Miracle-dz/UniFAR-FTUs huggingface dataset:
Choice Goal Attainment and Decision and Consumption Satisfaction

Several individual, social-setting, and choice-set factors have been shown to be related to satisfaction. This article argues that these factors operate through a set of choice goals. Using panel data on purchasers of consumer electronics, the authors examine how five goals (justifiability, confidence, anticipated regret, evaluation costs, and final negative affect) drive decision and consumption satisfaction, which in turn determine loyalty, product recommendations, and the amount and valence of word of mouth.
Are School Districts Allocating Resources Equitably? The Every Student Succeeds Act, Teacher Experience Gaps, and Equitable Resource Allocation

Ongoing federal efforts support equalizing access to experienced educators for low-income students and students of color, thereby narrowing the “teacher experience gap. ” I show that while high-poverty and high-minority schools have larger class sizes and receive less funding nationally, school districts allocate resource equitably, on average, across schools. However, the least experienced teachers are still concentrated in high-poverty and high-minority schools, both across and within districts. I then show that additional state and local funding is associated with more equitable district resource allocation. The study offers recommendations for state and federal education policy related to the Every Student Succeeds Act.
Comparison Between Reverberation-Ray Matrix, Reverberation-Transfer Matrix, and Generalized Reverberation Matrix

Different matrix formulations have been developed to investigate the elastic-wave propagation in a multilayered solid, which have been widely used in the fields of seismology, ocean acoustics(Pao et al., 2000), and non-destructive evaluation (Lowe, 1995), etc. Transfer matrix (TM) method (Haskell, 1953; Thomson, 1950), as one of the most important matrix formulations, yields a simple configuration and efficient computational ability to facilitate its wide application in many research fields. Stiffness matrix (SM) method (Rokhlin & Wang, 2002; Wang & Rokhlin, 2001) has been proposed to resolve the inherent computational instability for the large product of frequency and thickness in TM method. The SM formulation utilizes the stiffness matrix of each sublayer in a recursive algorithm to obtain the stacked stiffness matrix for the multilayered solid. However, the SM formulation is difficult to identify the generalized-ray propagation in the multilayered solid. In order to evaluate the transient wave propagation in the multilayered solid, Su, Tian, and Pao (Su et al., 2002; Tian & Xie, 2009; Tian et al., 2006) presented reverberation-ray matrix (RRM) formulation. Introducing the local scattering relations at interfaces and the phase relations in sublayers, a system of equations is formulated by a reverberation matrix R , which can be automatically represented as a series of generalized ray group integrals according to the times of reflections and refractions of generalized rays at interfaces. Each generalized ray group integral containing k R represents the set of K times reflections and transmissions of source waves arriving at receivers in the multilayered solid, which is very suitable to automatic computer programming for the simple multilayered-solid configuration. However, the dimension of the reverberation matrix will increase as the number of the sublayers increases, which may yield the lower calculation efficiency of the generalized-ray groups in the complex multilayered solid(Tian & Xie, 2009). In order to increase the calculation efficiency of the generalized-ray groups, Tian presented the reverberation-transfer matrix (RTM) and generalized reverberation matrix (GRM) formulations, respectively. In RTM formulation, RRM formulation is applied to the interested sublayer for the evaluation of the generalized rays and TM formulation to the other sublayers, to construct a RTM of the constant dimension, which is independent of the sublayer number. However, the RTM suffers from the inherent numerical instabilities particularly when the layer thickness becomes large and/ or the frequency is high. GRM
Discovering Resources in the VLO: A Pilot Study with Students of Translation Studies

Common Language Resources and Technology Infrastructure (CLARIN) provides access to language resources for scholars in the humanities and social sciences. In theory, scholars and students of Translation Studies may be assumed to be active data providers of language resources, as well as prolific users of the CLARIN services. However, data show that the uptake of CLARIN services by this user group is rather low. This paper investigates the needs of the students of Translation Studies and evaluates the CLARIN Virtual Language Observatory (VLO) from their perspective. It is based on a pilot study applying open and closed situated user assignments and an evaluation of the VLO service. The results provide insights into the needs of this user group and give suggestions to data and service providers that could increase the adoption of CLARIN services by the user group.
Understanding Good Coping: A Submarine Crew Coping with Extreme Environmental Conditions

The present study is based on in-depth interviews with 12 Israeli submarine crew members. The study examines various aspects of coping with submarine service and its unique characteristics from the crew members’ points of view. Content analysis reveals the following salient themes: First, positive perception of submarine service: positive thinking, optimism and sense of humor, accompanied by cynicism. Second, the submarine team is characterized by high moral standards, high team spirit and a sense of the importance of the service. Third, social relationships are characterized by avoidance of conflicts, while maintaining a good atmosphere and high social cohesion. Fourth, crew members perceived separation from home, friends and daily life as the most difficult aspects to deal with. Fifth, they perceived the submarine as dangerous place but reduced aspects of danger by developing a sense of trust in their submarine and in their ability to control potential dangers. Study results are discussed in light of relevant theories. This study is unique in that it was a rare opportunity to get a glimpse into the unknown world of an Israeli submarine crew which is mostly secret and not open to researchers.
Policy Sensitivity Analysis: simple versus complex fishery models

Traditional behaviour sensitivity analysis is used to judge the sensitivity of model behaviour to uncertain assumptions about model formulations and parameter values. It is argued that it may be just as important to test the sensitivity of policy recommendations to uncertain assumptions. However, in complex dynamic models, policy recommendations typically have elements of randomness and possibly subjectivity. This problem is avoided by using optimisation to identify unique policies for different model assumptions. The case is a cod fishery for which a quota policy combined with a simple capacity policy is investigated. It is found that the policies are not very sensitive to the choice of biological model (aggregated or age classes), while they are highly sensitive to uncertain assumptions about nonlinear economic relationships. Interestingly, these findings seem at odds with the priorities in much modelling activity, be it in the field of biology or economics. Copyright © 2005 John Wiley & Sons, Ltd.
Whitbrook, Amanda and Aickelin, Uwe and Garibaldi, Jonathan M. (2010) Two-timescale learning using idiotypic behaviour mediation for a navigating mobile

A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approach to solving mobile-robot navigation problems is presented and tested in both the real and virtual domains. The LTL phase consists of rapid simulations that use a Genetic Algorithm to derive diverse sets of behaviours, encoded as variable sets of attributes, and the STL phase is an idiotypic Artificial Immune System. Results from the LTL phase show that sets of behaviours develop very rapidly, and significantly greater diversity is obtained when multiple autonomous populations are used, rather than a single one. The architecture is assessed under various scenarios, including removal of the LTL phase and switching off the idiotypic mechanism in the STL phase. The comparisons provide substantial evidence that the best option is the inclusion of both the LTL phase and the idiotypic system. In addition, this paper shows that structurally different environments can be used for the two phases without compromising transferability.
LEAST-SQUARES FINITE ELEMENT METHODS FOR QUANTUM CHROMODYNAMICS

A significant amount of the computational time in large Monte Carlo simulations of lattice quantum chromodynamics (QCD) is spent inverting the discrete Dirac operator. Unfortunately, traditional covariant finite difference discretizations of the Dirac operator present serious challenges for standard iterative methods. For interesting physical parameters, the discretized operator is large and ill-conditioned, and has random coefficients. More recently, adaptive algebraic multigrid (AMG) methods have been shown to be effective preconditioners for Wilson’s discretization [1] [2] of the Dirac equation. This paper presents an alternate discretization of the Dirac operator based on least-squares finite elements. The discretization is systematically developed and physical properties of the resulting matrix system are discussed. Finally, numerical experiments are presented that demonstrate the effectiveness of adaptive smoothed aggregation (αSA ) multigrid as a preconditioner for the discrete field equations resulting from applying the proposed least-squares FE formulation to a simplified test problem, the 2d Schwinger model of quantum electrodynamics (QED).
Network-Wide Heavy-Hitter Detection for Real-Time Telemetry

Many network monitoring tasks identify subsets of traffic that stand out, e.g., topk flows for a particular statistic. We can efficiently determine these “heavy-hitter” flows on individual network elements, but network operators often want to identify interesting traffic on a network-wide basis. Determining the heavy hitters on a network-wide basis necessarily introduces a trade-off between the communication required to perform this distributed computation and the accuracy of the results. To perform distributed heavy-hitter detection in real time with high accuracy and low overhead, we extend the Continuous Distributed Monitoring (CDM) model to account for the realities of modern networks and devise practical solutions that detect heavy hitters with high accuracy and low communication overhead. We present two novel algorithms that automatically tune the set of monitoring switches in response to traffic dynamics. We implement our system using the P4 language, and evaluate it using real-world packet traces. We demonstrate that our solutions can accurately detect network-wide heavy hitters with up to 70% savings in communication overhead compared to existing approaches.
An End to End Model for Automatic Music Generation: Combining Deep Raw and Symbolic Audio Networks

We develop an approach to combine two types of music generation models, namely symbolic and raw audio models. While symbolic models typically operate at the note level and are able to capture long-term dependencies, they lack the expressive richness and nuance of performed music. Raw audio models train directly on raw audio waveforms, and can be used to produce expressive music; however, these models typically lack structure and long-term dependencies. We describe a work-in-progress model that trains a raw audio model based on the recently-proposed WaveNet architecture, but that incorporates the notes of the composition as a secondary input to the network. When generating novel compositions, we utilize an LSTM network whose output feeds into the raw audio model, thus yielding an end-to-end model that generates raw audio outputs combining the best of both worlds. We describe initial results of our approach, which we believe to show considerable promise for structured music generation.
New drag balance facility for skin-friction studies in turbulent boundary layer at high Reynolds numbers

A unique drag balance facility is described here for the study of skin-friction in high Reynolds number wall turbulence. The facility was tested in the High Reynolds Number Boundary Layer Wind Tunnel (HRNBLWT) at the University of Melbourne, giving direct measurements of skin-friction over a large surface. The approach utilizes a drag balance, however, here the implementation is unique in two aspects, the design and the Reynolds number at which the experiments were conducted. The drag balance consists of a large floating flat plate whose displacement is translated into a force measurement by a load cell. Measurements of skin-friction coefficient cf at different Reynolds numbers were obtained, and are compared with those obtained using a Clauser-chart method. Comparisons are also made with various empirical relations for cf available in literature. Both comparisons showed a very good collapse, which establishes the utility of the facility in determining wall shear stress.
Resonant Amplification of Instability Waves in Quasi-Subharmonic Triplets with Frequency and Wavenumber Detunings

Abstract : Probably the first experimental evidence of an important role of the subharmonic resonance in the process of the laminar-turbulent transition in adverse pressure gradient (APG) boundary layers was obtained. Until recently the only available direct experimental study of the subharmonic resonant interactions in the APG boundary layer was performed for rather small values of the Hartree parameter (beta H -0.06 and -0.09). In agreement with the theoretical prediction a rapid growth and subsequent saturation of subharmonic amplitudes was found under controlled disturbance conditions. However the double-exponential growth predicted by theory has not been found and resonant interactions with frequency and wavenumber detunings have not been examined. Some new results were obtained were all main properties of tuned resonances were studied for a moderate Hartree parameter beta H -0.115. Optimal parameters of resonant triplets were found a strong dependence of the interaction on phase relationships was examined and the double-exponential growth was discovered. However, many questions are still open. The goal of the present experiments was to narrow the gaps existing in this area. In particular, we aimed to study the resonant interactions in the presence of frequency and spanwise-wavenumber detunings for quasi-subharmonic modes.
Remote sensing of nearshore wave interference

Wave focusing of energetic swell fields can result in small-scale variations associated with coherent interference that can be important for nearshore circulation and beach dynamics. However, coherent interference is difficult to measure with conventional in situ instruments and is not accounted for in operational wave models. As a result, such effects are generally ignored. In this work, we analyze X-band radar observations collected at Ocean Beach, San Francisco using a Wigner-Ville or coupled-mode spectrum, to show how long-dwell remote sensing technology allows us to identify coherent wave interference. Our analysis demonstrates that during energetic swell events, the nearshore wave field consists of two noncollinear, but coherent, swell patterns that originate from the same offshore source but are directionally separated due to refraction over the San Francisco Bar. The length scale of the associated alongshore wave height variability (200 m) is consistent with the wavenumber separation obtained from the coupled mode analysis. This confirms that the small-scale variability is primarily due to coherent interference. In addition, our analysis shows that the shoreline exhibits a strong localized response near the radar site on the 200 m scale, which suggests that coherent interference effects can affect wave-driven nearshore transport processes and localized erosion.
Analysis, Simulation and Prediction of Multivariate Random Fields with Package RandomFields

Modeling of and inference on multivariate data that have been measured in space, such as temperature and pressure, are challenging tasks in environmental sciences, physics and materials science. We give an overview over and some background on modeling with crosscovariance models. The R package RandomFields supports the simulation, the parameter estimation and the prediction in particular for the linear model of coregionalization, the multivariate Matern models, the delay model, and a spectrum of physically motivated vector valued models. An example on weather data is considered, illustrating the use of RandomFields for parameter estimation and prediction.
Beyond One-Dimensional Portraits: A Synoptic Approach to the Visual Analysis of Biography Data

The study of biography data – and the reasoning with it – can be supported by multiple visualization techniques. Biographical databases contain massive amounts of temporally structured biographical entries, connecting events, places, institutions and actors with a variety of relations between them. We present a synoptic visualization concept for multi-dimensional biographical analyses, to go beyond well-established techniques to portray one-dimensional data aspects. We discuss synergies arising from the combination of multiple synchronic and diachronic views into a more coherent visual analytics environment. Possible synchronic views include geographic, relational and categorial perspectives on biography data (e.g., maps, network and treemap diagrams), while multiple diachronic perspectives are provided by coordinated multiple views, animation, layer superimposition, layer juxtaposition, and space-time cube representations. By closely intertwining these visualization methods we aim to support the creation of more integrated and connected mental models of biographical data. This visual framework is open for other fields of application like prosopographical research, digital history, or many other time-oriented arts and humanities data domains.
Imaging and Wear Analysis of Micro-tools Using Machine Vision

Tool positioning and tool wear or breakage is an integral part of the development of a micromachining center. The nature of worn tools, producing deficiencies in good surface finish and dimension control, is a major concern in machining operations. Current techniques in place for tool location depend on the encoder feedback of the CNC system, with the assumption of accurate tool radius compensation. Additionally, in order to maintain machining quality and to prevent damage to the work-piece, accurate monitoring or early prediction of tool condition is important. These techniques however are insufficient for micro-machining where the tool itself is usually invisible to the human eye. Because the diameter is so small, accuracy is inherently compromised. Furthermore, due to the micron scales of micro-machining, detection as well as determination of tool wear or breakage is quite challenging. This paper reports on the results of an ongoing research project to investigate and develop machine vision applications for micro machining tool location and tool wear monitoring. The determination of an optimal optical setup is reported together with some algorithms for image processing and feature classification. The optical setup utilizes a 3 mega pixel CMOS capturing device mounted on 12X ultra zoom lens. Lighting is achieved by direct, indirect and backlighting. Initial image analysis, utilizing basic Gaussian filters and histogram equalization indicates that lighting is a critical factor in this application. Wear determination is performed by a comparison of the image of an unused tool with that of a used tool using exclusive operators. Although the results seem promising, there is need for finer enhancements on images prior to the application of classification algorithms.
Characteristics of dehalogenase from bacteria isolated from the gut of pond-reared rohu (Labeo rohita) juveniles in Myanmar

Unwarranted accumulation of halogenated compounds in the rivers and streams has in recent years emerged due to the widespread use agricultural pesticides. The presence of these halogenated compounds in the water does not only suppress the immune system of fish but adversely induce serious morbidity and mortality among cultured stocks. Importantly, gradual accumulation of these compounds in the system of cultured and wild freshwater fish species cultured in ponds and floating net-cages in dams and rivers, respectively, poses some risks to humans, the end users. In this study, we attempted to isolate bacteria from the gut of pond-reared rohu (Labeo rohita) in Myanmar, screened the isolated bacteria for dehalogenase gene using molecular technique and tested the ability of these bacteria to degrade halogenated compounds in vitro. The eight bacterial strains studied were identified as Enterobacter mori strain MK- 121001, Enterobacter cloacae strains MK121003, MK-121004, MK121010, Ralstonia solanacearum strain 121002, Acinetobacter baumannii strain MK121007, Chromobacterium violaceum strain MK121009 and Pantoea vagans strain 121011. Only three bacterial strains (MK121002, MK121007 and MK121009) were capable of degrading 2,2-dichloropropionic acid (2,2-DCP) as the sole carbon source up to a final substrate concentration of 20 mM. Their mean growth doubling time ranging from 6-23 hours with the maximum of chloride ion released of 85%. PCR amplifica- tion with oligonucleotide primers designed from group I dehalogenase revealed the presence of deha- logenase genes in all isolates suggesting dehalogenase gene in strains 121001, 121003, 121004, 121010 and 121011 were silenced. In contrast, group II dehalogenase primers did not show any PCR amplification. These results suggest that MK121002, MK121007 and MK121009 only encode a group I dehalogenase and its non-stereoselectivity is in agreement with previoulsly described group I haloacid dehalogenase. The partial gene sequences were blasted but no significant sequence identity was observed. Therefore, it suggest the 2-haloacid dehalogenase of MK121002, MK12-1007 and MK121009 might be a novel group I 2-haloacid dehalogenase. The results indicated a broad distribution of dehalogenation genes in many micro- bial genomes that harbor dehalogenase(s) due to the exposure of the microorganisms to the naturally occurring or man-made halogenated compounds in the environmental systems. So far, microorganisms capable of producing dehalogenases were mainly isolated from soil and scarcely from aquatic animals and their environments. To the authors’ knowledge, this is the first report on the isolation of dehalogenase-producing bacteria from the gut of pond-reared freshwater fish, Labeo rohita, in Myanmar.
Postural assessment of primary school children in Liechtenstein: a longitudinal study 2008–2010

Studien deuten darauf hin, dass Haltungsschwächen bei Schulkindern in den letzten Jahrzehnten zugenommen haben. Diese besorgniserregende Entwicklung wird auch in der vorliegenden Längsschnittstudie bestätigt. Die Daten stammen aus schulischen Vorsorgeuntersuchungen, welche unter der Leitung des Amtes für Gesundheit in den Jahren 2008 und 2010 auf der 1. und 3. Primarschulstufe bei 367 Kindern (im Alter von 6–11 Jahren) durchgeführt wurden. Diese orthopädischen Untersuchungen umfassten zwei Parameter: eine statische Haltungsbeurteilung (5 Items) und eine dynamisch-muskuläre Funktionsprüfung (6 Items). Zusammenfassend zeigte sich eine signifikante Verschlechterung der Körperhaltung im Altersverlauf und im Durchschnitt wurde jedes 5. Kind ins Haltungsturnen empfohlen. Aufgrund der geringen Teilnahmequote an diesem freiwilligen und kostenlosen Förderangebot von lediglich 45.5% scheint eine kritische Evaluation der Umsetzungspraxis angezeigt. Abstract