Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Self-monitoring of Blood Glucose on a Behavioral Weight Loss Intervention for Patients With Type 2 Diabetes

Purpose The purpose of the study was to examine the association of self-monitoring of blood glucose (SMBG) to weight loss and A1C among participants in a behavioral weight loss intervention. Methods Multivariate analyses were employed to evaluate the relationship between SMBG and changes in patient weight and A1C levels. Bootstrapping was used to determine whether there was an indirect effect of SMBG on weight loss through diet adherence and an indirect effect of SMBG on A1C through weight loss. Results The relationship between increased SMBG and greater weight loss was mediated by better adherence to diet. The relationship of increased SMBG and greater reductions in A1C were mediated by greater weight loss. Conclusions Results of the study were consistent with the hypothesis that SMBG leads to an increased adherence to dietary recommendations. For patients who are taught to use their diet to lose weight, increased adherence to dietary recommendations is associated with increased weight loss and subsequently better glucose control. SMBG may be of value as an adjunctive intervention in behavioral programs for type 2 diabetes.
Model checking vs. generalized model checking: semantic minimizations for temporal logics

Three-valued models, in which properties of a system are either true, false or unknown, have recently been advocated as a better representation for reactive program abstractions generated by automatic techniques such as predicate abstraction. Indeed, for the same cost, model checking three-valued abstractions can be used to both prove and disprove any temporal-logic property, whereas traditional conservative abstractions can only prove universal properties. Also, verification results can be more precise with generalized model checking, which checks whether there exists a concretization of an abstraction satisfying a temporal-logic formula. Since generalized model checking includes satisfiability as a special case (when everything in the model is unknown), it is in general more expensive than traditional model checking. In this paper, we study how to reduce generalized model checking to model checking by a temporal-logic formula transformation, which generalizes a transformation for propositional logic known as semantic minimization in the literature. We show that many temporal-logic formulas of practical interest are self-minimizing, i.e., are their own semantic minimizations, and hence that model checking for these formulas has the same precision as generalized model checking.
Recent advances in clinical practice challenges and opportunities in the management of obesity

Despite advances in understanding the roles of adiposity, food intake, GI and adipocyte-related hormones, inflammatory mediators, the gut–brain axis and the hypothalamic nervous system in the pathophysiology of obesity, the effects of different therapeutic interventions on those pathophysiological mechanisms are controversial. There are still no low-cost, safe, effective treatments for obesity and its complications. Currently, bariatric surgical approaches targeting the GI tract are more effective than non-surgical approaches in inducing weight reduction and resolving obesity-related comorbidities. However, current guidelines emphasise non-surgical approaches through lifestyle modification and medications to achieve slow weight loss, which is not usually sustained and may be associated with medication-related side effects. This review analyses current central, peripheral or hormonal targets to treat obesity and addresses challenges and opportunities to develop novel approaches for obesity.
The quality of antipsychotic drug prescribing in nursing homes.

BACKGROUND The prescribing of antipsychotic drugs has been increasing in nursing homes (NHs) since the availability of second-generation antipsychotic agents, also known as the atypicals, but there is little information on the appropriateness of such prescribing. METHODS A retrospective analysis using the nationally representative data set of the Medicare Current Beneficiary Survey merged to Minimum Data Sets assessments, medication administration records, and Medicare claims. We identified a sample of 2.5 million Medicare beneficiaries in NHs during 2000-2001 (unweighted n = 1096) to assess prevalence of antipsychotic use, rates of adherence to NH prescribing guidelines, and changes in behavioral symptoms. RESULTS Approximately 693 000 (unweighted n = 302), or 27.6%, of all Medicare beneficiaries in NHs received at least 1 prescription for antipsychotics during the study period: 20.3% received atypicals only; 3.7%, conventionals only; and 3.6%, both atypicals and conventionals. Less than half (41.8%) of treated residents received antipsychotic therapy in accordance with NH prescribing guidelines. One (23.4%) in 4 patients had no appropriate indication, 17.2% had daily doses exceeding recommended levels, and 17.6% had both inappropriate indications and high dosing. Patients receiving antipsychotic therapy within guidelines were no more likely to achieve stability or improvement in behavioral symptoms than were those taking antipsychotics outside the guidelines. CONCLUSIONS This study detected the highest level of antipsychotic use in NHs in over a decade. Most atypicals were prescribed outside the prescribing guidelines and for doses and indications without strong clinical evidence. Failure to detect positive relationships between behavioral symptoms and antipsychotic therapy raises questions about the appropriateness of prescribing.
A New Approach to Estimating the Production Function for Housing

Dating to the classic works of Alonso, Mills, and Muth, the production function for housing has played a central role in urban economics and local public finance. This paper provides a new flexible approach for estimating the housing production function which treats housing quantities and prices as latent variables. The empirical analysis is based on a comprehensive database of recently built properties in Allegheny County, Pennsylvania. We find that the new method proposed in this paper works well in the application and provides reasonable estimates for the underlying production function.
SURF-based species identification system

The development of tools for the automated identifi cation of species will reduce the burden of routine identifications conducted by many biologists. The design of these tools is difficult because it depends on the proper extracti on of those most relevant characteristics of the image, namely, those unequivocally identify its spe cies. The appropriate software for such extraction does not exist in all cases. This work p oposes an architecture for the automated identification of the skulls of different mammalian species belonging to the order Eulipotyphla, which includes shrews, moles and hedgehogs, among o thers. Our system determines nine species of this mammalian group using existing object recog nition techniques, identifying them based on a set of images of the skulls of these species in a digital image database. To validate the proposed architecture, mobile and web applications have been d veloped. These applications use the image recognition technology provided by the OpenCV library for the detection of the keypoints and matching of the images. The application extract s the descriptor of the input image using the Speed Up Robust Features (SURF) method and compares this descriptor against the image database for matching using a Euclidean distance ba s d on the nearest-neighbor approach. The initial tests have achieved a reliability of 98%.
The effect of cold application on pain due to chest tube removal.

AIM AND OBJECTIVES The aim of the research is to determine the effect of cold application on the pain owing to chest tube removal for patients with single pleural chest tube. BACKGROUND Removal of chest tubes causes patients to feel pain and interventions used for reducing the pain owing to the removal of chest tubes are not sufficient. DESIGN Controlled clinical trial with repeated measures. METHODS This study was conducted with 140 patients, of whom 70 patients were in the experimental group and 70 patients were in the control group, in a thoracic hospital in Turkey. Data were collected using a data collection form consisting of patients' demographic and health history and Visual Analogue Scale. Cold was applied to patients in the experimental group prior to chest tube removal. In the experimental group, skin temperature and pain intensity was measured for each patient at four time points. In the control group, pain intensity was evaluated for each patient at three time points. Data were evaluated using Chi-square and Repeated Measurements two-way anova tests. RESULTS The Visual Analogue Scale score was measured immediately after the chest tube removal in the experimental group was 3·85, compared with 5·60 in the control group. There were significant differences on pain with cold application between the two groups prior and after the intervention. Age, gender, the number of days the chest tube was inserted and the chest tube insertion indication had no effect on the pain owing to chest tube removal. CONCLUSION Cold application is effective in reducing the pain owing to chest tube removal. RELEVANCE TO CLINICAL PRACTICE Cold application was recommended prior to chest tube removal to reduce the pain owing to removal of chest tube.
Opinion Mining in Newspapers for a Media Response Analysis

A part of the broad research domains Knowledge Discovery and Information Retrieval deals only with Data Mining in texts: Text Mining. In general, Text Mining tries to obtain knowledge by identifying patterns in textual data. One of its most important areas is Opinion Mining, which is the main topic of this thesis. Opinion Mining is a far-reaching research area, because it is potentially interesting for many different fields of application as well as its results are very valuable: Opinions are analysed in reviews of products, services, etc. to create very detailed reports about the subject of the reviews or to identify fake or spam reviews. Furthermore, contributions for Opinion Mining in Social Media try to discover opinions in these networks such as Twitter, Facebook, and Youtube. We concentrate on Opinion Mining in news articles, because automatically extracted opinions from news have a high economic value, especially for media monitoring services, but at the same time, this domain has been rather neglected by approaches for Opinion Mining. Thus, we complement this research area by tasks of a Media Response Analysis, which includes the extraction of statements, the classification of the tonality, and the determination of viewpoints. To establish these tasks within the Opinion Mining community, we published an own dataset of a Media Response Analysis (MRA). A major challenge is the extraction of statements for an MRA. In this step, the text parts of a news article have to be identified, which are most relevant for analysis objects and contain opinions, even if the tonality of the opinion is neutral. The classification of the tonality for a given text or text part represents the most difficult task for almost every Opinion Mining approach. Many contributions involve only this step and apply a broad spectrum of techniques to tackle this problem: The creation of sentiment dictionaries, the analysis of contextual information, machine learning, heuristic rules, profoundly linguistic analyses, and many more. During this thesis we investigate many characteristics for the determination of tonality in our domain in contrast to recent research and propose a very well working approach for the tonality classification of statements in newspaper articles, which is adjusted to the requirements of a practical solution and achieves better results for our task than current state-of-the-art techniques. Extracted and rated statements are difficult to assess for MRA, if they do not contain any information about the viewpoint. To complete a fully automated solution of Opinion Mining for a Media Response Analysis, we explain and evaluate our ontology-based approach for the determination of viewpoints.
Association between reproductive factors and breast cancer in an urban set up at central India: a case-control study.

BACKGROUND Epigenetic changes, geography and environmental factors do surpass the genetic factors in the development of breast cancer. This study investigates the association of reproductive factors with the breast cancer in this context. OBJECTIVE To detect the association of reproductive risk factors with breast cancer in an urban set up at central India. STUDY DESIGN Matched paired community-based case-control study. MATERIALS AND METHODS The study was conducted for a period of a year from October 2008 to August 2009 in Bhopal (MP). Demographic data and reproductive risk factor related information were collected using structured questionnaire. Data analysis was done by Epi-info and SPSS 16. RESULTS History of using oral contraceptive pills (OR = 3.02, 95% CI: 1.28-7.11), history of not having breastfeeding (OR = 3.62, 95% CI: 1.29-10.16) and family history of breast cancer (OR = 3.98, 95%CI: 1.06-14.826) were associated significantly with the occurrence of breast cancer in multivariate analysis. CONCLUSIONS The findings of the present study suggests that positive family history of breast cancer and history of using OCP may be the epigenetic factors promoting the occurrence of breast cancer while breastfeeding reduces the possibility of acquiring breast cancer.
Comparison of 1‐D and 2‐D LC MS/MS methods for proteomic analysis of human serum

1‐D and 2‐D LC methods were utilized for proteome analysis of undepleted human serum. Separation of peptides in 2‐D LC was performed either with strong cation exchange (SCX)‐RP chromatography or with an RP–RP 2‐D LC approach. Peptides were identified by MS/MS using a data‐independent acquisition approach. A peptide retention prediction model was used to highlight the potential false‐positive peptide identifications. When applying selected data filtration, we identified 52 proteins based on 316 peptides in serum in 1‐D LC setup. One hundred and eighty‐four proteins/1036 peptides and 142 proteins/905 peptides were identified in RP–RP and SCX‐RP 2‐D LC, respectively. The performance of both 2‐D LC methods for proteomic analysis is critically compared.
Enhancing M Currents: A Way Out for Neuropathic Pain?

Almost three decades ago, the M current was identified and characterized in frog sympathetic neurons (Brown and Adams, 1980). The years following this discovery have seen a huge progress in the understanding of the function and the pharmacology of this current as well as on the structure of the underlying ion channels. Therapies for a number of syndromes involving abnormal levels of excitability in neurons are benefiting from research on M currents. At present, the potential of M current openers as analgesics for neuropathic pain is under discussion. Here we offer a critical view of existing data on the involvement of M currents in pain processing. We believe that enhancement of M currents at the site of injury may become a powerful strategy to alleviate pain in some peripheral neuropathies.
To study the length, thickness, density and staining intensity of reticulin fibers in various grades of oral squamous cell carcinoma

Development of epithelial malignancies leads to well documented molecular and structural changes in the epithelium. Recently, it has been recognized that stromal biology is also altered significantly with preinvasive disease. Oral Squamous Cell Carcinoma comprises a bulk of all oral malignancies. In Oral Squamous Cell Carcinoma, cell invade the stroma in the form of islands, strands or sheets, which are embedded or surrounded by an extracellular matrix, thus producing reactive changes in the stroma. Reticulin fibers along with collagen fibers, is not only responsible for maintaining the functional integrity of tissues but is also thought to play an important role in pathogenesis and invasion in Oral Squamous Cell Carcinoma. In this study, reticulin fibers were studied histopathologically for the length, thickness, density of colour and uniformity of stain of in various grades of Oral Squamous Cell Carcinoma with Gomari silver reticulin stain. Thus, the present study helps in documentation of connective tissue changes in various grades of Oral Squamous Cell Carcinoma . Correspondence to: Ashwini Walke, Department of oral pathology and microbiology, Riyadh, Saudi Arabia, Tel: 9975771205; E-mail: ashwiniwalke2210@gmail.com
Hyperspectral darkfield microscopy of PEGylated gold nanoparticles targeting CD44‐expressing cancer cells

We present a new hyperspectral darkfield imaging system with a scanned broadband supercontinuum light source. We observed the specific attachment of the functionalized gold plasmonic nanoparticles (AuNPs) targeting CD44+ human breast cancer cells by conventional and by proposed hyperspectral darkfield microscopy. This wide‐field and low phototoxic hyperspectral imaging system has been successful for performing spectral three‐dimensional (3D) localization and spectroscopic identification of CD44‐targeted PEGylated AuNPs in fixed cell preparations. Such spatial and spectral information is essential for the improvement of nanoplasmonic‐based imaging, disease detection and treatment in complex biological environment. Presented system capability for 3D NP tracking will also enable investigation of specific sub‐cellular activity with the use of NPs as spectral sensors. (© 2013 WILEY‐VCH Verlag GmbH &Co. KGaA, Weinheim)
Opposite Clear Corneal Incisions versus Steep Meridian Incision Phacoemulsification for Correction of Pre-existing Astigmatism

Purpose To compare the efficacy of adding an opposite clear corneal incision (OCCI) on the steep meridian versus performing surgery on the steep meridian alone during phacoemulsification in reducing pre-existing corneal astigmatism. Methods This randomized clinical trial was performed on 120 eyes with corneal astigmatism of >1D undergoing phacoemulsification. Incisions were made based on the type of astigmatism as follows: superior or superior+OCCI for with-the-rule and temporal or temporal+OCCI for against-the-rule astigmatism. Patients were followed with refraction, keratometry and topography. Statistical analysis was performed using one- and two-way ANOVA and Tukey-a test. Results Mean corneal astigmatism was 1.82±0.86 D in the superior+OCCI group and 1.74±0.86 D in the temporal+OCCI group preoperatively which decreased to 1.31±0.59(P=0.013) and 1.19±0.64 (P=0.009) postoperatively respectively. No significant change occurred in the amount of astigmatism in any of the two single incision groups. Conclusion Paired OCCI on the steep axis is a useful technique to correct mild to moderate pre-existing astigmatism with no need for particular skill or additional instruments.
Entropy-Driven Simplification

In this paper, a new viewpoint-based simplification approach is proposed for polygonal meshes. This approach is driven by an information-theoretic metric, viewpoint entropy, which measures the amount of information from a scene or object that arrives at a certain viewpoint. Our algorithm applies the best half-edge collapse as a decimation criterion and uses the variation of viewpoint entropy to measure the edge collapse error. Compared to pure geometric-based simplifications, the models produced by our method are closer to the original model according to visual similarity. Our approach also achieves a higher simplification in hidden interiors, by being able to remove them all and to leave the visible areas of the mesh intact. Models generated by CAD applications can benefit from this feature, since these models are usually constructed by assembling smaller objects which can become partially hidden during joining operations. The main application of our method is for video games where models come from CAD applications and are geometrically not very complex, a few thousand polygons at the most, and in which visual similarity is the most important requirement.
Architecting a reliable CMP switch architecture

As silicon technologies move into the nanometer regime, transistor reliability is expected to wane as devices become subject to extreme process variation, particle-induced transient errors, and transistor wear-out. Unless these challenges are addressed, computer vendors can expect low yields and short mean-times-to-failure. In this article, we examine the challenges of designing complex computing systems in the presence of transient and permanent faults. We select one small aspect of a typical chip multiprocessor (CMP) system to study in detail, a single CMP router switch. Our goal is to design a BulletProof CMP switch architecture capable of tolerating significant levels of various types of defects. We first assess the vulnerability of the CMP switch to transient faults. To better understand the impact of these faults, we evaluate our CMP switch designs using circuit-level timing on detailed physical layouts. Our infrastructure represents a new level of fidelity in architectural-level fault analysis, as we can accurately track faults as they occur, noting whether they manifest or not, because of masking in the circuits, logic, or architecture. Our experimental results are quite illuminating. We find that transient faults, because of their fleeting nature, are of little concern for our CMP switch, even within large switch fabrics with fast clocks. Next, we develop a unified model of permanent faults, based on the time-tested bathtub curve. Using this convenient abstraction, we analyze the reliability versus area tradeoff across a wide spectrum of CMP switch designs, ranging from unprotected designs to fully protected designs with on-line repair and recovery capabilities. Protection is considered at multiple levels from the entire system down through arbitrary partitions of the design. We find that designs are attainable that can tolerate a larger number of defects with less overhead than naïve triple-modular redundancy, using domain-specific techniques, such as end-to-end error detection, resource sparing, automatic circuit decomposition, and iterative diagnosis and reconfiguration.
Face recognition based on separable lattice 2-D HMM with state duration modeling

This paper describes an extension of separable lattice 2-D HMMs (SL-HMMs) using state duration models for image recognition. SL-HMMs are generative models which have size and location invariances based on state transition of HMMs. However, the state duration probability of HMMs exponentially decreases with increasing duration, therefore it may not be appropriate for modeling image variations accuratelty. To overcome this problem, we employ the structure of hidden semi Markov models (HSMMs) in which the state duration probability is explicitly modeled by parametric distributions. Face recognition experiments show that the proposed model improved the performance for images with size and location variations.