LLukas22/scidocs huggingface dataset:
Randomised controlled trial of intrapleural streptokinase in community acquired pleural infection.

BACKGROUND
Standard treatment for pleural infection includes catheter drainage and antibiotics. Tube drainage often fails if the fluid is loculated by fibrinous adhesions when surgical drainage is needed. Streptokinase may aid the process of pleural drainage, but there have been no controlled trials to assess its efficacy.


METHODS
Twenty four patients with infected community acquired parapneumonic effusions were studied. All had either frankly purulent/culture or Gram stain positive pleural fluid (13 cases; 54%) or fluid which fulfilled the biochemical criteria for pleural infection. Fluid was drained with a 14F catheter. The antibiotics used were cefuroxime and metronidazole or were guided by culture. Subjects were randomly assigned to receive intrapleural streptokinase, 250,000 i.u. daily, or control saline flushes for three days. The primary end points related to the efficacy of pleural drainage--namely, the volume of pleural fluid drained and the chest radiographic response to treatment. Other end points were the number of pleural procedures needed and blood indices of inflammation.


RESULTS
The streptokinase group drained more pleural fluid both during the days of streptokinase/control treatment (mean (SD) 391 (200) ml versus 124 (44) ml; difference 267 ml, 95% confidence interval (CI) 144 to 390; p < .001) and overall (2564 (1663) ml, 95% CI 465 to 2545; p < 0.01). They showed greater improvement on the chest radiograph at discharge, measured as the fall in the maximum dimension of the pleural collection (6.0 (2.7) cm versus 3.4 (2.7) cm; difference 2.9 cm, 95% CI 0.3 to 4.4; p < 0.05) and the overall reduction in pleural fluid collection size (p < 0.05, two-tailed Fisher's exact test). Systemic fibrinolysis and bleeding complications did not occur. Surgery was required by three control patients but none in the streptokinase group.


CONCLUSIONS
Intrapleural streptokinase probably aids the treatment of pleural infections by improving pleural drainage without causing systemic fibrinolysis or local haemorrhage.
Evaluation of retinal nerve fiber layer thickness in Alzheimer disease using spectral-domain optical coherence tomography.

BACKGROUND/AIM
To evaluate the retinal nerve fiber layer (RNFL) thickness in patients with Alzheimer disease (AD) and to compare the results with those of healthy controls.


MATERIALS AND METHODS
Forty patients (mean age: 75.02 ± 6.34 years; 23 women) with untreated AD and 40 age-, sex-, and education-matched healthy patients were examined in this case-control prospective study. All patients underwent detailed ophthalmic and neurological examination. The Mini Mental State Examination (MMSE) was performed and RNFL thickness was measured using spectral-domain optical coherence tomography. The association between RNFL and MMSE score was also assessed.


RESULTS
The average RNFL thickness was 84 ± 7.0 µm in AD patients and 107 ± 6.3 µm in healthy subjects (P < 0.001). The mean MMSE score was 21.9 ± 2.13 in AD patients. There was no significant correlation between the RNFL thickness and MMSE score.


CONCLUSION
Patients with AD had reduced RNFL thickness in all quadrants compared with the control group. This finding suggests that RNFL thickness analysis may be useful in the early diagnosis of AD.
String model description of polarisation and angular distributions in ¯pp → ¯ΛΛ at low energies

Abstract:The observed polarisation of Λ hyperons from the inclusive pA → ΛX reaction at high energies has previously been well described within the Lund string model through polarised s¯s quark pair production in the string breaking hadronisation process. This model is here applied to the exclusive ¯pp → ¯ΛΛ reaction at low energies and compared to available data sets down to an incident-beam momentum of 1.835 GeV/c. This required an extension of the diquark scattering model to involve three components: an isotropic part relevant close to the threshold, a spectator part and a forward-scattering part as in pA → ΛX at high energies. The observed angular distributions are then reproduced and, for momentum transfers above | t'| = 0.2 GeV2, agreement with the measured polarisation is also obtained.
GestGlove: a wearable device with gesture based touchless interaction

Wearable devices have gained significant popularity in recent years and have enabled new modes of human computer interaction. Wearables have been explored to track user movements and gestures but typically require large arm motions. In this paper we propose a glove based wearable that is designed for active users like cyclists, motorists and skiers who typically wear a glove during their activity. The GestGlove has a gesture based user interface that enables single-handed touchless interaction. Inertial and bend sensors mounted on the device track subtle wrist and finger movements which are intuitive and convenient. We use the popular approach of Dynamic Time Warping (DTW) for the classification of this multivariate time series data. A Mahalanobis distance measure for DTW is proposed that uses the DTW warp path iteratively for metric calculation, an aspect that has not been explored in prior work.
MAX-MIN Ant System

Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for attacking hard combinatorial optimization problems. Yet, its performance, when compared to more fine-tuned algorithms, was rather poor for large instances of traditional benchmark problems like the Traveling Salesman Problem. To show that Ant Colony Optimization algorithms could be good alternatives to existing algorithms for hard combinatorial optimization problems, recent research in this area has mainly focused on the development of algorithmic variants which achieve better performance than Ant System. In this paper, we present MAX–MIN Ant System ( MMAS), an Ant Colony Optimization algorithm derived from Ant System.MMAS differs from Ant System in several important aspects, whose usefulness we demonstrate by means of an experimental study. Additionally, we relate one of the characteristics specific to MMAS — that of using a greedier search than Ant System — to results from the search space analysis of the combinatorial optimization problems attacked in this paper. Our computational results on the Traveling Salesman Problem and the Quadratic Assignment Problem show that MMAS is currently among the best performing algorithms for these problems. © 2000 Elsevier Science B.V. All rights reserved.
A modified particle swarm optimizer

In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer.
Tone Language Fluency Impairs Pitch Discrimination

Here we present evidence that native speakers of a tone language, in which pitch contributes to word meaning, are impaired in the discrimination of falling pitches in tone sequences, as compared to speakers of a non-tone language. Both groups were presented with monotonic and isochronous sequences of five tones (i.e., constant pitch and intertone interval). They were required to detect when the fourth tone was displaced in pitch or time. While speakers of a tone language performed more poorly in the detection of downward pitch changes, they did not differ from non-tone language speakers in their perception of upward pitch changes or in their perception of subtle time changes. Moreover, this impairment cannot be attributed to poor musical abilities since the impairment remains unchanged when individual differences in musical pitch-based processing is taken into account. Thus, the impairment appears highly specific and may reflect the influence of statistical regularities of tone languages.
Clustering Smart Card Data for Urban Mobility Analysis

Smart card data gathered by automated fare collection (AFC) systems are valuable resources for studying urban mobility. In this paper, we propose two approaches to cluster smart card data, which can be used to extract mobility patterns in a public transportation system. Two complementary standpoints are considered: a station-oriented operational point of view and a passenger-focused one. The first approach clusters stations based on when their activity occurs, i.e., how trips made at the stations are distributed over time. The second approach makes it possible to identify groups of passengers that have similar boarding times aggregated into weekly profiles. By applying our approaches to a real data set issued from the metropolitan area of Rennes, France, we illustrate how they can help reveal valuable insights about urban mobility, such as the presence of different station key roles, including residential stations used mostly in the mornings and work stations used only in the evening and almost exclusively during weekdays, as well as different passenger behaviors ranging from the sporadic and diffuse usage to typical commute practices. By cross comparing passenger clusters with fare types, we also highlight how certain usages are more specific to particular types of passengers.
Extreme programming promotes extreme learning?

Extreme programming (XP) is an agile methodology claimed to promote the rapid development of software systems, enabling the accommodation of changing customer requirements during the project lifecycle without excessive cost penalties. The mechanisms used to achieve this require the software development team to maintain accurate tacit knowledge through extensive face-to-face communication and peer learning. This characteristic of XP, the authors argue, makes it a suitable tool in the teaching of new technologies to software engineering students. This is borne out by feedback from a group of fourth-year Master of Engineering (MEng) software engineering undergraduate students who undertook an XP-based project as part of their course. Furthermore, the authors argue that the methodology is best taught in its full form through group project work. This is most effective when undertaken in the latter years of a computer science or software engineering course, after the students have been exposed to more traditional, plan-based methodologies.
Utility of the k-means clustering algorithm in differentiating apparent diffusion coefficient values of benign and malignant neck pathologies.

BACKGROUND AND PURPOSE
Does the K-means algorithm do a better job of differentiating benign and malignant neck pathologies compared to only mean ADC? The objective of our study was to analyze the differences between ADC partitions to evaluate whether the K-means technique can be of additional benefit to whole-lesion mean ADC alone in distinguishing benign and malignant neck pathologies.


MATERIAL AND METHODS
MR imaging studies of 10 benign and 10 malignant proved neck pathologies were postprocessed on a PC by using in-house software developed in Matlab. Two neuroradiologists manually contoured the lesions, with the ADC values within each lesion clustered into 2 (low, ADC-ADC(L); high, ADC-ADC(H)) and 3 partitions (ADC(L); intermediate, ADC-ADC(I); ADC(H)) by using the K-means clustering algorithm. An unpaired 2-tailed Student t test was performed for all metrics to determine statistical differences in the means of the benign and malignant pathologies.


RESULTS
A statistically significant difference between the mean ADC(L) clusters in benign and malignant pathologies was seen in the 3-cluster models of both readers (P = .03 and .022, respectively) and the 2-cluster model of reader 2 (P = .04), with the other metrics (ADC(H), ADC(I); whole-lesion mean ADC) not revealing any significant differences. ROC curves demonstrated the quantitative differences in mean ADC(H) and ADC(L) in both the 2- and 3-cluster models to be predictive of malignancy (2 clusters: P = .008, area under curve = 0.850; 3 clusters: P = .01, area under curve = 0.825).


CONCLUSIONS
The K-means clustering algorithm that generates partitions of large datasets may provide a better characterization of neck pathologies and may be of additional benefit in distinguishing benign and malignant neck pathologies compared with whole-lesion mean ADC alone.
A Fast Implementation of the Isodata Clustering Algorithm

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to ISODATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times. *A preliminary version of this paper appeared in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS'O3), Toulouse, France, 2003, Vol. 111, 2057-2059. +NASA Goddard Space Flight Center, Architecture and Automation Branch, Greenbelt, MD 20771 and Department of Computer Science, University of Maryland, College Park, Maryland, 20742. Email: nargess@cs.umd.edu. $ ~ e ~ a r t m e n t of Computer Science, University df Maryland, College Park, Maryland, 20742. The work of this author was supported by the Science Foundation under grant CCR-0098151. Email: mount@cs.umd.edu. l ~ e ~ a r t m e n t of Computer Science, Bar-Ilan University, Ramat-Gan 52900, Israel, and Center for Automation Research, University of Maryland, College Park, Maryland, 20742. Email: nathanOcs.biu.ac.il. NASA Goddard Space Flight Center, previously Applied Information Sciences Branch, currently Advanced Architectures and Automation Branch, Greenbelt, MD 20771. Email: Jacqueline.LeMoigne@nasa.gov. https://ntrs.nasa.gov/search.jsp?R=20070038185 2017-12-21T21:41:30+00:00Z
Rudiments of rough sets

Worldwide, there has been a rapid growth in interest in rough set theory and its applications in recent years. Evidence of this can be found in the increasing number of high-quality articles on rough sets and related topics that have been published in a variety of international journals, symposia, workshops, and international conferences in recent years. In addition, many international workshops and conferences have included special sessions on the theory and applications of rough sets in their programs. Rough set theory has led to many interesting applications and extensions. It seems that the rough set approach is fundamentally important in artificial intelligence and cognitive sciences, especially in research areas such as machine learning, intelligent systems, inductive reasoning, pattern recognition, mereology, knowledge discovery, decision analysis, and expert systems. In the article, we present the basic concepts of rough set theory and point out some rough setbased research directions and applications. 2006 Elsevier Inc. All rights reserved.
В поисках достоинства и ценности жизни российского гражданина

The article considers the limits of implementation of the equality, justice and freedom in Russian political and juridical culture, social institutes and practices. The author analyses the processes of shaping and functioning of Russian elite, its interaction with society, as well as the problems of political and juridical inequality.
Semantic Communication for Simple Goals Is Equivalent to On-line Learning

Previous works [11, 6] introduced a model of semantic communication between a “user” and a “server,” in which the user attempts to achieve a given goal for communication. They show that whenever the user can sense progress, there exist universal user strategies that can achieve the goal whenever it is possible for any other user to reliably do so. A drawback of the actual constructions is that the users are inefficient: they enumerate protocols until they discover one that is successful, leading to the potential for exponential overhead in the length of the desired protocol. Goldreich et al. [6] conjectured that this overhead could be reduced to a polynomial dependence if we restricted our attention to classes of sufficiently simple user strategies and goals. In this work, we are able to obtain such universal strategies for some reasonably general special cases by establishing an equivalence between these special cases and the usual model of mistake-bounded on-line learning [3, 15]. This equivalence also allows us to see the limits of constructing universal users based on sensing and motivates the study of sensing with richer kinds of feedback. Along the way, we also establish a new lower bound for the “beliefs model” [12], which demonstrates that constructions of efficient users in that framework rely on the existence of a common “belief” under which all of the servers in a class are designed to be efficient.
Two tongues for a dream: A hermeneutic study

............................................................................................................................. iv Dedication .......................................................................................................................... vi Acknowledgement ............................................................................................................ vii List of Tables ................................................................................................................... xiii List of Abbreviations ....................................................................................................... xvi
Interoperable Electronic Health Records Design: Towards a Service-Oriented Architecture

The digital automation of health information has traditionally focused on the formal implementation of electronic health records (EHRs). Most of these EHR systems are relational databases that focus on intra-enterprise applications; very few have become fully functional, scalable, distributed systems with interoperability. This paper identifies the design challenges in EHRs and explores the potential of service-oriented architecture in the development of interoperable EHRs. A prototype SOA model for an EHR in a health clinic setting is described. Challenges in the application of the SOA model to health care are discussed. The experience gained from this effort provides valuable insight into how SOA can be developed in health care organizations. The paradigm shift towards an SOA will involve the consideration of “health care services” as the fundamental basis for developing next generation health care systems.
Moderate visual impairment in India: the Andhra Pradesh Eye Disease Study.

AIM
To assess the prevalence and demographic associations of moderate visual impairment in the population of the southern Indian state of Andhra Pradesh.


METHODS
From 94 clusters in one urban and three rural areas of Andhra Pradesh, 11 786 people of all ages were sampled using a stratified, random, cluster, systematic sampling strategy. The eligible people were invited for interview and detailed dilated eye examination by trained professionals. Moderate visual impairment was defined as presenting distance visual acuity less than 6/18 to 6/60 or equivalent visual field loss in the better eye.


RESULTS
Of those sampled, 10,293 (87.3%) people participated in the study. In addition to the previously reported 1.84% prevalence of blindness (presenting distance visual acuity less than 6/60 or central visual field less than 20 degrees in the better eye) in this sample, 1237 people had moderate visual impairment, an adjusted prevalence of 8.09% (95% CI 6.89 to 9.30%). The majority of this moderate visual impairment was caused by refractive error (45.8%) and cataract (39.9%). Increasing age, female sex, decreasing socioeconomic status, and rural area of residence had significantly higher odds of being associated with moderate visual impairment.


CONCLUSIONS
These data suggest that there is a significant burden of moderate visual impairment in this population in addition to blindness. Extrapolation of these data to the population of India suggests that there were 82 million people with moderate visual impairment in the year 2000, and this number is likely to be 139 million by the year 2020 if the current trend continues. This impending large burden of moderate visual impairment, the majority of which is due to the relatively easily treatable refractive error and cataract, would have to be taken into account while estimating the eye care needs in India, in addition to dealing with blindness. Specific strategies targeting the elderly population, people with low socioeconomic status, those living in the rural areas, and females would have to be implemented in the long term to reduce moderate visual impairment.
Heritability of high sugar consumption through drinks and the genetic correlation with substance use.

BACKGROUND
High sugar consumption contributes to the rising prevalence of obesity. Sugar can have rewarding effects that are similar to, but less strong than, the effects of addictive substances. People who consume large amounts of sugar also tend to use more addictive substances, but it is unclear whether this is due to shared genetic or environmental risk factors.


OBJECTIVE
We examined whether there are genetic influences on the consumption of sugar-containing drinks and whether genetic factors can explain the association with substance use.


DESIGN
The frequency of consumption of sugar-containing drinks (e.g., cola, soft drinks, and energy drinks) and addictive substances (nicotine, caffeine, alcohol, cannabis, and illicit drugs) was obtained for 8586 twins who were registered at the Netherlands Twin Register (women: 68.7%; mean ± SD age: 33.5 ± 15.3 y). Participants were categorized as high or low sugar consumers (>1 compared with ≤1 SD above daily consumption in grams) and as high or low substance users (≥2 compared with <2 substances). Through bivariate genetic modeling, genetic and environmental influences on sugar consumption, substance use, and their association were estimated.


RESULTS
Genetic factors explained 48% of the variation in high sugar consumption, whereas unique environmental factors explained 52%. For high substance use, these values were 62% and 38%, respectively. There was a moderate phenotypic association between high sugar consumption and high substance use (r = 0.2), which was explained by genetic factors (59%) and unique environmental factors (41%).


CONCLUSIONS
The positive association between high sugar consumption and high substance use was partly due to unique environmental factors (e.g., social situations). Genetic factors were also of influence, suggesting that neuronal circuits underlying the development of addiction and obesity are related. Further research is needed to identify genes that influence sugar consumption and those that overlap with substance use.