Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Indigenous local language opportunities in community-based tourism initiatives in Haida Gwaii (British Columbia, Canada)

ABSTRACT This study explores visitor perceptions of Indigenous local language use at the Haida Heritage Centre at Kay Llnagaay and Haida Gwaii Museum. We explore visitor expectations of local language use, the meaning and value of language, and their openness to expanded forms of language expression. The objective was to understand the context and limitations in which the Haida could improve local language opportunities using community-based tourism initiatives to their advantage. An Indigenist methodology informed analysis of 27 in-depth visitor interviews and provided insight into three major themes (1) life experience and heritage informs expectations, (2) [It's a] “Means of Communication” masks a deeper understanding of language, and (3) creating a meaningful space for local language engagement. The findings suggest significant and untapped spaces in which to support the expanded use of culturally appropriate local languages to the well-being of speakers and visitors. Ultimately, visitor affirmation drew on shared experiences of language loss – laying the groundwork for engagement based on the value of language as opposed to its prescriptive use as a commodity. Practical ways forward are given. This research was part of a larger study aimed at encouraging greater visibility and accessibility to Haida language through community-based tourism initiatives.
Opiniones y propuestas de los estudiantes de Comunicación Audiovisual sobre los SPOC

En este articulo se presentan los resultados de la investigacion realizada con estudiantes universitarios del Grado en Comunicacion Audiovisual sobre la implementacion de cursos SPOC en las clases de contenido practico. La motivacion para realizar este trabajo surge de la disparidad identificada en las aulas del nivel de habilidad de los estudiantes para la operacion de los dispositivos tecnologicos. Los objetivos de la investigacion han sido conocer cuales son para ellos los valores de utilidad de las herramientas de «blended learning» y que competencias profesionales de produccion audiovisual consideran susceptibles de desarrollarse mediante SPOC. La investigacion se realizo de forma simultanea a la imparticion de un curso piloto sobre edicion de video y el analisis se llevo a cabo mediante sesiones grupales de discusion y encuestas individuales. Como resultado se han obtenido una lista cualificada de valores de utilidad y unas propuestas de contenidos para complementar la docencia presencial. Los estudiantes han expresado de forma muy homogenea la conveniencia de disponer de materiales didacticos en linea sobre operacion de los dispositivos tecnologicos mediante unos cursos que esten abiertos y accesibles para poder aprender a «su propio ritmo» y volver a ellos cuando sientan la necesidad de repasar a lo largo de toda la carrera.
Development of compositional and contextual communication of robots by using the multiple timescales dynamic neural network

The current paper introduces neurorobotics experiment on acquisition of complex communicative skills with human via learning. A dynamic neural network model which is characterized by its multiple timescale dynamics characteristics was utilized as a neuronal model for controlling a humanoid robot. In the experimental task, the humanoid robot was trained to generate specific sequential movement patterns as responding to various sequences of imperative gesture patterns demonstrated by the human subjects by following predefined compositional semantic rules. The experimental results showed that (1) the MTRNN can learn to extract compositional semantic rules with generalization in the higher cognitive level, (2) the MTRNN can develop further higher-order cognition capability for controlling the internal contextual processes as situated to on-going task sequences without being provided with cues for explicitly indicating task segmentation points. The analysis on the dynamic characteristics developed in the MTRNN through learning indicated that the aforementioned cognitive mechanisms were achieved by developing adequate functional hierarchy by utilizing the constraint of the multiple timescale property and the topological connectivity imposed on the network configuration.
The Mechanistic and Oxidative Study of Methomyl and Parathion Degradation by Fenton Process

The purpose of this study is to investigate the chemical degradation of the organophosphorus pesticide of parathion and carbamate insecticide of methomyl in the aqueous phase through Fenton process. With the employment of batch Fenton process, the degradation of the two selected pesticides at different pH, initial concentration, humic acid concentration, and Fenton reagent dosages was explored. The Fenton process was found effective to degrade parathion and methomyl. The optimal dosage of Fenton reagents (i.e., molar concentration ratio of H2O2 to Fe) at pH 7 for parathion degradation was equal to 3, which resulted in 50% removal of parathion. Similarly, the optimal dosage for methomyl degradation was 1, resulting in 80% removal of methomyl. This study also found that the presence of humic substances has enhanced pesticide degradation by Fenton process significantly. The mass spectroscopy results showed that the hydroxyl free radical may attack the single bonds with least energy of investigated pesticides to form smaller molecules which is more easily to degrade either through physio-chemical or bilolgical processes. Keywords—Fenton Process, humic acid, methomyl, parathion, pesticides
Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters

Although molecular dynamics (MD) simulations of biomolecular systems often run for days to months, many events of great scientific interest and pharmaceutical relevance occur on long time scales that remain beyond reach. We present several new algorithms and implementation techniques that significantly accelerate parallel MD simulations compared with current state-of-the-art codes. These include a novel parallel decomposition method and message-passing techniques that reduce communication requirements, as well as novel communication primitives that further reduce communication time. We have also developed numerical techniques that maintain high accuracy while using single precision computation in order to exploit processor-level vector instructions. These methods are embodied in a newly developed MD code called Desmond that achieves unprecedented simulation throughput and parallel scalability on commodity clusters. Our results suggest that Desmond's parallel performance substantially surpasses that of any previously described code. For example, on a standard benchmark, Desmond's performance on a conventional Opteron cluster with 2K processors slightly exceeded the reported performance of IBM's Blue Gene/L machine with 32K processors running its Blue Matter MD code
The Cryptococcus neoformans Rho-GDP Dissociation Inhibitor Mediates Intracellular Survival and Virulence

ABSTRACT Rho-GDP dissociation inhibitors (Rho-GDI) are repressors of Rho-type monomeric GTPases that control fundamental cellular processes, such as cytoskeletal arrangement, vesicle trafficking, and polarized growth. We identified and altered the expression of the gene encoding a Rho-GDI homolog in the human fungal pathogen Cryptococcus neoformans and investigated its impact on pathogenicity in animal models of cryptococcosis. Consistent with its predicted function to inhibit and sequester Rho-type GTPases, overexpression of RDI1 results in cytosolic localization of Cdc42. Likely as a result of this finding, RDI1-overexpressing strains exhibited altered morphology compared to that of the wild type, with apparent defects in maintaining proper cell polarity and cytokinesis. RDI1 deletion resulted in increased vacuole size in tissue culture medium and aberrant cell morphology at neutral pH. Maintenance of normal cell morphology is vital for C. neoformans pathogenicity. Accordingly, the rdi1Δ mutant strain also showed reduced intracellular survival in macrophages and severe attenuation of virulence in two murine models of cryptococcosis. This reduction in virulence of the rdi1Δ mutant occurs in the absence of major growth defects in rich medium and with classical virulence-associated phenotypes.
Using brain-based measures to compose teams: How individual capabilities and team collaboration strategies jointly shape performance

Abstract Advances in understanding neural processes open the possibility of using brain-based measures to compose collaborative work teams. Neuroimaging studies have shown that individual differences in patterns of brain activity can predict differences in performance of specific tasks. We extended this finding by examining performance not simply by a single brain, but by pairs of brains. We used measures derived from brain-based studies to compose 100 two-person teams in which members’ roles were either congruent or incongruent with their individual abilities. The assessed abilities are rooted in the visual system, which comprises independent “spatial” and “object” subsystems. The team task required one member to navigate through a virtual maze (a spatial task) and the other to remember “tag” repetitions of complex “greebles” (an object-properties task). Teams in which members’ role assignments were congruent with their abilities performed better than incongruent teams and teams in which both members scored high on only one of the abilities. In addition, verbal collaboration enabled members of incongruent teams to overcome their compositional disadvantage but did not enhance the performance of congruent teams—and actually impaired performance in teams in which both members were adept in only one of the two necessary abilities. The findings show that knowledge about brain systems can not only be used to compose teams, but also provides insights into how teams can best perform.
Aussie women game developers

Women are underrepresented in the digital games industry all over the world. In Australia, women’s level of contribution to game development is much lower than the USA, Canada, and UK. Reviewing literature from the areas of computer science, information technology, and digital games, this study focuses on the impact of social, structural and cultural aspects, and how these factors might influence women choosing a career in the Australian digital games industry. Using a mixed-method, Grounded Theory approach, a large-scale census of Australian digital game studios was conducted, and followed up by semi-structured interviews of a small group of women game developers. Findings reveal that the number of women game developers in Australia has recently increased, and although work culture stereotypes and poor workplace conditions persist overseas, Australian women are not experiencing these issues. However, getting interested in digital game development is still a major obstacle in convincing young women to enroll in game development degrees at university. Once enrolled though, attrition is a problem that has been attributed to teaching styles, lack of confidence and how male peers treat female students in their first year. Those women, who eventually graduate and pursue a career in digital games, more often share the influence of strong parents, male siblings, and enjoyed playing games from a young age.
Small RNAs in early mammalian development: from gametes to gastrulation

Small non-coding RNAs, including microRNAs (miRNAs), endogenous small interfering RNAs (endo-siRNAs) and Piwi-interacting RNAs (piRNAs), play essential roles in mammalian development. The function and timing of expression of these three classes of small RNAs differ greatly. piRNAs are expressed and play a crucial role during male gametogenesis, whereas endo-siRNAs are essential for oocyte meiosis. By contrast, miRNAs are ubiquitously expressed in somatic tissues and function throughout post-implantation development. Surprisingly, however, miRNAs are non-essential during pre-implantation embryonic development and their function is suppressed during oocyte meiosis. Here, we review the roles of small non-coding RNAs during the early stages of mammalian development, from gamete maturation through to gastrulation.
An In Vitro Comparison of Different Diagnostic Methods in Detection of Residual Dentinal Caries

The aim of this study was to investigate the efficiency of different diagnostic methods in detection of residual dentinal caries in excavated cavities. Fifty extracted molar with deep dentinal carious lesions were excavated using a slow-speed handpiece. All cavities were assessed by laser fluorescence(LF) device, electronic caries monitor(ECM), and caries detector dye(CDD) by three independent observers blindly. The measurements were repeated after two weeks. Specimens containing dentin slices 150 μm in thickness were prepared for histological analyses. The existence and absence of carious dentin was determined using a lightmicroscope. The average intraobserver accuracy was 1.00 (perfect agreement) for CDD, 0.86 (excellent agreement) for ECM, and 0.50 (good agreement) for LF. The average interobserver accuracy values were 0.92 (excellent agreement), (0.36 marginal agreement) and 0.48 (good agreement), for CDD, ECM, and LF, respectively. The average specificity was 0.60 for CDD, 73% for ECM, and 0.50 for LF. The average sensitivity was 0.55 for CDD, 0.85 for LF, and 0.47 for ECM. The average accuracy values were 0.53, 0.51, and 0.81 for CDD, ECM, and LF, respectively. LF had the greatest sensitivity and accuracy values of any of the methods tested. As a conclusion, LF device is appeared to most reliable method in detection of remain caries in cavity. However, because of its technical sensitivity it may susceptible to variations in measurements. To pay attention to the rule of usage and repeated measurements can minimize such variations in clinical practice. It was concluded that LF is an improvement on the currently available aids for residual caries detection.
Discovering Human Route-planning Knowledge from Everyday Location Traces

I n t roduction Location-aware systems are steadily increasing in popularity and becoming a standard implementation of handheld devices. Th ese systems provide a low level representation of position, mainly longitude and latitude, in which current and past research is utilized to provide more meaningful information to the user. Services and research such as this are becoming more prevalent due to the low cost of GPS devices and the removal of Selective Availability (noise added to civilian GPS signals). Trip planning applications currently use optimal route or optimal travel time to generate driving directions. Th ese systems neglect changing road conditions , traffi c, and unexpected interference, resulting in awkward and infl exible routes, but generating these types of data using human experts is economically and logistically infeasible. However, human route-planning knowledge can now be ascertained from location traces collected from wearable GPS devices. In this paper, we describe an algorithm for generating weights on a road network based on user GPS traces. Given such a graph, the standard shortest path algorithm can be used to fi nd the best path; the best path would be based on the typical routes of local users. Ba ckground In the last few years, the convergence of location and computing has generated a wide range of innovative and useful applications. Consequently, researchers have begun to reason beyond absolute location and into more meaningful information. GPS provides longitude and latitude coordinates, which are meaningless to humans. Humans, when speaking about location or travel, use a high level form of location (" my home " , " B-dubs " ,
Shape Correspondence for Mixture Gaussian Shape Modeling : A Shape Categorization Approach

Many natural structures exhibit some nonlinear type of shape variation that cannot be accurately described by statistical model that assumes the underlying distribution is Gaussian. In this paper we introduce a new shape correspondence method that organizes a population of shape instances into a set of shape categories. For each shape category a local shape-tree is found where nodes in the local tree represent shape instances with similar structure. These disjoint local shape-trees are combined to form a global shape-tree that is used to correspond the population. A mixture model is then found using the correspondence result in each shape category. Qualitative and quantitative experiments are performed that show the proposed approach better estimates structures that may have nonlinear shape variations over correspondences found by the state-of-theart Minimum Description Length method.
An FES-assisted training strategy combined with impedance control for a lower limb rehabilitation robot

In order to investigate the feasibility of integrating functional electrical stimulation (FES) with robot-based rehabilitation training, this paper proposes an FES-assisted training strategy combined with impedance control for our self-made exoskeleton lower limb rehabilitation robot. This control strategy is carried out in a leg press task. Through impedance control, an active compliance of the robot is established, and the patient's voluntary effort to accomplish the task is inspired. During the training process, the patient's related muscles are applied with FES which provides an extra assistance to the patient. The intensity of the FES is properly chosen aiming to induce a desired active torque which is proportional to the voluntary effort of the patient. This kind of enhancement serves as a positive feedback which reminds the patient of the correct attempt to fulfill the desired motion. FES control is conducted by a combination of neural network-based feedforward controller and a PD feedback controller. The feasibility of this control strategy has been verified in Matlab.
A Novel System of Electrodes Transparent to Ultrasound for Simultaneous Detection of Myoelectric Activity and B-mode Ultrasound Images of Skeletal Muscles Innovative Methodology

A novel system of electrodes transparent to ultrasound for simultaneous detection of myoelectric activity and B-mode ultrasound images of skeletal muscles. Application of two-dimensional surface electrode arrays can provide a means of mapping motor unit action potentials on the skin surface above a muscle. The resulting muscle tissue displacement can be quantified, in a single plane, using ultrasound (US) imaging. Currently , however, it is not possible to simultaneously map spatio-temporal propagation of activation and resulting tissue strain. In this paper, we developed and tested a material that will enable concurrent measurement of two-dimensional surface electromyograms (EMGs) with US images. Specific protocols were designed to test the compatibility of this new electrode material, both with EMG recording and with US analysis. Key results indicate that, for this new electrode material, 1) the electrode-skin impedance is similar to that of arrays of electrodes reported in literature; 2) the reflection of US at the electrode skin interface is negligible; 3) the likelihood of observing missing contacts, short-circuits, and artifacts in EMGs is not affected by the US probe; 4) movement of tissues sampled by US can be tracked accurately. We, therefore, conclude this approach will facilitate multimodal imaging of muscle to provide new spatio-temporal information regarding electromechanical function of muscle. This is relevant to basic physiology-biomechanics of active and passive force transmission through and between muscles, of motor unit spatio-temporal activity patterns, of their variation with architecture and task-related function, and of their adaptation with aging, training-exercise-disuse, neurological disease, and injury. MUSCLE ACTIVE CONTRIBUTION to motor tasks is traditionally revealed by electromyography (EMG). Since Adrian and Bronk (1) first used concentric needle electrodes to characterize the discharge of nerve fibers during breathing in rabbits, the value of EMG measurements has been recognized in a wide range of fields. The degree and the timing of muscle activation, for instance, might be assessed directly with wire or needle electrodes inserted in the muscle volume, or indirectly from the skin surface (24). Whether intramuscular or surface electrodes should be used depends on the circumstances and on the question one wishes to answer. Because of their larger detection volume, surface electrodes provide a more global view of muscle activation, although at the cost of, occasionally, sampling from fibers belonging to muscles other than those of interest (i.e., cross-talk). In the last decade, technological advances have led to the development of detection methods based on multiple electrode …
Orbital Comptonization in accretion disks around black holes

We have performed Monte Carlo simulations of Compton upscattering of low-energy photons in an accretion disk around a Schwarzschild black hole. The photons gain energy from the rotational motion of the electrons in the disk. The upscattering occurs near the black hole horizon, where the flow velocity of the electrons approaches the speed of light. We show that this type of bulk-flow Comptonization can produce power-law X- ray spectra similar to the ones observed in black-hole X-ray transients in the high/soft state, i.e., a soft bump dominating the spectrum below10 keV and a power-law tail with photon index in the range 2{3. In order to reproduce the observed hard to soft flux ratio the disk has to have vertical optical depth above 3 at the last stable orbit. We conclude that the power-law component of the high/soft state of black-hole transients may be due to an intrinsically cool disk extending all the way to the hole, without a separate hot plasma component.
Challenge proposal: verification of refactorings

Automated refactoring tools are an essential part of a software developer's toolbox. They are most useful for gradually improving large existing code bases and it is essential that they work reliably, since even a simple refactoring may affect many different parts of a program, and the programmer should not have to inspect every individual change to ensure that the transformation went as expected. Even extensively tested industrial-strength refactoring engines, however, are fraught with many bugs that lead to incorrect, non-behaviour preserving transformations. We argue that software refactoring tools are a prime candidate for mechanical verification, offering significant challenges but also the prospect of tangible benefits for real-world software development.
Optimizing Flight Selection using Tradeoff Analytics

Decision-making has always been a crucial part in any organization or in fact, in any area of life. A decisionmaker is often faced with multiple objectives while making choices. These choices can be conflicting or similar in nature. It is therefore helpful to have certain tools and techniques to help with informed decision-making. The aim of this project is to explore the usability and effectiveness of IBM Watsons Tradeoff Analytics to help users in the decision-making problem of selecting best flight while making travel plans. In this study we will explore how Tradeoff Analytics can help the users make better decisions from the variety of flight options available, considering multiple criteria while making the choice. These criteria will be set according to the users preferences and can be opposing or similar to each other. The cognitive abilities of Tradeoff Analytics service will provide the users with a set of optimal alternatives and their respective tradeoffs. These tradeoffs and options can then be explored and analyzed and best option can be decided on, thus leading to informed decision-making. The Tradeoff Analytics service that will be used in this study is an IBM Watson service and is offered under the Watson Developer Cloud that has REST APIs and SDKs which implement cognitive computing to solve complex problems.