Miracle-dz/UniFAR-FTUs huggingface dataset:
Periodontal findings in individuals with newly identified pre-diabetes or diabetes mellitus.

AIM To assess the periodontal status and number of missing teeth in patients with newly identified pre-diabetes or diabetes mellitus. METHODS A total of 1097 subjects with previously undiagnosed diabetes were available for study, and were categorized into normoglycaemic, potentially pre-diabetes or potentially diabetes groups based on a point-of-care (POC) HbA1c test. RESULTS In fully adjusted models, significant differences were observed between all groups for the per cent of teeth with at least one site with a probing depth of ≥5 mm. For bleeding on probing, there were significant differences between diabetes and pre-diabetes (p = 0.001), and between diabetes and normoglycaemic groups (p = 0.002). For missing teeth, there were significant differences between the pre-diabetes and normoglycaemic groups (p = 0.034), and the diabetes and normoglycaemic groups (p = 0.004). CONCLUSIONS Individuals with previously unidentified pre-diabetes demonstrate a level of periodontal destruction between that observed for normoglycaemic individuals and persons with diabetes. These data emphasize the association of oral findings to dysglycaemia, and suggest that periodontal disease and tooth loss can be early complications of diabetes mellitus.
The Junior High School: A Changing View

As to appropriateness, as long as the program and organization of the elementary schools differed sharply, there was, and is, real need for a bridge between the self-contained classroom of the elementary school with its broad and flexible units of work and the departmentalized program of the high school with its relatively greater emphasis on subjects and specialization. These differences are becoming much less sharp, however, as subjects
Pretreatment quality assurance of flattening filter free beams on 224 patients for intensity modulated plans: a multicentric study.

PURPOSE Pretreatment quality assurance data from four centers, members of the European TrueBeam council were analyzed with different verification devices to assess reliability of flattening filter free beam delivery for intensity modulated radiotherapy (IMRT) and RapidArc (RA) techniques. METHODS TrueBeam(®) (Varian Medical System) is a new linear accelerator designed for delivering flattened, as well as flattening filter free beams. Pretreatment dosimetric validation of plan delivery was performed with different verification devices and responses to high dose rates were tested. Treatment planning was done in Eclipse planning system (PRO 8.9, AAA 8.9). γ evaluation was performed with (dose difference) = 3% and (distance to agreement) = 3 mm scoring the gamma agreement index (GAI, % of field area passing the test). Two hundred and twenty-four patients with 1-6 lesions in various anatomical regions and dose per fraction ranging from 1.8 Gy to 25 Gy were included in the study; 88 were treated with 6 MV flattening filter free (X6FFF) beam energy and 136 with 10 MV flattening filter free (X10FFF) beam. Gafchromic films in solid water, delta(4), arccheck, and matrixx phantom were used to verify the dose distributions. Additionally, point measurements were performed using a PinPoint chamber and a Farmer chamber. RESULTS Dose calculation as well as dose delivery was equally accurate for IMRT and RA delivery (IMRT: GAI = 99.3% (±1.1); RA: GAI = 98.8% (±1.1) as well as for the two beams evaluated (X6FFF: GAI = 99.1% (±1.0); X10FFF: GAI = 98.8% (±1.2). Only small differences were found for the four verification devices. A point dose verification was performed on 52 cases, obtaining a dose deviation of 0.34%. The GAI variations with number of monitor units were statistically significant. CONCLUSIONS The TrueBeam FFF modality, analyzed with a variety of verification devices and planned with Eclipse planning system is dosimetrically accurate (within the specified limits 3 mm/3%) for both X6FFF and X10FFF beam energy.
Comparison of neural networks and an optical thin-film multilayer model for connectionist learning

Current work on connectionist models has been focused largely on artificial neural networks that are inspired by the networks of biological neurons in the human brain. However there are also other connectionist architectures that differ significantly from this biological exemplar. Li and Purvis (1999) proposed a connectionist learning architecture inspired by the physics associated with optical coatings of multiple layers of thin-films. The proposed model differs significantly from the widely used neuron-inspired models. With thin-film layer thicknesses serving as adjustable parameters (as compared with connection weights in a neural network) for the learning system, the optical thin-film multilayer model (OTFM) is capable of approximating virtually any kind of highly nonlinear mappings. We focus on a detailed comparison of a typical neural network model and the OTFM. We describe the architecture of the OTFM and show how it can be viewed as a connectionist learning model. We then present the experimental results of using the OTFM in solving a classification problem typical of conventional connectionist architectures.
MEMS Based Medical Microsensors

The medical applications of MEMS (Micro-Electro-Mechanical-Systems) microsensors have been introduced. MEMS based sensors such as pressure sensors, accelerometers, Glucose sensors, chemical gas sensors and etc. and its advantages with respect to the other sensors in medical applications are explained. Small size, low price, high functionality, high precision, fast response time and so on are some of MEMS sensors benefits. Also, some special applications of these sensors such as blood pressure measurement, pacemaker acceleration measurement, blood glucose measurement and etc. are evaluated.
The Diffusion of Advanced Vehicle Technologies 7

Since automobiles were introduced over a century ago, thousands of innovations have been introduced to their powertrains, structures, and other vehicle systems. New technologies allow manufacturers to provide vehicles of increasing levels of utility to consumers—better performance, greater effi ciency, more features, and greater carrying capacity. Some innovations, such as new structural materials, deliver improved quality or performance, but are otherwise transparent to customers. Others, such as automatic transmissions, require a consumer to become familiar with the new technology and choose to purchase a new vehicle that incorporates it over an existing vehicle that does not. The potential benefi ts of advanced technologies are only realized when those technologies are introduced into vehicles available in showrooms, and consumers purchase those advanced technology vehicles, replacing older vehicles in the vehicle fl eet. The spread of new technologies depends upon millions of individuals adopting those technologies; the aggregation of these actions leads to the diffusion of these technologies across the market. To assess the benefi ts of advanced technologies, it is therefore critical to understand how long this diffusion process will take. The purpose of this chapter is to demonstrate empirical evidence on the diffusion of automotive technologies to help calibrate our predictions about future technology adoption, energy consumption, and emissions, and inform the development of effective strategy and policy decisions. This chapter is divided into four sections, each addressing a theme related to the diffusion of innovations (technologies) in the automotive sector. First, a review of the innovation diffusion literature is provided, focusing on automotive applications. Second, the diffusion of vehicle features is analyzed using evidence from the United States over the past 40 years. Third, the diffusion of entire alternative fuel powertrains is considered, focusing on the case of the iconic Toyota Prius hybrid-electric vehicle (HEV) in the United States. Finally, the projection of future technology adoption to estimate future energy use and emissions impacts is discussed. Extensive literature examines the diffusion of innovations: the process by which new ideas, practices, and technologies spread through a population. The following section summarizes the theoretical foundations of the innovation diffusion literature, the modeling approaches used to quantify the diffusion of innovations, and the application of these tools in the automotive context. The diffusion of innovations commonly follows an S-shaped or logistic pattern over time, giving rise to Rogers' adopter classifi cations such as " innovators " and " early adopters. " More …
An improvment of weight scheme on adaBoost in the presence of noisy data

The first strand of this research is concerned with the classification noise issue. Classification noise, (worry labeling), is a further consequence of the difficulties in accurately labeling the real training data. For efficient reduction of the negative influence produced by noisy samples, we propose a new weight scheme with a nonlinear model with the local proximity assumption for the Boosting algorithm. The effectiveness of our method has been evaluated by using a set of University of California Irvine Machine Learning Repository (UCI) [1] benchmarks. We report promising results.
Diabetes self-assessment score and the development of diabetes

Abstract To verify that the Korean Diabetes Score (KDS), a self-assessment, predicts the risk of diabetes in various comprehensive risk models, and to investigate factors that enhance its predictive ability in a large cohort. We analyzed 8735 adults without diabetes in the Korean Genome and Epidemiology Study, an ongoing large community-based 10-year cohort study. Incident diabetes was defined as fasting blood glucose ≥126 mg/dL or postload 2-hour glucose ≥200 mg/dL by 75 g oral glucose tolerance test conducted biennually, or currently taking medication for diabetes. Hazard ratios (HRs) using Cox regression were calculated for relative risk of developing diabetes as associated with the KDS, and performance of risk models was assessed by area under the receiver-operating characteristic curve (AUC). Of 8735 participants, 1497 (17.1%) developed diabetes over 10 years. The prevalence of incident diabetes was 10.3% in people with a KDS <5 and was 21.8% in those with KDS ≥5 (P < .001). Increasing KDS was significantly associated with developing diabetes (adjusted HR: 1.13; 95% confidence interval:1.09,1.18). The comprehensive prediction model with KDS added to fasting glucose, glycated hemoglobin, postload 2-hour glucose, and triglyceride showed a markedly higher AUC (0.782) compared to KDS alone (0.641). A low insulinogenic index (IGI) level, but not insulin resistance, was a significant determinant of developing diabetes in subjects who had baseline KDS < 5. We confirmed that KDS as a 10-year risk model to predict diabetes becomes more potent when added to relevant laboratory parameters. Beta-cell function as assessed by IGI should be taken into account when predicting diabetes using the KDS.
Quantifying intermolecular interactions of ionic liquids using cohesive energy densities

For ionic liquids (ILs), both the large number of possible cation + anion combinations and their ionic nature provide a unique challenge for understanding intermolecular interactions. Cohesive energy density, ced, is used to quantify the strength of intermolecular interactions for molecular liquids, and is determined using the enthalpy of vaporization. A critical analysis of the experimental challenges and data to obtain ced for ILs is provided. For ILs there are two methods to judge the strength of intermolecular interactions, due to the presence of multiple constituents in the vapour phase of ILs. Firstly, cedIP, where the ionic vapour constituent is neutral ion pairs, the major constituent of the IL vapour. Secondly, cedC+A, where the ionic vapour constituents are isolated ions. A cedIP dataset is presented for 64 ILs. For the first time an experimental cedC+A, a measure of the strength of the total intermolecular interaction for an IL, is presented. cedC+A is significantly larger for ILs than ced for most molecular liquids, reflecting the need to break all of the relatively strong electrostatic interactions present in ILs. However, the van der Waals interactions contribute significantly to IL volatility due to the very strong electrostatic interaction in the neutral ion pair ionic vapour. An excellent linear correlation is found between cedIP and the inverse of the molecular volume. A good linear correlation is found between IL cedIP and IL Gordon parameter (which are dependent primarily on surface tension). ced values obtained through indirect methods gave similar magnitude values to cedIP. These findings show that cedIP is very important for understanding IL intermolecular interactions, in spite of cedIP not being a measure of the total intermolecular interactions of an IL. In the outlook section, remaining challenges for understanding IL intermolecular interactions are outlined.
Text Detection in Natural Scene Images Using Spatial Histograms

In this paper, we present a texture-based text detection scheme for detecting text in natural scene images. This is a preliminary work towards a complete system of text detection, localization and recognition in order to help visually impaired persons. We have employed spatial histograms computed from gray-level co-occurrence matrices for texture coding and three classifiers have been evaluated. Moreover, one feature selection mechanism is employed to select those histogram components that exhibit high discrimination power. The texture coding scheme is simple and can readily differentiate between text and non-text. The proposed scheme is evaluated on 50 images taken from ICDAR 2003 robust reading and text locating database. The results are encouraging with a text detection rate of 66% and a false alarms rate of 22% .
Composable code generation for distributed giotto

We present a compositional approach to the implementation of hard real-time software running on a distributed platform. We explain how several code suppliers, coordinated by a system integrator, can independently generate different parts of the distributed software. The task structure, interaction, and timing is specified as a Giotto program. Each supplier is given a part of the Giotto program and a timing interface, from which the supplier generates task and scheduling code. The integrator then checks, individually for each supplier, in pseudo-polynomial time, if the supplied code meets its timing specification. If all checks succeed, then the supplied software parts are guaranteed to work together and implement the original Giotto program. The feasibility of the approach is demonstrated by a prototype implementation.
Simplification syntaxique de phrases pour le français (Syntactic Simplification for French Sentences) [in French]

Syntactic Simplification for French Sentences This paper presents a method for the syntactic simplification of French texts. Syntactic simplification aims at making texts easier to understand by simplifying the elements that hinder reading. It is based on a corpus study that aimed at investigating the linguistic phenomena involved in the manual simplification of French texts. We have first gathered a parallel corpus of articles from Wikipedia and Vikidia, that we used to establish a typology of simplifications. In a second step, we implemented a system that carries out syntactic simplifications based on these corpus observations. We described simplification rules in order to generate simplified sentences. A module subsequently selects the best subset of sentences. The evaluation of our system shows that about 80% of the sentences produced by our system are accurate. MOTS-CLÉS : simplification automatique, lisibilité, analyse syntaxique.
Molecular Testing for Oncogenic Gene Alterations in Pediatric Thyroid Lesions.

BACKGROUND Thyroid nodules are less common in pediatric patients (i.e., those ≤18 years) than they are in adults. The Bethesda System for Reporting Thyroid Cytopathology allows for individual risk stratification, but a significant number of nodules are indeterminate. Incorporating gene mutation panels and gene expression classifiers may aid in preoperative diagnosis. The overall aim of this study was to assess the prevalence of oncogene alterations in a representative pediatric population and across a broad-spectrum of thyroid tumor diagnoses. METHODS This was a retrospective cross-sectional evaluation of 115 archived samples, including: 47 benign (29 follicular adenoma, 11 diffuse hyperplasia, four thyroiditis, and three multinodular goiter), six follicular thyroid carcinomas (FTC), 24 follicular variant of papillary thyroid carcinomas (fvPTC), 27 classic variant of PTC (cPTC), eight diffuse sclerosing variant of PTC (dsvPTC), and three other PTC. Molecular testing was performed by multiplex qualitative polymerase chain reaction followed by bead array cytometry. Oncogene results were analyzed for association with age, sex, histology, lymph node metastasis, and intrathyroidal spread. RESULTS A mutation in one of the 17 molecular markers evaluated was found in: 2/6 (33%) FTC, 8/24 (33%) fvPTC, 17/27 (63%) cPTC, and 4/8 (50%) dsvPTC. Mutations in RAS or PAX8/PPARG were exclusive to FTC and fvPTC. BRAF was the most common mutation in cPTC (12/17; 71%), and RET/PTC was the only mutation associated with dsvPTC. Overall, a mutation was found in 32/68 (47%) malignant specimens, with a single follicular adenoma positive for PAX8/PPARG. The relative distribution of gene alterations in pediatric lesions was similar to adults. The presence of a BRAF mutation in pediatric cPTC did not predict a more invasive phenotype. CONCLUSIONS Of 33 nodules with genetic alterations, 32 were malignant. Mutations in RAS were most frequently associated with FTC, RET/PTC rearrangements with dsvPTC, and invasive fvPTC, and BRAF with cPTC. These results suggest a clinical role for mutational analysis of pediatric nodules to guide the surgical approach.
Effect of Parent Involvement and Parent Expectations on Postsecondary Outcomes for Individuals Who Are d/Deaf or Hard of Hearing

The purpose of this article is to investigate the potential role of parent involvement and parent expectation in postschool outcomes for individuals who are d/Deaf or hard of hearing (DHH). Students who are DHH have lower retention and employment rates than their peers. Recognizing the importance of family in developmental outcomes for all individuals, this article focuses specifically on the role of parents in facilitating postsecondary outcomes. In an effort to address gaps in the literature in this area, this study utilizes the National Longitudinal Transition Survey 2 (NLTS-2) dataset to measure the effect of parental involvement and expectations as individuals who are DHH transition from secondary grades into a variety of postschool settings. Overall, none of the parental involvement variables were statistically significant when controlling for student and parent demographics. The parental expectation variables that had a statistically significant impact on outcomes included expectations to live independently, to be employed, and to pursue postsecondary education. This article discusses findings in the context of operationalization of study constructs in the NLTS-2 and literature related to transition and parental involvement for students who are DHH.
Hantaviruses Direct Endothelial Cell Permeability by Sensitizing Cells to the Vascular Permeability Factor VEGF, while Angiopoietin 1 and Sphingosine 1-Phosphate Inhibit Hantavirus-Directed Permeability

ABSTRACT Hantaviruses infect human endothelial cells and cause two vascular permeability-based diseases: hemorrhagic fever with renal syndrome and hantavirus pulmonary syndrome. Hantavirus infection alone does not permeabilize endothelial cell monolayers. However, pathogenic hantaviruses inhibit the function of αvβ3 integrins on endothelial cells, and hemorrhagic disease and vascular permeability deficits are consequences of dysfunctional β3 integrins that normally regulate permeabilizing vascular endothelial growth factor (VEGF) responses. Here we show that pathogenic Hantaan, Andes, and New York-1 hantaviruses dramatically enhance the permeability of endothelial cells in response to VEGF, while the nonpathogenic hantaviruses Prospect Hill and Tula have no effect on endothelial cell permeability. Pathogenic hantaviruses directed endothelial cell permeability 2 to 3 days postinfection, coincident with pathogenic hantavirus inhibition of αvβ3 integrin functions, and hantavirus-directed permeability was inhibited by antibodies to VEGF receptor 2 (VEGFR2). These studies demonstrate that pathogenic hantaviruses, similar to αvβ3 integrin-deficient cells, specifically enhance VEGF-directed permeabilizing responses. Using the hantavirus permeability assay we further demonstrate that the endothelial-cell-specific growth factor angiopoietin 1 (Ang-1) and the platelet-derived lipid mediator sphingosine 1-phosphate (S1P) inhibit hantavirus directed endothelial cell permeability at physiologic concentrations. These results demonstrate the utility of a hantavirus permeability assay and rationalize the testing of Ang-1, S1P, and antibodies to VEGFR2 as potential hantavirus therapeutics. The central importance of β3 integrins and VEGF responses in vascular leak and hemorrhagic disease further suggest that altering β3 or VEGF responses may be a common feature of additional viral hemorrhagic diseases. As a result, our findings provide a potential mechanism for vascular leakage after infection by pathogenic hantaviruses and the means to inhibit hantavirus-directed endothelial cell permeability that may be applicable to additional vascular leak syndromes.
A Nonparametric Multiscale Markov Random Field Model For Synthesizing Natural Textures

In this paper we present a non-causal, non-parametric, multiscale, Markov random field (MRF) texture model. The model is capable of capturing the characteristics of and synthesising a wide variety of textures, varying from the highly structured to the stochastic. We introduce a novel multiscale texture synthesis algorithm that allows us to nse large neighbourhood systems to model some complex natural textures. As an added advantage of using the novel multiscale texture synthesis algorithm, phase discontinuities in the synthetic textures are reduced. Finally we show how the high dimensional representation of the texture may be modelled with lower dimensional statistics without compromising the integrity of the representation. The power Of oar modelling technique is evident in that only a small training image is required to derive respectable results even when the texture contains long range characteristics.
Complex manoeuvres of heterogeneous MAV-UGV formations using a model predictive control

A problem of motion planning and coordination of compact formations of ground and aerial robots will be tackled in this paper. The scenarios when the formation composed from Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs), in particular Micro Aerial Vehicles (MAVs), has to reverse the direction of movement to fulfil task of collisionfree motion to a target zone will be solved. The presented motion planning and stabilization approach provides an effective technique to enable deployment of closely cooperating teams of robots in outdoor as well as indoor environment. The formation to target region problem is solved using a Model Predictive Control (MPC) methodology and the formation driving concept is based on a virtual-leader-follower approach. The mentioned MPC based process is used for trajectory planning and control of a virtual leader and also for control and stabilization of followers (MAVs and UGVs). The proposed approach is verified with numerous simulations and hardware experiments.