Miracle-dz/UniFAR-FTUs huggingface dataset:
Coronary Artery Calcification Is Related to Inflammation in Rheumatoid Arthritis: A Long-Term Follow-Up Study

Objective. A long-term follow-up of patients with rheumatoid arthritis (RA) to evaluate factors related to coronary artery calcification (CAC). Methods. All 22 eligible patients (4 males/18 females, mean age 65 years, and RA-duration 30–36 years) from the original (baseline; n = 39) study of atherosclerosis were included. Inflammation, cardiovascular risk factors, and biomarkers were measured at baseline. At follow-up 13 years later, CAC was assessed by computed tomography (CT) and the grade of inflammation was measured. Multivariate analysis of differences between patients with low (0–10) and high CAC (>10) was done by orthogonal projection to latent structures (OPLS). Results. Ten patients had CAC 0–10 and 12 had >10 (range 18–1700). Patients with high CAC had significantly higher ESR (24.3 versus 9.9 mm/h) and swollen joint count (2 versus 0). The OPLS models discriminated between patients having high or low CAC. With only baseline variables, the sensitivity was 73% and the specificity 82%. The model that also included inflammatory variables from follow-up had a sensitivity of 89% and a specificity of 85%. Exclusion of baseline intima media thickness and plaque from the latter model modestly reduced the accuracy (sensitivity 80% and specificity 83%). Conclusions. CAC is related to inflammation in patients with RA.
Wiki-Health: A Big Data Platform for Health Sensor Data Management

Quickly evolving modern technologies such as cloud computing, Internet of things, and intelligent data analysis have created great opportunities for better living. The authors visualize the role these technological innovations will play in the healthcare sector as they spearhead a shift in focus from offering better healthcare services only to people with problems to helping everyone achieve a healthier lifestyle. In this chapter, the authors first discuss the existing and potential barriers followed by an in-depth demonstration of a service platform named Wiki-Health that takes advantage of cloud computing and Internet of things for personal well-being data management. It is a social platform, which is designed and implemented for data-driven and context-specific discovery of citizen communities in the areas of health, fitness, and well-being. At the end of the chapter, the authors analyse a case study to illustrate how the Wiki-Health platform can be used to serve a real world personal health training application.
Fingerprint classification using a homogeneity structure of fingerprint's orientation field and neural net

Fingerprint classification is important part of fingerprint identification systems that work on large databases. It provides fingerprint indexing, which results in efficient matching. This work presents usage of a homogeneity structure of fingerprint's orientation field for fingerprint indexing. The homogeneity structure is described through a quad-tree structure. A description of the quad-tree structure is the input vector for neural net that was used as a classification system. The system is tested with fingerprints of three different quality levels to provide real results.
Emergency Severity Index Scores Differ by Health Provider’s Gender andPatient’s Age

Background: Experimental research shows that laywomen express higher levels of empathy than men to pain suffering behaviors in others and female practitioners interact with and may prescribe different levels of pain medication to patients than male practitioners. Objectives: In this study we conduct a small medical records review to examine the possibility that female emergency department nurses assign lower levels (i.e., more urgent, serious, resource extensive) of emergency severity index (ESI) scores of patients presenting for care in the emergency department than male nurses, raising the possibility that patients receive disparate treatment during triage depending on the gender of medical staff. Methods: The patient-provided pain scores and the examiner-determined ESI scores of forty-eight male, emergency de- partment patients (21-89yrs, Mage = 57.2, SDage = 19.3) were examined across multiple visits, along with the gender of their triage examiner at each visit of (127 total patient/provider interactions). Results: A cross-classified mixed-effects model to analyze the influence of examiner gender on the triage scores that showed a significant Examiner Gender x Patient Age interaction. Further probing showed that female practitioners ascribed significantly lower ESI scores than male practitioners, although this effect was limited to patients younger than 55 years of age. Conclusion: These findings warrant larger-scale investigations of patient and examiner influences on patient treatment, which are necessary for creating more standardized protocols for reliably assessing emergency-care patients and for reducing health disparities in patient treatment quality.
Unconditionally-Secure Universally Composable Password-Based Key-Exchange based on One-Time Memory Tokens

We continue the recent trend in cryptography to study protocol design in presence of tamper-proof hardware tokens. We present a very efficient protocol for password-based authenticated key exchange based on the weak model of one-time memory tokens, recently introduced by Goldwasser et al. (Crypto 2008). Our protocol only requires four moves, very basic operations, and the sender to send ` tokens in the first step for passwords of length `. At the same time we achieve information-theoretic security in Canetti’s universal composition framework (FOCS 2001) against adaptive adversaries (assuming reliable erasure), even if the tokens are not guaranteed to be transferred in an authenticated way, i.e., even if the adversary can read or substitute transmitted tokens (as opposed to many previous efforts).
Feature-Points Based Shape Matching

In this paper, we propose a shape contexts based method which incorporates appearance similarity term into the correspondence estimation to improve the performance of shape matching. The optimal correspondence result then can be acquired by balancing the cost of matching and appearance similarity. On the other hand, a feature-points based matching algorithm is also presented to reduce the search space and improve the efficiency on shape matching. The algorithm is tested on two famous databases, namely, the database of MPEG-7 CE-Shape-1 part B and the coil-100 database. We also evaluate this algorithm on some images with noisy background. The experimental results show that our approach is robust and efficient in images with noise.
Effect of Reactive Power Limit Modeling on Maximum System Loading and Active and Reactive Power Markets

This paper presents a comparative investigation of various representations of reactive power limits in maximum loadability and active and reactive power market studies. Previously proposed optimal power flow (OPF) models for these types of analyses are first reviewed and briefly discussed. Different models for representing reactive power limits in these optimization problems are then presented, concentrating in particular on the proper modeling of the generators' capability curves as terminal voltages change, which has been identified as a shortcoming of previous studies. Comparative numerical analyses of the effect of various reactive power limit models in maximum loading and active and reactive power dispatch and pricing levels are presented and discussed, to thus quantify the effect these various limit representations have on the corresponding results. Two test systems, namely, the CIGRE-32 benchmark system and a 1211-bus dispatch model of a European network, are used for numerical studies. The presented results show that in most OPF applications, the improvement on the reactive power limits representation lead to subtle differences at the cost of increased computational complexity, which in some cases may be difficult to justify in practice.
Prevalence of Overweight, Obesity, and Thinness in Cameroon Urban Children and Adolescents

Objective. This study examined the prevalence of thinness, overweight, and obesity in Cameroon children ranging from 8 to 15 years old using several published references as evaluation tools. Methods. A stratified sample was used with eleven schools randomly selected, and data from 2689 children (52.2% girls) ranging from 8 to 15 years were analyzed. Weight and height were recorded and BMI was calculated. BMI cutoffs used to define nutritional status grades included two international and three national published indices which were compared to our database-derived cutoffs. Results. A prevalence of 9.5% thinness and 12.4% overweight including 1.9% obesity according to international references was detected. A 2.2% low-weight-for-age, 5.7% low-height-for-age, and 5.2% low-weight-for-height were identified. Overall, there were significant differences using calculations based on our database versus published reference values and between boys versus girls. Conclusions. This study demonstrates that prevalence of thinness, overweight, and obesity is similar to that of other leading-emerging countries reported within the last decade, yet it is still lower than prevalence in developed countries. Ethnic background and social environment have impact on prevalences, highlighting the importance of evaluating the Cameroon population based on locally derived database.
Uncertainty decoding for noise robust automatic speech recognition

This report presents uncertainty decoding as a method for robust automatic speech recognition for the Noise Robust Automatic Speech Recognition project funded by Toshiba Research Europe Limited. The effects of noise on speech recognition are reviewed and a general framework for noise robust speech recognition introduced. Common and related noise robustness techniques are described in the context of this framework. Uncertainty decoding is also presented in this framework with the goal of providing fast noise compensation through the propagation of uncertainty to the decoder. Two forms are discussed, the Joint and SPLICE methods, and evaluated on the medium vocabulary Resource Management corpus at a range of artificially produced noise levels. It was found that the uncertainty decoding algorithms did not meet the performance of a matched system, but were more accurate than the baseline SPLICE enhancement technique and low numbers of CMLLR transforms.
Improved Prediction of Preterm Delivery Using Empirical Mode Decomposition Analysis of Uterine Electromyography Signals

Preterm delivery increases the risk of infant mortality and morbidity, and therefore developing reliable methods for predicting its likelihood are of great importance. Previous work using uterine electromyography (EMG) recordings has shown that they may provide a promising and objective way for predicting risk of preterm delivery. However, to date attempts at utilizing computational approaches to achieve sufficient predictive confidence, in terms of area under the curve (AUC) values, have not achieved the high discrimination accuracy that a clinical application requires. In our study, we propose a new analytical approach for assessing the risk of preterm delivery using EMG recordings which firstly employs Empirical Mode Decomposition (EMD) to obtain their Intrinsic Mode Functions (IMF). Next, the entropy values of both instantaneous amplitude and instantaneous frequency of the first ten IMF components are computed in order to derive ratios of these two distinct components as features. Discrimination accuracy of this approach compared to those proposed previously was then calculated using six differently representative classifiers. Finally, three different electrode positions were analyzed for their prediction accuracy of preterm delivery in order to establish which uterine EMG recording location was optimal signal data. Overall, our results show a clear improvement in prediction accuracy of preterm delivery risk compared with previous approaches, achieving an impressive maximum AUC value of 0.986 when using signals from an electrode positioned below the navel. In sum, this provides a promising new method for analyzing uterine EMG signals to permit accurate clinical assessment of preterm delivery risk.
Social identity motivations and intergroup media attractiveness

In this experiment we manipulated three features (intergroup social comparison, outgroup character stereotypicality, intergroup intimacy) of an intergroup TV pilot proposal. We examined how two underlying social identity motivations (social enhancement, social uncertainty reduction) were gratified by the aforementioned features, and whether this gratification predicted media attractiveness. Findings indicate that when social comparison was manipulated to advantage the ingroup, intergroup media gratified existing social enhancement motivations and led to audiences rating the show as more entertaining and attractive. This finding was most clearly evident in the absence of intergroup romance. The gratification of social uncertainty reduction motivations was also shown to increase audience perceptions of intergroup media attractiveness, but outgroup stereotypicality was weakly associated with the gratification of this motivation. These results are discussed in terms of both theoretical implications as well as applications to media campaigns.
1 Arsenic ( Metallic ) ( ATSDR , 2000 )

1. Summary Acute, 8-hour and chronic reference exposure levels (RELs) were derived for inorganic arsenic including arsine. Inorganic arsenic causes a wide variety of toxic effects in humans and experimental animals including effects on development, the vascular system, the nervous system, blood, lung, and skin. The most sensitive acute effects were seen in mice (fetal development) whereas the most sensitive 8-hour and chronic effects were decreased intellectual function in children. The key values are summarized below.
Global Gene Expression Profile of Nasopharyngeal Carcinoma by Laser Capture Microdissection and Complementary DNA Microarrays

A number of genetic and epigenetic changes underlying the development of nasopharyngeal carcinomas have recently been identified. However, there is still limited information on the nature of the genes and gene products whose aberrant expression and activity promote the malignant conversion of nasopharyngeal epithelium. Here, we have performed a genome-wide transcriptome analysis by probing cDNA microarrays with fluorescent-labeled amplified RNA derived from laser capture microdissected cells procured from normal nasopharyngeal epithelium and areas of metaplasia-dysplasia and carcinoma from EBV-associated nasopharyngeal carcinomas. This approach enabled the identification of genes differentially expressed in each cell population, as well as numerous genes whose expression can help explain the aggressive clinical nature of this tumor type. For example, genes indicating cell cycle aberrations (cyclin D2, cyclin B1, activator of S-phase kinase, and the cell cycle checkpoint kinase, CHK1) and invasive-metastatic potential (matrix metalloproteinase 11, v-Ral, and integrin β4) were highly expressed in tumor cells. In contrast, genes underexpressed in tumors included genes involved in apoptosis (B-cell CLL/lymphoma 6, secretory leukocyte protease inhibitor, and calpastatin), cell structure (keratin 7 and carcinoembryonic antigen-related cell adhesion molecule 6), and putative tumor suppressor genes (H-Ras-like suppressor 3, retinoic acid receptor responder 1, and growth arrested specific 8) among others. Gene expression patterns also suggested alterations in the Wnt/β-catenin and transforming growth factor β pathways in nasopharyngeal carcinoma. Thus, expression profiles indicate that aberrant expression of growth, survival, and invasion-promoting genes may contribute to the molecular pathogenesis of nasopharyngeal carcinoma. Ultimately, this approach may facilitate the identification of clinical useful markers of disease progression and novel potential therapeutic targets for nasopharyngeal carcinoma.
Selective modulation of collagenase 1 gene expression by the chemotherapeutic agent doxorubicin.

Matrix metalloproteinases (MMPs) play a crucial role in tumor cell invasion and metastasis due to their ability to digest basement membrane and extracellular matrix components, thereby facilitating cell movement through connective tissues. At noncytotoxic concentrations, i.e., concentrations lower than those normally used in cancer chemotherapy, the anthracycline doxorubicin specifically inhibited collagenase 1 (MMP-1) gene expression in the highly invasive and metastatic human melanoma cell line A2058. This inhibition was specific for collagenase 1 because it did not affect the expression of two other MMPs, gelatinase A (MMP-2) and gelatinase B (MMP-9). The reduction in collagenase 1 expression correlated with a decrease in the invasive ability of tumor cells through a collagen type I matrix and was independent of the cytotoxic and antiproliferative effects usually associated with this anticancer drug. The selective modulation of collagenase 1 expression by nontoxic doses of doxorubicin suggests a novel application for this chemotherapeutic agent, perhaps in combination therapy, because it decreases the invasive/metastatic potential of melanoma cells that are otherwise unaffected by this drug.
Correlation between Inter-Blink Interval and Episodic Encoding during Movie Watching

Human eye blinking is cognitively suppressed to minimize loss of visual information for important real-world events. Despite the relationship between eye blinking and cognitive state, the effect of eye blinks on cognition in real-world environments has received limited research attention. In this study, we focused on the temporal pattern of inter-eye blink interval (IEBI) during movie watching and investigated its relationship with episodic memory. As a control condition, 24 healthy subjects watched a nature documentary that lacked a specific story line while electroencephalography was performed. Immediately after viewing the movie, the subjects were asked to report its most memorable scene. Four weeks later, subjects were asked to score 32 randomly selected scenes from the movie, based on how much they were able to remember and describe. The results showed that the average IEBI was significantly longer during the movie than in the control condition. In addition, the significant increase in IEBI when watching a movie coincided with the most memorable scenes of the movie. The results suggested that the interesting episodic narrative of the movie attracted the subjects’ visual attention relative to the documentary clip that did not have a story line. In the episodic memory test executed four weeks later, memory performance was significantly positively correlated with IEBI (p<0.001). In summary, IEBI may be a reliable bio-marker of the degree of concentration on naturalistic content that requires visual attention, such as a movie.
PETER SHOR ’ S FACTORIZING ALGORITHM 3 . 1 Shor ’ s Algorithm

Quantum computation, the ultimate goal of future computing, is an interesting field for researchers. The concept of quantum computation is based on basics of quantum mechanics. A quantum computer is a device for computation that makes direct use of quantum mechanical phenomena such as superposition and entanglement, to perform operations on data. The basic principle behind quantum computation is that quantum properties can be used to represent data and perform operations on these data. A quantum computer operates by manipulating the qubits with a fixed sequence of quantum logic gates. The sequence of gates to be applied is called a quantum algorithm. The field of quantum computation algorithm is fast moving and the scope is vast. Major quantum algorithms are summarized in this paper along with their applications. General Terms Quantum Algorithms.
Cross-Seeding of Misfolded Proteins: Implications for Etiology and Pathogenesis of Protein Misfolding Diseases

Accumulation of misfolded protein aggregates is a hallmark event in diverse diseases. These structures are able to seed their own polymerization by acting as aggregation nuclei both in vitro and in vivo. Recent studies in animal models suggest that misfolded proteins associated with different diseases can synergize in a heterologous fashion, potentiating pathological mechanisms and accelerating disease progression. The coexistence of misfolded protein aggregates has been described in patients affected by several protein misfolding disorders, suggesting a possible molecular cross-talk between pathological processes associated with different diseases. One putative mechanism for this cross-talk is a direct interaction between misfolded proteins, leading to cross-seeding of protein aggregation. This article summarizes the evidence for the cross-seeding phenomenon recently obtained in studies performed in vitro, in animal models, and in human patients, as well as the potential contribution of this mechanism to our understanding of the still elusive etiology and progression of maladies such as Alzheimer's disease, where no effective diagnostic or therapeutic strategies exist.
Integrating ontology languages and answer set programming

We integrate ontology languages and logic programming (LP) by extending disjunctive logic programs (DLPs) and their semantics in order to support inverses and an infinite universe, without introducing function symbols. We show that this extension is still decidable, and can be used to simulate, on the one hand, answer set programming with a finite universe, and on the other hand, several expressive description logics (DLs), which can be seen as ontology languages. The integration leads to a "best of both worlds": from the LP side it inherits a flexible and intuitive representation of knowledge, whereas the DLs side provides the possibility to represent infinite knowledge.
Building a sustainable university–community partnership: case study in science education

ABSTRACT Collaboration with the educational systems is needed to leverage the community to address the problem of declining interest in science education among young people, yet building effective university–community partnerships is a highly complex process. This research investigated partnership building in a regional science initiative designed to encourage and develop relationships between academic experts, scientists, engineers, and community. The study goals were to evaluate (1) the organizational structures that enable operation of a multi-organizational regional partnership; (2) the members’ perceptions of the common goals benefits and costs of participation in the partnership. Using the sequential mixed-method approach, 60 interviews conducted in the first phase were used to develop a questionnaire to which 224 partners responded. The research results provided a comprehensive evaluation of the university–community partnership. The results also demonstrated the effectiveness of a scale employed defining four hierarchical levels of partnership for assessing the development of any partnership over time.