Miracle-dz/UniFAR-FTUs huggingface dataset:
Buying Representation: The Incentives, Ideology, and Influence of Campaign Contributors in American Politics

One of the foundational principles of a democratic government is that representatives do as their name implies – represent their constituencies. In defending the Constitution of the United States, Publius emphasized the need for representation in the legislature by saying, “First. As it is essential to liberty that the government in general should have a common interest with the people, so it is particularly essential that the branch of it under consideration should have an immediate dependence on, and an intimate sympathy with, the people” (Federalist 52). However, “the people” is a much more complicated term than one might initially think. Representatives must consider a variety of constituencies as they go about their work. These different groups clearly weigh in the mind of a representative with varying degrees of importance. I suggest that one group that exerts a great deal of influence over the political process is campaign contributors, and that their influence is due to the importance of fundraising in the electoral process. Yet, donors have received far less attention from legislative scholars than their potential influence warrants. In this dissertation, I investigate the strength of this financial connection and the degree to which political donations are influencing representatives in Congress and state legislatures. The second chapter investigates the motivations of donors and shows important differences in why people or organizations support candidates financially. Understanding why donors give money is vital for developing accurate hypotheses of how money may influences politics, yet we still know little about why donors choose to give. In this paper I present theories of why political action committees (PACs) and individuals, the two largest sources of campaign money, contribute to political candidates. PACs are primarily motivated by a desire to gain access to legislators and the legislating process while individuals are primarily motivated by ideological considerations. Additionally, a subset of PACs whose interests
Assessing Air Quality in Dhaka City

This study assessed the main factors that affect the city’s air pollution levels in Dhaka. Among the variables analyzed, specifically PM10, PM2.5, SOx, NOx, NO2, CO and O3, only PM10 and PM2.5 exceeded the Bangladesh air quality standards and World Health Organization air quality guidelines. Based on the air pollution level of Dhaka City, SO2, NO2, CO2, and O3 are not exited the air quality standards, and only PM10 and PM2.5 are polluted Level.
Københavns Universitet ( S ) Pinning down protein interactions by NMR

Protein molecules are highly diverse communication platforms and their interaction repertoire stretches from atoms over small molecules such as sugars and lipids to macromolecules. An important route to understanding molecular communication is to quantitatively describe their interactions. These types of analyses determine the amounts and proportions of individual constituents that participate in a reaction as well as their rates of reactions and their thermodynamics. Although many different methods are available, there is currently no single method able to quantitatively capture and describe all types of protein reactions, which can span orders of magnitudes in affinities, reaction rates, and lifetimes of states. As the more versatile technique, solution NMR spectroscopy offers a remarkable catalogue of methods that can be successfully applied to the quantitative as well as qualitative descriptions of protein interactions. In this review we provide an easy-access approach to NMR for the non-NMR specialist and describe how and when solution state NMR spectroscopy is the method of choice for addressing protein ligand interaction. We describe very briefly the theoretical background and illustrate simple protein–ligand interactions as well as typical strategies for measuring binding constants using NMR spectroscopy. Finally, this review provides examples of caveats of the method as well as the options to improve the outcome of an NMR analysis of a protein interaction reaction.
Nonparametric Estimation of Daily State-Price Densities Using Transaction-Level Data on S&P500 Index Options

A good estimate for the state-price density has important applications both in practice, to derivatives valuation, and in economic theory, to our understanding of risk preferences. I estimate the state-price density nonparametrically using transaction-level data on S&P500 call and put options from 1993. By using transaction-level data, I am able to obtain estimates for the state-price density for individual days and thereby avoid making the common assumption that the SPD is nonstochastic. The estimates are compared to the Black-Scholes lognormal state-price density and are seen to be negatively skewed, have higher kurtosis, and a higher center, particularly for high times to maturity.
A Structured Syntax-Semantics Interface for English-AMR Alignment

Abstract Meaning Representation (AMR) annotations are often assumed to closely mirror dependency syntax, but AMR explicitly does not require this, and the assumption has never been tested. To test it, we devise an expressive framework to align AMR graphs to dependency graphs, which we use to annotate 200 AMRs. Our annotation explains how 97% of AMR edges are evoked by words or syntax. Previously existing AMR alignment frameworks did not allow for mapping AMR onto syntax, and as a consequence they explained at most 23%. While we find that there are indeed many cases where AMR annotations closely mirror syntax, there are also pervasive differences. We use our annotations to test a baseline AMR-to-syntax aligner, finding that this task is more difficult than AMR-to-string alignment; and to pinpoint errors in an AMR parser. We make our data and code freely available for further research on AMR parsing and generation, and the relationship of AMR to syntax.
A Generalized Relative (α, β)-Entropy: Geometric Properties and Applications to Robust Statistical Inference

Entropy and relative entropy measures play a crucial role in mathematical information theory. The relative entropies are also widely used in statistics under the name of divergence measures which link these two fields of science through the minimum divergence principle. Divergence measures are popular among statisticians as many of the corresponding minimum divergence methods lead to robust inference in the presence of outliers in the observed data; examples include the ϕ-divergence, the density power divergence, the logarithmic density power divergence and the recently developed family of logarithmic super divergence (LSD). In this paper, we will present an alternative information theoretic formulation of the LSD measures as a two-parameter generalization of the relative α-entropy, which we refer to as the general (α,β)-entropy. We explore its relation with various other entropies and divergences, which also generates a two-parameter extension of Renyi entropy measure as a by-product. This paper is primarily focused on the geometric properties of the relative (α,β)-entropy or the LSD measures; we prove their continuity and convexity in both the arguments along with an extended Pythagorean relation under a power-transformation of the domain space. We also derive a set of sufficient conditions under which the forward and the reverse projections of the relative (α,β)-entropy exist and are unique. Finally, we briefly discuss the potential applications of the relative (α,β)-entropy or the LSD measures in statistical inference, in particular, for robust parameter estimation and hypothesis testing. Our results on the reverse projection of the relative (α,β)-entropy establish, for the first time, the existence and uniqueness of the minimum LSD estimators. Numerical illustrations are also provided for the problem of estimating the binomial parameter.
Design of intelligent controllers for electronic speed regulation of a diesel engine

An investigation pertaining to identification and expert control design of a diesel engine system is carried out. Diesel engines are known for their high versatility, making them useful in a wide range of industrial applications. Despite several of their attractive features, diesel engines suffer from highly nonlinear and time varying dynamics making them hard to control. The current study provides a means of comparing several types of controllers, some of which are adaptive based and others which are knowledge based. The main goal is to obtain the best possible performance in terms of speed regulation, robustness to load disturbances, and fuel efficiency. This is very helpful in gaining insights for designing a hierarchical based controller under which the system can switch smoothly from one controller to another depending on the operating conditions of the system.
DIGCOMP: A Framework for Developing and Understanding Digital Competence in Europe.

espanolEl documento describe el marco competencia digital desarrollado por EC CCI IPTS en nombre de la Direccion General de Educacion y Cultura con el objetivo general de contribuir a la mejor comprension y el desarrollo de la competencia digital en Europa. La competencia digital es una de las ocho competencias clave para el aprendizaje permanente y es esencial para la participacion en nuestra sociedad cada vez mas digitalizada. Por lo tanto, es necesario entender y definir lo que es la competencia digital y consiste en. El documento analiza varios aspectos de la competencia digital en primer lugar diferenciandolo de otros conceptos similares o coincidentes, luego discutir las implicaciones de la evolucion historica del termino, finalmente detallando el marco competencia digital en sus partes constituyentes. El marco de competencia digital propuesto consta de 21 competencias divididas en 5 zonas. Para cada competencia se preven tres niveles de competencia. Se discuten las aplicaciones actuales y posibles del marco. EnglishThe paper describes the digital competence framework developed by EC JRC IPTS on behalf of DG Education and Culture with the overall aim to contribute to the better understanding and development of digital competence in Europe. Digital competence is one of the eight key competences for lifelong learning and is essential for participation in our increasingly digitalised society. It is therefore necessary to understand and define what digital competence is and consists of. The paper discusses various aspects of digital competence firstly differentiating it from other similar or overlapping concepts, then discussing the implication of the historic evolution of the term, finally detailing the digital competence framework in its constituting parts. The proposed digital competence framework consists of 21 competences divided in 5 areas. For each competence three proficiency levels are foreseen. Current and possible applications of the framework are discussed.
Recommendations and illustrations for the evaluation of photonic random number generators

The never-ending quest to improve the security of digital information combined with recent improvements in hardware technology has caused the field of random number generation to undergo a fundamental shift from relying solely on pseudo-random algorithms to employing optical entropy sources. Despite these significant advances on the hardware side, commonly used statistical measures and evaluation practices remain ill-suited to understand or quantify the optical entropy that underlies physical random number generation. We review the state of the art in the evaluation of optical random number generation and recommend a new paradigm: quantifying entropy generation and understanding the physical limits of the optical sources of randomness. In order to do this, we advocate for the separation of the physical entropy source from deterministic post-processing in the evaluation of random number generators and for the explicit consideration of the impact of the measurement and digitization process on the rate of en.
Sharp L2 estimates of the Schrödinger maximal function in higher dimensions

We show that, for $n\geq 3$, $\lim_{t \to 0} e^{it\Delta}f(x) = f(x)$ holds almost everywhere for all $f \in H^s (\mathbb{R}^n)$ provided that $s>\frac{n}{2(n+1)}$. Due to a counterexample by Bourgain, up to the endpoint, this result is sharp and fully resolves a problem raised by Carleson. Our main theorem is a fractal $L^2$ restriction estimate, which also gives improved results on the size of divergence set of Schr\"odinger solutions, the Falconer distance set problem and the spherical average Fourier decay rates of fractal measures. The key ingredients of the proof include multilinear Kakeya estimates, decoupling and induction on scales.
Laser-induced damage of intrinsic and extrinsic defects by picosecond pulses on multilayer dielectric coatings for petawatt-class lasers

Abstract. We describe a damage testing system and its use in investigating laser-induced optical damage initiated by both intrinsic and extrinsic precursors on multilayer dielectric coatings suitable for use in high-energy, large-aperture petawatt-class lasers. We employ small-area damage test methodologies to evaluate the intrinsic damage resistance of various coatings as a function of deposition methods and coating materials under simulated use conditions. In addition, we demonstrate that damage initiation by raster scanning at lower fluences and growth threshold testing are required to probe the density of extrinsic defects, which will limit large-aperture optics performance.
Seawater-drowning-induced acute lung injury: From molecular mechanisms to potential treatments

Drowning is a crucial public safety problem and is the third leading cause of accidental fatality, claiming ~372,000 lives annually, worldwide. In near-drowning patients, acute lung injury (ALI) or acute respiratory distress syndrome (ARDS) is one of the most common complications. Approximately 1/3 of near-drowning patients fulfill the criteria for ALI or ARDS. In the present article, the current literature of near-drowning, pathophysiologic changes and the molecular mechanisms of seawater-drowning-induced ALI and ARDS was reviewed. Seawater is three times more hyperosmolar than plasma, and following inhalation of seawater the hyperosmotic seawater may cause serious injury in the lung and alveoli. The perturbing effects of seawater may be primarily categorized into insufficiency of pulmonary surfactant, blood-air barrier disruption, formation of pulmonary edema, inflammation, oxidative stress, autophagy, apoptosis and various other hypertonic stimulation. Potential treatments for seawater-induced ALI/ARDS were also presented, in addition to suggestions for further studies. A total of nine therapeutic strategies had been tested and all had focused on modulating the over-activated immunoreactions. In conclusion, seawater drowning is a complex injury process and the exact mechanisms and potential treatments require further exploration.
Role of Marketing Function in the Rubber Marketing Societies for the Benefit of Small Rubber Growers

The establishment of Rubber marketing co-operative marketing societies was the initiative of Govt. of Kerala in order to provide fair price and to bring the small growers from the unorganized segment to organized segment. The primary objective was to provide an efficient market system for helping the farmers for getting accessibility toward the market. However, the efforts of the government to improve the marketing system of rubber marketing have been only partially successful. Moreover, the progress of regulated markets is not uniform in all areas. The main objectives of a co-operative marketing society are to make arrangements for the sale of agricultural produce of its members and to work as marketing supporting organization. Hence in this article, emphasize is given on the marketing function for providing the needs of small rubber growers.
CONVOLUTIONAL NEURAL NETWORKS AND MULTITASK STRATEGIES FOR SEMANTIC MAPPING OF NATURAL LANGUAGE INPUT TO A STRUCTURED DATABASE - 0006174

In this work, we investigate mapping both natural language food and quantity descriptions to matching USDA database entries. We demonstrate that a convolutional neural network (CNN) model with a softmax layer on top to directly predict the most likely database matches outperforms our previous state-of-the-art approach of learning binary classification and subsequently ranking database entries using similarity scores with the learned embeddings. The softmax model achieves 97.3% top-5 USDA quantity and 91.1% food recall over the full database, compared to only 70.0% quantity and 46.4% food recall with a sigmoid model, where top-5 recall indicates the percentage of test cases in which the correct quantity or food is in the top-5 hits. Evaluated on 9,600 spoken meals over all foods, the softmax model achieves 91.6% top-5 quantity and 80.1% food recall. We also explore jointly learning both mappings with a single CNN to boost quantity mapping, and improve food mapping by reranking the food database entries using the predicted quantity matches.
1 Effects of Topical Anaesthetic and Buccal Meloxicam 2 Treatments on Concurrent Castration and Dehorning 3 of Beef Calves 4

The use of pain relief during castration and dehorning of calves on commercial beef 29 operations can be limited by constraints associated with the delivery of analgesic agents. As topical 30 anaesthetic (TA) and buccal meloxicam (MEL) are now available in Australia, offering practical 31 analgesic treatments for concurrent castration and dehorning of beef calves, a study was conducted 32 to determine their efficacy in providing pain relief when applied alone or in combination. Weaner 33 calves were randomly allocated to; (1) no castration and dehorning / positive control (CONP); (2) 34 castration and dehorning / negative control (CONN); (3) castration and dehorning with buccal 35 meloxicam (BM); (4) castration and dehorning with topical anaesthetic (TA); and (5) castration and 36 dehorning with buccal meloxicam and topical anaesthetic (BMTA). Weight gain, paddock 37 utilisation, lying activity and behaviour following treatment were measured. CONP and BMTA 38 calves had significantly greater weight gain than CONN calves (P < 0.001). CONN calves spent less 39 time lying compared to BMTA calves on all days (P < 0.001). All dehorned and castrated calves spent 40 more time walking (P = 0.024) and less time eating (P < 0.001) compared to CONP calves. There was 41 a trend for CONP calves to spend the most time standing and CONN calves to spend the least time 42 standing (P = 0.059). There were also trends for the frequency of head turns to be lowest in CONP 43 and BMTA calves (P = 0.098) and tail flicks to be highest in CONN and BM calves (P = 0.061). The 44 findings of this study suggest that TA and MEL can improve welfare and production of calves 45 following surgical castration and amputation dehorning. 46 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 31 January 2018 doi:10.20944/preprints201801.0294. v1 © 2018 by the author(s). Distributed under a Creative Commons CC BY license. Peer-reviewed version available at Animals 2018, 8, 35; doi:10.3390/ani8030035
Power Plants: Characteristics and Costs

This report analyzes the factors that determine the cost of electricity from new power plants. These factors — including construction costs, fuel expense, environmental regulations, and financing costs — can all be affected by government energy, environmental, and economic policies. The report provides projections of the possible cost of power from new fossil, nuclear, and renewable plants built in 2015, illustrating how different assumptions, such as for the availability of federal incentives, change the cost rankings of the technologies.
The influence of changes in sprint ability on the sled velocity profile during the skeleton start

Sprint times are key predictors of skeleton start petformance, but the effect of enhancing sprint ability on the development of sled velocity is unknown. Twelve well-trained skeleton athletes performed three dry-land push-starts and three 30-m sprints before and after 16 training weeks. Sled velocity profiles were characterised using three descriptors (pre-load velocity, pre-load distance and load effectiveness) and a sled acceleration index was used to evaluate performance. Increases in pre-load velocity and distance were related to improved sprint times. However, enhanced sprint ability did not guarantee a faster start as reductions in load effectiveness were also observed when higher velocities were attained. Coaches could supplement physical conditioning with load technique training to potentially improve the transfer of training-induced sled velocity increases across the loading phase.
SIGNALING IN A DYNAMIC CONTEST WITH BOUNDEDLY RATIONAL PLAYERS

I consider a two-stage (dynamic) elimination contest with uninformed and informed players. Informed players can signal their type to future uninformed opponents through their efforts in the first stage. Uninformed players might make wrong inferences. It is in this sense that they are boundedly rational. Relative to the benchmark case of complete information, I find that there exists an equilibrium in which an informed player exerts a higher effort in the semi-final in the incomplete-information version of the game, if the uninformed player is sufficiently weak. The informed player exerts a smaller effort, if the uninformed player is sufficiently strong. Intuitively, informed players may want to scare future uninformed opponents by exerting higher efforts in earlier rounds. However, trying to scare a very strong player may not be a sensible strategy because he might compete very fiercely. Surprisingly, I find that a higher semi-final effort by the informed player is not necessarily interpreted by the uninformed player as a signal of higher ability.