Miracle-dz/UniFAR-FTUs huggingface dataset:
Objective Measurement of Social Role Concepts via the Semantic Differential

A methodological study for quantifying the construct of role on three dimensions of a Semantic Differential: Evaluative, Potency, Activity. Male and female university students rated 8 social roles on a standard 25-item Semantic Differential under two instructional procedures. Support was obtained for a central assumption embraced by role theorists, that there is consensual agreement as to characteristics associated with certain roles. Ratings of the roles for the two instructional conditions, actual and ideal, closely paralleled the concepts “role” and “position,” respectively. Each of the three semantic dimensions significantly differentiated the 8 roles, indicating that three semantic dimensions provided greater precision in measurement than only an attitudinal dimension.
Spend, Baby, Spend: Windfalls, Specialization and Misallocation

Resource-rich countries tend to employ a much larger proportion of workers in the government sector than resource-poor countries. I construct a model with a productive government sector and examine optimal government employment in resource-rich countries. In the calibrated best-case-scenario model, predicted optimal government employment is nearly 10 times smaller than in the data. This implicit misallocation of resources has a large impact on welfare and aggregate productivity. Using the calibrated model I find that a ten percentage point increase in resource windfalls is associated with a 1.94% percent lower aggregate productivity and a 1.22% lower welfare arising from government misallocation. 1 This paper has been prepared for the XVIII Central Bank of Chile Annual conference. Thanks to Antonio Mele for useful discussion and comments. All errors are my own. Email: rls7@st-andrews.ac. uk.
Image Quality Enhancement for Tone Mapped HDR Image Using Wavelet Based Fusion

Tone-mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images, so as to visualize HDR images on standard displays. Different TMOs create different tone-mapped images and a natural question is which one has the best quality. this paper introduces a fusion technique based on wavelet transforms that combines the output of several operators in a single image, based on objective quality maps that do not depend on the dynamic range of neither the input nor the output images, thus offering a better detail preservation capability compared to the case where each operator is independently applied. Here an algorithm is proposed for fusing the LDR image outputs obtained by applying different TMOs on the same HDR input image.
A sparse and prior based method for 3D image denoising

Denoising algorithms via sparse representation are among the state-of-the art for 2D image restoration. In this work, we propose a novel sparse and prior-based algorithm for 3D image denoising (SPADE). SPADE is a modification of total variation (TV) problem with an additional functional that promotes sparsity with respect to a prior image. The prior is obtained from the noisy image by combining information from neighbor slices. The functional is minimized using the split Bregman method, which leads to an efficient method for large scale 3D denoising, with computational cost given by three FFT per iteration. SPADE is compared to TV and dictionary learning on the Shepp-Logan phantom and on human knee data acquired on a spectral computerized tomography scanner. SPADE converges in approximately ten iterations and provides comparable or better results than the other methods. In addition, the exploitation of the prior image avoids the patchy, cartoon-like images provided by TV and provides a more natural texture.
Mastering English: An Advanced Grammar for Non-Native and Native Speakers

Mastering English presentsa new, pedagogically sound approach to English grammar. Breaking with the terse, and often dry, matter of fact mode of traditional grammars, the reader is taken along a reasoned course through the grammar of English. Both an advanced textbook and a reference work, Mastering English is different in a number of ways: It offers a simple but comprehensive syntactic system which enables the student to analyse any sentence down to word level with a specification of both the form and the function of constituents at all levels. It combines coherent discussion, rule presentation and rich examplification, rather than simply offering lists of facts. it includes a thorough treatment of a number of areas neglected by most other grammars, such as inversion, discontinuity, negation, and order and position of adverbials and adjectival modifiers.
The visualisation and quanti fi cation of human gastrointestinal fat distribution with MRI : a randomised study in healthy subjects

We aimed to study the fate of fat during digestion. For this purpose, we validated and investigated the non-invasive quantification of gastric and duodenal fat emptying and emulsion processing (creaming and phase separation) using the MRI method iterative decomposition with echo asymmetry and least squares estimation (IDEAL). In total, twelve healthy subjects were studied on two separate visits in a single-blind, randomised, cross-over design study. IDEAL was utilised to repeatedly acquire quantitative fat fraction maps of the gastrointestinal tract after infusion of one of two fat emulsions: E1 (acid stable, droplet size 0·33mm) and E4 (acid unstable, 0·38mm). In vitro and in vivo validation was carried out using diluted emulsion and gastric content samples, respectively, and resulted in Lin’s concordance correlation coefficients of 1·00 (95% CI 0·98, 1·00) and 0·91 (95% CI 0·87, 0·94), respectively. Fat fraction maps and intragastric emulsion profiles enabled the identification of features of intraluminal phase separation and creaming that were not visible in conventional MRI. Gastric fat emptying was faster for E4 compared with E1 with a difference of 2·5 (95% CI 1·9, 3·1)ml/h. Duodenal content volumes were larger for E1 than for E4 with a difference of 4·9 (95% CI 3·9, 8·5)ml. This study demonstrated that with IDEAL it was possible (1) to visualise the intragastric and duodenal fat distribution and (2) to quantify the differences in emptying, phase separation and creaming of an acid-stable and an acid-unstable emulsion. This method has potential to bridge the gap between current in vitro digestive models and in vivo behaviour and to be applied in the development of effective functional foods.
TIME REVERSAL LOCALIZATION OF CONTINUOUS AND BURST AE SOURCES UNDER NOISE

Time reversal (TR) processing of acoustic and ultrasonic signals is effective tool for complicated problems solution in NDT /E and structural health monitoring. TR enables space-time focusing of elastic wave and thereby relatively easy location and partial reconstruction of both burst and continuous acoustic emission (AE) sources. AE source location problems come up in situations with high external noise, wave dispersion in thin-wall structures, and wave velocity changes in complex structures containing welds, flanges, branches, etc. Localization problems in such cases mostly require large sensor arrays and sophisticated signal processing and filtration. A new solution with using TR approach is suggested in this paper. This approach allows planar location of burst AE sources with only one transducer, and continuous AE sources with two transducers, both under high background noise from other sources. TR procedure is in this paper applied to long random noise (leakage) signals for the first time. Suggested method was experimentally verified by simulated burst and continuous AE sources on a thick steel plate and thin Al-plate with various holes. Source location results certified high robustness of suggested approach. Need of detailed scanning of a region around a pre-localized source constitutes certain disadvantage of that method. Numerical simulations shown that scanning can be omitted by inserting experimental TR signals into the computer model of monitored structure (“digital twin”) and perform the source location in the model. Localization accuracy of suggested procedure proved by LDV is about one mm, which is better than the wavelength and transducer aperture.
Distributed Link Scheduling Algorithm Based on Successive Interference Cancellation in MIMO Wireless Networks

The performance of multiple input multiple output (MIMO) wireless networks is limited mainly by concurrent interference among sensor nodes. Effective link scheduling algorithms with the technology of successive interference cancellation (SIC) can maximize throughput in MIMO wireless networks. Most previous works on link scheduling in MIMO wireless networks did not consider SIC. In this paper, we propose a MIMO-SIC (MSIC) algorithm under the SINR model. First, a mathematical framework is established for the cross-layer optimization of routing and scheduling, with constraints of traffic balance and link capacity. Second, the interference regions are divided to characterize the level of interference between links. Finally, we propose a distributed link scheduling algorithm based on MSIC to eliminate the interference between competing links in the MIMO network. Experimental results show that the MSIC algorithm can increase the end-to-end throughput per unit by approximately 73% on average compared with non-SIC algorithms.
An approach to generate MDPs using HTN representations

Planning for deterministic and probabilistic domains differ significantly in representations they require, the algorithms that solve them and the way in which results are represented. Hierarchical Task Networks (HTN) and Markov Decision Process (MDPs) are representative formalisms of, respectively, deterministic and stochastic planning. Stochastic domain specifications can easily become opaque to a human designer, especially as the domain size increases. Our research aims to develop algorithms for lossless and automatic mapping of HTN models that are easily intelligible to humans into MDPs. In this paper we develop algorithms to convert deterministic planning domains with HTN domain knowledge and an action error model into MDPs that can then be solved, while maintaining a bound on the number of MDP states.
Solution of 2 D Electromagnetic Scattering Using IEFG-UPML Method

This paper presents a new approach for solution of 2D electromagnetic scattering using interpolating element-free galerkin method with perfectly matched layers technique in order to limit the computational domain. The uniaxial perfectly matched layers in cylindrical coordinates and the first-order Bayliss-Turkel absorbing aboundary conditions are used to limit the computational domain. It is considered the TMz plane wave scattering by a z-infinite dielectric cylinder and the results obtained from proposed technique are compared with analytical solution.
Development of operational forecasting for icing and wind power at cold climate sites

Based on icing measurements from 12 meteorological stations in Sweden a methodology for calculating icing from meso scale model data has been developed over the past 5 years. Operational data from seven wind farms in cold climate regions in Sweden (total of 272 MW and 111 individual turbines) have in addition been utilized to develop a state-of-the-art model for estimating production losses due to icing (IceLoss). Operational forecasting of energy production, icing and production losses due to icing has been carried out for the four wind farms which all experiences losses due to icing. The forecast simulations are run 4 times daily, each with a lead time of 48 hours. It is shown that the method is able to realistically describe the periods when ice is influencing the energy production for the wind farms. 63-82% of the time periods when icing is influencing the energy production are captured by the forecasts. Essential to forecast icing events is the ability to forecast the events at the correct time. For 67-71 % of the strongest icing events the timing was correctly forecasted. These icing events accounted for approximately 90 % of the production losses from the wind farms. The power forecasts with and without losses due to icing are compared to the hourly production data from the wind farm. It is evident that the accuracy of the forecasts is improved when the power losses caused by icing are taken into account, resulting in a reduction of the mean absolute error (MAE), reduction of the average bias and increase of hourly correlation coefficients. The results show that the number of cases when the produced energy is overpredicted is reduced when including power losses due to icing, while the cases of under-prediction the produced energy is somewhat increased.
A Lexically Scoped Distributed $\pi$-Calculus

We define the syntax, the operational semantics, and a type system for lsdπ, an asynchronous and distributed π-calculus with local communication and process migration. The calculus follows a simple model of distribution for mobile calculi, with a lexical scoping mechanism that provides both for remote communication and for process migration, making explicit migration primitives superfluous.
New lower segment repairing surgery to control bleeding in repeated caesarean section , a randomized controlled trail

Objective: Bleeding was very common in repeated caesarean section, but most of the existed surgical methods were targeted at atony of the uterine corpus. We attempted to describe a new suturing technique in order to control bleeding from the lower segment of uterus in repeated CS. Methods 110 elective repeated caesarean section (ERCS) patients were included. We randomly assigned them into two groups according to a computer generated randomized block with 55 patients in each group (repair group: new suturing method was performed; control group: classic CS was performed). Intraoperative and postoperative parameters were compared. Results: The repair group was found to be superior to the control group with less blood loss (523.64±253.97 vs 660.00±278.55 g, p=0.008). Although multivariate analysis showed no superiority of this method in reducing the rate of PPH and application of tocolytic agent (adjusted OR 0.90, 95% CI 0.10, 7.91; adjusted OR 0.26, 95% CI 0.06, 1.07; respectively), hospital stay time of the repair group was shorter (adjusted OR 3.96, 95% CI 1.36, 11.56). There were no differences in neonatal Apgar score at 5 minute, surgery time or risk of puerperal morbidity. Conclusion: This new suturing method could reduce blood loss effectively in the lower segment of uterus in ERCS patients. Because of its simplicity of application and less time taken, it should be a preferred choice.
Augmented Reality Interfaces for Procedural Tasks

Procedural tasks involve people performing established sequences of activities while interacting with objects in the physical environment to accomplish particular goals. These tasks span almost all aspects of human life and vary greatly in their complexity. For some simple tasks, little cognitive assistance is required beyond an initial learning session in which a person follows one-time compact directions, or even intuition, to master a sequence of activities. In the case of complex tasks, procedural assistance may be continually required, even for the most experienced users. Approaches for rendering this assistance employ a wide range of written, audible, and computer-based technologies. This dissertation explores an approach in which procedural task assistance is rendered using augmented reality. Augmented reality integrates virtual content with a user’s natural view of the environment, combining real and virtual objects interactively, and aligning them with each other. Our thesis is that an augmented reality interface can allow individuals to perform procedural tasks more quickly while exerting less effort and making fewer errors than other forms of assistance. This thesis is supported by several significant contributions yielded during the exploration of the following research themes: What aspects of AR are applicable and beneficial to the procedural task problem? In answering this question, we developed two prototype AR interfaces that improve procedural task accomplishment. The first prototype was designed to assist mechanics carrying out maintenance procedures under field conditions. An evaluation involving professional mechanics showed our prototype reduced the time required to locate procedural tasks and resulted in fewer head movements while transitioning between tasks. Following up on this work, we constructed another prototype that focuses on providing assistance in the underexplored psychomotor phases of procedural tasks. This prototype presents dynamic and prescriptive forms of instruction and was evaluated using a demanding and realistic alignment task. This evaluation revealed that the AR prototype allowed participants to complete the alignment more quickly and accurately than when using an enhanced version of currently employed documentation systems. How does the user interact with an AR application assisting with procedural tasks? The application of AR to the procedural task problem poses unique user interaction challenges. To meet these challenges, we present and evaluate a novel class of user interfaces that leverage naturally occurring and otherwise unused affordances in the native environment to provide a tangible user interface for augmented reality applications. This class of techniques, which we call Opportunistic Controls, combines hand gestures, overlaid virtual widgets, and passive haptics to form an interface that was proven effective and intuitive during quantitative evaluation. Our evaluation of these techniques includes a qualitative exploration of various preferences and heuristics for Opportunistic Control-based designs.
Reading and writing the game: Creative and dialogic pedagogies in sports education1 ABSTRACT Sports educators have long used coaching and teaching methods based on regimes of mechanical execution of movements. Without accounting for the social context in which sports

Sports educators have long used coaching and teaching methods based on regimes of mechanical execution of movements. Without accounting for the social context in which sports education takes place, these methodologies consider exhaustive action replication the best way to master physical skills. The past decades have seen a surge in alternative pedagogies that acknowledge that sporting bodies are much more than a combination of techniques. Pedagogies such as Game Sense approach the sports teaching-learning process through a constructivist perspective in which the intellectual dimensions of games are highlighted. This paper empirically examines how dialogic pedagogies can be put to work in sports education in order for students’ bodies to become creative and a central part of their own development. Using autoethnographic data drawn from the authors’ international personal experiences as sports coaches, physical educators, researchers and evaluators in two sports education contexts – school sports education and sport for development (SfD) – the paper aims to reveal pedagogies that foster creative participants who can enjoy, read and write their own games. The authors conclude that while dialogic sports education is not without conflict, it enables sports educators to create spaces in which continuous dialogue can occur. These pedagogies are not simply a tool for inquiry-based educational possibilities; they are the actual dialogic education.
A Communication Efficient Hierarchical Distributed Optimization Algorithm for Multi-Agent Reinforcement Learning

Policy evaluation problems in multi-agent reinforcement learning (MARL) have attracted growing interest recently. In these settings, agents collaborate to learn the value of a given policy with private local rewards and jointly observed state-action pairs. However, most fully decentralized algorithms treat each agent equally, without considering the communication structure of the agents over a given network, and the corresponding effects on communication efficiency. In this paper, we propose a hierarchical distributed algorithm that differentiates the roles of each of the agents during the evaluation process. This allows us to freely choose various mixing schemes (and corresponding mixing matrices that are not necessarily doubly stochastic), in order to reduce the communication cost, while still maintaining convergence at rates as fast as or even faster than the previous approaches. Theoretically, we show the proposed method, which contains existing distributed methods as a special case, achieves the same order of convergence rate as state-of-the-art methods. Numerical experiments on real datasets demonstrate the superior performances of our approach over other advanced algorithms in terms of convergence and total communication efficiency.
The pedagogical model of SIAL: an adaptive and open-ended intelligent tutoring system for first order logic

This paper describes the Pedagogical Model of an Intelligent Tutoring System (ITS) for learning Computational Logic: SIAL. This ITS teaches classical refutation by resolution concepts. SIAL is a Model-Based System as its Domain Model is an Automated Theorem Prover (ATP) for First Order Logic (FOL). This allows SIAL to perform an accurate error diagnosis process while, at the same time, accepting several equivalent valid solutions to the same problem. This feature adds a general open-ended solution capability to SIAL which facilitates the adaptation to the students' way of thinking and allows them to explore and take their own decisions (and make their own mistakes). The Pedagogical Model of SIAL takes advantage of the error diagnosis capabilities of the Domain Model to offer a learner-adaptive tutorial action, according to the user cognitive profile. An example of the knowledge involved in the assessment of the next tutorial action based on the student model, and how SIAL adapts its behaviour to the student's assessed cognitive capabilities, is included. Some data obtained after a period of use of SIAL is also presented.
Towards a grounded theory of how students identify computing

In order to apply their computing knowledge to everyday situations, students first need to be able to identify those situations in which computing even plays a role. This task becomes increasingly difficult, however, as computing systems become more and more ubiquitous and invisible. Based on the analysis of 28 semi-structured focus interviews, we aim to develop a grounded theory of students' conceptions and reasoning related to this identification process. In this paper, we outline our motivation and study design.
Active Learning for Improving Decision-Making from Imbalanced Data

This extended abstract considers the reliability of prediction-based decision-making in a task of deciding which action a to take for a target unit after observing its covariates x̃ and predicted outcomes p̂(ỹ | x̃, a). An example case is personalized medicine and the decision of which treatment to give to a patient. A common problem when learning these models from observational data is imbalance, that is, difference in treated/control covariate distributions. We propose to assess the decision-making reliability by estimating the model’s Type S error rate, which is the probability of the model inferring the sign of the treatment effect wrong. Furthermore, we use the estimated reliability as a criterion for active learning, in order to collect new (possibly expensive) observations, instead of making a forced choice based on unreliable predictions. We demonstrate the effectiveness of this decision-making aware active learning in two decision-making tasks: in simulated data with binary outcomes and in a medical dataset with synthetic and continuous treatment outcomes.