Miracle-dz/UniFAR-FTUs huggingface dataset:
Repeated Measurements of Arm Joint Passive Range of Motion After Stroke: Interobserver Reliability and Sources of Variation

Background Goniometric measurements of hemiplegic arm joints must be reliable to draw proper clinical and scientific conclusions. Previous reliability studies were cross-sectional and based on small samples. Knowledge about the contributions of sources of variation to these measurement results is lacking. Objective The aims of this study were to determine the interobserver reliability of measurements of passive range of motion (PROM) over time, explore sources of variation associated with these measurement results, and generate smallest detectable differences for clinical decision making. Design This investigation was a measurement-focused study with a longitudinal design, nested within a 2-arm randomized controlled trial. Methods Two trained physical therapists assessed 7 arm movements at baseline and after 4, 8, and 20 weeks in 48 people with subacute stroke using a standardized protocol. One physical therapist performed the passive movement, and the other read the hydrogoniometer. The therapists then switched roles. The relative contributions of several sources of variation to error variance were explored with analysis of variance. Results Interobserver reliability coefficients ranged from . 89 to . 97. The PROM measurements were influenced by error variance ranging from 31% to 50%. The participant × time interaction made the largest contribution to error variance, ranging from 59% to 81%. Smallest detectable differences were 6 to 22 degrees and were largest for shoulder movements. Limitations Verification of shoulder pain and hypertonia as sources of error variance led to a substantial number of unstable variance components, necessitating a simpler analysis. Conclusions The assessment of PROM with a standardized protocol, a hydrogoniometer, and 2 trained physical therapists yielded high interobserver reliability indexes for all arm movements. Error variance made a large contribution to the variation in measurement results. The resulting smallest detectable differences can be used to interpret future hemiplegic arm PROM measurements with more confidence.
Estimated estimating equations : Semiparametric inference for clustered / longitudinal data 18 January 2005

1 Summary. We introduce a flexible marginal modelling approach for statistical inference for clustered/longitudinal data under minimal assumptions. This Estimated Estimating Equations (EEE) approach is semiparametric and the proposed models are fitted by quasi-likelihood regression , where the unknown marginal means are a function of the fixed-effects linear predictor with unknown smooth link, and variance-covariance is an unknown smooth function of the marginal means. We propose to estimate the nonparametric link and variance-covariance functions via smoothing methods, while the regression parameters are obtained via the estimated estimating equations. These are score equations that contain nonparametric function estimates. The proposed EEE model is motivated by its flexibility and easy implementation. Moreover, if data follow a Generalized Linear Mixed Model (GLMM), with either specified or unspecified distribution of random effects and link function, the EEE model emerges as the corresponding marginal (population-average) version and can be used to obtain inference for the fixed effects in the underlying GLMM. Among marginal models, the EEE approach provides a flexible alternative to modeling with Generalized Estimating Equations (GEE). Applications of EEE include diagnostics and link selection. The asymptotic distribution of the proposed estimators for the model parameters is derived, enabling statistical inference. Practical illustrations include Poisson modeling of repeated epileptic seizure counts and simulations for clustered binomial responses.
Displacement fields around Guinier–Preston 1 zones in Al–Cu alloys: investigations using MD and ADF-STEM image simulations

ABSTRACT The displacements of atoms around Guinier–Preston 1 (GP1) zones in Al–Cu alloys at a temperature of 295 K have been investigated using molecular dynamics (MD) simulations. The magnitude of the displacements at the first Al layer adjacent to a GP1 zone reached 24% strain and this value decreased with distance from the zone to zero at about 40th Al layer. Strain fields near a GP1 zone were evaluated by calculating strain tensors around individual atoms. The obtained strain maps suggested that the equilibrium Cu content in a GP1 zone should be 100%. The atomic configurations determined by MD simulations were utilised for multislice image simulations of annular dark-field scanning transmission electron microscopy (ADF-STEM) to investigate the effect of foil thickness and the depth position of a GP1 zone in a foil on ADF-STEM images. The atomic displacements in ADF-STEM images were smaller than the MD result due to foil thickness and electron channelling.
A GUI (Graphical User Interface) framework to Introduce H-H Model in Comparison with Kv3.3 Model

The technique of modeling a neuron is mandatory and complex. In this paper, we introduce a simulating window by using graphical user interface (GUI) and it also helps researches in learning Hodgkin-Huxley (HH) complex mathematical equations. By using such type of simulator, users can build any panel for easy analysis and visualization of results. Therefore, here we discuss this type of panel for H-H model in comparison with Kv3.3 model that motivates to propose a new version of neuron modeling.
Swimming near the substrate: a simple robotic model of stingray locomotion

Studies of aquatic locomotion typically assume that organisms move through unbounded fluid. However, benthic fishes swim close to the substrate and will experience significant ground effects, which will be greatest for fishes with wide spans such as benthic batoids and flatfishes. Ground effects on fixed-wing flight are well understood, but these models are insufficient to describe the dynamic interactions between substrates and undulating, oscillating fish. Live fish alter their swimming behavior in ground effect, complicating comparisons of near-ground and freestream swimming performance. In this study, a simple, stingray-inspired physical model offers insights into ground effects on undulatory swimmers, contrasting the self-propelled swimming speed, power requirements, and hydrodynamics of fins swimming with fixed kinematics near and far from a solid boundary. Contrary to findings for gliding birds and other fixed-wing fliers, ground effect does not necessarily enhance the performance of undulating fins. Under most kinematic conditions, fins do not swim faster in ground effect, power requirements increase, and the cost of transport can increase by up to 10%. The influence of ground effect varies with kinematics, suggesting that benthic fish might modulate their swimming behavior to minimize locomotor penalties and incur benefits from swimming near a substrate.
Population dynamics of Aphis gossypii Glover and Aphis craccivora Koch ( Hemiptera : Heteroptera : Aphididae ) in sole and intercropping systems of cotton and cowpea

Population dynamics of aphids have been studied in sole and intercropping systems. These studies have required the use of more precise analytical tools in order to better understand patterns in quantitative data. Mathematical models are among the most important tools to explain the dynamics of insect populations. This study investigated the population dynamics of aphids Aphis gossypii and Aphis craccivora over time, using mathematical models composed of a set of differential equations as a helpful analytical tool to understand the population dynamics of aphids in arrangements of cotton and cowpea. The treatments were sole cotton, sole cowpea, and three arrangements of cotton intercropped with cowpea (t1, t2 and t3). The plants were infested with two aphid species and were evaluated at 7, 14, 28, 35, 42, and 49 days after the infestations. Mathematical models were used to fit the population dynamics of two aphid species. There were good fits for aphid dynamics by mathematical model over time. The highest population peak of both species A. gossypii and A. craccivora was found in the sole crops, and the lowest population peak was found in crop system t2. These results are important for integrated management programs of aphids in cotton and cowpea.
Learning users' and personality-gender preferences in close human-robot interaction

Robots are expected to interact with persons in their everyday activities and should learn the preferences of their users in order to deliver a more natural interaction. Having a memory system that remembers past events and using them to generate an adapted robot's behavior is a useful feature that robots should have. Nevertheless, robots will have to face unknown situations and behave appropriately. We propose the usage of user's personality (introversion/extroversion) to create a model to predict user's preferences so as to be used when there are no past interactions for a certain robot's task. For this, we propose a framework that combines an Emotion System based on the OCC Model with an Episodic-Like Memory System. We did an experiment where a group of participants customized robot's behavior with respect to their preferences (personal distance, gesture amplitude, gesture speed). We tested the obtained model against preset behaviors based on the literature about extroversion preferences on interaction. For this, a different group of participants was recruited. Results shows that our proposed model generated a behavior that was more preferred by the participants than the preset behaviors. Only the group of introvert-female participants did not present any significant difference between the different behaviors.
Context-Aware Access Control for RDF Graph Stores

We present SHI3LD, an access control framework for RDF stores. Our solution supports access from mobile devices with context-aware policies and is exclusively grounded on standard Semantic Web languages. Designed as a pluggable filter for generic SPARQL endpoints, the module uses RDF named graphs and SPARQL to protect triples. Evaluation shows faster execution time for low-selective queries and less impact on larger datastores.
A New Fossil Mayfly Species of the Genus Borinquena Traver, 1938 (Insecta: Ephemeroptera: Leptophlebiidae: Atalophlebiinae) from Miocene Dominican Amber

Abstract. The Neotropical mayfly genus Borinquena Traver, 1938 so far comprises three described extant species from the Caribbean basin. Furthermore, three fossil species from Dominican amber have been described in this genus. Based on a single male imago, Borinquena schawallfussi sp. nov. is described in this contribution as the fourth fossil species of Borinquena from Miocene Dominican amber. The new species clearly differs from all other fossil and recent representatives of the genus Borinquena in forewing colouration and venation, hind wing shape and venation, and in the shape of penis lobes and their ventral spines.
Representativity studies of ZEPHYR fast/thermal coupled cores for SFR-like reactivity effects during core meltdown

The aim of the present paper is to present first representativity studies of local reactivity effects in a fast lattice during severe core accident (SCA) in Liquid Metal-cooled Fast Breeder Reactors (LMFBRs) sequence. The representativity study is based on sensitivity analysis of reactivity coefficients and local flux distributions against core degradation being analyzed in the ASTRID CFV-V0 inner core. During severe accident sequence, voiding and fuel meltdown can have pronounced influence on the neutronic characteristics of the core, and can in particular lead to prompt/superprompt recriticality. In order to predict the core behavior during such disruptions it is necessary to develop accurate and precise computational and experimental tools and methodologies. The assessment of reactivity behavior that represents different stages of the disrupted core configurations is one of the challenges associated to ZEPHYR, and requires a new way of performing measurements in critical assemblies. Serpent Monte Carlo sensitivity and uncertainty analysis of a CFV-like assembly degradation, from voiding to fuel meltdown, is performed in the ZEPHYR fast zone, using the MASURCA fast ZPR fuel materials. The SFR assembly is modelled by MASURCA MOX fuel and sodium rodlets for normal situations, and by metal fuels and stainless steel plates in case of meltdown. The sequence covers full meltdown, from partial to the collapsing of fuel corium. in the upper and lower assembly parts. The sequence focuses on sensitivity profiles similarities, and hence establishes a transposition of the awaited ZEPHYR experimental results to the ASTRID case.
Interleukin-1 Regulates Multiple Atherogenic Mechanisms in Response to Fat Feeding

Background Atherosclerosis is an inflammatory process that develops in individuals with known risk factors that include hypertension and hyperlipidaemia, influenced by diet. However, the interplay between diet, inflammatory mechanisms and vascular risk factors requires further research. We hypothesised that interleukin-1 (IL-1) signaling in the vessel wall would raise arterial blood pressure and promote atheroma. Methodology/Principal Findings Apoe−/− and Apoe−/−/IL-1R1−/− mice were fed high fat diets for 8 weeks, and their blood pressure and atherosclerosis development measured. Apoe−/−/IL-R1−/− mice had a reduced blood pressure and significantly less atheroma than Apoe−/− mice. Selective loss of IL-1 signaling in the vessel wall by bone marrow transplantation also reduced plaque burden (p<0.05). This was associated with an IL-1 mediated loss of endothelium-dependent relaxation and an increase in vessel wall Nox 4. Inhibition of IL-1 restored endothelium-dependent vasodilatation and reduced levels of arterial oxidative stress. Conclusions/Significance The IL-1 cytokine system links atherogenic environmental stimuli with arterial inflammation, oxidative stress, increased blood pressure and atherosclerosis. This is the first demonstration that inhibition of a single cytokine can block the rise in blood pressure in response to an environmental stimulus. IL-1 inhibition may have profound beneficial effects on atherogenesis in man.
Advances in monitoring cardiovascular signals. Contribution of nonlinear signal processing

Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their status, thus providing necessary interventions in time. To obtain this important objective it is necessary to integrate technological development with systems performing biomedical knowledge extraction and classification. Methods extracting non linear characteristics from HRV signal are presented and discussed to stress that integrated and multiparametric signal processing approaches can contribute to new diagnostic and classification indices. Examples report heart rate variability analysis in long periods in patients with cardiovascular disease. Fetal ECG monitoring is another example. In this case, coupling nonlinear parameters and linear time and frequency techniques increases diagnostic power and reliability of the monitoring. The paper shows that integrated signal analysis is very helpful to describe pathophysiological mechanisms involved in the cardiovascular and neural system control. It is a reliable basis to set up knowledge-based monitoring systems.
Arch Aortogram Fails to Identify Aortic Atherosclerotic Lesions Detected on Transesophageal Echocardiogram

Background and Purpose. Transesophageal echocardiogram is used to evaluate the aortic arch during diagnostic evaluations of ischemic stroke events. Conventional angiography is increasingly used in diagnosing and treating atherosclerotic vascular lesions in patients with ischemic stroke. Although catheterbased aortography can be performed with cerebral angiography, there is limited information about the utility of aortography in identifying atherosclerotic abnormalities of the aortic arch. Methods. A retrospective chart review was performed to identify patients who underwent aortography as part of the i r angiographic study and transesophageal echocardiogram. Both studies were reviewed independently in the absence of knowledge of the results of the other study. The findings of these aortograms were correlated with the findings of transesophageal echocardiogram. Results. A total of 34 patients underwent both aortography and echocardiography. Of a total of 34 transesophageal echocardiograms, 29 showed abnormal findings in the aorta (85%) and 5 appeared normal (15%). These aortic abnormalities included mild to moderate atherosclerosis in 18 cases (52%), moderate to severe atherosclerosis in 4 cases (12%), and severe atherosclerosis in 7 cases (21%). None of these abnormalities were detected by aortography. No disease was visualized in the origin of the supraaortic arteries. Conclusions. Aortic arch atherosclerosis is common in patients with ischemic stroke; however, aortograms performed during conventional angiography fail to identify abnormalities detected on transesophageal echocardiogram.
Segmentation of lumbar vertebrae from clinical CT using active shape models and GVF-snake

Lumbar area of the vertebral column bears the most load of the human body and thus it is responsible for the major portion of lower back pain from which 80% to 90% of people suffer from during their lifetime. Vertebra related diseases are mainly fracture and are usually diagnosed from X-ray radiographs or CT scans depending on the severity of the problem. In this paper, we propose a fully automated lumbar vertebra segmentation that accurately and robustly produces a smooth contour around each of the vertebrae. This segmentation is very useful in any subsequent CAD system for diagnosis and quantification of vertebrae fractures. It also serves the radiologist during the clinical routine. Our method shows an excellent level of vertebra boundary smootheness that was visually approved by our collaborating radiologist for each vertebra and each case from our fifty cases dataset that includes both normal and abnormal cases.
Predicting Surgical Success in Patients with Idiopathic Epiretinal Membrane Using the Spectral-Domain Optical Coherence Tomography Segmentation Module for Single Retinal Layer Analysis

ABSTRACT Introduction: Idiopathic epiretinal membrane (ERM) is a proliferation of cells formed on the internal surface of the retina and may cause a slow decrease in visual acuity (VA). The aim of this study was to evaluate the individual layers of the retina by optical coherence tomography (OCT) before and after vitrectomy with ERM peeling in order to refine surgical decision-making. Methods: Forty-seven eyes of 45 patients (aged 55–87 years) with ERM were enrolled retrospectively from a tertiary referral center. OCT examination was performed preoperatively and at a mean of 3.2 months postoperatively in all cases. Nine retinal surfaces were subjected to automated all-layer segmentation using the manufacturer’s software and assessed for their correlation with VA. Results: There was a significant correlation between the initial retinal morphology and change in VA postoperatively. Patients who gained at least two lines of VA had a significantly higher total retinal perimacular volume and retinal nerve fiber layer (each p < 0.0001) preoperatively. Conclusion: Patients with high preoperative retinal volumes and therefore increased tractive components seemed to benefit more from surgery than those with low tractive components.
Singing voice detection in music tracks using direct voice vibrato detection

In this paper we investigate the problem of locating singing voice in music tracks. As opposed to most existing methods for this task, we rely on the extraction of the characteristics specific to singing voice. In our approach we suppose that the singing voice is characterized by harmonicity, formants, vibrato and tremolo. In the present study we deal only with the vibrato and tremolo characteristics. For this, we first extract sinusoidal partials from the musical audio signal . The frequency modulation (vibrato) and amplitude modulation (tremolo) of each partial are then studied to determine if the partial corresponds to singing voice and hence the corresponding segment is supposed to contain singing voice. For this we estimate for each partial the rate (frequency of the modulations) and the extent (amplitude of modulation) of both vibrato and tremolo. A partial selection is then operated based on these values. A second criteria based on harmonicity is also introduced. Based on this, each segment can be labelled as singing or non-singing. Post-processing of the segmentation is then applied in order to remove short-duration segments. The proposed method is then evaluated on a large manually annotated test-set. The results of this evaluation are compared to the one obtained with a usual machine learning approach (MFCC and SFM modeling with GMM). The proposed method achieves very close results to the machine learning approach : 76.8% compared to 77.4% F-measure (frame classification). This result is very promising, since both approaches are orthogonal and can then be combined.
Development of hydrogels, oleogels, and bigels as local drug delivery systems for periodontitis

Abstract Periodontal disease is a chronic inflammation of gum and tissues that surround and support the teeth. Nonsteroidal anti-inflammatory drugs (NSAIDs) can be used in the treatment of periodontitis to ease swelling and inflammation. One approach of treating periodontitis is loading the NSAIDs in local drug delivery systems. Therefore, the objective of this study was to investigate the local delivery of the NSAIDs model drug ibuprofen to treat periodontitis using different types of gel formulations (hydrogel, oleogel, and bigel). Gel formulations were characterized in terms of their rheological properties (flow behavior, viscoelastic, and bioadhesive properties) using a controlled-stress rheometer. The in vitro drug release of ibuprofen from gel formulations was investigated using Franz diffusion cells. Gels exhibited more solid-like (elastic) behavior. The viscosity and viscoelastic properties were in the order of oleogel > bigel > hydrogel, respectively. In bioadhesion study, mucin dispersion/plain ibuprofen-hydrogel mixture showed a frequency-dependent interaction of ΔG’ = −31 and ΔG’ = + 53 Pa at 1 and 10 rad/s, respectively. A strong positive interaction (ΔG’ = + 6000 and +130,667 Pa at 1 and 10 rad/s, respectively) was found in mucin dispersion/plain ibuprofen–oleogel mixture. The extent of the negative interaction increased in mucin dispersion/plain ibuprofen-bigel mixture (ΔG’ = −59,000 and −79,375 Pa at 1 and 10 rad/s, respectively). After 6 h, ibuprofen release from hydrogel, oleogel, and bigel was 59.5 ± 2.2, 80.6 ± 3.9, and 94.6 ± 3.2%, respectively. Results showed that the rheological and bioadhesive properties and in vitro drug release were influenced by the type of gel formulations.
Flexible Learning with Semantic Visual Exploration and Sequence-Based Recommendation of MOOC Videos

Massive Open Online Course (MOOC) platforms have scaled online education to unprecedented enrollments, but remain limited by their rigid, predetermined curricula. To overcome this limitation, this paper contributes a visual recommender system called MOOCex. The system recommends lecture videos across different courses by considering both video contents and sequential inter-topic relationships mined from course syllabi; and more importantly, it allows for interactive visual exploration of the semantic space of recommendations within a learner's current context. When compared to traditional methods (e.g., content-based recommendation and ranked list representations), MOOCex suggests videos from more diverse perspectives and helps learners make better video playback decisions. Further, feedback from MOOC learners and instructors indicates that the system enhances both learning and teaching effectiveness.