Miracle-dz/UniFAR-FTUs huggingface dataset:
Gradient assimilation in French cross-word /n/+velar stop sequences

Articulatory studies have revealed cross-linguistic variation in the realization of cross-word nasal+stop sequences. Whereas languages such as Italian and Spanish show largely categorical regressive place assimilation (Kochetov & Colantoni 2011, Celata et al. 2013), English and German alveolar nasals are often characterized by gradient assimilation, modulated by the degree of overlap with the following gesture (Barry 1991, Ellis & Hardcastle 2002, Jaeger & Hoole 2011). The lack of comparable instrumental studies for French may be due to the common assumption that the language lacks nasal place assimilation in general. We investigate here the production of French /n/+/k ɡ/ sequences via electropalatography. Four female speakers of European and Quebecois French wearing custom 62-electrode acrylic palates read the sentences C'est une bonne casquette ‘That's a good cap’ and C'est une bonne galette ‘That's a good tart/cookie’ alongside comparable control sentences involving /n/+/t d/ sequences. For each sequence, assimilation type was determined both qualitatively via visual inspection of the linguopalatal profiles and quantitatively using two contact indices. None of the /n/-tokens exhibited either categorical assimilation (i.e. [ŋk]) or lack of assimilation (i.e. [n(ə)k]). Rather, an intermediate pattern was attested with the nasal involving overlapped coronal and velar gestures ([nn͡ŋ]) and continuous retraction of the constriction. The degree of overlap varied among speakers, extending up to half of the nasal interval. Overall, these French patterns are strikingly different from the categorical processes reported for other Romance languages, yet similar to the gradient assimilation attested in Germanic languages. We conclude by discussing possible sources of these differences.
Optimizing Complexity Measures for fMRI Data: Algorithm, Artifact, and Sensitivity

Introduction Complexity in the brain has been well-documented at both neuronal and hemodynamic scales, with increasing evidence supporting its use in sensitively differentiating between mental states and disorders. However, application of complexity measures to fMRI time-series, which are short, sparse, and have low signal/noise, requires careful modality-specific optimization. Methods Here we use both simulated and real data to address two fundamental issues: choice of algorithm and degree/type of signal processing. Methods were evaluated with regard to resilience to acquisition artifacts common to fMRI as well as detection sensitivity. Detection sensitivity was quantified in terms of grey-white matter contrast and overlap with activation. We additionally investigated the variation of complexity with activation and emotional content, optimal task length, and the degree to which results scaled with scanner using the same paradigm with two 3T magnets made by different manufacturers. Methods for evaluating complexity were: power spectrum, structure function, wavelet decomposition, second derivative, rescaled range, Higuchi’s estimate of fractal dimension, aggregated variance, and detrended fluctuation analysis. To permit direct comparison across methods, all results were normalized to Hurst exponents. Results Power-spectrum, Higuchi’s fractal dimension, and generalized Hurst exponent based estimates were most successful by all criteria; the poorest-performing measures were wavelet, detrended fluctuation analysis, aggregated variance, and rescaled range. Conclusions Functional MRI data have artifacts that interact with complexity calculations in nontrivially distinct ways compared to other physiological data (such as EKG, EEG) for which these measures are typically used. Our results clearly demonstrate that decisions regarding choice of algorithm, signal processing, time-series length, and scanner have a significant impact on the reliability and sensitivity of complexity estimates.
A variational approach to moving contact line hydrodynamics

In immiscible two-phase flows, the contact line denotes the intersection of the fluid–fluid interface with the solid wall. When one fluid displaces the other, the contact line moves along the wall. A classical problem in continuum hydrodynamics is the incompatibility between the moving contact line and the no-slip boundary condition, as the latter leads to a non-integrable singularity. The recently discovered generalized Navier boundary condition (GNBC) offers an alternative to the no-slip boundary condition which can resolve the moving contact line conundrum. We present a variational derivation of the GNBC through the principle of minimum energy dissipation (entropy production), as formulated by Onsager for small perturbations away from equilibrium. Through numerical implementation of a continuum hydrodynamic model, it is demonstrated that the GNBC can quantitatively reproduce the moving contact line slip velocity profiles obtained from molecular dynamics simulations. In particular, the transition from complete slip at the moving contact line to near-zero slip far away is shown to be governed by a power-law partial-slip regime, extending to mesoscopic length scales. The sharp (fluid–fluid) interface limit of the hydrodynamic model, together with some general implications of slip versus no slip, are discussed.
Optimization of Natural Lipstick Formulation Based on Pitaya (Hylocereus polyrhizus) Seed Oil Using D-Optimal Mixture Experimental Design

The D-optimal mixture experimental design was employed to optimize the melting point of natural lipstick based on pitaya (Hylocereus polyrhizus) seed oil. The influence of the main lipstick components—pitaya seed oil (10%–25% w/w), virgin coconut oil (25%–45% w/w), beeswax (5%–25% w/w), candelilla wax (1%–5% w/w) and carnauba wax (1%–5% w/w)—were investigated with respect to the melting point properties of the lipstick formulation. The D-optimal mixture experimental design was applied to optimize the properties of lipstick by focusing on the melting point with respect to the above influencing components. The D-optimal mixture design analysis showed that the variation in the response (melting point) could be depicted as a quadratic function of the main components of the lipstick. The best combination of each significant factor determined by the D-optimal mixture design was established to be pitaya seed oil (25% w/w), virgin coconut oil (37% w/w), beeswax (17% w/w), candelilla wax (2% w/w) and carnauba wax (2% w/w). With respect to these factors, the 46.0 °C melting point property was observed experimentally, similar to the theoretical prediction of 46.5 °C. Carnauba wax is the most influential factor on this response (melting point) with its function being with respect to heat endurance. The quadratic polynomial model sufficiently fit the experimental data.
Prioritizing community behaviors to improve wild dog management in peri-urban areas

ABSTRACT Wild dogs contribute to a range of negative impacts in Australian peri-urban regions. We identified and prioritized 13 behaviors that peri-urban residents could engage in to reduce the impacts of wild dogs in their communities. Key-informant interviews and stakeholder focus groups were used to develop a list of wild dog-management behaviors. On-line surveys with wild dog experts (n = 10) and peri-urban residents (n = 302) were used to create a Behavior Prioritization Matrix (BPM), which ranked the behaviors in terms of projected impact, based on: (a) expert estimates of effectiveness, (b) current adoption levels (penetration), and (c) likelihood of future adoption. BPM analysis indicated that increasing community reporting of wild dogs and their impacts would produce the greatest overall benefits for wild dog management. Behaviors rated as highly effective by experts (e.g., baiting and trapping) had low projected impact given that they were unlikely to be adopted by most residents.
Heuristics for information visualization evaluation

Heuristic evaluation is a well known discount evaluation technique in human-computer interaction (HCI) but has not been utilized in information visualization (InfoVis) to the same extent. While several sets of heuristics have been used or proposed for InfoVis, it is not yet known what kind of heuristics are useful for finding general InfoVis problems. We performed a meta-analysis with the goal of exploring the issues of heuristic evaluation for InfoVis. This meta-analysis concentrates on issues pertaining to the selection and organization of heuristics, and the process itself. For this purpose, we used three sets of previously published heuristics to assess a visual decision support system that is used to examine simulation data. The meta-analysis shows that the evaluation process and results have a high dependency on the heuristics and the types of evaluators chosen. We describe issues related to interpretation, redundancy, and conflict in heuristics. We also provide a discussion of generalizability and categorization of these heuristics.
Synovial pathology in an ovine model of osteoarthritis: effect of intraarticular hyaluronan (Hyalgan).

OBJECTIVES Published scoring methods for quantifying synovitis focus on acute inflammatory parameters, and are unsuitable as outcome measures in experimental surgical models of osteoarthritis (OA). The aim of the present study was to define a modified histopathological scoring system for ovine synovium more suited to the chronic pathology induced by ovine meniscectomy, and to apply it to detect any therapeutic effects following intraarticular injection of hyaluronan (HA) (Hyalgan). METHODS OA was induced in 12 sheep by bilateral lateral meniscectomy, before weekly intraarticular injections of HA or saline vehicle from 16-20 weeks post-operatively, prior to sacrifice at 26 weeks. Six matched sheep were used as controls. Synovial sections were qualitatively scored for hyperplasia, inflammatory infiltrate, fibrosis, and hypervascularity; cell number, depth of fibrosis, and vessel number were also quantified using a graticule. RESULTS OA synovia had significantly elevated scores for inflammatory cell infiltration, subintimal fibrosis, vascularity, and aggregate score relative to controls. HA-treated sheep had significantly lower vascularity score (p=0.015), aggregate score (p=0.007), depth of fibrosis (p=0.003) and vessel number (p=0.048) compared to saline-injected sheep. CONCLUSION This study confirms the presence of a chronic synovitis in this OA model, characterised by subintimal fibrosis and hypervascularity (but only modest infiltrate and minimal intimal hyperplasia), which is partially ameliorated by intraarticular hyaluronate therapy.
An Evaluation of the Role of Sentiment in Second Screen Microblog Search Tasks

The recent prominence of the real-time web is proving both challenging and disruptive for information retrieval and web data mining research. User-generated content on the real-time web is perhaps best epitomised by content on microblogging platforms, such as Twitter. Given the substantial quantity of microblog posts that may be relevant to a user's query at a point in time, automated methods are required to sift through this information. Sentiment analysis offers a promising direction for modelling microblog content. We build and evaluate a sentiment-based filtering system using real-time user studies. We find a significant role played by sentiment in the search scenarios, observing detrimental effects in filtering out certain sentiment types. We make a series of observations regarding associations between document-level sentiment and user feedback, including associations with user profile attributes, and users' prior topic sentiment.
Intelligent protection for embedded generation using active impedance estimation

With the increased use of distributed generation (DG) such as wind generation with characteristics of intermittence and fluctuation, the ability to maintain a reliable and a secure supply with high power quality in power systems is becoming more challenging. The increased use of power electronic converters within loading systems causes further problems for power quality – harmonics etc. It has been shown that knowledge of power system parameters (particularly the net power system impedance to source) at any instant in time is central to addressing these problems. This paper presents a method for real-time power system impedance estimation, which has the potential to enhance the performance of power quality devices such as STATCOM to provide additional capability for grid support and more intelligent protection. Experimental results verify the identification method.
Discriminative Analysis of Lip Motion Features for Speaker Identification and Speech-Reading

There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to lip intensity and/or geometry information, for speaker identification and speech-reading within a unified feature selection and discrimination analysis framework, and addresses two important issues: 1) Is using explicit lip motion information useful, and, 2) if so, what are the best lip motion features for these two applications? The best lip motion features for speaker identification are considered to be those that result in the highest discrimination of individual speakers in a population, whereas for speech-reading, the best features are those providing the highest phoneme/word/phrase recognition rate. Several lip motion feature candidates have been considered including dense motion features within a bounding box about the lip, lip contour motion features, and combination of these with lip shape features. Furthermore, a novel two-stage, spatial, and temporal discrimination analysis is introduced to select the best lip motion features for speaker identification and speech-reading applications. Experimental results using an hidden-Markov-model-based recognition system indicate that using explicit lip motion information provides additional performance gains in both applications, and lip motion features prove more valuable in the case of speech-reading application
Development of a method of ICP algorithm accuracy improvement during shaped profiles and surfaces control

In this paper we propose a method of improvement of operating accuracy of iterative closest point algorithm used for metrology problems solving when determining a location deviation. Compressor blade profiles of a gas turbine engine (GTE) were used as an object for application of the method of deviation determining. It is proposed to formulate the problem of the best alignment in the developed method as a multi- objective problem including criteria of minimum of squared distances, normal vectors differences and depth of camber differences at corresponding points of aligned profiles. Variants of resolving the task using an integral criterion including the above-mentioned were considered. Optimization problems were solved using a quasi- Newton method of sequential quadratic programming. The proposed new method of improvement of the registration algorithm based on geometric features showed greater accuracy in comparison with the discussed methods of optimization of a distance between fitting points, especially if a small quantity of measurement points on the profiles was used.
Main challenges in practical applications of cognitive radio

Facing more and more serious scarcity of radio resources in today's society, cognitive radio offers a great solution from the theoretical level. But in the process of converting theoretical research into practical application, cognitive radio still has lots of inevitable problems. In this paper, demonstration about problems the cognitive radio encounters in practical applications is made from three aspects of spectrum sensing, spectrum handoff and information security. The analysis of the reasons why the problems occur and summary of present solutions are also introduced in the article.
A Dynamic 3D Graphical Representation for RNA Structure Analysis and Its Application in Non-Coding RNA Classification

With the development of new technologies in transcriptome and epigenetics, RNAs have been identified to play more and more important roles in life processes. Consequently, various methods have been proposed to assess the biological functions of RNAs and thus classify them functionally, among which comparative study of RNA structures is perhaps the most important one. To measure the structural similarity of RNAs and classify them, we propose a novel three dimensional (3D) graphical representation of RNA secondary structure, in which an RNA secondary structure is first transformed into a characteristic sequence based on chemical property of nucleic acids; a dynamic 3D graph is then constructed for the characteristic sequence; and lastly a numerical characterization of the 3D graph is used to represent the RNA secondary structure. We tested our algorithm on three datasets: (1) Dataset I consisting of nine RNA secondary structures of viruses, (2) Dataset II consisting of complex RNA secondary structures including pseudo-knots, and (3) Dataset III consisting of 18 non-coding RNA families. We also compare our method with other nine existing methods using Dataset II and III. The results demonstrate that our method is better than other methods in similarity measurement and classification of RNA secondary structures.
Imaging Cells in the Developing Nervous System with Retrovirus Expressing Modified Green Fluorescent Protein

To visualize the movements of cells and their processes in developing vertebrates, we constructed replication-incompetent retroviral vectors encoding green fluorescent protein (GFP) that can be detected as a single integrated copy per cell. To optimize GFP expression, the CMV enhancer and avian beta-actin promoter were incorporated within a retrovirus construct to drive transcription of redshifted (F64L, S65T) and codon-modified GFP (EGFP), EGFP tagged with GAP-43 sequences targeting the GFP to the cell membrane, or EGFP with additional mutations that increase its ability to fold properly at 37 degrees C (S147P or V163A, S175G). We have used these viruses to efficiently mark and follow the developmental progression of a large population of cells in rat neocortex and whole avian embryos. In the chick embryo, the migration and development of GFP-marked neural crest cells were monitored using time-lapse videomicroscopy. In the neocortex, GFP clearly delineates the morphology of a variety of neuronal and glial phenotypes. Cells expressing GFP display normal dendritic morphologies, and infected cells persist into adulthood. Cortical neurons appear to form normal local axonal and long-distance projections, suggesting that the presence of cytoplasmic or GAP-43-tagged GFP does not significantly interfere with normal development.
Organising Patterns into Languages Towards a Pattern Language for Object Oriented Design

Since the publication of the Design Patternsbook, a large number of design patterns have been identified and codified. Unfortunately, these patterns are mostly organised in an ad hoc fashion, making it hard for programmers to know which pattern to apply to any particular problem. We have organised a large number of existing object oriented design patterns into a pattern language, by analysing the patterns and the relationships between them. Organising patterns into languages has the potential to make large collections of patterns easier to understand and to use.
Pruning for Monte Carlo Distributed Reinforcement Learning in Decentralized POMDPs

Decentralized partially observable Markov decision processes (Dec-POMDPs) offer a powerful modeling technique for realistic multi-agent coordination problems under uncertainty. Prevalent solution techniques are centralized and assume prior knowledge of the model. Recently a Monte Carlo based distributed reinforcement learning approach was proposed, where agents take turns to learn best responses to each other’s policies. This promotes decentralization of the policy computation problem, and relaxes reliance on the full knowledge of the problem parameters. However, this Monte Carlo approach has a large sample complexity, which we address in this paper. In particular, we propose and analyze a modified version of the previous algorithm that adaptively eliminates parts of the experience tree from further exploration, thus requiring fewer samples while ensuring unchanged confidence in the learned value function. Experiments demonstrate significant reduction in sample complexity – the maximum reductions ranging from 61% to 91% over different benchmark Dec-POMDP problems – with the final policies being often better due to more focused exploration.
Development and evaluation of add-on end-effector for linear power assist unit with variable assist gain

This paper proposes a linear power assist unit to be simply designed by using an add-on end-effector and gives a controller design for the unit explicitly taking into consideration mechanical impedances of both a human operator and environment. The proposed end-effector transmits assisting force to the environment via a pair of assisting springs, and the displacement of the assisting springs is controlled to generate a desirable power assisting according to the force applied by the operator. In the proposed system, the assist gain, i.e., the ratio of the sum of the human-applied force and the assisting force to the human-applied force, can be online changed so as to easily adjust a stress loading, and it could be helpful in rehabilitations to tune the load depending on the degree of recovery. A prototype of the proposed power assist unit has been developed and was evaluated from viewpoints of both the time and frequency domains. Experimental results showed that the prototype has robustly worked well against perturbations of the environment, keeping the power assist control bandwidth about 1 to 3 Hz, and the validity of the variable assist gain control has also confirmed.
Cooperation control in Parallel SAT Solving: a Multi-armed Bandit Approach

In recent years, Parallel SAT solvers have leveraged with the so called Parallel Portfolio architecture. In this setting, a collection of independent Conflict-Directed Clause Learning (CDCL) algorithms compete and cooperate through Clause Sharing. However, when the number of cores increases, systematic clause sharing between CDCLs can slow down the search performance. Previous work has shown how the efficiency of the approach can be improved through controlling dynamically the amount of information shared by the cores [Hamadi et al., IJCAI09], specifically the allowed length of the shared clauses. In the present paper, a new approach is used to control the cooperation topology (pairs of units able to exchange clauses). This approach, referred to as Bandit Ensemble for parallel SAT Solving (BESS), relies on a multi-armed bandit formalization of the cooperation choices. BESS is empirically validated on the recent 2012 SAT challenge benchmark.
How experience affects assessment – a longitudinal study of assessment of university students’ essays

ABSTRACT The study shows how experience changes the way examiners assess students’ essays. Using a large number of written assessments, 192 examiners were followed over a period of five years, and the contents of their assessments were analysed both quantitatively and qualitatively. Multilevel regression analysis revealed that, with experience, examiners tended to make more positive remarks and provide more instructions. Qualitative analysis of the assessments showed that, with experience, some examiners tended to use less menu-marking and write more freely, providing instructions for the students rather than limiting themselves to evaluative text only. The assumption that it would be harder to govern examiners with more experience found no support in our study.