LLukas22/scidocs huggingface dataset:
Enhancement of Diabetic Retinopathy Imagery Using Contrast Limited Adaptive Histogram Equalization

Diabetic Retinopathy (DR), a common micro vascular disease observed in diabetics, is also a major cause of adult blindness across the globe. It results in observable changes in retina which may be cured, provided, if it is detected in the preliminary stage. However, the ocular images produced by fluorescent oscilloscope are often noisy and low in contrast making it seriously difficult for doctors to precisely detect the inherent abnormalities. In the present paper, we propose to use a regional contrast enhancement scheme, popularly known as Contrast Limited Adaptive Histogram Equalization (CLAHE) to aid the detection of retinal changes in DR imagery. CLAHE is an adaptive extension of Histogram Equalization followed by thresholding, which helps in dynamic preservation of the local contrast characteristics of an image. Following CLAHE, median filtering of DR images is carried in order to smoothen the background noise. Results of the proposed algorithm show a considerable improvement in the enhancement of DR image. Keywords—Diabetic retinopathy, contrast enhancement, histogram equalisation, clahe, smoothening.
Improvement in Asthma Control and Inflammation in Children Undergoing Adenotonsillectomy

Background:Observational studies suggest that asthma control improves after adenotonsillectomy, but longitudinal studies that correlate the effect of the procedure on the levels of biomarkers associated with airway inflammation are limited.Methods:We conducted a longitudinal, observational study on pediatric patients, both with and without asthma, undergoing adenotonsillectomy. Asthma control test (ACT) scores and chitinase activity in the circulation were measured at time of surgery and at 6-mo follow-up.Results:Sixty-six children with asthma and 64 control subjects were enrolled. Mean ACT scores improved by three points (P < 0.001) after 6 mo. 85% of children with poorly controlled asthma demonstrated an increase in ACT score of at least three points or a decrease in emergency department/urgent care visits, oral corticosteroid courses, or rescue short acting bronchodilator usage. Chitinase activity decreased significantly in asthmatics who improved (P < 0.01). Higher chitinase activity levels at baseline were associated with improved asthma control following surgery (P < 0.01).Conclusion:In children with high preoperative circulating chitinase activity levels, asthma control and healthcare utilization were significantly improved after adenotonsillecotmy. Chitinase activity decreased after surgery in children with improved control. This suggests that adenotonsillectomy modulates chitinase activity, affecting airway inflammation and improving airway disease.
Strategic talent management: A review and research agenda

Despite a significant degree of academic and practitioner interest the topic of talent management remains underdeveloped. A key limitation is the fact that talent management lacks a consistent definition and clear conceptual boundaries. The specific contribution of the current paper is in developing a clear and concise definition of strategic talent management. We also develop a theoretical model of strategic talent management. In so doing we draw insights from a number of discreet literature bases. Thus, the paper should aid future research in the area of talent management through (1) helping researchers to clarify the conceptual boundaries of talent management and (2) providing a theoretical framework that could help researchers in framing their research efforts in the area. Additionally, it aids managers in engaging with some of the issues they face with regard to talent management.
Porous materials for oil spill cleanup: A review of synthesis and absorbing properties

This paper reviews the synthesis and the absorbing properties of the wide variety of porous sorbent materials that have been studied for application in the removal of organics, particularly in the area of oil spill cleanup. The discussion is especially focused on hydrophobic silica aerogels, zeolites, organoclays and natural sorbents many of which have been demonstrated to exhibit (or show potential to exhibit) excellent oil absorption properties. The areas for further development of some of these materials are identified.
An Efficient Deep Learning Technique for the Navier-Stokes Equations : Application to Unsteady Wake Flow Dynamics

We present an efficient deep learning technique for the model reduction of the Navier-Stokes equations for unsteady flow problems. The proposed technique relies on the Convolutional Neural Network (CNN) and the stochastic gradient descent method. Of particular interest is to predict the unsteady fluid forces for different bluff body shapes at low Reynolds number. The discrete convolution process with a nonlinear rectification is employed to approximate the mapping between the bluff-body shape and the fluid forces. The deep neural network is fed by the Euclidean distance function as the input and the target data generated by the full-order Navier-Stokes computations for primitive bluff body shapes. The convolutional networks are iteratively trained using the stochastic gradient descent method with the momentum term to predict the fluid force coefficients of different geometries and the results are compared with the full-order computations. We attempt to provide a physical analogy of the stochastic gradient method with the momentum term with the simplified form of the incompressible Navier-Stokes momentum equation. We also construct a direct relationship between the CNN-based deep learning and the Mori-Zwanzig formalism for the model reduction of a fluid dynamical system. A systematic convergence and sensitivity study is performed to identify the effective dimensions of the deeplearned CNN process such as the convolution kernel size, the number of kernels ∗Corresponding author Email address: mperkj@nus.edu (R. K. Jaiman) Preprint submitted to arXiv August 16, 2018 ar X iv :1 71 0. 09 09 9v 3 [ ph ys ic s. fl udy n] 1 5 A ug 2 01 8 and the convolution layers. Within the error threshold, the prediction based on our deep convolutional network has a speed-up nearly four orders of magnitude compared to the full-order results and consumes an insignificant fraction of computational resources. The proposed CNN-based approximation procedure has a profound impact on the parametric design of bluff bodies and the feedback control of separated flows.
From Social Media to Social Product Development : The Impact of Social Media on Co-Creation of Innovation

The objective of this paper is to discuss the impact of social media on customer co-creation in the innovation process. Customer cocreation denotes an active, creative and social collaboration process between producers and customers (users), facilitated by a company, in the context of new product or service development. We propose a typology of co-creation activities in order to develop conceptual arguments how social media can impact the relationships among customers involved in co-creation as well as the relationship between customers and the hosting firm. Social media can make economic-exchange relations more collaborative and social, but interestingly may also turn relations formerly based on social-exchange into “money markets” with strong competition among actors. As a result, we develop a set of questions that can lead future research in these regards.
Using a Digital Services Capability Model to Assess Readiness for the Digital Consumer

The increasing proliferation of digital technologies is transforming economies in many ways. This is particularly true in consumer-facing industries where the emergence of digital services is enabling novel value propositions, closer consumer relationships and greater automation of consumer-facing business processes.2 These digital services are providing value-creating consumer interactions. For instance, an Italian auto insurer uses a telematics device installed in customers’ vehicles to capture driving behavior and uses this data to create novel value propositions via personalized insurance services.3 The Finnish airline Finnair harnesses Facebook as a platform to create a customer community and a sense of collective identity with the company.4 The City of Boston introduced an iPhone app that senses potholes on city roads and allows citizens to contribute to road management in a highly automated fashion.5
Which factors predict glycemic control in children diagnosed with type 1 diabetes before 6.5 years of age?

Predictors of long-term glycemic control and growth patterns in children diagnosed with type 1 diabetes (T1D) before 6.5 years of age were evaluated. One hundred seventy-three children (84 boys) with a mean diabetes duration of 4.9 ± 2.8 years participated in this observational study. Medical charts were reviewed for background, disease- and treatment-related parameters, and growth parameters. Study endpoints were HbA1c value, rates of severe hypoglycemia and diabetic ketoacidosis events, and growth patterns. Mean HbA1c for the total duration of diabetes (HbA1c–TDD) was 7.9 ± 0.8%. Comparison of the study variables between patients with HbA1c–TDD <7.5% (n = 53) or ≥7.5% yielded a significantly shorter duration of diabetes (P = 0.01) and lower rate of diabetic ketoacidosis (P = 0.02) in those with HbA1C–TDD <7.5%, without differences between these groups in age at diabetes onset, insulin regimens, daily glucose measurements, and rate of severe hypoglycemia. Factors significantly predicting achievement of the mean target HbA1c–TDD <7.5% were lower HbA1c at 0.5 years and 1 year after diabetes diagnosis (P = 0.002 and P < 0.001, respectively). Patients followed for at least 5 years (n = 48) showed a significant decrease in height-SDS (P < 0.001) and a significant increase in weight-SDS (P = 0.004) from diabetes diagnosis to the last follow-up visit, without a significant change in weight-SDS from 0.5 years after diagnosis to the last follow-up visit. Our results suggest that in patients with T1D diagnosed during the preschool-age, mean HbA1c level in the first year is a strong predictor of achieving target HbA1c level in the subsequent years, regardless the type of insulin regimen. This “metabolic tracking” emphasizes the importance of achieving early optimal control even in younger children.
Is Nietzsche a political thinker

Abstract Nietzsche claimed to be a political thinker in Ecce Homo and elsewhere. He constantly compared his thought with other political theorists, chiefly Rousseau, Kant and Mill, and he claimed to offer an alternative to the bankruptcy of Enlightenment liberalism. It is worthwhile re‐examining Nietzsche's claim to offer serious criticisms of liberal political philosophy. I shall proceed by setting out seven criteria for serious political thought: understanding of material need; procedural justification; liberty and its worth; racial, ethnic and religious difference; gender and family; justice between nations; and moral psychology. I shall argue polemically that on the first six issues Nietzsche has nothing to offer, but that on the seventh, moral psychology, he makes a profound contribution. Serious political theory, however, needs to forget about Nietzsche and turn to those thinkers he found so boring ‐ the liberal Enlightenment thinkers.
Upper extremity rehabilitation of stroke: Facilitation of corticospinal excitability using virtual mirror paradigm

Several experimental studies in stroke patients suggest that mirror therapy and various virtual reality programs facilitate motor rehabilitation. However, the underlying mechanisms for these therapeutic effects have not been previously described. We attempted to delineate the changes in corticospinal excitability when individuals were asked to exercise their upper extremity using a real mirror and virtual mirror. Moreover, we attempted to delineate the role of visual modulation within the virtual environment that affected corticospinal excitability in healthy subjects and stroke patients. A total of 18 healthy subjects and 18 hemiplegic patients were enrolled into the study. Motor evoked potential (MEP)s from transcranial magnetic stimulation were recorded in the flexor carpi radialis of the non-dominant or affected upper extremity using three different conditions: (A) relaxation; (B) real mirror; and (C) virtual mirror. Moreover, we compared the MEPs from the virtual mirror paradigm using continuous visual feedback or intermittent visual feedback. The rates of amplitude increment and latency decrement of MEPs in both groups were higher during the virtual mirror task than during the real mirror. In healthy subjects and stroke patients, the virtual mirror task with intermittent visual feedback significantly facilitated corticospinal excitability of MEPs compared with continuous visual feedback. Corticospinal excitability was facilitated to a greater extent in the virtual mirror paradigm than in the real mirror and in intermittent visual feedback than in the continuous visual feedback, in both groups. This provides neurophysiological evidence supporting the application of the virtual mirror paradigm using various visual modulation technologies to upper extremity rehabilitation in stroke patients.
Information technology and organizational learning in knowledge alliances and networks: Evidence from U.S. pharmaceutical industry

Recent years have witnessed a change in firms’ innovation patterns, from closed to open, in which information technology (IT) has played an important role. This paper aims to open up the black box of ITenabled absorptive capacity by theorizing and testing the role of IT in two organizational learning processes, which are either interactive with partners in the knowledge alliance or non-interactive with others in the knowledge network. In particular, we formulate a model explaining how a firm’s IT investment moderates its organizational learning processes in knowledge alliances and networks, which sheds light on the role of IT as an enabler of absorptive capacity. Using a panel data set from the U.S. pharmaceutical industry, the results show the moderating role of IT in strengthening the organizational learning processes from knowledge alliance experience to coinvented knowledge and from knowledge network centrality to assimilated knowledge, which, in turn, improve firm competitiveness. 2014 Elsevier B.V. All rights reserved. * Corresponding author at: Department of Innovation Management and Strategy, Faculty of Economics and Business, University of Groningen, 9747 AE Groningen, The Netherlands. Tel.: +31 50 363 4839. E-mail address: john.dong@rug.nl (J.Q. Dong).
Design a Circular Microstrip Patch Antenna for Dual Band

This paper presents a circular patch microstrip antenna operate in dual band (1.66 GHz and 2.777GHz). The proposed Circular patch antenna will be in light weight, flexible, slim and compact unit compare with current antenna used in dual band [1]. The paper also presents the detail steps of designing the circular patch microstrip antenna and the simulated result. IE3D software is used to compute the gain, power, radiation pattern, and S11 of the antenna. KeywordsCircular patch microstrip antenna, VSWR, Return loss, Bandwidth.
The value of channel prediction in CoMP systems with large backhaul latency

The quality of channel state information (CSI) has large impact on the performance of coordinated multi-point (CoMP) systems. In this paper we study the impact of channel prediction on the performance of coherent CoMP transmission in time-varying channels with large backhaul latency. We resort to large system analysis to derive an explicit expression of the average user rate of the CoMP system when predicted channels are employed for downlink precoding. By comparing with the Non-CoMP systems, we find that channel prediction brings much higher performance gain to CoMP systems with respect to channel estimation. As a result, a CoMP system can perform well for mobile users even under large backhaul latency, if channel prediction will be used instead of channel estimation. Simulation results are provided to validate our analysis.
Polypropylene foam behaviour under dynamic loadings: Strain rate, density and microstructure effects

Expanded polypropylene foams (EPP) can be used to absorb shock energy. The performance of these foams has to be studied as a function of several parameters such as density, microstructure and also the strain rate imposed during dynamic loading. The compressive stress–strain behaviour of these foams has been investigated over a wide range of engineering strain rates from 0.01 to 1500 s 1 in order to demonstrate the effects of foam density and strain rate on the initial collapse stress and the hardening modulus in the post-yield plateau region. A flywheel apparatus has been used for intermediate strain rates of about 200 s 1 and higher strain rate compression tests were performed using a viscoelastic Split Hopkinson Pressure Bar apparatus (SHPB), with nylon bars, at strain rates around 1500 s 1 EPP foams of various densities from 34 to 150 kgm 3 were considered and microstructural aspects were examined using two particular foams. Finally, in order to assess the contribution of the gas trapped in the closed cells of the foams, compression tests in a fluid chamber at quasi-static and dynamic loading velocities
Deep Learning vs . traditional Machine Learning algorithms used in Credit Card Fraud Detection

With the continuing growth of E-commerce, credit card fraud has evolved exponentially, where people are using more on-line services to conduct their daily transactions. Fraudsters masquerade normal behaviour of customers to achieve unlawful gains. Fraud patterns are changing rapidly where fraud detection needs to be re-evaluated from a reactive to a proactive approach. In recent years Deep Learning has gained lot of popularity in image recognition, speech recognition and natural language processing. This paper seeks to understand how Deep Learning can be helpful in finding fraud in credit card transactions and compare Deep Learning against several state of the art algorithms (RF, GBM, GLM) and sampling methods (Over, Under, Hybrid, SMOTE and ROSE) used in fraud detection. The results show that Deep Learning performed best with the highest Recall (accuracy of identifying fraudulent transactions), which means lowest financial losses to the company. However, Deep Learning achieved the lowest Precision rate (classified more legitimate transactions as fraudulent), which can cause customer dissatisfaction. Among other chosen classifiers, oversampling method performed best in terms of AUC, precision was highest for GLM and F-Score was highest for model trained using ROSE sampling method. Recall and Precision both have high cost, so there cannot be any trade of one against the other. Selecting the best classifier to identify fraud is based on the business goal. Keywords—Imbalanced class, Data mining, Sampling methods, H2O, Gradient Boosting, Random Forest, Generalized Linear Models, Deep Learning, Grid search, Hyper parameter optimization, Ensemble methods.
The global pattern of household wealth

We provide the first estimate of the level and distribution of global household wealth. The level of assets and debts for 39 countries are measured using household balance sheet and survey data centred on the year 2000. Average wealth holdings are imputed to countries lacking direct evidence. Microdata on household wealth distribution are assembled for 20 countries. Wealth inequality is imputed to other countries from the observed relation between wealth and income distribution in these countries. We find that the top 10 per cent owned 85 per cent of world wealth, and the Gini coefficient was 0.893, greater than that for the global distribution of income. Copyright # 2009 John Wiley & Sons, Ltd.
Use of virtual reality technique for the training of motor control in the elderly

Virtual augmented exercise, an emerging technology that can help to promote physical activity and combine the strengths of indoor and outdoor exercise, has recently been proposed as having the potential to increase exercise behavior in older adults. By creating a strong presence in a virtual, interactive environment, distraction can be taken to greater levels while maintaining the benefits of indoor exercises which may result in a shift from negative to positive thoughts about exercise. Recent findings on young participants show that virtual reality training enhances mood, thus, increasing enjoyment and energy. For older adults virtual, interactive environments can influence postural control and fall events by stimulating the sensory cues that are responsible in maintaining balance and orientation. However, the potential of virtual reality training has yet to be explored for older adults. This manuscript describes the potential of dance pad training protocols in the elderly and reports on the theoretical rationale of combining physical game-like exercises with sensory and cognitive challenges in a virtual environment. Eine durch virtuelle Realität ergänzte Bewegungsausführung stellt eine neue und sich schnell entwickelnde Technologie dar. Sie fördert die Lust zur Bewegung, vereinigt die Vorteile von Indoor- und Outdooraktivitäten und vermag sogar das Bewegungsverhalten von älteren Menschen zu verbessern. Eine starke Ablenkung von der eigentlichen Bewegungsausführung, verursacht durch ein überzeugendes Gefühl des Eintauchens in eine virtuell-interaktive Umgebung, kann dazu führen, dass sich die Meinung über Bewegung vom Negativen zum Positiven hin wendet. Neuste Erkenntnisse mit jungen Personen zeigen, dass das Training in einer virtuellen Umgebung Vergnügen bereitet, die Gemütslage und den Energielevel anhebt. Bei älteren Menschen kann eine virtuell-interaktive Umgebung die Haltungskontrolle beeinflussen und auch als Sturzprophylaxe dienen, in dem sie die sensorischen Bereiche stimuliert, die für die Kontrolle des Gleichgewichts und der Orientierung zuständig sind. Dennoch muss das Potenzial eines Trainings in einer virtuellen Umgebung bei älteren Menschen noch weiter erforscht werden. Dieser Artikel beschreibt die Möglichkeiten eines Einsatzes von elektronischen Tanzmatten bei älteren Menschen und erklärt die theoretischen Hintergründe der Kombination von körperlicher Aktivität mit gleichzeitigen sensorisch-kognitiven Aufgaben in einer virtuellen Umgebung.
School Quality, School Cost, and the Public/Private School Choices of Low-Income Households in Pakistan

Variation in school attributes, proximity, and fees across neighborhoods is used to identify factors which affect whether poor households send their children to government school, private school, or no school. Analysis shows that even the poorest households use private schools extensively, and that utilization increases with income. Lowering private school fees or distance or raising measured quality raises private school enrollments, partly by transfers from government schools and partly from enrollments of children who otherwise would not have gone to school. The strong demand for private schools is consistent with evidence of greater mathematics and language achievement in private schools than in government schools. These results strongly support an increased role for private delivery of schooling services to poor households in developing countries. School Quality, School Cost and the Public/Private School Choices of Low Income Households in Pakistan