LLukas22/scidocs huggingface dataset:
Benefits , impediments and critical success factors in B 2 C E-business adoption

This paper reports the results of a study carried out to assess the benefits, impediments and major critical success factors in adopting business to consumer e-business solutions. A case study method of investigation was used, and the experiences of six online companies and two bricks and mortar companies were documented. The major impediments identified are: leadership issues, operational issues, technology, and ineffective solution design. The critical success factors in the adoption of e-business are identified as: combining e-business knowledge, value proposition and delivery measurement, customer satisfaction and retention, monitoring internal processes and competitor activity, and finally building trust. Findings suggest that above all, adoption of e-business should be appropriate, relevant, value adding, and operationally as well as strategically viable for an organization instead of being a result of apprehensive compliance. q 2004 Published by Elsevier Ltd.
Racial Differences in the Progression to Cirrhosis and Hepatocellular Carcinoma in HCV-Infected Veterans

OBJECTIVES:The race of patients infected with hepatitis C virus (HCV) in the United States may be associated with the risk for cirrhosis and hepatocellular carcinoma (HCC). However, previous studies are too small to provide convincing data regarding the effect of race on cirrhosis and HCC risk after accounting for demographic, clinical, and virological factors.METHODS:We used the Veterans Administration (VA) HCV Clinical Case Registry to identify patients with confirmed viremia between 2000 and 2009 and with at least 1 year of follow-up in the VA. We identified cirrhosis and HCC cases through early 2010. Cox proportional hazard regression models were performed to examine the effect of race on the risk for cirrhosis and HCC while adjusting for patients’ age, gender, period of service (World War I/II, Vietnam era, post-Vietnam era), HIV coinfection, HBV coinfection, alcohol abuse, diabetes, body mass index, and antiviral treatment receipt and response.RESULTS:There were 149,407 patients with active HCV viremia. Of them, 56.3% were non-Hispanic White (NHW), 36.1% were African American (AA), 6.0% were Hispanic, and 1.6% belonged to other racial groups. After an average follow-up of 5.2 years, 13,099 patients were seen to have a recorded diagnosis of cirrhosis and 3,551 had HCC. Hispanics had the highest annual incidence rates of cirrhosis and HCC (28.8 and 7.8%, respectively), whereas AAs had the lowest rates (13.3% and 3.9%, respectively) compared with NHWs (21.6 and 4.7%, respectively). There were differences among NHW, AA, and Hispanic patients in the rates of HIV infection (2.1, 2.5, and 6.0%, respectively), HCV genotype 1 (50.0, 50.6, and 64.2%, respectively), obesity (28.0, 25.4, and 30.9%, respectively), diabetes (8.7, 16.1, and 16.1%, respectively), and absence of antiviral treatment (81.1, 89.6, and 82.1%, respectively). However, adjusting for differences in demographic and clinical factors did not change the magnitude or direction of the race effect. Compared with NHWs, Hispanic patients had a higher risk of having cirrhosis recorded (adjusted hazard ratio (HR)=1.28, 95% confidence interval (CI)=1.21–1.37) and HCC (1.61, 95% CI=1.44–1.80). In contrast, AAs had a lower risk of cirrhosis (HR=0.58, 95% CI=0.55–0.60) and HCC (0.77, 95% CI=0.71–0.83) compared with NHWs.CONCLUSIONS:Hispanics with HCV are at a significantly higher risk, whereas AAs are at a considerably lower risk of developing cirrhosis and HCC than are NHWs. These associations persisted even after adjusting for a range of factors including HCV genotype, HCV treatment, diabetes, and body mass index.
Towards a unified approach to document similarity search using manifold-ranking of blocks

Document similarity search (i.e. query by example) aims to retrieve a ranked list of documents similar to a query document in a text corpus or on the Web. Most existing approaches to similarity search first compute the pairwise similarity score between each document and the query using a retrieval function or similarity measure (e.g. Cosine), and then rank the documents by the similarity scores. In this paper, we propose a novel retrieval approach based on manifold-ranking of document blocks (i.e. a block of coherent text about a subtopic) to re-rank a small set of documents initially retrieved by some existing retrieval function. The proposed approach can make full use of the intrinsic global manifold structure of the document blocks by propagating the ranking scores between the blocks on a weighted graph. First, the TextTiling algorithm and the VIPS algorithm are respectively employed to segment text documents and web pages into blocks. Then, each block is assigned with a ranking score by the manifold-ranking algorithm. Lastly, a document gets its final ranking score by fusing the scores of its blocks. Experimental results on the TDT data and the ODP data demonstrate that the proposed approach can significantly improve the retrieval performances over baseline approaches. Document block is validated to be a better unit than the whole document in the manifold-ranking process. 2007 Elsevier Ltd. All rights reserved.
TiO2-graphene nanocomposites for gas-phase photocatalytic degradation of volatile aromatic pollutant: is TiO2-graphene truly different from other TiO2-carbon composite materials?

The nanocomposites of TiO(2)-graphene (TiO(2)-GR) have been prepared via a facile hydrothermal reaction of graphene oxide and TiO(2) in an ethanol-water solvent. We show that such a TiO(2)-GR nanocomposite exhibits much higher photocatalytic activity and stability than bare TiO(2) toward the gas-phase degradation of benzene, a volatile aromatic pollutant in air. By investigating the effect of different addition ratios of graphene on the photocatalytic activity of TiO(2)-GR systematically, we find that the higher weight ratio in TiO(2)-GR will decrease the photocatalytic activity. Analogous phenomenon is also observed for the liquid-phase degradation of dyes over TiO(2)-GR. In addition, the key features for TiO(2)-GR including enhancement of adsorptivity of pollutants, light absorption intensity, electron-hole pairs lifetime, and extended light absorption range have also been found in the composite of TiO(2) and carbon nanotubes (TiO(2)-CNT). These strongly manifest that TiO(2)-GR is in essence the same as other TiO(2)-carbon (carbon nanotubes, fullerenes, and activated carbon) composite materials on enhancement of photocatalytic activity of TiO(2), although graphene by itself has unique structural and electronic properties. Notably, this key fundamental question remains completely unaddressed in a recent report ( ACS Nano 2010 , 4 , 380 ) regarding liquid-phase degradation of dyes over the TiO(2)-GR photocatalyst. Thus, we propose that TiO(2)-GR cannot provide truly new insights into the fabrication of TiO(2)-carbon composite as high-performance photocatalysts. It is hoped that our work could avert the misleading message to the readership, hence offering a valuable source of reference on fabricating TiO(2)-carbon composites for their application as a photocatalyst in the environment cleanup.
PORTFOLIO MANAGEMENT INTENSITY AND PERFORMANCE IMPLICATIONS : AN INTERNATIONAL EMPIRICAL INVESTIGATION

This paper investigates whether it is possible to create value through the active management of direct property portfolios. Using data from Australia, the United States and the United Kingdom, we examine whether portfolio trading activity and growth explain outperformance of listed property companies. The results indicate that beating the market using such a strategy is difficult even in direct property markets. When the property type in which the firm specializes is included as a control variable in the regressions, none of the portfolio management intensity indicators developed in this paper are significantly associated with outperformance. Brounen is with the Rotterdam School of Management of Erasmus University Rotterdam, Eichholtz is with Maastricht University and the University of Amsterdam and Ling is with the Warrington College of Business of the University of Florida. The authors gratefully acknowledge research support from the Real Estate Research Institute. Excellent research assistance was provided by Hugh Marble. Furthermore, Jeroen Beimer is thanked for providing access to the GPR database. Contact Author: Dirk Brounen, Erasmus University Rotterdam, Department of Financial Management, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands, dbrounen@fbk.eur.nl. PORTFOLIO MANAGEMENT INTENSITY AND PERFORMANCE IMPLICATIONS: AN INTERNATIONAL EMPIRICAL INVESTIGATION
Do consciousness and attention have shared neural correlates

Over the last few years our understanding of the brain processes underlying consciousness and attention has considerably improved, mainly thanks to the advances in functional neuroimaging techniques. However, caution is needed for the correct interpretation of empirical findings, since both research and reflection are hampered by a number of conceptual difficulties. This paper reviews some of the most relevant theoretical issues surrounding the concepts of consciousness and attention in the neuroscientific literature, and presents the implications of these reflections for a coherent model of the neural correlates of these cognitive functions. Although orthogonally defined as essentially separate neural processes, consciousness and attention show a consistent and overlapping pattern of brain activity, specifically recurrent processing within fronto-parietal association areas. Future research will shed more light on the possible relationship of processes that relate to common brain activity across functions.
WSN based power monitoring in smart grids

Smart grid technology is one of the recent developments in the area of electric power systems that aid the use of non-conventional sources of energy in parallel with the conventional sources of energy. Monitoring and control of smart grids is essential for its efficient and effective functioning. In this paper, we propose an architecture for monitoring power in smart grid applications using wireless sensor network (WSN) technology. A prototype power sensing module is designed and developed to calculate the power for any kind of loads. Using WSN technology, the monitored power is communicated to the sink at periodic intervals. Multi hop wireless mesh network is set up using IRIS motes to enhance the communication between the power sensing nodes and the sink. The data collected is a rich source of repository for data analysis and modelling. A number of smart actions and applications, such as power theft detection, energy efficient building design, smart automation systems and smart metering can evolve out of the proposed model. A novel Power theft detection algorithm is proposed and simulated in this paper. The system is also scaled using GSM technology to extend the range of communication. Load monitoring can aid distributed architecture in smart grids with automated technology to switch between the non-conventional source of energy and the grid.
Rethinking Spatiotemporal Feature Learning For Video Understanding

In this paper we study 3D convolutional networks for video understanding tasks. Our starting point is the stateof-the-art I3D model of [3], which “inflates” all the 2D filters of the Inception architecture to 3D. We first consider “deflating” the I3D model at various levels to understand the role of 3D convolutions. Interestingly, we found that 3D convolutions at the top layers of the network contribute more than 3D convolutions at the bottom layers, while also being computationally more efficient. This indicates that I3D is better at capturing high-level temporal patterns than low-level motion signals. We also consider replacing 3D convolutions with spatiotemporal-separable 3D convolutions (i.e., replacing convolution using a kt×k×k filter with 1× k× k followed by kt× 1× 1 filters); we show that such a model, which we call S3D, is 1.5x more computationally efficient (in terms of FLOPS) than I3D, and achieves better accuracy. Finally, we explore spatiotemporal feature gating on top of S3D. The resulting model, which we call S3D-G, outperforms the state-of-the-art I3D model by 3.5% accuracy on Kinetics and reduces the FLOPS by 34%. It also achieves a new state-of-the-art performance when transferred to other action classification (UCF-101 and HMDB51) and detection (UCF-101 and JHMDB) datasets.
Fully Automatic Facial Action Recognition in Spontaneous Behavior

We present results on a user independent fully automatic system for real time recognition of facial actions from the facial action coding system (FACS). The system automatically detects frontal faces in the video stream and codes each frame with respect to 20 action units. We present preliminary results on a task of facial action detection in spontaneous expressions during discourse. Support vector machines and AdaBoost classifiers are compared. For both classifiers, the output margin predicts action unit intensity
Reviewing the Concept of Brand Equity and Evaluating Consumer-Based Brand Equity ( CBBE ) Models

The purpose of this paper is to explore the concept of brand equity and discuss its different perspectives, we try to review existing literature of brand equity and evaluate various Customer-based brand equity models to provide a collection from well-known databases for further research in this area.
Passive Millimeter Wave Imaging

The use of the millimeter wave regime for imaging is becoming more widespread as a means for concealed weapons detection. A primer on the phenomenology of passive millimeter wave imaging will be presented to help explain how this imaging is accomplished with only ambient radiation. Examples of images acquired by passive millimeter wave cameras will be presented. A comparison between imaging indoors and outdoors will be made, highlighting the factors to be considered in both scenarios
Blood transfusion management in the severely bleeding military patient.

PURPOSE OF REVIEW
Hemorrhage remains the primary cause of preventable death on the battlefield and in civilian trauma. Hemorrhage control is multifactorial and starts with point-of-injury care. Surgical hemorrhage control and time from injury to surgery is paramount; however, interventions in the prehospital environment and perioperative period affect outcomes. The purpose of this review is to understand concepts and strategies for successful management of the bleeding military patient. Understanding the life-threatening nature of coagulopathy of trauma and implementing strategies aimed at full spectrum hemorrhage management from point of injury to postoperative care will result in improved outcomes in patients with life-threatening bleeding.


RECENT FINDINGS
Timely and appropriate therapies impact survival. Blood product resuscitation for life-threatening hemorrhage should either be with whole blood or a component therapy strategy that recapitulates the functionality of whole blood. The US military has transfused over 10 000 units of whole blood since the beginning of the wars in Iraq and Afghanistan. The well recognized therapeutic benefits of whole blood have pushed this therapy far forward into prehospital care in both US and international military forces. Multiple hemostatic adjuncts are available that are likely beneficial to the bleeding military patient; and other products and techniques are under active investigation.


SUMMARY
Lessons learned in the treatment of combat casualties will likely continue to have positive impact and influence and the management of hemorrhage in the civilian trauma setting.
Dynamic behavior of wavelength converters based on FWM in SOAs

As wavelength converters based on four-wave mixing (FWM) in semiconductor optical amplifiers (SOAs) attract more attention, dynamic effects and wavelength dependent performance become key aspects to be investigated. Such issues are particularly important, as complex configurations are likely to be used to overcome challenges like tunability and polarization dependence. In this paper a numerical model is used to predict the dynamic performance of three FWM configurations and an analytical model is used to derive design rules. First, the wavelength dependent behavior of a wavelength converter is investigated and the requirement for a widely tunable converter is identified. Secondly, a configuration for extinction ratio (ER) improvement is studied and novel design rules are obtained analytically, tested experimentally and explained by the numerical model; experimental results with ER improvement at 10 Gb/s were achieved for the first time. The third configuration studied is a dual-pump arrangement enabling wide tunability. Fixed input/tunable output and tunable input/fixed output configurations are discussed in terms of optical signal-to-noise ratio and tunability. Design rules are extracted and verified for all three configurations that are likely to be deployed: simple wavelength converters, regenerating converters and tunable wavelength converters.
Best practices in digital radiography.

After completing this article, the reader should be able to:  Describe the various biopsy types that require specimen imaging.  List methods of guiding biopsy procedures.  Explain the reasons behind specimen imaging.  Describe various methods for imaging specimens.
A* CCG Parsing with a Supertag and Dependency Factored Model

We propose a new A* CCG parsing model in which the probability of a tree is decomposed into factors of CCG categories and its syntactic dependencies both defined on bi-directional LSTMs. Our factored model allows the precomputation of all probabilities and runs very efficiently, while modeling sentence structures explicitly via dependencies. Our model achieves the stateof-the-art results on English and Japanese CCG parsing.1
Fusion of Matching Algorithms for Human Identification Using Dental X-Ray Radiographs

The goal of forensic dentistry is to identify individuals based on their dental characteristics. In this paper, we introduce a system that uses some scenarios to fuse three matching techniques for identifying individuals based on their dental X-ray images. The system integrates a method for teeth segmentation, and three different methods for representing and matching teeth. The first method for matching antemortem (AM) and postmortem (PM) images represents each tooth contour by a set of signature vectors obtained at salient points on the contour of the tooth. The second method uses hierarchical chamfer distance for matching AM and PM teeth to reduce the search space and accordingly reduce the retrieval time. The third matching method represents each tooth by a small set of features extracted using the forcefield energy function and Fourier descriptors. For each matcher, given a query PM image, AM radiographs that are mostly similar to the PM image, are found and presented to the user. To improve the performance of the system, we present different scenarios to fuse the three matchers. We fuse the matchers using three different approaches at the matching level, the decision level, and using the Bayesian framework. Preliminarily results demonstrate that fusing the matching techniques improves the overall performance of the dental identification system.
The cost of obesity and overweight in 2005: a case study of Alberta, Canada.

OBJECTIVE
The aim of this paper is to highlight the potential impact of costs associated with overweight and obesity for provincial policy and prevention initiatives.


METHOD
Prevalence-based cost-of-illness methodology was used to estimate the direct costs (hospital care, drugs, physician care, institutional care, additional costs) and indirect costs (short- and long-term disability, premature mortality) associated with excess weight for 22 health conditions. Total costs for each health condition were estimated using the Public Health Agency of Canada's Economic Burden of Illness database. Population attributable fractions (PAF) were also estimated using 2004 and 2005 CCHS data and current literature reviews.


RESULTS
In 2005, the cost of excess weight in Alberta totaled $1.27 billion. The direct cost of excess weight was $630.1M (49.5%), the indirect cost $643.8M (50.5%). Excluding costs associated with premature mortality and caregiving, obesity accounted for 69.5% ($500.8M) of costs and overweight the remaining 30.5% ($220.2M). Among the 22 health conditions, coronary heart disease had the highest costs attributable to excess weight ($307.1 M), followed by osteoarthritis ($167.7M) and type 2 diabetes ($161.5M). The total cost of excess weight equated to 5.6% of the province's annual health care expenditures for 2005.


CONCLUSION
While obesity costing research often focuses on the direct health care costs, this study reveals that the indirect costs of excess weight are also significant and can account for over half of the total costs. Interventions to reduce excess weight among Canadians have the potential to improve the health of the population while reducing provincial and national health care costs.
Robust real-time visual odometry for dense RGB-D mapping

This paper describes extensions to the Kintinuous [1] algorithm for spatially extended KinectFusion, incorporating the following additions: (i) the integration of multiple 6DOF camera odometry estimation methods for robust tracking; (ii) a novel GPU-based implementation of an existing dense RGB-D visual odometry algorithm; (iii) advanced fused realtime surface coloring. These extensions are validated with extensive experimental results, both quantitative and qualitative, demonstrating the ability to build dense fully colored models of spatially extended environments for robotics and virtual reality applications while remaining robust against scenes with challenging sets of geometric and visual features.
Estimation of the area under the concentration-versus-time curve of carboplatin following irinotecan using a limited sampling model

Objectives: The aim of this study was to develop limited sampling models for estimating the area under the concentration-versus-time curve (AUC) of carboplatin. Methods: Based on pharmacokinetic analyses of 14 patients who received 300 mg · m2 of carboplatin over a 90-min infusion following irinotecan, we developed limited sampling models with stepwise multiple linear regression analysis. We validated these models to be unbiased and precise using pharmacokinetic data of a second group of 14 patients. We also compared the observed and the predicted AUC in the patients using Calvert's formula with the patients' renal function. Results: We developed the following models: AUC (mg · ml−1 · min) = 0.784 × C4 + 1.30 (r 2 = 0.930) and AUC = 0.100 × C0.25 + 0.597 × C4 + 0.140 (r 2 = 0.992), where C0.25 and C4 denote unbound plasma concentrations (μg · ml−1) of carboplatin at 0.25 h and 4 h after the end of infusion, respectively. These models were validated to be unbiased and precise: a mean prediction error (MPE) with standard deviation (SD) = 2.41 (9.45)% and a root mean squared error (RMSE) = 9.42% for the one-sample model, and MPE with (SD) = 1.22 (5.56)% and RMSE = 5.49% for the two-sample model. We also calculated predicted AUC in the patients using Calvert's formula: MPE with (SD) =−5.87 (21.5)% and RMSE = 21.5%. Conclusions: These estimations were, as expected, more accurate than the prediction using Calvert's formula based on patients' renal function. The result of this study confirmed the idea that the pharmacokinetic parameters derived from limited sampling models would be more suitable for pharmacokinetic analysis of carboplatin than those obtained using Calvert's formula.