Miracle-dz/UniFAR-FTUs huggingface dataset:
Zinc Status Biomarkers and Cardiometabolic Risk Factors in Metabolic Syndrome: A Case Control Study

Metabolic syndrome (MS) involves pathophysiological alterations that might compromise zinc status. The aim of this study was to evaluate zinc status biomarkers and their associations with cardiometabolic factors in patients with MS. Our case control study included 88 patients with MS and 37 controls. We performed clinical and anthropometric assessments and obtained lipid, glycemic, and inflammatory profiles. We also evaluated zinc intake, plasma zinc, erythrocyte zinc, and 24-h urinary zinc excretion. The average zinc intake was significantly lower in the MS group (p < 0.001). Regression models indicated no significant differences in plasma zinc concentration (all p > 0.05) between the two groups. We found significantly higher erythrocyte zinc concentration in the MS group (p < 0.001) independent from co-variable adjustments. Twenty-four hour urinary zinc excretion was significantly higher in the MS group (p = 0.008), and adjustments for age and sex explained 21% of the difference (R2 = 0.21, p < 0.001). There were significant associations between zincuria and fasting blood glucose concentration (r = 0.479), waist circumference (r = 0.253), triglyceride concentration (r = 0.360), glycated hemoglobin concentration (r = 0.250), homeostatic model assessment—insulin resistance (r = 0.223), and high-sensitivity C-reactive protein concentration (r = 0.427) (all p < 0.05) in the MS group. Patients with MS had alterations in zinc metabolism mainly characterized by an increase in erythrocyte zinc and higher zincuria.
Using distance learning electronic tools within the class to engage ADHD students: A key to inclusion?

Research increasingly emphasizes the possible development and benefits of technological use in distance learning. Electronic distance learning tools however may have a very different educational use than the one they were originally conceived to meet. With attention deficit disorder being increasingly diagnosed in secondary students and inclusion policy dictating a differentiated teaching approach with the mainstream classroom, these distance learning tools may enable mainstream classroom teachers to address attention issues while they maintain regular curriculum delivery with other students. This article will review existing literature on distance learning tools and differentiated teaching suitable to ADHD students and assess whether an eco-systemic "match" between the classroom needs of these students and the potential of these electronic tools may be possible and may have escaped pedagogical theory to date.
A transferrin-target magnetic/fluorescent dual-mode probe significantly enhances the diagnosis of non-small cell lung cancer

To enhance the diagnosis of non-small cell lung cancer (NSCLC), we prepared a dual-modal probe Cy5.5-Tf-Gd-DTPA. Gd-DTPA and near-infrared (NIR) dyes were conjugated to holo-Transferrin (Tf) sequentially, the result of ICP-AES and UV showed 25 Gd ions and 1 Cy5.5 could be loaded per protein, respectively. The calculated longitudinal relaxivity R1 of Cy5.5-Tf-DTPA-Gd was 4.21 mM−1S−1 per Gd while that of Magnevist (Gd-DTPA) was only 4.02 mM−1S−1. Confocal laser scanning microscopy and immunohistochemical analyses revealed that the Cy5.5-Tf-DTPA-Gd was localized and accumulated in cytoplasmic vesicles; the cell toxicity assay showed no apparent toxicity. MR and NIR imaging of mice with subcutaneous H1299 xenografte tumors following intravenous injection of Cy5.5-Tf-DTPA-Gd revealed a strong positive contrast of the tumors, which caused a longer lasting enhancement of the MRI signal and fluorescence signal. Taken together, these studies indicate that Cy5.5-Tf-DTPA-Gd could be a good agent for MR/NIRF dual mode applications to detect both tumor in situ and its metastasis.
A software system for data mining with twitter

The rise of social network usage through mobile devices makes the rigorous analysis of these systems of paramount importance for intelligence gathering and decision making. This paper describes the outcome of a multidisciplinary project carried out for the purpose of Twitter data collection and analysis. In particular, a proposal for enabling the discovery of spatial patterns within geo-located Twitter content has been investigated and implemented.
Improved Lattice Reduction-Aided MIMO Successive Interference Cancellation Under Imperfect Channel Estimation

Lattice reduction (LR) and successive interference cancellation (SIC) are two well-known techniques that can be used to improve detection performance over linear detectors for multiple-input multiple-output (MIMO) systems. However, the LR technique and the SIC technique usually need perfect knowledge on the channel at the receiver, and the use of these techniques with an erroneous channel matrix even worsens the detection performance compared to linear detectors. In this correspondence, we shall show how to modify these techniques to make them robust under imperfect channel estimation. Information needed for the proposed algorithm is moderate; the variance of channel estimation error is the only requirement. Furthermore, our algorithm is not sensitive to the error in the variance of channel estimation error.
The MERLIN corpus: Learner language and the CEFR

The MERLIN corpus is a written learner corpus for Czech, German,and Italian that has been designed to illustrate the Common European Framework of Reference for Languages (CEFR) with authentic learner data. The corpus contains 2,290 learner texts produced in standardized language certifications covering CEFR levels A1-C1. The MERLIN annotation scheme includes a wide range of language characteristics that enable research into the empirical foundations of the CEFR scales and provide language teachers, test developers, and Second Language Acquisition researchers with concrete examples of learner performance and progress across multiple proficiency levels. For computational linguistics, it provide a range of authentic learner data for three target languages, supporting a broadening of the scope of research in areas such as automatic proficiency classification or native language identification. The annotated corpus and related information will be freely available as a corpus resource and through a freely accessible, didactically-oriented online platform.
An empirical study of hall and hofstede's cultural values: a content analysis of internet advertising in korea and the united states (edward t. hall, geert hofstede)

This study intends to test the idea that advertising reflects cultural values through advertising appeals in a predictable manner. Hall and Hofstede's cultural values are employed as theoretical frameworks for comparing cultural values reflected in Internet advertising in Korea and the United States. Their cultural value systems were related to the modified version of Pollay's advertising appeal system. A content analysis of 600 advertising websites was performed to seek answers to the following questions: What are the dominant cultural values manifest in Korean and U.S. Internet advertising? In what cultural value dimensions does Internet advertising differ between Korea and the US? Are there any differences in the use of information, creative, and technological elements in Korean and U.S. Internet advertising? If there are differences, how are they related with cultural values and why? Similarities were visible in the use of primary appeals, information cues, and creative strategies, but when the ads were examined within the theoretical frameworks, a clear pattern of dissimilarities were observed between Korean and U.S. Internet advertising, supporting the idea that the observed between-country differences were attributable to between-country differences in cultural values. Despite the similarities in the use of primary information cues and creative strategies, significant between-country differences were observed in the quantity and types of information cues and the use of Symbolic Assertion, Repeated Assertion, and Obligation strategy. The use of technological elements such as text links and animated images was also significantly different between the two countries. This study demonstrated the effectiveness of the theoretical frameworks and their linkages with advertising appeals in visualizing a broad representative picture of cultural differences in Internet advertising. However, the mixed results of the study suggest that neither a perfectly standardized nor a specialized approach yet exists in Internet advertising. The author speculates that several factors may explain why neither of these “ideal-type” advertising strategies prevails in Internet advertising: strong medium-specific characteristics, the time lag to adopt innovative technology, integration of the world economy, and changing values within a single culture.
Query Optimization by Predicate Move-Around

Query optimization which is done by making a graph of the query and moving predicates around in the graph so that they will be applied early in the optimized query generated from the graph. Predicates are first propagated up from child nodes of the graph to parent nodes and then down into different child nodes. After the predicates have been moved, redundant predicates are detected and removed. Predicates are moved through aggregation operations and new predicates are deduced from aggregation operations and from functional dependencies. The optimization is not dependent on join order and works where nodes of the graph cannot be merged.
A Text Representation and Retrieval Method Based on Concept Algebra

This paper introduces the concept algebra (CA) theory as a basis for the conceptual representation and the derivation of text processing to realize a semantic based retrieval system. We also take advantage of Hownet to create the concept attributes space for concept algebra. With the help of LTP, we get the key words and their dependent relations of every sentence to build the CA concept representation of the content with a five-tuple. Concepts make it possible to express both the keyword itself and the semantic relation with its context. According to the demands of text retrieval, some CA operations are optimized to calculate the relations and similarity between concepts. Besides, a text retrieval system framework which processes information based on the concept relations at a concept level is also proposed to verify the advantages of our method.
Towards Realistic Vehicular Network Modeling Using Planet-scale Public Webcams

Realistic modeling of vehicular mobility has been particularly challenging due to a lack of large libraries of measurements in the research community. In this paper we introduce a novel method for large-scale monitoring, analysis, and identification of spatio-temporal models for vehicular mobility using the freely available online webcams in cities across the globe. We collect vehicular mobility traces from 2,700 traffic webcams in 10 different cities for several months and generate a mobility dataset of 7.5 Terabytes consisting of 125 million of images. To the best of our knowl- edge, this is the largest data set ever used in such study. To process and analyze this data, we propose an efficient and scalable algorithm to estimate traffic density based on background image subtraction. Initial results show that at least 82% of individual cameras with less than 5% deviation from four cities follow Loglogistic distribution and also 94% cameras from Toronto follow gamma distribution. The aggregate results from each city also demonstrate that Log- Logistic and gamma distribution pass the KS-test with 95% confidence. Furthermore, many of the camera traces exhibit long range dependence, with self-similarity evident in the aggregates of traffic (per city). We believe our novel data collection method and dataset provide a much needed contribution to the research community for realistic modeling of vehicular networks and mobility.
Comparison of Mllr and Cdcn for Speech Recognition in Additive Noise by Experiments

This paper investigates the problem of robust speech recognition in additive noise. Model compensation and cepstral feature compensation techniques are evaluated and compared by experiments. The approaches considered here are MLLR and CDCN. Both approaches can be combined with CMN, which is a simple but efficient approach for robust speech recognition. Different combinations of CDCN and CMN are investigated in this paper. Noisy speech is simulated by adding different noise to clean speech with different SNR. Experiments are implemented on an isolated word recognition system. And the experimental results show that MLLR can give better performance in clean and light degraded environments, while CDCN can provide better in degraded conditions.
Energy reducing dynamic multi-dimensional resource allocation in cloud data center

Consolidation virtual machine (VM) on fewer physical servers is an efficient way to reduce energy consumption in data center. However, VMs often have inherent dependencies which bring complex load interactions among the underlying physical servers. Unreasonable migration will lead to a decline in network performance. In this paper, aiming at energy saving, we propose an application-aware policy in VM consolidation process. Moreover, in order to guarantee that the migrated VMs can be efficiently placed on physical servers determined by the application-aware policy, we also propose a multi-dimensional resource allocation algorithm (MDRA). Experiment results show that the proposed application-aware policy can efficiently reduce energy consumption as well as improving network performance. And the proposed MDRA algorithm can ensure the effectiveness of our policy.
Ultra-fast noise immune CMOS threshold logic gates

This paper details a systematic method for significantly improving the noise margins of very fast threshold gates. The method is based on adding nonlinear terms determined from the Boolean form of the threshold function to be implemented. Simulation results support the theoretical claims. Finally, two methods for drastically reducing the dissipated power of such threshold gates down to <50%, and respectively <10% are also suggested.
Quantifying the Limits and Success of Extractive Summarization Systems Across Domains

This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and legal documents. We present a study that explores the summary space of each domain via an exhaustive search strategy, and finds the probability density function (pdf) of the ROUGE score distributions for each domain. We then use this pdf to calculate the percentile rank of extractive summarization systems. Our results introduce a new way to judge the success of automatic summarization systems and bring quantified explanations to questions such as why it was so hard for the systems to date to have a statistically significant improvement over the lead baseline in the news domain.
Understanding Technology Mediated Learning in Higher Education: A Repertory Grid Approach

Given the considerable opportunities that Web 2.0 technologies are seen to present for the enhancement of learning and teaching, understanding what motivates today’s students to use this technology in their learning is crucial. Drawing from technology mediated learning (TML) and Uses and Gratifications (U&G) perspectives, this study investigates university students’ motivations for using Web 2.0 technologies in learning. The Repertory Grid Interview technique (RGT) is used to interview 16 participants and capture their technology use motivations. A grounded approach was used to resolve eleven categories of motivations: Access and Content Control, Accessibility, Communication Efficiency, Communication Mode, Communication Quality, Course Management, Information Seeking, Interaction, Learning Capability, Managing Contents, and Self-Disclosure. The findings suggest that today’s students have different motivations for using technologies when it comes to learning.
Relations between cognitive control and emotion in typically developing children

Objective: The goal of this study was to investigate relations between aspects of cognitive control and emotion in typically developing children, 7 to 9 years of age. This was investigated by examining performance on n-back working memory tasks that varied according to the level of cognitive control and emotion (e.g., faces, reward value) processing required. Relations between n-back performance and parental questionnaires of behavior were also examined. Participants & Methods: Participants included 77 typically developing children, 7 to 9 years of age. Each participant completed two novel n-back tasks. The first task involved working memory (0-back, 1-back, and 2-back levels) for emotional faces (neutral, happy, sad). The second task involved working memory (0-back, 1-back, and 2-back levels) for number stimuli with differing levels of reward (two tokens, six tokens). Matrix Reasoning was also completed as a screening measure of cognitive function. Parents completed a Child History questionnaire, the BRIEF, Conners 3 AI-Parent, and the Emotion Questionnaire. iv Results: No significant main effect was found for emotive content of stimuli or reward value. A significant effect of n-back level was found, both in terms of per hit RT and accuracy rates for both Emotive and Reward n-back. Significant relations were found between age and Sad conditions on 1-back and 2-back of the Emotive n-back, as well as 2-back conditions in the Reward n-back. No relations were found between BRIEF scales and performance on either n-back task. Significant correlations were found between Emotionality and accuracy measures of the Reward n-back task. Conclusions: This study made several important contributions to understanding emotion and cognitive control interplay. These contributions include introducing novel tasks for assessing this interplay, and providing insight on developmental relations and interaction between emotion and working memory and individual differences in emotionality in day to day life. Results are discussed with respect to theories of emotional and cognitive control interplay, temperament and individual differences, and the development of cognitive control. Directions for future research and implications are discussed.
System design and converter control for super capacitor and battery hybrid energy system of compact electric vehicles

In this paper, two main aspects of battery and super capacitor (SC) hybrid energy storage system (HESS) for a compact electric vehicle prototype are introduced. The aspect of system design for EV prototype is presented in detail. The capacity decision method of battery and super capacitor banks for EV application is introduced. For the aspect of control of hybrid energy system, a novel three-layer control strategy for the EV energy and power management is proposed. In order to share the power flow between SC and battery banks, the output current control of super capacitor banks using on three-level converter topologies is proposed. The converter selection and current control method are also presented. All of the works give guidance for designing our EV prototype and HESS platform, which is powered by hybrid energy system as the platform of our further research.
SpeX: A Medium‐Resolution 0.8–5.5 Micron Spectrograph and Imager for the NASA Infrared Telescope Facility

We present the design, construction, and performance of SpeX, a medium‐resolution 0.8–5.5 μm cryogenic spectrograph and imager, now in operation at the 3.0 m NASA Infrared Telescope Facility (IRTF) on Mauna Kea. The design uses prism cross‐dispersers and gratings to provide resolving powers up to R∼2000 simultaneously across 0.8–2.4, 1.9–4.2, or 2.4–5.5 μm, with a 15″ long slit. A high‐throughput low‐resolution R∼200 prism mode is also provided for faint‐object and occultation spectroscopy. Single‐order 60″ long‐slit modes with resolving powers up to R∼2000 are available for extended objects. The spectrograph employs an Aladdin 3 1024 × 1024 InSb array and uses narrow slits and a spatial scale of 0. ″15 pixel -1 for optimum sensitivity on point sources. An autonomous infrared slit viewer is used for object acquisition, infrared guiding, and scientific imaging in the wavelength range 0.8–5.5 μm. The imager employs an Aladdin 2 512 × 512 InSb array that covers a 60′′ × 60′′ field of view at 0. ″12 pixel -1. SpeX was successfully commissioned on IRTF during 2000 May, June, and July. Astronomical observations are presented to illustrate performance.
A load balancing mechanism based on ant colony and complex network theory in open cloud computing federation

Although cloud computing is generally recognized as a technology which will has a significant impact on IT in the future. However, Cloud computing is still in its infancy, many crucial problems need to be solved for the realization of the fine scenery which theoretically depicted by cloud computing. Load balancing is one of these problems; it plays a very important role in the realization of Open Cloud Computing Federation. We proposal a load balancing mechanism based on ant colony and complex network theory in open cloud computing federation in this paper, it improves many aspects of the related Ant Colony algorithms which proposed to realize load balancing in distributed system, Furthermore, this mechanism take the characteristic of Complex Network into consideration. Finally, the performance of this mechanism is qualitatively analyzed, and a prototype is developed to enable the quantitative analysis, simulation results manifest the analysis.
The Impact of Obesity on Employment

The objective of this paper is to empirically estimate the impact of obesity on employment probability of Canadian men and women. The paper considers the possible endogeneity of obesity variable in employment equation. To take into account the endogeneity issue, the paper utilized recursive bivariate probit approach. Over all results suggest that obesity has a significant positive effect on employment in male sample while it has significant negative impact on female employment.
Do Grammars Minimize Dependency Length?

A well-established principle of language is that there is a preference for closely related words to be close together in the sentence. This can be expressed as a preference for dependency length minimization (DLM). In this study, we explore quantitatively the degree to which natural languages reflect DLM. We extract the dependencies from natural language text and reorder the words in such a way as to minimize dependency length. Comparing the original text with these optimal linearizations (and also with random linearizations) reveals the degree to which natural language minimizes dependency length. Tests on English data show that English shows a strong effect of DLM, with dependency length much closer to optimal than to random; the optimal English grammar also has many specific features in common with English. In German, too, dependency length is significantly less than random, but the effect is much weaker than in English. We conclude by speculating about some possible reasons for this difference between English and German.