LLukas22/scidocs huggingface dataset:
Unsteady aerodynamics and flow control for flapping wing flyers

The creation of micro air vehicles (MAVs) of the same general sizes and weight as natural fliers has spawned renewed interest in flapping wing flight. With a wingspan of approximately 15 cm and a flight speed of a few meters per second, MAVs experience the same low Reynolds number (10–10) flight conditions as their biological counterparts. In this flow regime, rigid fixed wings drop dramatically in aerodynamic performance while flexible flapping wings gain efficacy and are the preferred propulsion method for small natural fliers. Researchers have long realized that steady-state aerodynamics does not properly capture the physical phenomena or forces present in flapping flight at this scale. Hence, unsteady flow mechanisms must dominate this regime. Furthermore, due to the low flight speeds, any disturbance such as gusts or wind will dramatically change the aerodynamic conditions around the MAV. In response, a suitable feedback control system and actuation technology must be developed so that the wing can maintain its aerodynamic efficiency in this extremely dynamic situation; one where the unsteady separated flow field and wing structure are tightly coupled and interact nonlinearly. For instance, birds and bats control their flexible wings with muscle tissue to successfully deal with rapid changes in the flow environment. Drawing from their example, perhaps MAVs can use lightweight actuators in conjunction with adaptive feedback control to shape the wing and achieve active flow control. This article first reviews the scaling laws and unsteady flow regime constraining both biological and man-made fliers. Then a summary of vortex dominated unsteady aerodynamics follows. Next, aeroelastic coupling and its effect on lift and thrust are discussed. Afterwards, flow control strategies found in nature and devised by man to deal with separated flows are examined. Recent work is also presented in using microelectromechanical systems (MEMS) actuators and angular speed variation to achieve active flow control for MAVs. Finally, an explanation for aerodynamic gains seen in flexible versus rigid membrane wings, derived from an unsteady three-dimensional computational fluid dynamics model with an integrated distributed control algorithm, is presented. r 2003 Elsevier Ltd. All rights reserved.
Skeletal muscle mass reference curves for children and adolescents.

BACKGROUND
Skeletal muscle is key to motor development and represents a major metabolic end organ that aids glycaemic regulation.


OBJECTIVES
To create gender-specific reference curves for fat-free mass (FFM) and appendicular (limb) skeletal muscle mass (SMMa) in children and adolescents. To examine the muscle-to-fat ratio in relation to body mass index (BMI) for age and gender.


METHODS
Body composition was measured by segmental bioelectrical impedance (BIA, Tanita BC418) in 1985 Caucasian children aged 5-18.8 years. Skeletal muscle mass data from the four limbs were used to derive smoothed centile curves and the muscle-to-fat ratio.


RESULTS
The centile curves illustrate the developmental patterns of %FFM and SMMa. While the %FFM curves differ markedly between boys and girls, the SMMa (kg), %SMMa and %SMMa/FFM show some similarities in shape and variance, together with some gender-specific characteristics. Existing BMI curves do not reveal these gender differences. Muscle-to-fat ratio showed a very wide range with means differing between boys and girls and across fifths of BMI z-score.


CONCLUSIONS
BIA assessment of %FFM and SMMa represents a significant advance in nutritional assessment since these body composition components are associated with metabolic health. Muscle-to-fat ratio has the potential to provide a better index of future metabolic health.
Investigation of the single case in neuropsychology: confidence limits on the abnormality of test scores and test score differences

Neuropsychologists often need to estimate the abnormality of an individual patient's test score, or test score discrepancies, when the normative or control sample against which the patient is compared is modest in size. Crawford and Howell [The Clinical Neuropsychologist 12 (1998) 482] and Crawford et al. [Journal of Clinical and Experimental Neuropsychology 20 (1998) 898] presented methods for obtaining point estimates of the abnormality of test scores and test score discrepancies in this situation. In the present study, we extend this work by developing methods of setting confidence limits on the estimates of abnormality. Although these limits can be used with data from normative or control samples of any size, they will be most useful when the sample sizes are modest. We also develop a method for obtaining point estimates and confidence limits on the abnormality of a discrepancy between a patient's mean score on k-tests and a test entering into that mean. Computer programs that implement the formulae for the confidence limits (and point estimates) are described and made available.
On surface electromagnetic waves

The problem of surface electromagnetic waves is discussed. In spite of recent experimental evidence for the existence of Zenneck surface waves, theoretical consensus on this issue is lacking.
Regional differences in grey and white matter in children and adults with autism spectrum disorders: an activation likelihood estimate (ALE) meta-analysis.

Structural alterations in brain morphology have been inconsistently reported in children compared to adults with autism spectrum disorder (ASD). We assessed these differences by performing meta-analysis on the data from 19 voxel-based morphometry studies. Common findings across the age groups were grey matter reduction in left putamen and medial prefrontal cortex (mPFC) and grey matter increases in the lateral PFC, while white matter decreases were seen mainly in the children in frontostriatal pathways. In the ASD sample, children/adolescents were more likely than adults to have increased grey matter in bilateral fusiform gyrus, right cingulate and insula. Results show that clear maturational differences exist in social cognition and limbic processing regions only in children/adolescents and not in adults with ASD, and may underlie the emotional regulation that improves with age in this population.
Perceived functioning, well-being and psychiatric symptoms in patients with stable schizophrenia treated with long-acting risperidone for 1 year.

BACKGROUND
The extent to which antipsychotics improve patients' well-being is uncertain.


AIMS
To examine psychopathology and patient-rated functioning and well-being in patients treated with risperidone.


METHOD
In a 1-year, open-label, international multicentre trial of long-acting risperidone in 615 stable adult patients with schizophrenia, self-rated functioning and well-being were measured every 3 months using the Short Form 36-item questionnaire (SF-36). Psychopathology was quantified using the Positive and Negative Syndrome Scale (PANSS).


RESULTS
Significant improvements were found on the SF-36 mental component summary score and vitality and social functioning scales. PANSS and mental component summary scores were moderately correlated.


CONCLUSIONS
Patient-reported functioning and well-being appear to differ from investigator-rated psychotic symptoms. Patient-rated well-being should be assessed with symptoms to help measure treatment outcomes.
Improvement in adolescent screening and counseling rates for risk behaviors and developmental tasks.

BACKGROUND
High-quality preventive services for youth aged 11 to 18 include assessment and counseling regarding health behavior risks and developmental tasks/strengths of adolescence. Nationally, primary care health behavior risk screening and counseling rates lag considerably behind other preventive health services. The purpose of this project was to assist pediatric and family medicine practices to make office systems-based changes that promote comprehensive screening and counseling for risks and developmental tasks/strengths during adolescent preventive services visits.


METHODS
Over a 9-month period, 7 pediatric and 1 family medicine primary care practices (13 physicians and 3 nurse practitioners) participated in a modified Breakthrough Series Collaborative. This project was designed to support primary care practitioner efforts to implement comprehensive screening and counseling for risk behaviors and developmental tasks/strengths for their adolescent patients and increase the rate of brief office intervention and referral. Composite variables were designed to reflect whether screening and counseling were documented for risks and developmental tasks. Statistical comparisons were made by using the nonparametric Wilcoxon matched-pairs signed rank test.


RESULTS
There were increases in the composite measures of screening and counseling for risk behaviors (all 6 risks: 26%-50%, P = .01) and 3 of 4 developmental tasks/strengths (32%-66%, P = .01). Documentation of office interventions for identified risks and out-of office referral rates did not change.


CONCLUSIONS
With the use of an office systems-based approach, screening and counseling for all critical risk behaviors and developmental tasks/strengths during adolescent preventive services visits can be improved in primary care practices.
Computing: A vision for data science

I believe that four advancements are necessary to achieve that aim. Methods for integrating diverse algorithms seamlessly into big-data architectures need to be found. Software development and archiving should be brought together under one roof. Data reading must become automated among formats. Ultimately, the interpretation of vast streams of scientific data will require a new breed of researcher equally familiar with science and advanced computing.
Accurately and Efficiently Interpreting Human-Robot Instructions of Varying Granularities

Humans can ground natural language commands to tasks at both abstract and fine-grained levels of specificity. For instance, a human forklift operator can be instructed to perform a high-level action, like “grab a pallet” or a low-level action like “tilt back a little bit.” While robots are also capable of grounding language commands to tasks, previous methods implicitly assume that all commands and tasks reside at a single, fixed level of abstraction. Additionally, methods that do not use multiple levels of abstraction encounter inefficient planning and execution times as they solve tasks at a single level of abstraction with large, intractable state-action spaces closely resembling real world complexity. In this work, by grounding commands to all the tasks or subtasks available in a hierarchical planning framework, we arrive at a model capable of interpreting language at multiple levels of specificity ranging from coarse to more granular. We show that the accuracy of the grounding procedure is improved when simultaneously inferring the degree of abstraction in language used to communicate the task. Leveraging hierarchy also improves efficiency: our proposed approach enables a robot to respond to a command within one second on 90% of our tasks, while baselines take over twenty seconds on half the tasks. Finally, we demonstrate that a real, physical robot can ground commands at multiple levels of abstraction allowing it to efficiently plan different subtasks within the same planning hierarchy.
COMBINED INTERLEAVING AND COMPANDING FOR PAPR REDUCTION IN OFDM SYSTEMS

Peak to Average Power Ratio (PAPR) is one of the serious problems in any wireless communication systems using multicarrier modulation technique as OFDM, which reduces the efficiency of transmit high power amplifier. In this paper, proposed scheme will be introduced, which combines interleaving technique and companding technique to reduce PAPR. This scheme will be compared with the system that uses other technique for reduction which is the clipping technique. By using proposed scheme, the PAPR of OFDM signal can be reduced by 6.8 dB over the original system, i.e., without PAPR reduction. Also, SNR decreases by more than 5 dB for Bit Error Rate (BER) of 10−3 over the original system. Moreover, the proposed scheme gives improvement more than 4.5 dB for BER of 10−3 over the system that uses clipping. All these systems will be evaluated in the presence of nonlinear power amplifier.
Feature extraction approaches from natural language requirements for reuse in software product lines: A systematic literature review

Requirements for implemented system can be extracted and reused for a production of a new similar system. Extraction of common and variable features from requirements leverages the benefits of the software product lines engineering (SPLE). Although various approaches have been proposed in feature extractions from natural language (NL) requirements, no related literature review has been published to date for this topic. This paper provides a systematic literature review (SLR) of the state-of-the-art approaches in feature extractions from NL requirements for reuse in SPLE. We have included 13 studies in our synthesis of evidence and the results showed that hybrid natural language processing approaches were found to be in common for overall feature extraction process. A mixture of automated and semi-automated feature clustering approaches from data mining and information retrieval were also used to group common features, with only some approaches coming with support tools. However, most of the support tools proposed in the selected studies were not made available publicly and thus making it hard for practitioners’ adoption. As for the evaluation, this SLR reveals that not all studies employed software metrics as ways to validate experiments and case studies. Finally, the quality assessment conducted confirms that practitioners’ guidelines were absent in the selected studies. © 2015 Elsevier Inc. All rights reserved. c t t t r c S o r ( l w t r t
Flexural-torsional-coupled vibration analysis of axially loaded closed-section composite Timoshenko beam by using DTM

This study introduces the differential transform method (DTM) to analyse the free vibration response of an axially loaded, closed-section composite Timoshenko beam which features material coupling between flapwise bending and torsional vibrations due to ply orientation. The governing differential equations of motion are derived using Hamilton’s principle and solved by applying DTM. The mode shapes are plotted, the natural frequencies are calculated and the effects of the bending–torsion coupling, the axial force and the slenderness ratio on the natural frequencies are investigated using the computer package, Mathematica. Wherever possible, comparisons are made with the studies in open literature. r 2007 Elsevier Ltd. All rights reserved.
Keratosis pilaris rubra: a common but underrecognized condition.

BACKGROUND
Keratosis pilaris is a common skin disorder of childhood that often improves with age. Less common variants of keratosis pilaris include keratosis pilaris atrophicans and atrophodermia vermiculata.


OBSERVATIONS
In this case series from dermatology practices in the United States, Canada, Israel, and Australia, the clinical characteristics of 27 patients with keratosis pilaris rubra are described. Marked erythema with follicular prominence was noted in all patients, most commonly affecting the lateral aspects of the cheeks and the proximal arms and legs, with both more marked erythema and widespread extent of disease than in keratosis pilaris. The mean age at onset was 5 years (range, birth to 12 years). Sixty-three percent of patients were male. No patients had atrophy or scarring from their lesions. Various treatments were used, with minimal or no improvement in most cases.


CONCLUSIONS
Keratosis pilaris rubra is a variant of keratosis pilaris, with more prominent erythema and with more widespread areas of skin involvement in some cases, but without the atrophy or hyperpigmentation noted in certain keratosis pilaris variants. It seems to be a relatively common but uncommonly reported condition.
Kimama Well - Photos

The Snake River Plain (SRP), Idaho, hosts potential geothermal resources due to elevated groundwater temperatures associated with the thermal anomaly Yellowstone-Snake River hotspot. Project HOTSPOT has coordinated international institutions and organizations to understand subsurface stratigraphy and assess geothermal potential. Over 5.9km of core were drilled from three boreholes within the SRP in an attempt to acquire continuous core documenting the volcanic and sedimentary record of the hotspot: (1) Kimama, (2) Kimberly, and (3) Mountain Home. The Kimama drill site was set up to acquire a continuous record of basaltic volcanism along the central volcanic axis and to test the extent of geothermal resources beneath the Snake River aquifer. Data submitted by project collaborator Doug Schmitt, University of Alberta
The Ratchet Effect Re-examined: A Learning Perspective

We study dynamic moral hazard where principal and agent are symmetrically uncertain about job difficulty. Since effort is unobserved, shirking leads the principal to believe that the job is hard, increasing the agent’s continuation value. So deterring shirking requires steeper incentives, which induce the agent to over-work today, since he can quit if the principal believes that the job is easy. With continuous effort choices, no interior effort is implementable in the first period. The agent’s continuation value function is non-differentiable and convex, since the principal makes the agent indifferent between his discrete (participation) choices in the second period. The problem can be solved if the agent’s participation decision is made continuous, or if there are long-term commitments, and we provide conditions for the first order approach to work. However, the impossibility result recurs in other agency models that combine discrete and continuous choices.
Association between legume intake and self-reported diabetes among adult men and women in India

BACKGROUND
It is postulated that a diet high in legumes may be beneficial in preventing diabetes. However, little empirical evidence on this association exists in developing countries. We aimed to examine the association between legume intake and self-reported diabetes status in adult men and women in India.


METHODS
The analysis is based on a population-based cross sectional study of 99,574 women and 56,742 men aged 20-49 years included in India's third National Family Health Survey conducted in 2005-06. Association of legume intake, determined by the frequency of consumption of pulses and beans (daily, weekly and occasionally or never), with the reported prevalence of diabetes were estimated using multiple logistic regression after adjusting for frequency of consumption of other food items, BMI status, tobacco smoking, alcohol drinking, watching television, age, education, living standard of the household, residence and geographic regions.


RESULTS
Daily (OR: 0.71; 95% CI: 0.59-0.87; p=0.001) and weekly (OR: 0.66; 95% CI: 0.54-0.80; p<0.001) legumes intake were associated with a significantly reduced prevalence of diabetes among adult Indian women even after controlling for the effects of potentially confounding factors, whereas non-significant inverse associations were observed in men.


CONCLUSION
Daily or weekly intake of legumes was inversely associated with presence of diabetes in the Indian population. However, this is an observational finding and uncontrolled confounding cannot be excluded as an explanation for the association. More epidemiological research with better measures of legumes intake and clinical measures of diabetes is needed to clarify this relationship.
Triple Non-negative Matrix Factorization Technique for Sentiment Analysis and Topic Modeling

​ Topic modeling refers to the process of algorithmically sorting documents into categories based on some common relationship between the documents. This common relationship between the documents is considered the “topic” of the documents. Sentiment analysis refers to the process of algorithmically sorting a document into a positive or negative category depending whether this document expresses a positive or negative opinion on its respective topic. In this paper, I consider the open problem of document classification into a topic category, as well as a sentiment category. This has a direct application to the retail industry where companies may want to scour the web in order to find documents (blogs, Amazon reviews, etc.) which both speak about their product, and give an opinion on their product (positive, negative or neutral). My solution to this problem uses a Non-negative Matrix Factorization (NMF) technique in order to determine the topic classifications of a document set, and further factors the matrix in order to discover the sentiment behind this category of product. Introduction to Sentiment Analysis:​ In the United States, the incredible accessibility of the internet gives a voice to every consumer. Furthermore, internet blogs and common review sites are the first places the majority of consumers turn to when researching the pros and cons behind a product they are looking to purchase. Discovering sentiment and insights behind a company's products is hardly a new challenge, but a constantly evolving one given the complexity and sheer number of reviews buried inside a multitude of internet domains. Internet reviews, perhaps more frequently than a traditionally written and formatted magazine or newspaper review, are riddled with sarcasm, abbreviations, and slang. Simple text classification techniques based on analyzing the number of positive and negative words that occur in a document are error prone because of this. The internet requires a new solution to the trend of “reviews in 140 characters or less” which will necessitate unsupervised or semi-supervised machine learning and natural language processing techniques. Observed in [Ng et al., 2009] semi-supervised dictionary based approaches yield unsatisfactory results, with resulting lexicons of large coverage and low precision, or limited coverage and higher precision. In this paper, I will attempt to utilize these previously created dictionaries (of positive and negative words) and incorporate them into a machine learning approach to classify unlabeled documents. Introduction to Non-negative Matrix Factorization and Topic Modeling:​ Non-negative Matrix Factorization has applications to many fields such as computer vision, but we are interested in the specific application to topic modeling (often referred to as document clustering). NMF is the process of factoring a matrix into (usually) two parts where a [A x B] matrix is approximated by [A x r] x [r x B] where r is a chosen value, less than A and B. Every element in [A x r] and [r x B] must be non-negative throughout this process.
5G roadmap: 10 key enabling technologies

The fifth generation (5G) mobile communication networks will require a major paradigm shift to satisfy the increasing demand for higher data rates, lower network latencies, better energy efficiency, and reliable ubiquitous connectivity. With prediction of the advent of 5G systems in the near future, many efforts and revolutionary ideas have been proposed and explored around the world. The major technological breakthroughs that will bring renaissance to wireless communication networks include (1) a wireless software-defined network, (2) network function virtualization, (3) millimeter wave spectrum, (4) massive MIMO, (5) network ultra-densification, (6) big data and mobile cloud computing, (7) scalable Internet of Things, (8) device-to-device connectivity with high mobility, (9) green communications, and (10) new radio access techniques. In this paper, the state-of-the-art and the potentials of these ten enabling technologies are extensively surveyed. Furthermore, the challenges and limitations for each technology are treated in depth, while the possible solutions are highlighted. © 2016 Elsevier B.V. All rights reserved.