Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluoride Release and Recharge from Different Materials Used as Fissure Sealants

Objectives: Fluoride release/recharge properties of fissure sealants are important for their long-term inhibition of caries. This study was conducted to examine the relationship between fluoride release and recharge of pit-and-fissure sealants. Methods: Specimens were prepared from 5 different sealant materials: Fissurit F, a conventional resin; Fuji VII, a glass-ionomer cement (GIC); Fuji II LC, a resin-modified GIC; Ionosit, a polyacid-modified composite resin (PMRC); and Aelite Flo, a flowable composite resin. Specimens stored in a polyethylene test tube containing 5.0 ml ultrapure water. On day 21, specimens were exposed to 1.23% APF gel. Fluoride release was measured using a fluoride-specific ion electrode at 1–7, 14, 21, 22, 28, 35 and 42 days. Results: The glass-ionomer based sealants Fuji VII and Fuji II LC had significantly higher fluoride release than the other materials at all times tested (P<.05). Fluoride release of all materials tested increased following exposure to APF gel (P<.05). Conclusions: Within the limitations of this short-term study, glass ionomer-based sealants were shown to have higher initial fluoride release as well as higher fluoride recharge capacity than other sealants.
Foreign Currency Borrowing by Small Firms

We examine the firm- and country-level determinants of the currency denomination of small business loans. We first model the choice of loan currency in a framework which features a trade-off between lower cost of debt and the risk of firm-level distress costs, and also incorporates the impact of information asymmetry between banks and firms. When foreign currency funds come at a lower interest rate, all foreign currency earners as well as those local currency earners with high revenues and low distress costs choose foreign currency loans. When the banks have imperfect information on the currency and level of firm revenues, even more local earners switch to foreign currency loans, as they do not bear the full cost of the corresponding credit risk. We then test the implications of our model by using a 2005 survey with responses from 9,098 firms in 26 transition countries. The survey contains details on 3,105 recent bank loans. At the firm level, our findings suggest that firms with foreign currency income and assets are more likely to borrow in a foreign currency. In contrast, firm-level distress costs and financial transparency affect the currency denomination only weakly. At the country level, the interest rate advantages of foreign currency funds and the exchange rate volatility do not explain the foreign currency borrowing in our sample. However, foreign bank presence, weak corporate governance and the absence of capital controls encourage foreign currency borrowing. All in all, we cannot confirm that "carry-trade behavior" is the key driver of foreign currency borrowing by small firms in transition economies. Our results do, however, support the conjecture that banking-sector structures and institutions that aggravate information asymmetries may facilitate foreign currency borrowing.
Augmenting reality in mobile substrates On the design of computer support for process control

The paper investigates augmented reality as a perspective on the design of computer support for process control in a distributed environment. Based on empirical studies of work in a wastewater treatment plant, three technical approaches on augmented reality — augmenting the user; the object of work; and the environment — are examined in terms of a collection of design scenarios . We conclude that these approaches when used, as metaphors rather than a consistent theoretical framework, may inform design of mobile support for process control work.
SENTIMENT CLASSIFICATION of MOVIE REVIEWS USING CONTEXTUAL VALENCE SHIFTERS

We present two methods for determining the sentiment expressed by a movie review. The semantic orientation of a review can be positive, negative, or neutral. We examine the effect of valence shifters on classifying the reviews. We examine three types of valence shifters: negations, intensifiers, and diminishers. Negations are used to reverse the semantic polarity of a particular term, while intensifiers and diminishers are used to increase and decrease, respectively, the degree to which a term is positive or negative. The first method classifies reviews based on the number of positive and negative terms they contain. We use the General Inquirer to identify positive and negative terms, as well as negation terms, intensifiers, and diminishers. We also use positive and negative terms from other sources, including a dictionary of synonym differences and a very large Web corpus. To compute corpus‐based semantic orientation values of terms, we use their association scores with a small group of positive and negative terms. We show that extending the term‐counting method with contextual valence shifters improves the accuracy of the classification. The second method uses a Machine Learning algorithm, Support Vector Machines. We start with unigram features and then add bigrams that consist of a valence shifter and another word. The accuracy of classification is very high, and the valence shifter bigrams slightly improve it. The features that contribute to the high accuracy are the words in the lists of positive and negative terms. Previous work focused on either the term‐counting method or the Machine Learning method. We show that combining the two methods achieves better results than either method alone.
The String landscape, black holes and gravity as the weakest force

We conjecture a general upper bound on the strength of gravity relative to gauge forces in quantum gravity. This implies, in particular, that in a four-dimensional theory with gravity and a U(1) gauge field with gauge coupling g, there is a new ultraviolet scale Λ = gMPl, invisible to the low-energy effective field theorist, which sets a cutoff on the validity of the effective theory. Moreover, there is some light charged particle with mass smaller than or equal to Λ. The bound is motivated by arguments involving holography and absence of remnants, the (in) stability of black holes as well as the non-existence of global symmetries in string theory. A sharp form of the conjecture is that there are always light ``elementary'' electric and magnetic objects with a mass/charge ratio smaller than the corresponding ratio for macroscopic extremal black holes, allowing extremal black holes to decay. This conjecture is supported by a number of non-trivial examples in string theory. It implies the necessary presence of new physics beneath the Planck scale, not far from the GUT scale, and explains why some apparently natural models of inflation resist an embedding in string theory.
Protocol State Fuzzing of TLS Implementations

We describe a largely automated and systematic analysis of TLS implementations by what we call 'protocol state fuzzing': we use state machine learning to infer state machines from protocol implementations, using only blackbox testing, and then inspect the inferred state machines to look for spurious behaviour which might be an indication of flaws in the program logic. For detecting the presence of spurious behaviour the approach is almost fully automatic: we automatically obtain state machines and any spurious behaviour is then trivial to see. Detecting whether the spurious behaviour introduces exploitable security weaknesses does require manual investigation. Still, we take the point of view that any spurious functionality in a security protocol implementation is dangerous and should be removed. We analysed both server- and client-side implementations with a test harness that supports several key exchange algorithms and the option of client certificate authentication. We show that this approach can catch an interesting class of implementation flaws that is apparently common in security protocol implementations: in three of the TLS implementations analysed new security flaws were found (in GnuTLS, the Java Secure Socket Extension, and OpenSSL). This shows that protocol state fuzzing is a useful technique to systematically analyse security protocol implementations. As our analysis of different TLS implementations resulted in different and unique state machines for each one, the technique can also be used for fingerprinting TLS implementations.
Anomalies of asymmetry of pyramidal cell density and structure in dorsolateral prefrontal cortex in schizophrenia

Background Studies suggest that neuronal density in left dorsolateral prefrontal cortex is increased in schizophrenia. Aims To replicate these findings and extend them to both hemispheres. Method Neuronal density, size and shape were estimated in the prefrontal cortex (Brodmann area 9) of the left and right hemispheres of brains taken postmortem from 10 people with schizophrenia and 10 without mental illness (6 men, 4 women in both groups). Results Overall neuronal density (individually corrected for shrinkage) did not differ between the groups. In the control brains, density was generally greater in the left than the right hemisphere, the reverse was seen in the schizophrenia brains; this loss or reversal of asymmetry was most significant in cortical layer 3. Pyramidal neurons in this cell layer were significantly larger on the left and more spherical in shape than on the right side in control brains, but size and shape did not differ between the two sides in schizophrenia. Non-pyramidal and glial cell densities were unchanged. Conclusions We failed to find an increase in neuronal density, but found evidence at a cellular level of loss or reversal of asymmetry, consistent with the hypothesis of a primary change in the relative development of areas of heteromodal association cortex in the two hemispheres.
Facial expression recognition teaching to preschoolers with autism: a natural user interface approach

The recognition of facial expressions is important for the perception of emotions. Understanding emotions is essential in human communication and social interaction. Children with autism have been reported to exhibit deficits in the recognition of affective expressions. Their difficulties in understanding and expressing emotions lead to inappropriate behavior derived from their inability to interact adequately with other people. Those deficits seem to be rather permanent in individuals with autism so intervention tools for improving those impairments are desirable. Educational interventions for teaching emotion recognition from facial expressions should occur as early as possible in order to be successful and to have a positive effect. It is claimed that Serious Games can be very effective in the areas of therapy and education for children with autism. However, those computer interventions require considerable skills for interaction. Before the age of 6, most children with autism do not have such basic motor skills in order to manipulate a mouse or a keyboard. Our approach takes account of the specific characteristics of preschoolers with autism and their physical inabilities. By creating an educational computer game, which provides physical interaction by employing natural user interface (NUI), we aim to support early intervention and to foster facial expression learning.
IV-deficient mice running in Ca 2 + / calmodulin-dependent protein kinase Skeletal muscle adaptation in response to voluntary

[PDF] [Full Text] [Abstract] , July 1, 2007; 293 (1): E286-E292. Am J Physiol Endocrinol Metab T. E. Jensen, A. J. Rose, Y. Hellsten, J. F. P. Wojtaszewski and E. A. Richter muscle Caffeine-induced Ca2+ release increases AMPK-dependent glucose uptake in rodent soleus [PDF] [Full Text] [Abstract] , August 20, 2007; 30 (3): 300-312. Physiol Genomics X. Mu, L. D. Brown, Y. Liu and M. F. Schneider transformation of cultured adult mouse skeletal muscle fibers Roles of the calcineurin and CaMK signaling pathways in fast-to-slow fiber type [PDF] [Full Text] [Abstract] , March 15, 2008; 586 (6): 1731-1741. J. Physiol. S. L. McGee, K. J. Mustard, D. G. Hardie and K. Baar protein kinase {alpha}1 following overload in LKB1 knockout mice Normal hypertrophy accompanied by phosphoryation and activation of AMP-activated [PDF] [Full Text] [Abstract] , April 25, 2008; 283 (17): 11850-11859. J. Biol. Chem. C. Hickner, T. M. Coffman, A. V. Somlyo, Z. Yan and T. A. J. Haystead R. A. Kwon, E. McCook, P. Li, S. Wang, R. J. Thresher, S. E. Miller, J.-C. Perriard, T. P. Gavin, A. A. Wooldridge, C. N. Fortner, B. Lontay, T. Akimoto, R. L. Neppl, C. Facemire, M. B. Datto, Exercise-adapted Phenotype in Vascular Smooth Muscle Deletion of the Protein Kinase A/Protein Kinase G Target SMTNL1 Promotes an [PDF] [Full Text] [Abstract] , June 1, 2008; 28 (11): 3600-3609. Mol. Cell. Biol. Richardson, R. Bassel-Duby and E. N. Olson M. -S. Kim, J. Fielitz, J. McAnally, J. M. Shelton, D. D. Lemon, T. A. McKinsey, J. A. Performance Protein Kinase D1 Stimulates MEF2 Activity in Skeletal Muscle and Enhances Muscle
An Interpretive Phenomenological Analysis of Doctoral Counselor Education Students' Experience of Receiving Cybersupervision

Cybersupervision with counselor education doctoral students is an understudied practice. This phenomenological study explored five doctoral-level counselor education supervisees’ lived experiences engaging in cybersupervision, Their experiences, which were embedded in their converging professional roles, included skepticism and anxiety, learning and growth in their relationship with supervisors, and unique context-dependent meaning making. Limitations and implications for practice and future research are discussed.
Exploring Structured Sparsity by a Reweighted Laplace Prior for Hyperspectral Compressive Sensing

Hyperspectral compressive sensing (HCS) can greatly reduce the enormous cost of hyperspectral images (HSIs) on imaging, storage, and transmission by only collecting a few compressive measurements in the image acquisition. One of the most challenging problems for HCS is how to reconstruct the HSI accurately from such a few measurements. It has been proved that introducing structure information into sparsity prior can improve the reconstruction performance of standard compressive sensing models. However, the structured sparsity of HSIs is unknown in reality and easily affected by random noise, which makes it difficult to explore the structured sparsity in HCS. To address this problem, we propose a novel reweighted Laplace prior-based HCS method in this paper. First, a hierarchical reweighted Laplace prior is proposed to model the distribution of sparsity in an HSI, which relieves the undemocratic penalization of traditional Laplace prior on nonzero coefficients of a sparse signal. Then, a latent variable-based Bayesian model is employed to learn the optimal configuration of the reweighted Laplace prior from the measurements. This model unifies signal recovery, sparsity prior learning, and noise estimation into a variational framework, where these three tasks are alternatively optimized till convergence. The finally learned sparsity prior can well represent the underlying structure in the sparse signal and is adaptive to the unknown noise. These advantages together improve the reconstruction accuracy of HCS obviously. Moreover, the proposed method is extended to learn a matrix normal distribution-based prior with a full covariance matrix, which depicts the underlying structure in the sparse signal better. As a result, the reconstruction accuracy is further improved. Extensive experimental results on three hyperspectral data sets demonstrate that the proposed method outperforms several state-of-the-art HCS methods in terms of the reconstruction accuracy.
Modeling the Effects of Distance and Spatial Dependence in International Trade

The gravity model has been widely used estimate the effect that distance has in international trade; however, two important areas have seen little attention in the literature, namely, the influence of using a more accurate measure of distance and how distance effect estimates change when controlling for spatial dependence in observed trade flows. Using transportation networks to measure distance and estimating both a spatial lag and spatial error gravity model, Canadian provincial exports to the lower 48 states in the United States were analyzed to address these previously ignored issues. It was found that the traditional distance measure of great circle distance underestimated the distance between any given province and state pair by an average of 20%, however, it did so consistently across all pairs, therefore having no significant influence on the distance effect estimate, regardless of estimation technique. When trade was disaggregated into mode of transportation distance effect estimates differed significantly, reflecting the most efficient uses of each transport mode and also the commodities that flowed across them. Finally, when using the spatial lag gravity model, distance effect estimates decreased substantially compared to traditional least squares estimation, while the spatial error model provided asymptotically equivalent parameter estimates to least squares, but with overall increased predictive power.
A Mixed Method Exploration of Suicidality in Clients with Intellectual Disability

The goal of this dissertation was to investigate suicidality in individuals with intellectual disability (ID). Study 1 reviewed files of adolescent clients at an agency that serves individuals with ID to estimate the prevalence of suicidality, identify factors associated with suicidality, and describe clinical practices regarding suicidality. Study 2 used in-depth interviews with clinicians, which were analyzed qualitatively, to explore their experiences with suicidality in their clients with ID and their practices to address clients’ suicidality. The results of both studies were integrated using a mixed-methods approach. In study 1, 192 case files of adolescent clients aged 12 to 17 were systematically reviewed using a researcher-generated coding scheme. Data was collected on variables that spanned demographic information, mental and physical health, personal characteristics and experiences, family stressors, and suicidality domains. Adequate inter-rater reliability of data collection was achieved. The estimated suicidality prevalence was 13.0%. Factors associated with suicidality included abuse history, trauma history, psychopathology in the family, and higher functioning (i.e., borderline intelligence and mild ID). These factors provided some support for diathesisstress models of suicide in youth with ID. Files infrequently documented clinical practices addressing client suicidality. iii In study 2, semi-structured interviews with 10 clinicians were analyzed using Grounded Theory to create an explanatory framework for understanding clinicians’ experiences with suicidality in their child, adolescent, and adult clients with ID. Although aspects of responding to suicidality in clients with ID were similar to that of clients without ID, the process was more complex due to the inadequacy of the mental health system to address clients’ needs, and clients’ cognitive and communication difficulties made it more difficult to assess suicidality and implement interventions. Suicidality in clients also put an inordinate burden on their caregivers, and the clinicians felt that they were facing the unknown when they worked with these clients.
On the Relation between the Credit Spread Puzzle and the Equity Premium Puzzle

Structural models of default calibrated to historical default rates, recovery rates, and Sharpe ratios typically generate Baa--Aaa credit spreads that are significantly below historical values. However, this "credit spread puzzle" can be resolved if one accounts for the fact that default rates and Sharpe ratios strongly covary; both are high during recessions and low during booms. As a specific example, we investigate credit spread implications of the Campbell and Cochrane (1999) pricing kernel calibrated to equity returns and aggregate consumption data. Identifying the historical surplus consumption ratio from aggregate consumption data, we find that the implied level and time variation of spreads match historical levels well. The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.
Spitzer Observations of z ~ 3 Lyman Break Galaxies: Stellar Masses and Mid-Infrared Properties

We describe the spectral energy distributions (SEDs) of Lyman break galaxies (LBGs) at z ~ 3, using deep mid-infrared and optical observations of the extended Groth strip, obtained with IRAC and MIPS on board Spitzer and from the ground, respectively. We focus on LBGs with detections at all four IRAC bands, in particular the 26 galaxies with IRAC 8 μm band (rest-frame K-band) detections. We use stellar population-synthesis models and probe the stellar content of these galaxies. Based on best-fit continuous star formation models, we derive estimates of the stellar mass for these LBGs. As in previous studies, we find that a fraction of LBGs have very red colors and large estimated stellar masses (M* > 5 × 1010 M☉); the current Spitzer data allow us, for the first time, to study these massive LBGs in detail. We discuss the link between these LBGs and submillimeter-luminous galaxies, and we find that the number density of these massive LBGs at high redshift is higher than predicted by current semianalytic models of galaxy evolution.
Please Scroll down for Article the Quarterly Journal of Experimental Psychology Examining the Influence of Action on Spatial Working Memory: the Importance of Selection

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.
Moving beyond is Identity: Concepts and Discourses

The ongoing debate about the identity of the Information Systems (IS) discipline is examined from a new perspective. Two recent studies are contrasted to demonstrate the limits of retrospective analysis for defining the discipline of IS. A new model for discovery transdisciplinary IS research, based on concepts and discourses is suggested. Latent Semantic Analysis is proposed as an approach to identifying concepts which form transdisciplinary discourses. Conceptual mapping across disciplines may elucidate fruitful areas of research and a transdisciplinary approach to research may improve research salience and intellectual contributions. Such an approach may also weaken or dissolve the discipline as an applied business/organizational field focused on the information technology artifact. This may have the long term effect of maintaining intellectual plasticity and relevance, and expanding the range of intellectual contributions available to IS researchers. But moving beyond IS identity as presently constituted will require rethinking institutional structures upon which the identity of IS is currently dependent.