bogor; n = 882). The questionnaire consisted of multiple choice and rating scale items covering ‘locally’ relevant open-access resource use issues. With a confirmatory tau-equivalent LISREL model, construct validity was assessed. The ability to extract relevant information from problem descriptions provided (situational knowledge) did not differ between third and seventh semester students. While it was high for ecological and socio-economic items, it was markedly lower for institutional knowledge. Knowledge of relevant scientific concepts (conceptual knowledge) increased in the ecological and socio-economic domains but the effect was small. Conceptual knowledge in the socio-economical and institutional domains tended to be lower than ecological knowledge. Although there was certain improvement, student judgments on the efficacy of resource management options (procedural knowledge) differed strongly from expert judgments for beginners as well as for senior students. We conclude that many of the university students in the sampled programs displayed substantial gaps in their capacity to solve complex, real-world natural resource management problems. Specifically, the socio-economic and institutional knowledge domains—and their integration with ecological knowledge—may require attention by educational planners.
Head Behavior Detection Method Based on Optical Flow Theory

In order to make the intelligent virtual classroom distinguish out the rotation direction of the user's head, a method for head behavior detection based on optical flow is proposed in this paper. Firstly, we select the key feature points of user's facial area. Then we calculate the user's head movement parameter through the data of feature points which have been recorded. Secondly, a kind of head direction sensing model has been provided for detecting the head identified parameters. Finally, according to the interaction mechanism of the interaction scenario, intelligent virtual classroom will respond to the user's head movement based on the result of the head direction judgment. By online tests, the results show that the method is of high recognition rate and quick real-time.
Optimal HDA codes for sending a Gaussian source over a Gaussian channel with bandwidth compression in the presence of an interference

In this paper, we consider transmission of a Gaussian source over a Gaussian channel under bandwidth compression in the presence of interference known only to the transmitter. We study hybrid digital-analog (HDA) joint source-channel coding schemes and propose two novel coding schemes that achieve the optimal mean-squared error (MSE) distortion. This can be viewed as the extension of results by Wilson et al. [1], originally proposed for sending a Gaussian source over a Gaussian channel in two cases: 1) Matched bandwidth with known interference only at the transmitter, 2) bandwidth compression where there is no interference in the channel. The proposed HDA codes can cancel the interference of the channel and obtain the “optimum performance theoretically attainable” (OPTA) of the AWGN channel with no interference in the case of bandwidth compression. We also provide performance analysis in the presence of signal-to-noise ratio (SNR) mismatch where we expect that HDA schemes perform better than strictly digital schemes.
HORIZON OCCLUSION CULLING FOR REAL-TIME RENDERING OF HIERARCHICAL TERRAINS USING PROGRAMMABLE GRAPHICS HARDWARE

Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and ground-based aircraft testing using synthetic sensor stimulation. The main problem is to maintain dynamic, viewdependent triangle meshes and texture maps that produce good images at the required frame rate. This report describes a technique to improve the horizon occlusion-culling algorithm for hierarchical terrains using programmable graphics hardware techniques so that the hierarchical terrains could be rendered in real-time efficiently. The occlusion horizon is a well-known algorithm. The main issue of this work is the adaptation of this algorithm to hierarchical terrains. The algorithm will be implemented with the usage of programmable graphics hardware to accelerate the rendering time. The chosen occlusion algorithm is simple to implement and requires minimal pre-processing and additional storage. The occlusion horizon is constructed as the terrain is traversed in an approximate front to back ordering. Regions of the terrain are compared to the horizon to determine when they are completely occluded from the viewpoint. Quad trees are selected to construct the hierarchical structure for the terrains. By this work, the improvement of rendering time using hardware programming techniques for occlusion culling on hierarchical terrains will be observed.
Exploratory Text Analysis using Lexical Episode Plots

In this paper, we present Lexical Episode Plots, a novel automated text-mining and visual analytics approach for exploratory text analysis. In particular, we first describe an algorithm for automatically annotating text regions to examine prominent themes within natural language texts. The algorithm is based on lexical chaining to find spans of text in which the frequency of a term is significantly higher than its average in the document. In a second step we present an interactive visualization supporting the exploration and interpretation of Lexical Episodes. The visualization links higher-level thematic structures with content-level details. The methodological capabilities of our approach are illustrated by analyzing the televised US presidential election debates.
Lessons learned from a multidisciplinary heart failure clinic for older women: a randomised controlled trial.

BACKGROUND many heart failure disease management programs are primarily conducted in the male population. An approach incorporating disciplines such as physiotherapy, occupational therapy, social work, dietary and pharmacy in a standardized clinical pathway merits further investigation in older women with HF. METHODS in this randomized controlled trial, female patients in the intervention group received the multidisciplinary clinical pathway consisting of a series of 12 visits over a 6-week period in an outpatient clinic. RESULTS ninety-one community dwelling female patients aged 63 to 89 were randomized. Comparison of change between the two groups from baseline in the Minnesota Living with Heart Failure Questionnaire score did not show a difference (P<0.470). There was also no difference between the two groups in functional outcome as measured by change from baseline by the Physical Self-Maintenance Scale (P<0.321). The treatment group had significantly more hospitalizations, and cardiologist visits during the study period (P < 0.0001). CONCLUSION It is feasible to conduct a randomized study in a frail community-based older female population and to test a complex multidisciplinary pathway. Future studies should provide insight into the optimal intensity and duration of heart failure management programs with optimal targeting.
Sketch2Cartoon: composing cartoon images by sketching

In this paper, we introduce the Sketch2Cartoon system, which is an automatic cartoon making system by leveraging a novel sketch-based clipart image search engine. Different from existing work, most of which either limited users to the pre-prepared characters or only used keyword queries to search materials, Sketch2Cartoon enables users to sketch major curves of characters and props in their mind, and real-time search results from millions of clipart images could be selected to compose the cartoon images. The selected components are vectorized and thus could be further edited. By enabling sketch-based input, the cartoon image making process becomes more natural, and even a child who is too young to read or write can draw whatever he/she imagines and get interesting cartoon images.
Prototyping Praxis: Constructing Computer Systems and Building Belief

This article explores the consequences of the uncertainty introduced into the system-development life cycle by a prototyping approach and the practical strategies employed by developers in prototyping projects. Drawing on various strands of the sociology of technology, the article discusses findings from a multidisciplinary research project, which investigated the use of prototyping in commercial information systems development in the United Kingdom during the period 1995 to 1998. Qualitative semistructured interviews with commercial practitioners were followed by a series of mini case studies. We draw on interview and participant observation material and the practitioner literature on Rapid Application Development. In the course of the project, we encountered a variety of practical strategies that attempted to extend the sphere of developers' influence beyond the technical realm to affect (but not determine) how the user and customer participate in the development process. Various techniques attempt to create a climate of joint ownership and shared approaches to change management. For example, the role of an ambassador user encompasses shaping the environment in which the system will operate via information, training, and advocacy. Rather than a cause-and-effect model from user requirements to specification to implementation, developer strategies usefully can be considered in terms of sociological work on reflexive elaboration of networks. From this perspective, prototyping is more akin to trying to stabilize a network of evolving prototypes, user expectations, requirements, and working practices than meeting a fixed specification.
Computational Fluid Dynamics based Flow Diagnostics in Hydraulic Capsule Pipeline Bends

Hydraulic Capsule Pipelines (HCPs) are the third generation of pipelines that are based on the transport of hollow spherical, or cylindrical, capsules by the force exerted on them from the carrier fluid, which is water. These hollow capsules can be filled with a variety of cargo goods, such as minerals, jewellery etc. The hydrodynamics of this transport phenomena is quite complex, and researchers around the globe have been trying to analyse the hydrodynamics of such systems. However, most of these studies are based on experimental investigations, which can provide reasonably accurate results for the pressure drop etc. across the pipeline. However, the flow structure within HCPs cannot be easily mapped using experimental facilities. Furthermore, in case of pipe bends, the difficulty level increases exponentially due to a constant curvature in the geometry of the pipeline, and hence mounting the flow measuring instruments can be very challenging. The present study makes use of the advanced Computational Fluid Dynamics (CFD) based solvers, with powerful computing services, in order to analyse the flow structure within HCP bends. It is expected that this information can provide valuable information to the HCP designers, not only to calculate pressure drop across HCP bends, but in order to select the correct size etc. bends for the pipeline.
Finding Landmarks in the Functional Brain using Feature Reduction and Alignment Techniques

Identifying brain regions of interest from functional magnetic resonance imaging (fMRI) studies involves the comparison of individual activations and inference of a group activation model. Due to the shortcomings of the standard voxel-based analysis, which models the data as a smooth random field embedded in an anatomical reference space, the most interesting effects, i.e. correlates of higher-order cognitive brain functions, may be obscured. A more promising approach to the analysis of individual variations and commonalities in the functional organisation of the human brain is to directly compare the individual activation patterns observed with fMRI. In our work, an elastic graph matching is used to identify those activations that are in close relation to local anatomical landmarks in the individual brains and form a pattern that is replicable across subjects. An optimal, generative model of the spatial distribution of the activation foci of interest can then be computed by employing factor analysis and model selection techniques. We show the advantages of our approach to finding functional landmarks on synthetic data and data from an auditory fMRI experiment.
Effective finiteness theorems for maps between canonically polarizedcompact complex manifolds

Effective bounds for the finite number of surjective holomorphic maps between canonically polarized compact complex manifolds of any dimension with fixed domain are proven. Both the case of a fixed target and the case of varying targets are treated. In the case of varying targets, bounds on the complexity of Chow varieties are used. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)