Miracle-dz/UniFAR-FTUs huggingface dataset:
Unidimensional Simulation of the Spatial Attribute ?Ensemble Depth? for Training Purposes ? Part 2: Creation and Validation of Reference Stimuli

In the context of devising a spatial ear-training system, a study into the perceptual construct ‘ensemble depth’ was executed. Based on the findings of a pilot study into the auditory effects of early reflection (ER) pattern characteristics, exemplary stimuli were created. Changes were highly controlled to allow unidimensional variation of the intended quality. To measure the psychological structure of the stimuli and hence to evaluate the success of the simulation, Multidimensional Scaling (MDS) techniques were employed. Supplementary qualitative data were collected to assist with the analyses of the perceptual (MDS) spaces. Results show (1) that syllabicity1 of source material (rather than ER design) is crucial to depth hearing and (2) that unidimensionality was achieved, thus suggesting the stimuli to be suitable for training purposes.
Population estimation with sparse data: the role of estimators versus indices revisited

The use of indices to evaluate small-mammal populations has been heavily criticized, yet a review of small- mammal studies published from 1996 through 2000 indicated that indices are still the primary methods employed for measuring populations. The literature review also found that 98% of the samples collected in these studies were too small for reliable selection among population-estimation models. Researchers therefore generally have a choice between using a default estimator or an index, a choice for which the consequences have not been critically evaluated. We examined the use of a closed-population enumeration index, the number of unique individuals captured (Mt+1), and 3 population estimators for estimating simulated small populations (N = 50) under variable effects of time, trap-induced behavior, individual heterogeneity in trapping probabilities, and detection probabilities. Simulation results indicated that the estimators produced population estimates with low bias and high precision when the estimator reflected the under- lying sources of variation in capture probability. However, when the underlying sources of variation deviated from model assumptions, bias was often high and results were inconsistent. In our simulations, Mt+1 generally exhibited lower variance and less sensitivity to the sources of variation in capture probabilities than the estimators. Resume : L'utilisation d'indices pour evaluer les populations de petits mammiferes est tres critiquee et pourtant les etudes publiees entre 1996 et 2000 sur les petits mammiferes demontrent que l'utilisation d'indices est toujours la me - thode la plus courante d'evaluation des populations. Dans la litterature, 98 % des echantillons recueillis pour les etudes etaient trop petits pour permettre le choix judicieux d'un modele d'estimation de population. Les chercheurs se retrou- vent donc devant un choix a faire entre une methode par defaut ou un indice, choix dont les consequences n'ont pas ete evaluees de facon formelle. Nous avons examine les resultats de l'utilisation d'un indice de denombrement d'une population fermee, du nombre d'individus particuliers captures (Mt+1), et de 3 estimateurs de population pour estimer de petites populations simulees (N = 50) soumises a des effets divers du temps, du comportement relie au piegeage, de l'heterogeneite dans la probabilite de capture des individus et des probabilites de detection. Les resultats de cette simu- lation ont demontre que les estimateurs donnent des evaluations qui comportent peu d'erreur et qui sont d'une grande precision lorsque l'estimateur utilise reflete les sources de variation sous-jacentes des probabilites de capture. Cepen- dant, lorsque les sources de variation sous-jacentes s'eloignent des presuppositions du modele, les chances d'erreur sont souvent elevees et les resultats sont changeants. Dans nos simulations, Mt+1 a generalement une faible variance et mani- feste moins de sensibilite aux sources de variation des probabilites de capture que les autres estimateurs. (Traduit par la Redaction) 1765
Deliberation and Oversight in Monetary Policy, 1976-2008

The focus of this paper is on the relationship of the Federal Reserve vis-a-vis Congress, starting in the mid-1970s — the period of sustained high inflation — and ending in early 2008, thereby capturing the early days of the financial crisis. As part of a larger book project, this paper provides a bird’s eye view of the discourse in the House and Senate banking committees as they conducted oversight hearings on monetary policy from 1976 to 2008. We use automated textual analysis software to gauge (statistically and graphically) deliberation within these committee hearings, using the verbatim transcripts. We analyze in full (i.e., every word, every phrase) 61 hearings over the 33 year period in order to measure empirically the deliberative discourse by politicians and central bankers on US monetary policy over three decades. We examine (1) the themes that do (and do not) interest legislators when they question the Fed chairman; (2) how these themes have evolved over three decades; and (3) differences in focus between both the Fed chairman and legislators, and between Democrats and Republicans.
57 Extending the MPSM Join

Hardware vendors are improving their (database) servers in two main aspects: (1) increasing main memory capacities of several TB per server, mostly with non-uniform memory access (NUMA) among sockets, and (2) massively parallel multi-core processing. While there has been research on the parallelization of database operations, still many algorithmic and control techniques in current database technology were devised for disk-based systems where I/O dominated the performance. Furthermore, NUMA has only recently caught the community’s attention. In [AKN12], we analyzed the challenges that modern hardware poses to database algorithms on a 32-core machine with 1 TB of main memory (four NUMA partitions) and derived three rather simple rules for NUMA-affine scalable multi-core parallelization. Based on our findings, we developed MPSM, a suite of massively parallel sort-merge join algorithms, and showed its competitive performance on large main memory databases with billions of objects. In this paper, we go one step further and investigate the effectiveness of MPSM for non-inner join variants and complex query plans. We show that for noninner join variants, MPSM incurs no extra overhead. Further, we point out ways of exploiting the roughly sorted output of MPSM in subsequent joins. In our evaluation, we compare these ideas to the basic execution of sequential MPSM joins and find that the original MPSM performs very well in complex query plans.
Corporate Image Management: A Marketing Discipline for the 21st Century

Corporate Image Management is a comprehensive, practical introduction to one of the most potent marketing and management tools available for the use of senior executives. Progressive corporate leaders will want to use this new discipline to drive their organizations in today's increasingly competitive markets. The corporate image communicates the organization's mission, the professionalism of its leadership, the calibre of its employees, and its roles within the marketing environment or political landscape. Historically, thinking and writing about the subject has come from the area of graphic design. This approach no longer suits the global, dynamic, cross-border and cross-cultural world in which many of today's businesses and organizations compete. Corporate Image Management describes the discipline which will be a key to successful marketing well into the next century. Steven Howard, who has over 18 years' senior marketing experience in the Asia/Pacific region, illustrates the concept of corporate image management with case stories from Singapore Airlines, MasterCard International, Amazon.com, the National Basketball Association, Britain's Royal Family, and many others. Treats corporate image correctly as a marketing discipline, not a design issueCorporate image is a critical component of relationship excellenceCan be used for implementing strategic change within any organization
Edge-preserving based adaptive ICC method for image diffusion

Image diffusion is the underlying machine vision research method, and is frequently used to remove image noise. In this paper, we propose a new kernel function for image diffusion by combining the intervening contour (IC) and the color (C) component, called ICC kernel function, which can smooth inner messy texture while maintaining image structure. The intervening contour is used to ensure the diffusion process not to cross the boundary, and the color component ensures the photometric similarity between two pixels. A pixel-segmentation-property based approach is applied to adaptively select the kernel parameters. Experiments show that the adaptive ICC method has better performance of edge-preserving and messy texture smoothing than bilateral filtering and mean shift. Our adaptive ICC method enhances image features representation and helps to improve high-level recognition algorithms.
Multi-Locus Sequence Typing of a Geographically and Temporally Diverse Sample of the Highly Clonal Human Pathogen Bartonella quintana

Bartonella quintana is a re-emerging pathogen and the causative agent of a variety of disease manifestations in humans including trench fever. Various typing methods have been developed for B. quintana, but these tend to be limited by poor resolution and, in the case of gel-based methods, a lack of portability. Multilocus sequence typing (MLST) has been used to study the molecular epidemiology of a large number of pathogens, including B. henselae, a close relative of B. quintana. We developed a MLST scheme for B. quintana based on the 7 MLST loci employed for B. henselae with two additional loci to cover underrepresented regions of the B. quintana chromosome. A total of 16 B. quintana isolates spanning over 60 years and three continents were characterized. Allelic variation was detected in five of the nine loci. Although only 8/4270 (0.002%) of the nucleotide sites examined were variable over all loci, these polymorphisms resolved the 16 isolates into seven sequence types (STs). We also demonstrate that MLST can be applied on uncultured isolates by direct PCR from cardiac valve tissue, and suggest this method presents a promising approach for epidemiological studies in this highly clonal organism. Phylogenetic and clustering analyses suggest that two of the seven STs form a distinct lineage within the population.
Endogenous Preferences : The Cultural Consequences of Markets and other Economic Institutions

Thanks to Eric Verhoogen, James Heintz, Stephanie Eckman, Nicole Huber, and Melissa Osborne for research assistance, to the University of Siena for providing an unparalleled environment for research and writing, to Robert Boyd, Colin Camerer, Robert Cialdini, Lilia Costabile, Joshua Cohen, Gerald Cohen, Martin Daly, Peter Dorman, Catherine Eckel, Marcus Feldman, Ernst Fehr, Nancy Folbre, Christina Fong, Bruno Frey, Herbert Gintis, Karla Hoff, Daniel Kahneman, Melvin Kohn, David Kreps, Timur Kuran, George Loewenstein, Elinor Ostrom, Bentley MacLeod, Paul Malherbe, Karl Ove Moene, Casey Mulligan, Richard Nisbett, Ugo Pagano, Jean-Philippe Platteau, John Roemer, Susan Rose-Ackerman, Paul Romer, Paul Rozin, Andrew Schotter, Paul Seabright, Gil Skillman, Peter Skott, Rohini Somanathan, Hillel Steiner, Philippe van Parijs, Burton Weisbrod, Elisabeth Wood, Erik Olin Wright, Viviana Zelizer, and two anonymous referees for guidance in the literatures covered here and comments on an earlier draft, and to the MacArthur Foundation for financial support. Correspondence to bowles@econs.umass. edu.
i Vector used in Speaker Identification by Dimension Compactness

The automatic speaker identification procedure is used to extract features that help to identify the components of the acoustic signal by discarding all the other stuff like background noise, emotion, hesitation, etc. The acoustic signal is generated by a human that is filtered by the shape of the vocal tract, including tongue, teeth, etc. The shape of the vocal tract determines and produced, what signal comes out in real time. The analytically develops shape of the vocal tract, which exhibits envelop for the short time power spectrum. The ASR needs efficient way of extracting features from the acoustic signal that is used effectively to makes the shape of the individual vocal tract. To identify any acoustic signal in the large collection of acoustic signal i.e. corpora, it needs dimension compactness of total variability space by using the GMM mean super vector. This work presents the efficient way to implement dimension compactness in total variability space and using cosine distance scoring to predict a fast output score for small size utterance.
Active loop closing based on laser data in indoor environment

In Artificial Intelligence, Loop Closing is a key issue of Simultaneous Localization and Mapping (SLAM) that helps SLAM work efficiently and robustly. To solve the problem of the quantity of scene matching increasing linearly with time when loop closing in SLAM for mobile robots, a laser range finder based method is proposed for classifying the geometric scene and determining the set of similar frames for indoor corridor environment. Firstly, based on the turning function, a new line segment extraction method is designed to swiftly obtain the segment feature of scenes. Secondly, the set of basically similar frames is constructed according to scene entropy, scan area and close scan area. Finally, the method describing geometric scenes with the sequences of turning angle is proposed based on the turning angle histogram. By using Longest Common Subsequence matching and Hu-moment-based contour matching, the compact set of similar frames and the best matched frames of query frame are found. The experiment proves that the compact set and the best matched frames can be obtained efficiently and accurately, and based on that, the quantity of scene matching could be greatly reduced.
Computer Solution of Calculus Word Problems

A program was written to solve calculus word problems. The program, CARPS (CAlculus Rate Problem Solver), is restricted to rate problems. The overall plan of the program is similar to Bobrow's STUDENT, the primary difference being the introduction of "structures" as the internal model in CARPS. Structures are stored internally as trees, each structure holding the information gathered about one object. It was found that the use of structures made CARPS more powerful than STUDENT in several respects. 1) CARPS is better able to recognize that two phrases describe the same object. (e.g., CONICAL PILE and PILE OF SAND) 2) Information about an object can be gathered in piecemeal fashion. In calculus word problems it is not uncommon to have two or three sentences providing information for one equation. 3) CARPS to a limited degree is able to use its knowledge to parse its input sentences. For example, in a problem about a filter, ALTITUDE was interpreted as ALTITUDE OF THE FILTER because CARPS knew that since the filter was a cone and cones have altitudes the filter had an altitude. The program has solved 14 calculus problems, most taken (sometimes with slight modifications) from standard calculus texts.
Density Estimation Based on Mass

Density estimation is the ubiquitous base modelling mechanism employed for many tasks such as clustering, classification, anomaly detection and information retrieval. Commonly used density estimation methods such as kernel density estimator and k-nearest neighbour density estimator have high time and space complexities which render them inapplicable in problems with large data size and even a moderate number of dimensions. This weakness sets the fundamental limit in existing algorithms for all these tasks. We propose the first density estimation method which stretches this fundamental limit to an extent that dealing with millions of data can now be done easily and quickly. We analyze the error of the new estimation (from the true density) using a bias-variance analysis. We then perform an empirical evaluation of the proposed method by replacing existing density estimators with the new one in two current density-based algorithms, namely, DBSCAN and LOF. The results show that the new density estimation method significantly improves the runtime of DBSCAN and LOF, while maintaining or improving their task-specific performances in clustering and anomaly detection, respectively. The new method empowers these algorithms, currently limited to small data size only, to process very large databases â€" setting a new benchmark for what density-based algorithms can achieve.
Secret sharing with a single d -level quantum system

We give an example of a wide class of problems for which quantum-information protocols based on multisystem entanglement can be mapped into much simpler ones involving one system. Secret sharing is a cryptographic primitive which plays a central role in various secure multiparty computation tasks and management of keys in cryptography. In secret sharing protocols, a classical message is divided into shares given to recipient parties in such a way that some number of parties need to collaborate in order to reconstruct the message. Quantum protocols for the task commonly rely on multipartite GHZ entanglement. We present a multiparty secret sharing protocol which requires only sequential communication of a single quantum $d$-level system (for any prime $d$). It has huge advantages in scalability and can be realized with state-of-the-art technology.
Enrollment of SME managers to growth-oriented training programs

Purpose – Entrepreneurial learning through formal growth-oriented training programs for SME managers promises to enhance the growth competences and growth intentions of the enrolled managers. The impact of such programs, however, depends on who enrolls since initial competence and growth-intention levels vary significantly. Potential participants may suffer from limited ability to transform new knowledge into practice, absence of growth intention and too high or too low a prior competence level to be able to benefit substantially. Selection and self-selection processes therefore have a bearing on the extent to which such programs result in additionality, i.e. improved growth performance compared to non-intervention. The paper aims to discuss these issues. Design/methodology/approach – Selection and self-selection processes are explored through a study of a large-scale training program for growth-oriented managers of small Danish firms. This program has, from 2012 to 2015, trained about 700 SME managers. D.
Male sex pheromone components in the butterfly Heliconius melpomene

Sex specific pheromones are known to play an important role in butterfly courtship, and may influence both individual reproductive success and reproductive isolation between species. Extensive ecological, behavioural and genetic studies of Heliconius butterflies have made a substantial contribution to our understanding of speciation. However, although long suspected to play an important role, chemical signals have received relatively little attention in this genus. Here, we combine morphological, chemical and behavioural analyses of a male pheromone in the neotropical butterfly Heliconius melpomene. First we identify specialized brush-like scales that are putative androconia, and lie within the shiny grey region found on the hindwing of males. We then describe six putative male sex pheromone compounds, which are largely confined to the androconial region of the hindwing of mature males, but not immature males or females. Finally, behavioural assays reveal subtle, but detectable, differences in female response to models scented with hindwing androconial extracts of mature conspecific males as compared to unscented controls. Collectively, the results describe structures involved in release of the pheromone and a list of potential male sex pheromone compounds triggering a behavioural response in females.
Fair Shares between Worker and Investor:Economic Experiments on Functional Income Distribution

Declines in labor wage rate accompanied with increases in dividend or stocks are worldwide tendencies since 1980s that designates significant change in functional income distribution between capital and labor. Whereas some empirical studies in macro-level analyzes these changes are caused by institutional changes in recent decades such as financialization, studies on micro-level analysis on functional income distributions are few. However, how workers and investors consider distribution justice may have significant importance for explaining recent changes in functional distribution. If both of workers and investors contributed to a production process in different ways, what is ‘fair’ share for each of them? In this paper we have performed economic experiments, consisting of investment stage, production stage and distribution stage and examined fairness ideals in functional income distribution. In our experiment each subject is pair-matched to constitute a two-player’s team consisting of a worker and an investor. After investment stage by an investor and production stage by a worker, each team member was required to give a proposal to separate a team earning with one’s pair. We have performed two different treatments: a) with-labor treatment in which investors are required to work to earn investment funds; b) without-labor treatment in which investment funds are given to investors as their endowments. We have classified each subject’s distribution proposal into three fairness ideals: selfish; libertarian; and radical egalitarian, and examined what factors are significant for subject’s distribution justice. Our findings are threefold. 1) First, few libertarian-marginalist, who believes one should ‘get according to their production by production measurements they own’ was observed. 2) Second, labor value theory seems to have more impact on fairness ideals of individuals: in with-labor treatment investors have to work for their investment funds, both of investors and workers tend to be unselfish, whereas in without-labor treatment investors do not need to work, both of investors and workers tend to be selfish. 3) Third, investors have significant tendencies to commit libertarian egalitarian, that enable them to hold their rest investment funds as their asset, whereas workers have significant tendencies to adhere radical-egalitarian, that enable them to redistribute investor’s assets. These tendencies may be understood from self-serving bias that both of workers and investors have. Although a difference between libertarian-egalitarian and radical-egalitarian distributions seems to be not so serious for finding a compromise, however, in the case investors’ capitals do not based on their labors, a discrepancy in distribution between workers and investors seems to be created. Our experimental results may partly explain recent declines in labor-wage accompanied with institutional changes: financialization tend to make investors to adhere more selfish distribution whereas weakened collective bargaining power by unions promote those tendencies.