varunr14/newsummary huggingface dataset:
In today s dynamic media landscape products are reviewed by consumers in social media and reported by journalists in traditional media . This paper will focus on the relationship among the two types of earned media and product sales . Previous studies have focused on either traditional or social earned media but rarely both . We will aim to bridge that gap using the following points of analysis the New York Times Best Seller List as traditional media Amazon user reviews as social media and book purchases through Amazon as product sales . We find that both traditional and social earned media influence sales sales have a reciprocal effect on social earned media and traditional and social earned media influence each other . Communication through multiple media is known to produce the synergy effect in which one media activity enhances the effect of another . Our results suggest a new benefit unique to the use of multiple earned media . We call this the multiplier effect which occurs when one earned media activity increases the level of another by becoming a sounding board that amplifies positive messages as well as a bridge that allows messages to propagate freely in an interactive media system . Therefore multiple earned media produce combined sales effects greater than those resulting from the sum of their parts . This analysis supports Amazon s decision to use multiple earned media to benefit from an ecosystem where product sales and earned media both influence and are influenced by one another . The paper will address the implications for marketing communication and media industry . 


Summary: Both social and traditional earned media influence product sales. Product sales have a reciprocal effect on social earned media. Social and traditional earned media influence each other. Multiplier effect makes combined earned media effects larger than sum of the parts. Social and traditional media have a foe and friend relationship in a digital ecosystem.
Immunization saves millions of lives against vaccine preventable diseases . Yet 24 million children born every year do not receive proper immunization during their first year . UNICEF and WHO have emphasized the need to strengthen the immunization surveillance and monitoring in developing countries to reduce childhood deaths . In this regard we present a software application called Jeev to track the vaccination coverage of children in rural communities . Jeev synergistically combines the power of smartphones and the ubiquity of cellular infrastructure QR codes and national identification cards . We present the design of Jeev and highlight its unique features along with a detailed evaluation of its performance and power consumption using the National Immunization Survey datasets . We are in discussion with a non profit organization in Haiti to pilot test Jeev in order to study its effectiveness and identify socio cultural issues that may arise in a large scale deployment . 


Summary: Jeev is a novel smartphone application for tracking the vaccination coverage of children. Jeev synergistically combines smartphones QR codes and national id cards. Jeev is scalable and power efficient.
The domain of cancer treatment is a promising field for the implementation and evaluation of a protocol based clinical decision support system because of the algorithmic nature of treatment recommendations . However many factors can limit such systems potential to support the decision of clinicians technical challenges related to the interoperability with existing electronic patient records and clinical challenges related to the inherent complexity of the decisions often collectively taken by panels of different specialists . In this paper we evaluate the performances of an Asbru based decision support system implementing treatment protocols for breast cancer which accesses data from an oncological electronic patient record . Focusing on the decision on the adjuvant pharmaceutical treatment for patients affected by early invasive breast cancer we evaluate the matching of the system s recommendations with those issued by the multidisciplinary panel held weekly in a hospital . 


Summary: We design and built a decision support system for the treatment of breast cancer based on Asbru. The DSS is integrated with the electronic patient record in use in a Medical Oncology Unit. We evaluated the DSS in the multidisciplinary meeting for the decision of the adjuvant treatment. The results show an agreement of nearly 90 between the meeting decisions and the DSS recommendations. We discuss the reasons for non agreement and additional insights into the design of effective DSS.
Increased heterogeneity of the lung disturbs pulmonary gas exchange . During bronchoconstriction inflammation of lung parenchyma or acute respiratory distress syndrome inhomogeneous lung ventilation can become bimodal and increase the risk of ventilator induced lung injury during mechanical ventilation . A simple index sensitive to ventilation heterogeneity would be very useful in clinical practice . In the case of bimodal ventilation the index can be defined as the ratio between the longer and shorter time constant characterising regions of contrary mechanical properties . These time constants can be derived from the Otis model fitted to input impedance measured using forced oscillations . In this paper we systematically investigated properties of the aforementioned approach . The research included both numerical simulations and real experiments with a dual lung simulator . Firstly a computational model mimicking the physical simulator was derived and then used as a forward model to generate synthetic flow and pressure signals . These data were used to calculate the input impedance and then the Otis inverse model was fitted to Z in by means of the Levenberg Marquardt algorithm . Finally the obtained estimates of model parameters were used to compute H. The analysis of the above procedure was performed in the frame of Monte Carlo simulations . For each selected value of H forward simulations with randomly chosen lung parameters were repeated 1000 times . Resulting signals were superimposed by additive Gaussian noise . The estimated values of H properly indicated the increasing level of simulated inhomogeneity however with underestimation and variation increasing with H. The main factor responsible for the growing estimation bias was the fixed starting vector required by the LM algorithm . Introduction of a correction formula perfectly reduced this systematic error . The experimental results with the dual lung simulator confirmed potential of the proposed procedure to properly deduce the lung heterogeneity level . We conclude that the heterogeneity index H can be used to assess bimodal ventilation imbalances in cases when this phenomenon dominates lung properties however future analyses including the impact of lung tissue viscoelasticity and distributed airway or tissue inhomogeneity on H estimates as well as studies in the time domain are advisable . 


Summary: We analyse the method for bimodal lung ventilation heterogeneity identification. Respiratory impedance measurement by forced oscillations in bimodal model was proposed. In case of the Otis model the index H was defined as the ratio of two time constants. Mean values of heterogeneity were computed both for simulated and experimental data. The knowledge of bimodality may be helpful when using mechanical ventilation.
Financial data are often thick tailed and exhibit skewness . The versatile Generalized Tukey Lambda distribution is able to capture varying degrees of skewness in thin or thick tailed data . Such versatility makes the GTL distribution potentially useful in the area of financial risk measurement . Moreover for GTL distributed random variables the familiar risk measures of Value at Risk and Expected Shortfall may be expressed in simple analytical forms . It turns out that both analytically and through Monte Carlo simulations GTL s VaR and ES differ significantly from other flexible distributions . The asymptotic properties of the maximum likelihood estimator of the GTL parameters are also examined . In order to study risk in financial data the GTL distribution is inserted into a GARCH model . This GTL GARCH model is estimated with data on daily returns of GE stock demonstrating that for certain data sets GTL may capture risk measurements better than other distributions . Online supplementary materials consist of appendices with proofs and additional Monte Carlo results data used in this study an R script for fitting GTL densities by maximum likelihood and an R script for estimation of the GTL GARCH model . 


Summary: We derive Value at Risk and expected shortfall for GTL distributed random variables. GTL s VaR and ES statistics differ significantly from other flexible distributions. We derive asymptotic properties of the ML estimator of the GTL parameters. We insert GTL and other flexible distributions in a GARCH model. A GTL GARCH model may fit real data better than GARCH with other distributions.
Objective To survey researchers efforts in response to the new and disruptive technology of smartphone medical apps mapping the research landscape form the literature into a coherent taxonomy and finding out basic characteristics of this emerging field represented on motivation of using smartphone apps in medicine and healthcare open challenges that hinder the utility and the recommendations to improve the acceptance and use of medical apps in the literature . Methods We performed a focused search for every article on smartphone medical or health related app in four major databases MEDLINE Web of Science ScienceDirect and IEEE Xplore . Those databases are deemed broad enough to cover both medical and technical literature . Results The final set included 133 articles . Most articles are reviews and surveys that refer to actual apps or the literature to describe medical apps for a specific specialty disease or purpose or to provide a general overview of the technology . Another group carried various studies from evaluation of apps to exploration of desired features when developing them . Few researchers presented actual attempts to develop medical apps or shared their experiences in doing so . The smallest portion proposed general frameworks addressing the production or operation of apps . Discussion Since 2010 researchers followed the trend of medical apps in several ways though leaving areas or aspect for further attention . Regardless of their category articles focus on the challenges that hinder the full utility of medical apps and do recommend mitigations to them . Conclusions Research on smartphone medical apps is active and various . We hope that this survey contribute to the understanding of the available options and gaps for other researchers to join this line of research . 


Summary: Mapping the research landscape of smartphone medical apps into a coherent taxonomy. Figure out the motivation of using smartphone apps in medicine healthcare. Highlight the open challenges that hinder the utility of medical apps. Recommendations Lists to improve the acceptance of medical apps in the literature.
We derive explicit formulas for the bases of conic sections and planar rational cubic curves . Using the bases for planar rational cubic curves we find explicit formulas for their implicit equations and double points . We also extend the explicit formula for the bases of conic sections to bases for rational curves of degree n in n dimensions . 


Summary: We provide explicit formulas for the bases of conic sections and planar rational cubic curves. We derive explicit formulas for the implicit equations and double points of planar rational cubic curves from the bases of planar rational cubic curves. We also give explicit formulas for the bases of rational curves of degree n in n dimensions.
Bone drilling is a common procedure in many types of surgeries including orthopedic neurological and otologic surgeries . Several technologies and control algorithms have been developed to help the surgeon automatically stop the drill before it goes through the boundary of the tissue being drilled . However most of them rely on thrust force and cutting torque to detect bone layer transitions which has many drawbacks that affect the reliability of the process . This paper describes in detail a bone drilling algorithm based only on the position control of the drill bit that overcomes such problems and presents additional advantages . The implication of each component of the algorithm in the drilling procedure is analyzed and the efficacy of the algorithm is experimentally validated with two types of bones . 


Summary: Description of an admittance algorithm for bone drilling procedures. Layer transitions properly detected before bone breakthrough. Robust performance without collecting experimental data or retuning the control parameters. Only a position sensor is needed.
Background and objectives Document annotation is a key task in the development of Text Mining methods and applications . High quality annotated corpora are invaluable but their preparation requires a considerable amount of resources and time . Although the existing annotation tools offer good user interaction interfaces to domain experts project management and quality control abilities are still limited . Therefore the current work introduces Marky a new Web based document annotation tool equipped to manage multi user and iterative projects and to evaluate annotation quality throughout the project life cycle . Methods At the core Marky is a Web application based on the open source CakePHP framework . User interface relies on HTML5 and CSS3 technologies . Rangy library assists in browser independent implementation of common DOM range and selection tasks and Ajax and JQuery technologies are used to enhance user system interaction . Results Marky grants solid management of inter and intra annotator work . Most notably its annotation tracking system supports systematic and on demand agreement analysis and annotation amendment . Each annotator may work over documents as usual but all the annotations made are saved by the tracking system and may be further compared . So the project administrator is able to evaluate annotation consistency among annotators and across rounds of annotation while annotators are able to reject or amend subsets of annotations made in previous rounds . As a side effect the tracking system minimises resource and time consumption . Conclusions Marky is a novel environment for managing multi user and iterative document annotation projects . Compared to other tools Marky offers a similar visually intuitive annotation experience while providing unique means to minimise annotation effort and enforce annotation quality and therefore corpus consistency . Marky is freely available for non commercial use at http sing.ei.uvigo.es marky . 


Summary: The ultimate goal of Text Mining is to learn how to recognise and contextualise information of interest. Depending on the application area the creation of such semantically annotated corpora is a resource and time consuming activity. Annotation consistency needs to be actively monitored during the annotation process in order to guarantee the quality of the generated corpus. Marky is a novel environment for managing multi user and iterative document annotation projects. Marky implements the main steps of the annotation project life cycle with particular emphasis on annotation quality assessment.
In this paper the gHRV software tool is presented . It is a simple free and portable tool developed in python for analysing heart rate variability . It includes a graphical user interface and it can import files in multiple formats analyse time intervals in the signal test statistical significance and export the results . This paper also contains as an example of use a clinical analysis performed with the gHRV tool namely to determine whether the heart rate variability indexes change across different stages of sleep . Results from tests completed by researchers who have tried gHRV are also explained in general the application was positively valued and results reflect a high level of satisfaction . gHRV is in continuous development and new versions will include suggestions made by testers . 


Summary: gHRV is an open source tool for HRV analysis. gHRV is implemented in python and binaries are available for Linux Windows and Apple OS X. It imports and exports files in several formats and creates high quality plots that can be exported to file.
The Gene Ontology is a structured repository of concepts that are associated to one or more gene products . The process of association is referred to as annotation . The relevance and the specificity of both GO terms and annotations are evaluated by a measure defined as information content . The analysis of annotated data is thus an important challenge for bioinformatics . There exist different approaches of analysis . From those the use of association rules may provide useful knowledge and it has been used in some applications e.g . improving the quality of annotations . Nevertheless classical association rules algorithms do not take into account the source of annotation nor the importance yielding to the generation of candidate rules with low IC . This paper presents GO WAR a methodology for extracting weighted association rules . GO WAR can extract association rules with a high level of IC without loss of support and confidence from a dataset of annotated data . A case study on using of GO WAR on publicly available GO annotation datasets is used to demonstrate that our method outperforms current state of the art approaches . 


Summary: GO WAR is a tool for learning cross ontology weighted association rules. GO WAR is currently the only tool available for this problem. GO WAR is more flexible than previous approaches. A case study demonstrates the effectiveness of GO WAR approach.
Methods are introduced for the analysis of large sets of sleep study data using a 5 state 20 transition type structure defined by the American Academy of Sleep Medicine . Application of these methods to the hypnograms of 5598 subjects from the Sleep Heart Health Study provide the first analysis of sleep hypnogram data of such size and complexity in a community cohort with a range of sleep disordered breathing severity introduce a novel approach to compare 5 state to 3 state sleep structures to assess information loss from combining sleep state categories extend current approaches of multivariate survival data analysis to clustered recurrent event discrete state discrete time processes and provide scalable solutions for data analyses required by the case study . The analysis provides detailed new insights into the association between sleep disordered breathing and sleep architecture . The example data and both R and SAS code are included in online supplementary materials . 


Summary: We explore associations of sleep disordered breathing and sleep structure. 5 state hypnograms are systematically compared to 3 state. We analyze a community cohort of 5598 subjects 2.7 million rows total . We reduce analysis time from 8 hours to 30 s.
Breast ultrasound image segmentation is a challenging task due to the speckle noise poor quality of the ultrasound images and size and location of the breast lesions . In this paper we propose a new BUS image segmentation algorithm based on neutrosophic similarity score and level set algorithm . At first the input BUS image is transferred to the NS domain via three membership subsets T I and F and then a similarity score NSS is defined and employed to measure the belonging degree to the true tumor region . Finally the level set method is used to segment the tumor from the background tissue region in the NSS image . Experiments have been conducted on a variety of clinical BUS images . Several measurements are used to evaluate and compare the proposed method s performance . The experimental results demonstrate that the proposed method is able to segment the BUS images effectively and accurately . 


Summary: This study proposes a novel method to segment the tumor in the breast ultrasound images. The proposed approach combined the neutrosophic similarity score with level set algorithm for image segmentation. Neutrosophic similarity score is employed to deal with uncertain information on image segmentation.
We show that a weighted least squares approximation of B zier coefficients with factored Hahn weights provides the best constrained polynomial degree reduction with respect to the Jacobi norm . This result affords generalizations to many previous findings in the field of polynomial degree reduction . A solution method to the constrained multi degree reduction with respect to the Jacobi norm is presented . 


Summary: We study the problem of constrained degree reduction with respect to Jacobi norms. Our results generalize several previous findings on polynomial degree reduction. We explore the space of Jacobi parameters on the reduced polynomial approximation.
Non invasive treatment of neurodegenerative diseases is particularly challenging in Western countries where the population age is increasing . In this work magnetic propagation in human head is modelled by Finite Difference Time Domain method taking into account specific characteristics of Transcranial Magnetic Stimulation in neurodegenerative diseases . It uses a realistic high resolution three dimensional human head mesh . The numerical method is applied to the analysis of magnetic radiation distribution in the brain using two realistic magnetic source models a circular coil and a figure 8 coil commonly employed in TMS . The complete model was applied to the study of magnetic stimulation in Alzheimer and Parkinson Diseases . The results show the electrical field distribution when magnetic stimulation is supplied to those brain areas of specific interest for each particular disease . Thereby the current approach entails a high potential for the establishment of the current underdeveloped TMS dosimetry in its emerging application to AD and PD . 


Summary: Magnetic propagation in Transcranial Magnetic Stimulation TMS for neurodegenerative diseases is modelled by FDTD. A computing tool for the current underdeveloped TMS dosimetry in its emerging clinical application to AD and PD is presented. A realistic high resolution three dimensional human head mesh is used. Two realistic magnetic source models are employed a circular and a figure 8 coil. Results show the electrical field distribution when magnetic stimulation is supplied to those brain areas of specific interest for each particular disease.