Miracle-dz/UniFAR-FTUs huggingface dataset:
Language Development of Individuals Who Require Aided Communication: Reflections on State of the Science and Future Research Directions

Abstract Language acquisition theories differ in the importance they assign to production as a learning mechanism. This review summarizes some of the theoretical issues linked to this debate and considers their implications for children with severe speech and physical impairments. The unique aspects of the language-learning contexts of these children are explored. Drawing largely on papers published within the journal Augmentative and Alternative Communication, this review summarizes features of language development that have been described over the past 3 decades and considers how these findings might illuminate our understanding of language development across both spoken and aided modalities. Implications for assessment, intervention and for further research are suggested.
Neuropsychological Functioning of Adults with Attention Deficit Hyperactivity Disorder

The neuropsychological functioning of adults with Attention Deficit Hyperactivity Disorder (ADHD) was compared to that of healthy controls and individuals with mild psychiatric disorders including attentional complaints. Thirty adults in each group were examined on the Conners' Continuous Performance Test (CPT) and measures of attention, executive function, psychomotor speed, and arithmetic skills. The ADHD group performed lower than healthy controls on most measures. However when compared to the psychiatric group, the performances of the ADHD group were not significantly lower on any of the measures. The predictive power of the tests was poor in discriminating ADHD from psychiatric disorder. Implications for the clinical diagnosis of ADHD are discussed.
Why Does Ethnicity Affect Prevalence of Gestational Diabetes? The Underwater Volcano Theory

To study why gestational diabetes (GDM) is more common in some ethnic groups than others, we tested the hypothesis that GDM is more common in people who are temporally closer to developing non‐insulin‐dependent (Type 2) diabetes mellitus (NIDDM). The prevalence of GDM and the mean age of affected women in each major ethnic group were determined. From our database of NIDDM 6052 patients, the mean age of onset in each ethnic group was calculated and the mean difference between age of developing GDM and age of developing NIDDM derived (NIDDM–GDM age gap). This age gap was used to adjust for the susceptibility to GDM of each group. The overall prevalence of GDM was 6.7 % (CI 6.0 %–7.4 %). In Anglo‐Celtic women it was 3.0 % (CI 2.3 %–3.7 %). For the other ethnic groups the prevalence and odds ratio (OR) were: Chinese (15.0 % CI 11.8 %–18.2 % OR 5.6), Vietnamese (9.6 % CI 6.6 %–12.5 % OR 3.6), Indian (16.7 % CI 9.8 %–23.5 % OR 6.4), Arabic (7.3 % CI 4.6 %–10.1 % OR 2.5) and Aborigines (10.1 % CI 3.8 %–16.4 % OR 3.7). The OR for susceptibility to GDM did not change after adjustment for BMI and maternal age and it correlated significantly with the NIDDM–GDM age gap (r = −0.85; p = 0.03). However, it fell substantially after adjustment for NIDDM‐GDM age gap. For women of different ethnic origins there is a difference in the time gap between their pregnancies and the time at which they would on average be expected to develop diabetes. This difference may be an important factor underlying the higher prevalence of GDM in some ethnic populations.
3D Shape Reconstruction by Using Vanishing Points

This paper investigates the quantitative reconstruction of the 3D structure of a scene from a line drawing, by using the geometrical constraints provided by the location of vanishing points. The additional information on vanishing points allows the design of an algorithm which has several advantages with respect to the usual approach based on a reduction to linear programming (Sugihara, 1982). These advantages range from a lower computational complexity to error tolerance and exact reconstruction of the 3D-geometry of the objects. These features make the algorithm a useful tool for the quantitative analysis of real-world images, which is useful for several tasks from scene understanding to automatic vehicle guidance.
Integrating Vision and Touch for Object Recognition Tasks

A robotic system for object recognition is described that uses passive stereo vision and active exploratory tactile sensing. The complementary nature of these sensing modalities allows the system to discover the underlying 3-D structure of the objects to be recognized. This structure is embodied in rich, hierarchical, viewpoint-independent 3-D models of the objects which include curved surfaces, concavities and holes. The vision processing provides sparse 3-D data about regions of interest that are then actively explored by the tactile sensor mounted on the end of a six-degree-of-freedom manipulator. A robust, hierarchical procedure has been developed to inte grate the visual and tactile data into accurate 3-D surface and feature primitives. This integration of vision and touch provides geometric measures of the surfaces and features that are used in a matching phase to find model objects that are consistent with the sensory data. Methods for verification of the hypothesis are presented, including the sensing of visually occluded areas with the tactile sensor. A number of experi ments have been performed using real sensors and real, noisy data to demonstrate the utility of these methods and the ability of such a system to recognize objects that would be difficult for a system using vision alone.
A survey of left‐handed polyproline II helices

Left‐handed polyproline II helices (PPII) are contiguous elements of protein secondary structure in which the ø and Ψ angles of constituent residues are restricted to around –75° and 145°, respectively. They are important in structural proteins, in unfolded states and as ligands for signaling proteins. Here, we present a survey of 274 nonhomologous polypeptide chains from proteins of known structure for regions that form these structures. Such regions are rare, but the majority of proteins contain at least one PPII helix. Most PPII helices are shorter than five residues, although the longest found contained 12 amino acids. Proline predominates in PPII, but Gln and positively charged residues are also favored. The basis of Gln's prevalence is its ability to form an i, i + 1 side‐chain to main‐chain hydrogen bond with the backbone carbonyl oxygen of the proceeding residue; this helps to fix the Ψ angle of the Gln and the ø and Ψ of the proceeding residue in PPII conformations and explains why Gln is favored at the first position in a PPII helix. PPII helices are highly solvent exposed, which explains why apolar amino acids are disfavored despite preferring this region of ø/Ψ space when in isolation. PPII helices have perfect threefold rotational symmetry and within these structures we find significant correlation between the hydrophobicity of residues at i and i + 3; thus, PPII helices in globular proteins can be considered to be amphipathic.
Robust Image Matching using Statistical Modeling and Geometric Similarity

We propose a robust image matching method using statistical modeling and clustering of geometric similarity between matching-pairs. Local feature matching is an uncertain process which may provide incorrect matches due to some causes that include among other factors, the uncertainly in feature location. Since the statistical modeling of the Log Distance Ratio (LDR) for outliers are significantly different from those of inliers. Although fast and efficiently, LDR has some weakness, especially related to the inability to take into consideration the uncertainly in the feature location and performance degrades when strong perspective transform. We add a method that clustering the similarity of geometric relationship. The proposed method robustly matches images, even with various kinds of transformation.
Simultaneous Fuzzy Clustering with Multiple Correspondence Analysis

Multiple correspondence analysis is a simple method for analyzing multivariate categorical data. The method has been extended to generate cluster structures between respondents and variable categories by combining multiple correspondence analysis with twoway clustering (Hwang and Dillon, 2010). However, because clear boundaries are not idenrifiable in many real-world clustering problems, hard classification methods such as k-means clustering appear overly restricted. In this study, we propose a method simultaneously combines multiple correspondence analysis with two-way fuzzy c-means clustering, which is an overlapping clustering method. We represent the classification structures of respondents and categorical variables as fuzziness and hardness, respectively. To facilitate the interpretation of the relationships between variable categories and the cluster structure of respondents, the method provides a low-dimensional map that simultaneously displays the object scores of respondents, variable categories, and cluster centroids. The utility of the proposed method in real data is assessed by comparing the results of our simultaneous approach with those of multiple correspondence analysis.
Exploring the selectivity of a ligand complex with CDK2/CDK1: a molecular dynamics simulation approach

Cyclin‐dependent kinases (CDKs) are core components of the cell cycle machinery that govern the transition between phases during cell cycle progression. Abnormalities in CDKs activity and regulation are common features of cancer, making CDK family members attractive targets for the development of anticancer drugs. Their inhibitors have entered in clinical trials to treat cancer. Very recently, Heathcote et al. (J. Med. Chem. 2010, 53:8508–8522) have found a ligand BS194 that has a high affinity with CDK2 (IC50 = 3 nm) but shows low affinity with CDK1 (IC50 = 30 nm). To understand the selectivity, we used homology modeling, molecular docking, molecular dynamics, and free‐energy calculation to analyze the interactions. A rational three‐dimensional model of the CDK1/BS194 complex is built. We found that Leu83 is a key residue that recognizes BS194 more effectively with CDK2 with good binding free energies rather than CDK1. Energetic analysis reveals that van der Waals interaction and non‐polar contributions to solvent are favorable in the formation of complexes and amine group of the ligand, which plays a crucial role for binding selectivity between CDK2 and CDK1. Copyright © 2012 John Wiley & Sons, Ltd.
Improved LFIAs for highly sensitive detection of BNP at point-of-care

Heart failure (HF) has become a major cause of morbidity and mortality with a significant global economic burden. Although well-established clinical tests could provide early diagnosis, access to these tests is limited in developing countries, where a relatively higher incidence of HF is present. This has prompted an urgent need for developing a cost-effective, rapid and robust diagnostic tool for point-of-care (POC) detection of HF. Lateral flow immunoassay (LFIA) has found widespread applications in POC diagnostics. However, the low sensitivity of LFIA limits its ability to detect important HF biomarkers (e.g., brain natriuretic peptide [BNP]) that are normally present in low concentration in blood. To address this issue, we developed an improved LFIA by optimizing the gold nanoparticle (GNP)–antibody conjugate conditions (e.g., the conjugate pH and the amount of added antibody), the diameter of GNP and the concentration of antibody embedded on the test line and modifying the structure of test strip. Through these improvements, the proposed test strip enabled the detection of BNP down to 0.1 ng/mL within 10–15 min, presenting ~15-fold sensitivity enhancement over conventional lateral flow assay. We also successfully applied our LFIA in the analysis of BNP in human serum samples, highlighting its potential use for clinical assessment of HF. The developed LFIA for BNP could rapidly rule out HF with the naked eye, offering tremendous potential for POC test and personalized medicine.
A laboratory evaluation to determine the compatibility of microbiological control agents with the pollinator Bombus terrestris.

BACKGROUND This study was undertaken to identify any potential adverse side effects of the use of seven microbiological control agents (MCAs) on the bumblebee, Bombus terrestris L. , in the context of combined use in integrated pest management (IPM). AQ10 (Ampelomyces quisqualis), Binab-T-vector (Hypocrea parapilulifera + T. atroviride; 1/1), Prestop-Mix (Gliocladium catenulatum J1446), Serenade (Bacillus subtilis QST713), Trianum-P (Trichoderma harzianum T22), Botanigard (Beauveria bassiana GHA) and Granupom (Cydia pomonella granulovirus), comprising five biofungicides and two bioinsecticides, were investigated. Bumblebee workers were exposed under laboratory conditions to each MCA at its maximum field recommended concentration (MFRC) via three different routes of exposure: dermal contact and orally via either treated sugar water or pollen. RESULTS The tested MCAs were found to be safe for workers of B. terrestris, with the exception of Botanigard and Serenade. Exposure to Botanigard via contact at its MFRC caused 92% mortality after 11 weeks, while the 1/10 MFRC killed 46% of exposed workers. For Serenade, topical contact and oral delivery via sugar water resulted in 88 and 100% worker mortality respectively. With lower concentrations (1/2, 1/5 and 1/10 MFRC) the toxicity decreased, but the effect depended on the route of exposure. In addition to lethal effects, nests were also evaluated for sublethal effects after treatment with the seven MCAs at their respective MFRCs over 11 weeks. In these bioassays, only Botanigard and Serenade gave rise to a significant (P < 0.05) decrease in drone production. Sublethal effects on foraging behaviour were also evaluated, and only Botanigard at its MFRC delivered via treated sugar water induced negative effects. CONCLUSION The results demonstrated that most of the MCAs tested can be considered safe for use in combination with B. terrestris, based on the International Organisation for Biological Control of Noxious Animals and Plants (IOBC) classification. However, some can be harmful, such as the biofungicide Serenade and the bioinsecticide Botanigard. Therefore, it is recommended that all should be tested before use in combination with pollinators. In this context, it is also advisable that these MCAs should be evaluated in more realistic field situations for the assessment of potentially deleterious effects on foraging behaviour.
Snowflake Divertor Experiments in the DIII-D, NSTX, and NSTX-U Tokamaks Aimed at the Development of the Divertor Power Exhaust Solution

Experimental results from the National Spherical Torus Experiment (NSTX), a medium-size spherical tokamak with a compact divertor, and DIII-D, a large conventional aspect ratio tokamak, demonstrate that the snowflake (SF) divertor configuration may provide a promising solution for mitigating divertor heat loads and target plate erosion compatible with core H-mode confinement in the future fusion devices, where the standard radiative divertor solution may be inadequate. In NSTX, where the initial high-power SF experiment was performed, the SF divertor was compatible with H-mode confinement, and led to the destabilization of large Edge Localized Modes (ELMs). However, a stable partial detachment of the outer strike point was also achieved where inter-ELM peak heat flux was reduced by factors 3-5, and peak ELM heat flux was reduced by up to 80% (see standard divertor). The DIII-D studies show the SF divertor enables significant power spreading in attached and radiative divertor conditions. Results include: compatibility with the core and pedestal, peak inter-ELM divertor heat flux reduction due to geometry at lower ne, and ELM energy and divertor peak heat flux reduction, especially prominent in radiative D2-seeded SF divertor, and nearly complete power detachment and broader radiated power distribution in the radiative D2-seeded SF divertor at PSOL = 3 - 4 MW. A variety of SF configurations can be supported by the divertor coil set in NSTX Upgrade. Edge transport modeling with the multifluid edge transport code UEDGE shows that the radiative SF divertor can successfully reduce peak divertor heat flux for the projected PSOL ≃ 9 MW case. The radiative SF divertor with carbon impurity provides a wider ne operating window, 50% less argon is needed in the impurity-seeded SF configuration to achieve similar qpeak reduction factors (see standard divertor).
Behavior Recognition in Mouse Videos using Contextual Features Encoded by Spatial-temporal Stacked Fisher Vectors

Manual measurement of mouse behavior is highly labor intensive and prone to error. This investigation aims to efficiently and accurately recognize individual mouse behaviors in action videos and continuous videos. In our system each mouse action video is expressed as the collection of a set of interest points. We extract both appearance and contextual features from the interest points collected from the training datasets, and then obtain two Gaussian Mixture Model (GMM) dictionaries for the visual and contextual features. The two GMM dictionaries are leveraged by our spatial-temporal stacked Fisher Vector (FV) to represent each mouse action video. A neural network is used to classify mouse action and finally applied to annotate continuous video. The novelty of our proposed approach is: (i) our method exploits contextual features from spatiotemporal interest points, leading to enhanced performance, (ii) we encode contextual features and then fuse them with appearance features, and (iii) location information of a mouse is extracted from spatio-temporal interest points to support mouse behavior recognition. We evaluate our method against the database of Jhuang et al. [7] and the results show that our method outperforms several state-of-the-art approaches.
Intensional specifications of security protocols

It is often difficult to specify exactly what a security protocol is intended to achieve, and there are many example of attacks on protocol which have been proved to satisfy the 'wrong', or too unreal a specification. Contrary to the usual approach of attempting to capture what it is that protocol achieves in abstract terms, we propose a readily automatable style of specification which simply asserts that a node can only complete its part in a protocol run if the pattern of messages anticipated by the designer has occurred. While this intensional style of specification does not replace more abstract ones such as confidentiality, it does appear to preclude a wide range of the styles of attack that are hardest to exclude by other means.
High-level energy estimation of template-based QDI asynchronous circuits based on transition counting

This paper introduces an innovative high-level method to estimate energy consumption of a well known family of asynchronous circuits at CSP level, therefore removing the need for performing time consuming SPICE simulation. Our method is based on transition count and helps the PCHB/PCFB template based QDI asynchronous circuit designers to have an early estimation of power with the accuracy of more than 80%. This estimation, obtained from commercial functional simulators, may lead to power optimization of the circuit in high levels of design.
Size and Shape in Biology

Tom Colton received a B.A. in biology from the State University of New York at Binghamton, in 1977 and a Ph.D. in Zoology from Duke University in 1983. Since then he has taught at Duke University, the University of North Carolina at Greensboro, and Wake Forest University. As a senior lecturer at the University of Chicago since 1991, he teaches labs in biological diversity, physiology, and biomechanics, lectures in a biology course for non-majors, and directs the web site for the undergraduate biology program.
Research utilization and evidence-based practice among Saskatchewan massage therapists

Abstract While massage therapy (MT) is an increasingly used health care service with a growing evidence base, there is insufficient information about the extent to which MT practice is evidence-based. The purpose of this study was to provide a comprehensive view of Saskatchewan MT’s research utilization to inform the development of evidence-based massage therapy practice. The main objectives of the study were to describe MT’s perceptions of research, their appraised self-efficacy in research literacy and to identify the characteristic of practitioners who use research. Using a survey design all 815 registered members of the Massage Therapist Association of Saskatchewan were invited to complete a mail-out questionnaire. A total of 333 questionnaires were completed and returned for a 41% response rate. Univariate and logistic regression analysis was conducted using SPSS 17.0. While overall perceptions of research were positive, self-efficacy in research literacy was low and research utilization was limited. Characteristics associated with research use included referring to online research databases and peer-reviewed journals, belief that practice should be based on research, and 20 or greater hours per week of practice. Provincial regulatory status may be the first step to quality service delivery and research literacy training and support is needed for practitioners.
Review on Multilabel Classification Algorithms Ms .

Multilabel classification is a framework in which each input data in training data set can be related to more than one class labels simultaneously. The goal of multilabel classification is to produce set of labels for unseen instances by analyzing training dataset. This paper presents fundamentals of multilabel classification, some multilabel classification algorithms and evaluation metrics.
Test-retest reliability of a group-administered paper-pencil measure of delay discounting.

The purpose of this study was to determine the reliability of an easily administered paper-pencil temporal discounting task modeled loosely on the hypothetical money choice task (Rachlin, Raineri, & Cross, 1991). Our group-administered task used 2 descriptions of discounting, the slope constant (k) of the hyperbolic function V = A/(1 + kD) and the area under the curve (AUC). The task was initially administered to 387 (163 men, 188 women, and 35 unspecified gender) introductory psychology students in groups ranging in size from 15 to 45. Six weeks later, 299 students (131 men and 168 women) repeated the task in groups ranging from 15 to 30. At each test time, the data from participants who met specified discounting criteria (about 85%) were fit well with the hyperbolic function (mean r(2) = . 90). The test-retest correlation for logk was r = . 64; for AUC scores, it was r = . 70, with a correlation of r = -. 96 between logk and AUC scores at Test 1. The (dislike for) Cognitive Complexity and Cognitive Instability subscales of the Barratt Impulsivity Scales, Version 11, administered only at the retest correlated with k values (r = .20, p = .001, and r = .179, p = .003), and women discounted more than men (p < .001) at both test times. The results are discussed in terms of the utility of the procedure and a detailed comparison of k and AUC measures of discounting.