LLukas22/scidocs huggingface dataset:
"The Fly": a new clinical assessment and treatment method for deficits of movement control in the cervical spine: reliability and validity.

STUDY DESIGN
Test-retest and case-control study designed to detect accuracy of cervical spine movements by comparing 3 incrementally difficult movement patterns. An asymptomatic group, a nontrauma neck pain group, and a group with whiplash-associated disorders, Grade II, were tested (n = 18 in each group).


OBJECTIVE
To determine the test-retest reliability and the discriminative validity of the new Fly method.


SUMMARY OF BACKGROUND DATA
A lack of reliable and valid measures for grading the deficits of movement control in the cervical spine makes it impossible to prescribe treatment appropriate to each patient's respective impairment level.


METHODS
Head tracking of a moving fly which appeared on a computer screen. Easy, medium, and difficult patterns, each of which was repeated 3 times in random order, were tested. Amplitude accuracy (deviation of movements), directional accuracy (time on target, undershoots vs. overshoots) were compared across patterns and groups on 2 occasions, 1 week apart.


RESULTS
The intraclass correlation coefficient(2,1) ranged from 0.53 to 0.82 for both variables, except for the subvariable "overshoots" (0.14-0.42). The limits of agreement (LOA) were progressively wider across patterns (easy-medium-difficult) and groups (asymptomatic-nontrauma-whiplash-associated disorder). Analysis of variance with repeated measures revealed significant differences between patterns within each group and between groups respectively for both outcome variables (P < 0.001).


CONCLUSION
The Fly method provides reliable and valid measures for movement control of the cervical spine. Higher means and wider LOA across patterns and subject groups are reasoned to be inherent in the new Fly method and the subject groups tested. The wide LOA in the symptomatic groups supports the development of a normative database. The new Fly method can be used both as an assessment and a treatment method and ensures gradual progression in the treatment for deficits of movement control in patients with neck pain.
Diffusion of efficacious interventions for children and adolescents with mental health problems.

BACKGROUND
Child and adolescent mental health problems are prevalent and require adequate interventions. Despite several evidence-based interventions for these problems described in the literature, few studies addressed strategies to diffuse efficacious interventions for child mental disorders especially in developing countries.


METHODS
An extensive but not systematic review of the literature was performed aiming to identify evidence-based interventions for children and adolescents with mental disorders, professionals to target in disseminating these interventions, and the available strategies to diffuse information.


RESULTS
Substantial evidence-based information is available to guide preventive, psychosocial and psychopharmacological interventions. The effectiveness of treatments in real-world settings and the cost-effectiveness of interventions are rarely tested. Professionals at different levels (teachers, school counselors, social workers, general practitioners, pediatricians, child psychologists and psychiatrists) should be targeted in diffusing efficacious interventions for child mental health problems worldwide. Telepsychiatry and the internet seem to be the most promising strategies to diffuse knowledge with lower costs.


CONCLUSIONS
Medical and allied professionals must incorporate child and adolescent mental health issues in their under- and postgraduate curricula, and be better prepared to critically evaluate available information. Professionals need to disseminate evidence-based programs to guide parents and teachers in developing countries to deal with child and adolescent difficulties. Countries need to explore internet solutions for dissemination of medical information.
Investigation of the Drug Release and Surface Morphological Properties of Film-Coated Pellets, and Physical, Thermal and Mechanical Properties of Free Films as a Function of Various Curing Conditions

The purpose of the present investigation was to elucidate the influence of curing on different physical properties of Eudragit® NE and RS coating systems. Increased curing times resulted in decreased drug release rates from Eudragit® NE-coated beads. However, an increase in drug release rates was noticed at longer curing times and higher temperatures for the Eudragit® RS coating system. The surface morphological changes of the film-coated beads revealed that there were no visible macroscopic changes as a result of curing. The absence of any ibuprofen melting peak in the DSC thermograms of cured NE and RS coated beads confirmed that there was no surface crystallization of ibuprofen. These results indicated that the increase in drug release rates from RS coated pellets, when subjected to long curing times, resulted from loss of plasticizer. Free films of Eudragit® NE exhibited an increase in tensile strength with increased curing times, whereas Eudragit® RS free films showed a decrease in tensile strength beyond 4 h of curing at 70 and 90 °C. The film thicknesses and weights of free films of Eudragit® RS prepared with triethyl citrate plasticizer were found to change more dramatically with curing than did free films of Eudragit® RS prepared with ibuprofen as the plasticizer. An increase in pore volume was also observed with increased curing times for Eudragit® RS free films. Such changes with curing were shown to be due to the loss of plasticizer molecules, leading to the formation of molecular-scale voids and channels.
Clinical efficacy and safety of abatacept in methotrexate-naive patients with early rheumatoid arthritis and poor prognostic factors

OBJECTIVES
To assess the efficacy and safety of abatacept in methotrexate-naive patients with early rheumatoid arthritis (RA) and poor prognostic factors.


METHODS
In this double-blind, phase IIIb study, patients with RA for 2 years or less were randomly assigned 1 : 1 to receive abatacept (approximately 10 mg/kg) plus methotrexate, or placebo plus methotrexate. Patients were methotrexate-naive and seropositive for rheumatoid factor (RF), anti-cyclic citrullinated protein (CCP) type 2 or both and had radiographic evidence of joint erosions. The co-primary endpoints were the proportion of patients achieving disease activity score in 28 joints (DAS28)-defined remission (C-reactive protein) and joint damage progression (Genant-modified Sharp total score; TS) at year 1. Safety was monitored throughout.


RESULTS
At baseline, patients had a mean DAS28 of 6.3, a mean TS of 7.1 and mean disease duration of 6.5 months; 96.5% and 89.0% of patients were RF or anti-CCP2 seropositive, respectively. At year 1, a significantly greater proportion of abatacept plus methotrexate-treated patients achieved remission (41.4% vs 23.3%; p<0.001) and there was significantly less radiographic progression (mean change in TS 0.63 vs 1.06; p = 0.040) versus methotrexate alone. Over 1 year, the frequency of adverse events (84.8% vs 83.4%), serious adverse events (7.8% vs 7.9%), serious infections (2.0% vs 2.0%), autoimmune disorders (2.3% vs 2.0%) and malignancies (0.4% vs 0%) was comparable for abatacept plus methotrexate versus methotrexate alone.


CONCLUSIONS
In a methotrexate-naive population with early RA and poor prognostic factors, the combination of abatacept and methotrexate provided significantly better clinical and radiographic efficacy compared with methotrexate alone and had a comparable, favourable safety profile.
CM-GANs: Cross-modal Generative Adversarial Networks for Common Representation Learning

It is known that the inconsistent distributions and representations of different modalities, such as image and text, cause the heterogeneity gap, which makes it very challenging to correlate heterogeneous data and measure their similarities. Recently, generative adversarial networks (GANs) have been proposed and have shown their strong ability to model data distribution and learn discriminative representation. It has also been shown that adversarial learning can be fully exploited to learn discriminative common representations for bridging the heterogeneity gap. Inspired by this, we aim to effectively correlate large-scale heterogeneous data of different modalities with the power of GANs to model cross-modal joint distribution. In this article, we propose Cross-modal Generative Adversarial Networks (CM-GANs) with the following contributions. First, a cross-modal GAN architecture is proposed to model joint distribution over the data of different modalities. The inter-modality and intra-modality correlation can be explored simultaneously in generative and discriminative models. Both compete with each other to promote cross-modal correlation learning. Second, the cross-modal convolutional autoencoders with weight-sharing constraint are proposed to form the generative model. They not only exploit the cross-modal correlation for learning the common representations but also preserve reconstruction information for capturing the semantic consistency within each modality. Third, a cross-modal adversarial training mechanism is proposed, which uses two kinds of discriminative models to simultaneously conduct intra-modality and inter-modality discrimination. They can mutually boost to make the generated common representations more discriminative by the adversarial training process. In summary, our proposed CM-GAN approach can use GANs to perform cross-modal common representation learning by which the heterogeneous data can be effectively correlated. Extensive experiments are conducted to verify the performance of CM-GANs on cross-modal retrieval compared with 13 state-of-the-art methods on 4 cross-modal datasets.
Use of Contraceptives and Unmet Need for Family Planning among Tribal Women in India and Selected Hilly States

The paper provides a comprehensive picture of knowledge and use of contraceptives among scheduled tribes of India and selected central hilly states where tribal population contributes more than 30% of the total tribal population of the country. An attempt is also made to know how far scheduled tribes differ from non-tribes in the states, namely Jharkhand, Madhya Pradesh, and Chhattisgarh, using information collected in the third round of District-level Household Survey (DLHS-RCH III: 2007-2008). Bivariate analysis was used for understanding the level of knowledge, use of and unmet need for contraception among different tribal and non-tribal groups. Binary logistic regression was used for understanding the factors associated with the use of contraception and unmet need for family planning among tribal women. Knowledge and use of temporary contraceptive methods are considerably lower among tribal women compared to their non-tribal counterparts in the three states under study. Low acceptance due to phobia of adverse health consequences, accessibility to and lack of sound knowledge of contraception are the leading reasons for not using contraceptives. The unmet need for family planning among them was quite high, especially in the state of Jharkhand. Multivariate analysis substantiated the role of women and husbands' education, age of women, and number of surviving boys in the use of any modem method of contraception. Educating women and their respective husbands about proper use and benefits of modem contraceptives is important to solve the problem of high unmet need for family planning among these tribal women. A simultaneous attention to the health systems strengthening component is crucial for ensuring sustained delivery of good-quality family planning services.
Approaches to reflexivity in qualitative research.

Introduction Reflexivity is a curious term with various meanings. Finding a definition of reflexivity that demonstrates what it means and how it is achieved is difficult (Colbourne and Sque 2004). Moreover, writings on reflexivity have not been transparent in terms of the difficulties, practicalities and methods of the process (Mauthner and Doucet 2003). Nevertheless, it is argued that an attempt be made to gain ‘some kind of intellectual handle’ on reflexivity in order to make use of it as a guiding standard (Freshwater and Rolfe 2001). The role of reflexivity in the many and varied qualitative methodologies is significant. It is therefore a concept of particular relevance to nursing as qualitative methodologies play a principal function in nursing enquiry. Reflexivity assumes a pivotal role in feminist research (King 1994). It is also paramount in participatory action research (Robertson 2000), ethnographies, and hermeneutic and post-structural approaches (Koch and Harrington 1998). Furthermore, it plays an integral part in medical case study research reflexivity epistemological critical feminist ▲ ▲ ▲ ▲ k e y w o rd s
Markov Localization for Mobile Robots in Dynamic Environments

Localization, that is the estimation of a robot's location from sensor data, is a fundamental problem in mobile robotics. This papers presents a version of Markov localization which provides accurate position estimates and which is tailored towards dynamic environments. The key idea of Markov localization is to maintain a probability density over the space of all locations of a robot in its environment. Our approach represents this space metrically, using a fine-grained grid to approximate densities. It is able to globally localize the robot from scratch and to recover from localization failures. It is robust to approximate models of the environment (such as occupancy grid maps) and noisy sensors (such as ultrasound sensors). Our approach also includes a filtering technique which allows a mobile robot to reliably estimate its position even in densely populated environments in which crowds of people block the robot's sensors for extended periods of time. The method described here has been implemented and tested in several real-world applications of mobile robots, including the deployments of two mobile robots as interactive museum tour-guides. Introduction Markov Localization The Basic Idea Basic Notation Recursive Localization 1 of 2 12/10/00 10:59 AM Markov Localization for Mobile Robots in Dynaic Environments http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume11/fox99a-html/jair-localize.html
A Robust Password-based Authentication Scheme for Heterogeneous Sensor Networks

Abstract User authentication is a critical security function for computer systems that allow legitimate users remote access over an insecure communication network. In this paper, we propose a new password-based authentication scheme for heterogeneous sensor networks that consist of sensor nodes of different types. The proposed scheme allows legitimate users to query sensor data at any sensor node in the network, provides not only mutual authentication but also key agreement between a user and a sensor node, and adopts fuzzy identity-based encryption for gateway nodes and high-end sensor nodes. Additionally, our analysis shows that the proposed scheme is immune to some of the most notorious attacks, such as replay attacks, forgery attacks, offline-dictionary attacks, stolen smart card attacks, insider attacks, and many other potential breaches of security.
A pre-test post-test study of a brief educational intervention demonstrates improved knowledge of potential acute myocardial infarction symptoms and appropriate responses in cardiac rehabilitation patients.

BACKGROUND
Patient delay in recognizing and responding to potential acute myocardial infarction (AMI) symptoms is an international issue. Cardiac rehabilitation provides an ideal opportunity to deliver an intervention.


AIMS
This study examines an individual educational intervention on knowledge of heart attack warning signs and specific chest pain action plans for people with coronary heart disease.


METHODS
Cardiac rehabilitation participants at five hospitals were assessed at program entry and tailored education was provided using the Heart Foundation of Australia's Heart Attack Warning Signs campaign educational tool. Participants (n=137) were reassessed at program conclusion (six to eight weeks).


RESULTS
Study participants had a mean age of 64.48 years (SD 12.22), were predominantly male (78%) and most commonly presented with a current referral diagnosis of a percutaneous coronary intervention (PCI) (80%) and/or AMI (60%). There were statistically significant improvements in the reporting of 11 of the 14 warning signs of heart attack, with patients reporting 2.56 more warning signs on average at outcome (p<.0001). Patients reported more heart attack warning signs if they had completed high school education (β=1.14) or had better knowledge before the intervention (β=.57). There were statistically significant improvements in reporting of all appropriate actions in response to potential AMI symptoms, with patients reporting an average of 1.3 more actions at outcome (p<.001), with no change in the median time they would tolerate symptoms (p=.16).


CONCLUSIONS
A brief education session using a single standardised tool and adapted to a patient assessment is effective in improving knowledge of potential AMI symptoms and appropriate responses in cardiac rehabilitation up to two months following.
Web Based Instructional Tools For Heat And Mass Transfer

This paper demonstrates four web-based instructional tools for heat and mass transfer based on JAVA applets. These tools are closely related to topics in two chemical engineering courses: transport phenomena and chemical reactor design. They simulate four classic problems which are one dimensional unsteady mass diffusion, one dimensional unsteady-state heat conduction in slabs, cylinders and spheres, Heisler charts for unsteady state heat transfer, and reaction and diffusion in porous catalytic substrates. They provide students with a dynamic observation of heat and mass transfer process unavailable in traditional textbooks. Educators and instructors can use these tools to enhance students understanding of the concepts of heat and mass transfer.
Traceability Patterns : An Approach to Requirement-Component Traceability in Agile Software Development

Requirements traceability, regardless of the process used to produce a software system, is an important quality attribute for the resulting software product. However, existing approaches to achieving requirements traceability have been specifically designed for traditional software development with formal requirements processes. With the wide industry adoption of agile development methodologies, where requirements are captured and communicated through informal channels, the applicability of existing traceability approaches to agile software projects has been restricted. In this paper, we introduce traceability patterns as a solution to requirementcomponent tractability in agile software development. In our approach, we achieve traceability through source code, which is the main development artifact in agile methodologies. Key–Words: Requirements Traceability, Traceability Pattern, Agile Software Development
MRPC: maximizing network lifetime for reliable routing in wireless environments

We propose MRPC, a new power-aware routing algorithm for energy-efficient routing that increases the operational lifetime of multi-hop wireless networks. In contrast to conventional power-aware algorithms, MRPC identifies the capacity of a node not just by its residualbattery energy,but also by the expected energy spent in reliably forwarding a packet over a specific link. Such a formulation better captures scenarios where link transmission costs also depend on physical distances between nodes and the link error rates. Using a max-min formulation, MRPC selects the path that has the largest packet capacity at the ‘critical’ node (the one with the smallest residual packet transmission capacity). We also present CMRPC, a conditional variant of MRPC that switches from minimum energy routing to MRPC only when the packet forwarding capacity of nodes falls below a threshold. Simulationbased studies have been used to quantify the performance gains of our algorithms.
Incept-N: A Convolutional Neural Network based Classification Approach for Predicting Nationality from Facial Features

Nationality of a human being is a well-known identifying characteristic used for every major authentication purpose in every country. Albeit advances in application of Artificial Intelligence and Computer Vision in different aspects, its’ contribution to this specific security procedure is yet to be cultivated. With a goal to successfully applying computer vision techniques to predict a human’s nationality based on his facial features, we have proposed this novel method and have achieved an average of 93.6% accuracy with very low misclassification rate. KeywordsNationality, Artificial Intelligence, Computer Vision
Understanding patterns of service utilization among informal caregivers of community older adults.

PURPOSE
The article seeks to identify patterns of service utilization among informal caregivers of frail older adults. In particular, the study examined determinants that explain heterogeneous variations in caregivers' service use patterns.


METHODS
Using a latent class analysis (LCA) on the 2004 National Long-Term Care Survey and Informal Caregiver data (n = 1,908), this study classifies overall patterns of caregiver service utilization: financial information, support group, respite service, day care or senior center, personal or nursing care, housework, meal delivery, transportation, house modification, and assistive devices. With an emphasis on caregivers' service use patterns and social network derived from the Network Episode Model, the modified Andersen model guides determinants of these patterns.


RESULTS
The LCA classified a hierarchical structure of service use patterns: multiple service users, selective in-home service users, and light service users. Caregivers' network compositions signified heterogeneity in service use patterns. Care recipient- and caregiver-related needs contributed to distinguishing service use patterns.


IMPLICATIONS
Differentiation of services may be important for meeting caregivers' needs and distributing program resources by identifying target populations for intervention. This typology process may tailor specific interventions to better support caregivers.
User interface development for interactive television: extending a commercial DTV platform to the virtual channel API

We explore the generation of interactive computer graphics at digital set-top boxes in place of the fixed graphics that were embedded to the television video before the broadcast. This direction raises new requirements for user interface development, since the graphics are merged with video at each set-top box dynamically, without the traditional quality control from the television producers. Besides the technical issues, interactive computer graphics for television should be evaluated by television viewers. We employ an animated character in an interactive music television application that was evaluated by consumers, and was developed using the Virtual Channel Control Library, a custom high-level API, that was built using Microsoft Windows and TV technologies. r 2004 Elsevier Ltd. All rights reserved.