LLukas22/scidocs huggingface dataset:
Accurate Heart Rate Monitoring During Physical Exercises Using PPG

Objective: The challenging task of heart rate (HR) estimation from the photoplethysmographic (PPG) signal, during intensive physical exercises, is tackled in this paper. Methods: The study presents a detailed analysis of a novel algorithm (WFPV) that exploits a Wiener filter to attenuate the motion artifacts, a phase vocoder to refine the HR estimate and user-adaptive post-processing to track the subject physiology. Additionally, an offline version of the HR estimation algorithm that uses Viterbi decoding is designed for scenarios that do not require online HR monitoring (WFPV+VD). The performance of the HR estimation systems is rigorously compared with existing algorithms on the publically available database of 23 PPG recordings. Results: On the whole dataset of 23 PPG recordings, the algorithms result in average absolute errors of 1.97 and 1.37 BPM in the online and offline modes, respectively. On the test dataset of 10 PPG recordings which were most corrupted with motion artifacts, WFPV has an error of 2.95 BPM on its own and 2.32 BPM in an ensemble with two existing algorithms. Conclusion:  The error rate is significantly reduced when compared with the state-of-the art PPG-based HR estimation methods. Significance: The proposed system is shown to be accurate in the presence of strong motion artifacts and in contrast to existing alternatives has very few free parameters to tune. The algorithm has a low computational cost and can be used for fitness tracking and health monitoring in wearable devices. The MATLAB implementation of the algorithm is provided online.
On the relationship between visual attributes and convolutional networks

One of the cornerstone principles of deep models is their abstraction capacity, i.e. their ability to learn abstract concepts from `simpler' ones. Through extensive experiments, we characterize the nature of the relationship between abstract concepts (specifically objects in images) learned by popular and high performing convolutional networks (conv-nets) and established mid-level representations used in computer vision (specifically semantic visual attributes). We focus on attributes due to their impact on several applications, such as object description, retrieval and mining, and active (and zero-shot) learning. Among the findings we uncover, we show empirical evidence of the existence of Attribute Centric Nodes (ACNs) within a conv-net, which is trained to recognize objects (not attributes) in images. These special conv-net nodes (1) collectively encode information pertinent to visual attribute representation and discrimination, (2) are unevenly and sparsely distribution across all layers of the conv-net, and (3) play an important role in conv-net based object recognition.
Integrative analysis of multi-dimensional imaging genomics data for Alzheimer's disease prediction

In this paper, we explore the effects of integrating multi-dimensional imaging genomics data for Alzheimer's disease (AD) prediction using machine learning approaches. Precisely, we compare our three recent proposed feature selection methods [i.e., multiple kernel learning (MKL), high-order graph matching based feature selection (HGM-FS), sparse multimodal learning (SMML)] using four widely-used modalities [i.e., magnetic resonance imaging (MRI), positron emission tomography (PET), cerebrospinal fluid (CSF), and genetic modality single-nucleotide polymorphism (SNP)]. This study demonstrates the performance of each method using these modalities individually or integratively, and may be valuable to clinical tests in practice. Our experimental results suggest that for AD prediction, in general, (1) in terms of accuracy, PET is the best modality; (2) Even though the discriminant power of genetic SNP features is weak, adding this modality to other modalities does help improve the classification accuracy; (3) HGM-FS works best among the three feature selection methods; (4) Some of the selected features are shared by all the feature selection methods, which may have high correlation with the disease. Using all the modalities on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, the best accuracies, described as (mean ± standard deviation)%, among the three methods are (76.2 ± 11.3)% for AD vs. MCI, (94.8 ± 7.3)% for AD vs. HC, (76.5 ± 11.1)% for MCI vs. HC, and (71.0 ± 8.4)% for AD vs. MCI vs. HC, respectively.
Investigating students' perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system

Although the benefits of e-learning have been discussed in various previous studies; it is a critical issue of better understanding the reasons why some learners are dissatisfied with the e-learning experience. Therefore, this research investigates learners’ satisfaction, behavioral intentions, and the effectiveness of the Blackboard e-learning system. A total of 424 university students were surveyed using a standard questionnaire. The results showed that perceived self-efficacy is a critical factor that influences learners’ satisfaction with the Blackboard e-learning system. Perceived usefulness and perceived satisfaction both contribute to the learners’ behavioral intention to use the e-learning system. Furthermore, e-learning effectiveness can be influenced by multimedia instruction, interactive learning activities, and e-learning system quality. This research proposes a conceptual model for understanding learners’ satisfaction, behavioral intention, and effectiveness of using the e-learning system. 2007 Elsevier Ltd. All rights reserved.
Nonlinear resistive electric field grading Part 2: Materials and applications

The article emphasizes the ability of new nonlinear resistive materials to be tuned for specific applications, which opens up new possibilities in designing electric field control of products for medium and high voltage applications.
Thomas Jefferson: An Intimate History

This portrayal of a complex man, this biography explores Thomas Jefferson's inner life and his relationship with Sally Hemings. Jefferson is shown to be a man of passion and feeling. The author shows how Jefferson wrestled with issues of revolution, religion, power, race and love - ambivalences that exerted a powerful influence on his political writing and decision making.
Characterising and exploiting workloads of highly interactive video-on-demand

This paper presents a detailed characterisation of user behaviour for a series of interactive video experiments over a 12 month period, in which we served popular sporting and musical content. In addition to generic VCR-like features, our custom-built video-on-demand application provides advanced interactivity features such as bookmarking. The dramatic impact of such functionality on how users consume content is studied and analysed. We discuss in detail how this user behaviour can be exploited by content distributors to improve user experience. Specifically, we study how simple dynamic bookmark placement and interactivity-aware content pre-fetching and replication can reduce the impact of highly interactive media on CDN performance.
A longitudinal examination of the link between youth physical fitness and academic achievement.

BACKGROUND
Childhood obesity has been linked with other persistent health problems, but research is just beginning to examine its relationship with academic performance. This article tracks students longitudinally to examine the ways student physical fitness and changes in fitness align with school performance.


METHODS
Using matched administrative data and individual growth modeling, we examine the relationship between academic achievement and overall physical fitness longitudinally from fourth to seventh and sixth to ninth grades for students in a California community.


RESULTS
Comparing those who are persistently fit to those who are persistently unfit, we find disparities in both math and English language arts test scores. These academic disparities begin even before students begin fitness testing in fifth grade and are larger for girls and Latinos. Overall physical fitness is a better predictor of academic achievement than obesity as measured by body mass index. Socioeconomic status acts as a buffer for those who have poor physical fitness but strong academic performance.


CONCLUSION
The findings indicate the presence of a physical fitness achievement gap that has consequences for potential students' future educational and health outcomes. This gap begins as early as fourth grade, which is before physical fitness testing begins in California.
Analysis of shade, temperature and hydrogen peroxide concentration during dental bleaching: in vitro study with the KTP and diode lasers

Many dental bleaching techniques are now available, several of them using a laser source. However, the literature on the exact role of coherent light in the biochemical reaction of the whitening process is very discordant. The aims of this in vitro study were: (1) to compare two different laser sources, a KTP laser with a wavelength of 532 nm and a diode laser with a wavelength of 808 nm, during dental bleaching, and (2) to investigate the relationships among changes in gel temperature, tooth shade and hydrogen peroxide (HP) concentration during laser irradiation. Altogether, 116 bovine teeth were bleached using a 30% HP gel, some of them with gel only and others with gel plus one of the two lasers (532 or 808 nm) at two different powers (2 and 4 W). The KTP laser produced a significant shade variation with a minimal temperature increase. The diode laser led to a higher temperature increase with a greater reduction in HP concentration, but the change in shade was only statistically significant with a power of 4 W. At a power of 2 W, the KTP laser caused a greater change in shade than the diode laser. No significant correlations were found among temperature, HP concentration and shade variation. The KTP laser appears to provide better results with less dangerous thermal increases than the diode laser. This might call into question most of the literature affirming that the action of laser bleaching is by increasing the gel temperature and, consequently, the speed of the redox reaction. Further study is required to investigate the correlations between the parameters investigated and efficacy of the bleaching process.
Product recommendation with temporal dynamics

In many E-commerce recommender systems, a special class of recommendation involves recommending items to users in a life cycle. For example, customers who have babies will shop on Diapers.com within a relatively long period, and purchase different products for babies within different growth stages. Traditional recommendation algorithms produce recommendation lists similar to items that the target user has accessed before (content filtering), or compute recommendation by analyzing the items purchased by the users who are similar to the target user (collaborative filtering). Such recommendation paradigms cannot effectively resolve the situation with a life cycle, i.e., the need of customers within different stages might vary significantly. In this paper, we model users’ behavior with life cycles by employing handcrafted item taxonomies, of which the background knowledge can be tailored for the computation of personalized recommendation. In particular, our method first formalizes a user’s long-term behavior using the item taxonomy, and then identifies the exact stage of the user. By incorporating collaborative filtering into recommendation, we can easily provide a personalized item list to the user through other similar users within the same stage. An empirical evaluation conducted on a purchasing data collection obtained from Diapers.com demonstrates the efficacy of our proposed method. 2012 Elsevier Ltd. All rights reserved.
Knowledge capture for power engineering human resource needs

This is a summary of the presentation on the panel titled "Issues and Challenges in Power Engineering Careers at the 2005 IEEE/PES GM in San Francisco, CA.
Safety and efficacy of bivalirudin with glycoprotein IIb/IIIa for high-risk percutaneous coronary intervention.

AIMS
The aim of the study was to assess the safety and efficacy of bivalirudin + glycoprotein (Gp) IIb/IIIa inhibitor as compared to unfractionated heparin (UFH) + Gp IIb/IIIa inhibitor in high risk patients undergoing elective percutaneous coronary intervention (PCI). The primary end point was time to sheath removal and ambulation where as peri-procedure myocardial damage, access site bleeding and major adverse cardiac events (MACE) rates were secondary end points.


METHODS
One hundred and one high risk patients undergoing elective PCI were randomly assigned to either bivalirudin + GpIIb/IIIa inhibitor or UFH + Gp IIb/IIIa inhibitor. PCI was performed by standard technique and activated clotting time was monitored immediately on arrival to recovery area and every 60 min thereafter. Sheath were pulled out once ACT was below 150 seconds and patients were mobilized 6hrs after sheath were removed. Peri-procedure myocardial damage was assessed by serial Trop I levels.


RESULTS
Patient assigned to bivalirudin + tirofiban has significantly reduced time to sheath removal and ambulation as compared to those who received UFH + tirofiban (p < 0.0001) although peak Act did not differ in the groups. Peak Trop I levels were significantly lower in bivalirudin + tirofiban group (p = 0.023) and peri-procedure Trop I elevation occurred in significantly lower number of patients treated with bivalirudin + tirofiban (p = 0.029).


CONCLUSIONS
The combination of bivalirudin + tirofiban was safe and effective as compared to UFH + tirofiban in high risk patients undergoing elective PCI.
The impact of shopping mall development on small township retailers

The retail sector forms a critical element of a community’s economic and social welfare. It provides people with choices and services. These choices were until recently very limited in township areas. The pre-1994 retail landscape was dominated by small, often informal businesses offering basic household necessities to relatively low income earners. This has resulted in township residents’ preference to shop outside townships, known as ‘outshopping’. Rapid income growth of township residents since 1994 resulted in a substantial increase in consumer expenditure in these areas, known as ‘in-bound shopping’. This lucrative emerging market forms the last retail frontier in South Africa and is being explored by national retailers, especially supermarket chains. This article is aimed at establishing the impact of shopping mall development in townships on the traditional small township retailers including spaza/tuck shops. The net balance sheet on the impact of shopping mall development on small township retailers clearly suggests a decline in the township retailers’ market share. A change in small business model towards, inter alia, effective customer service with a small dedicated assortment of merchandise, satisfaction of emergency needs, selling in small units and extension of credit facilities may result in the survival of some small township retailers (albeit often at a smaller turnover). JEL L81
Formation of a carbon fiber/polyhedral oligomeric silsesquioxane/carbon nanotube hybrid reinforcement and its effect on the interfacial properties of carbon fiber/epoxy composites

A carbon fiber/polyhedral oligomeric silsesquioxane/carbon nanotube (CF–POSS–CNT) hybrid reinforcement was prepared by grafting CNTs onto the carbon fiber surface using octaglycidyldimethylsilyl POSS as the linkage in an attempt to improve the interfacial properties between carbon fibers and an epoxy matrix. X-ray photoelectron spectroscopy, scanning electron microscopy, dynamic contact angle analysis and single fiber tensile testing were performed to characterize the hybrid reinforcements. Interlaminar shear strength (ILSS), impact toughness, dynamic mechanical analysis and force modulation atomic force microscopy were carried out to investigate the interfacial properties of the composites. Experimental results show that POSS and CNTs are grafted uniformly on the fiber surface and significantly increase the fiber surface roughness. The polar functional groups and surface energy of carbon fibers are obviously increased after the modification. Single fiber tensile testing results demonstrate that the functionalization does not lead to any discernable decrease in the fiber tensile strength. Mechanical property test results indicate the ILSS and impact toughness are enhanced. The storage modulus and service temperature increase by 11 GPa and 17 C, respectively. POSS and CNTs effectively enhance the interfacial adhesion of the composites by improving resin wettability, increasing chemical bonding and mechanical interlocking. 2011 Elsevier Ltd. All rights reserved.
Radon transform processing for accurate centreline estimation of thick lines

The accurate fitting of a line to noisy measurements of points along its length is a much studied problem in the literature. In this paper, we interpret the maximum-likelihood estimator (MLE) for line-direction and perpendicular offset estimation in terms of convolution on the RADON Transform of an image which is ideal in a certain sense. We use our convolution-based MLE approach to find good estimates for the parameters of a line in digital images. By interpreting the MLE as a minimal variance estimator, it is possible to show how the conventional RADON Transform can be used to estimate thick (wider than one pixel) line segment parameters, i.e., the direction of the centreline and its perpendicular offset. We compare our new method to the HOUGH Tranform as well as the CRAMÉRRAO Lower Bound in synthetic digital images.
Reinforcement Learning for Coreference Resolution

Coreference resolution is an important step for a number of higher level NLP tasks that involve natural language understanding. Conventional methods treat this task as a classification problem [2] where a pair of mentions are classified as coreferents or as a clustering problem where each cluster represents a named entity. The availability of partial structured information for supervision motivates the formulation of this problem in a reinforcement learning setting. Using similarity between two clusterings as our reward, we propose to employ function approximation to learn generalizable rules for coreference resolution.
Methodology for Risk Analysis of Dam Gates and Associated Operating Equipment Using Fault Tree Analysis

With limited maintenance dedicated to aging dam spillway gate structures, there is an increased risk of gate inoperability and corresponding dam failure due to malfunction or inadequate design. This report summarizes research on methodologies to assist in quantifying risks related to dam gates and associated operating equipment, and how those risks relate to overall spillway failure risk. The objective of the research was to demonstrate how fault tree analytical methods may be applied to improve the quality of dam gate risk analysis. Two different methods of prescreening analysis are presented and evaluated. The first uses probabilities for more events, defined more precisely than in standard practice, and adds criticality ranking; the second uses more traditional estimation of failure probabilities in conjunction with subsystem importance-ranking factors to estimate overall gate system failure probability. Both methods can be linked qualitatively with the Lafitte risk method through event costs and consequences to determine the overall risk for a dam spillway system. Enhancement of the two demonstrated methods would require a direct application of the methods to an existing dam gate system. Also, additional research would be necessary to better determine the risk consequence factor, α, used in the Lafitte equation for calculating overall risk. DISCLAIMER: The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED. DO NOT RETURN IT TO THE ORIGINATOR.
Comparison of Binaural Interaction Component ( BIC ) in Symmetrical and Asymmetrical Hearing Loss : Pilot Study

Background and Objective: Binaural interaction component has been seen to be effective in assessing the binaural interaction process in normal hearing individuals. However, there is a lack of literature regarding the effects of SNHL on the Binaural Interaction Component of ABR. Hence, it is necessary to study binaural interaction occurs at the brainstem when there is an associated hearing impairment. Methods: Three groups of participants in the age range of 30 to 55 years were taken for study i.e. one control group and two experimental groups (symmetrical and asymmetrical hearing loss). The binaural interaction component was determined by subtracting the binaurally evoked auditory potentials from the sum of the monaural auditory evoked potentials: BIC= [{left monaural + right monaural)-binaural}. The latency and amplitude of V peak was estimated for click evoked ABR for monaural and binaural recordings. Results: One way ANOVA revealed a significant difference for binaural interaction component in terms of latency between different groups. One-way ANOVA also showed no significant difference seen between the three different groups in terms of amplitude. Conclusion: The binaural interaction component of auditory brainstem response can be used to evaluate the binaural interaction in symmetrical and asymmetrical hearing loss. This will be helpful to circumvent the effect of peripheral hearing loss in binaural processing of the auditory system. Additionally the test does not require any behavioral cooperation from the client, hence can be administered easily.
Assessment of four DNA fragments (COI, 16S rDNA, ITS2, 12S rDNA) for species identification of the Ixodida (Acari: Ixodida)

The 5’ region of cytochrome oxidase I (COI) is the standard marker for DNA barcoding. However, COI has proved to be of limited use in identifying some species, and for some taxa, the coding sequence is not efficiently amplified by PCR. These deficiencies lead to uncertainty as to whether COI is the most suitable barcoding fragment for species identification of ticks. In this study, we directly compared the relative effectiveness of COI, 16S ribosomal DNA (rDNA), nuclear ribosomal internal transcribed spacer 2 (ITS2) and 12S rDNA for tick species identification. A total of 307 sequences from 84 specimens representing eight tick species were acquired by PCR. Besides the 1,834 published sequences of 189 tick species from GenBank and the Barcode of Life Database, 430 unpublished sequences representing 59 tick species were also successfully screened by Bayesian analyses. Thereafter, the performance of the four DNA markers to identify tick species was evaluated by identification success rates given by these markers using nearest neighbour (NN), BLASTn, liberal tree-based or liberal tree-based (+threshold) methods. Genetic divergence analyses showed that the intra-specific divergence of each marker was much lower than the inter-specific divergence. Our results indicated that the rates of correct sequence identification for all four markers (COI, 16S rDNA, ITS2, 12S rDNA) were very high (> 96%) when using the NN methodology. We also found that COI was not significantly better than the other markers in terms of its rate of correct sequence identification. Overall, BLASTn and NN methods produced higher rates of correct species identification than that produced by the liberal tree-based methods (+threshold or otherwise). As the standard DNA barcode, COI should be the first choice for tick species identification, while 16S rDNA, ITS2, and 12S rDNA could be used when COI does not produce reliable results. Besides, NN and BLASTn are efficient methods for species identification of ticks.