Natural scene logo recognition by joint boosting feature selection in salient regions

NASA Astrophysics Data System (ADS)

Fan, Wei; Sun, Jun; Naoi, Satoshi; Minagawa, Akihiro; Hotta, Yoshinobu

2011-01-01

Logos are considered valuable intellectual properties and a key component of the goodwill of a business. In this paper, we propose a natural scene logo recognition method which is segmentation-free and capable of processing images extremely rapidly and achieving high recognition rates. The classifiers for each logo are trained jointly, rather than independently. In this way, common features can be shared across multiple classes for better generalization. To deal with large range of aspect ratio of different logos, a set of salient regions of interest (ROI) are extracted to describe each class. We ensure the selected ROIs to be both individually informative and two-by-two weakly dependant by a Class Conditional Entropy Maximization criteria. Experimental results on a large logo database demonstrate the effectiveness and efficiency of our proposed method.

A multi-feature integration method for fatigue crack detection and crack length estimation in riveted lap joints using Lamb waves

NASA Astrophysics Data System (ADS)

He, Jingjing; Guan, Xuefei; Peng, Tishun; Liu, Yongming; Saxena, Abhinav; Celaya, Jose; Goebel, Kai

2013-10-01

This paper presents an experimental study of damage detection and quantification in riveted lap joints. Embedded lead zirconate titanate piezoelectric (PZT) ceramic wafer-type sensors are employed to perform in situ non-destructive evaluation (NDE) during fatigue cyclical loading. PZT wafers are used to monitor the wave reflection from the boundaries of the fatigue crack at the edge of bolt joints. The group velocity of the guided wave is calculated to select a proper time window in which the received signal contains the damage information. It is found that the fatigue crack lengths are correlated with three main features of the signal, i.e., correlation coefficient, amplitude change, and phase change. It was also observed that a single feature cannot be used to quantify the damage among different specimens since a considerable variability was observed in the response from different specimens. A multi-feature integration method based on a second-order multivariate regression analysis is proposed for the prediction of fatigue crack lengths using sensor measurements. The model parameters are obtained using training datasets from five specimens. The effectiveness of the proposed methodology is demonstrated using several lap joint specimens from different manufactures and under different loading conditions.

Group sparse multiview patch alignment framework with view consistency for image classification.

PubMed

Gui, Jie; Tao, Dacheng; Sun, Zhenan; Luo, Yong; You, Xinge; Tang, Yuan Yan

2014-07-01

No single feature can satisfactorily characterize the semantic concepts of an image. Multiview learning aims to unify different kinds of features to produce a consensual and efficient representation. This paper redefines part optimization in the patch alignment framework (PAF) and develops a group sparse multiview patch alignment framework (GSM-PAF). The new part optimization considers not only the complementary properties of different views, but also view consistency. In particular, view consistency models the correlations between all possible combinations of any two kinds of view. In contrast to conventional dimensionality reduction algorithms that perform feature extraction and feature selection independently, GSM-PAF enjoys joint feature extraction and feature selection by exploiting l(2,1)-norm on the projection matrix to achieve row sparsity, which leads to the simultaneous selection of relevant features and learning transformation, and thus makes the algorithm more discriminative. Experiments on two real-world image data sets demonstrate the effectiveness of GSM-PAF for image classification.

MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis.

PubMed

Yang, Wanqi; Gao, Yang; Shi, Yinghuan; Cao, Longbing

2015-11-01

Learning about multiview data involves many applications, such as video understanding, image classification, and social media. However, when the data dimension increases dramatically, it is important but very challenging to remove redundant features in multiview feature selection. In this paper, we propose a novel feature selection algorithm, multiview rank minimization-based Lasso (MRM-Lasso), which jointly utilizes Lasso for sparse feature selection and rank minimization for learning relevant patterns across views. Instead of simply integrating multiple Lasso from view level, we focus on the performance of sample-level (sample significance) and introduce pattern-specific weights into MRM-Lasso. The weights are utilized to measure the contribution of each sample to the labels in the current view. In addition, the latent correlation across different views is successfully captured by learning a low-rank matrix consisting of pattern-specific weights. The alternating direction method of multipliers is applied to optimize the proposed MRM-Lasso. Experiments on four real-life data sets show that features selected by MRM-Lasso have better multiview classification performance than the baselines. Moreover, pattern-specific weights are demonstrated to be significant for learning about multiview data, compared with view-specific weights.

Refining patterns of joint hypermobility, habitus, and orthopedic traits in joint hypermobility syndrome and Ehlers-Danlos syndrome, hypermobility type.

PubMed

Morlino, Silvia; Dordoni, Chiara; Sperduti, Isabella; Venturini, Marina; Celletti, Claudia; Camerota, Filippo; Colombi, Marina; Castori, Marco

2017-04-01

Joint hypermobility syndrome (JHS) and Ehlers-Danlos syndrome, hypermobility type (EDS-HT) are two overlapping heritable disorders (JHS/EDS-HT) recognized by separated sets of diagnostic criteria and still lack a confirmatory test. This descriptive research was aimed at better characterizing the clinical phenotype of JHS/EDS-HT with focus on available diagnostic criteria, and in order to propose novel features and assessment strategies. One hundred and eighty-nine (163 females, 26 males; age: 2-73 years) patients from two Italian reference centers were investigated for Beighton score, range of motion in 21 additional joints, rate and sites of dislocations and sprains, recurrent soft-tissue injuries, tendon and muscle ruptures, body mass index, arm span/height ratio, wrist and thumb signs, and 12 additional orthopedic features. Rough rates were compared by age, sex, and handedness with a series of parametric and non-parametric tools. Multiple correspondence analysis was carried out for possible co-segregations of features. Beighton score and hypermobility at other joints were influenced by age at diagnosis. Rate and sites of joint instability complications did not vary according to age at diagnosis except for soft-tissue injuries. No major difference was registered by sex and dominant versus non-dominant body side. At multiple correspondence analysis, selected features tend to co-segregate in a dichotomous distribution. Dolichostenomelia and arachnodactyly segregated independently. This study pointed out a more protean musculoskeletal phenotype than previously considered according to available diagnostic criteria for JHS/EDS-HT. Our findings corroborated the need for a re-thinking of JHS/EDS-HT on clinical grounds in order to find better therapeutic and research strategies. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Study for Updated Gout Classification Criteria (SUGAR): identification of features to classify gout

PubMed Central

Taylor, William J.; Fransen, Jaap; Jansen, Tim L.; Dalbeth, Nicola; Schumacher, H. Ralph; Brown, Melanie; Louthrenoo, Worawit; Vazquez-Mellado, Janitzia; Eliseev, Maxim; McCarthy, Geraldine; Stamp, Lisa K.; Perez-Ruiz, Fernando; Sivera, Francisca; Ea, Hang-Korng; Gerritsen, Martijn; Scire, Carlo; Cavagna, Lorenzo; Lin, Chingtsai; Chou, Yin-Yi; Tausche, Anne-Kathrin; Vargas-Santos, Ana Beatriz; Janssen, Matthijs; Chen, Jiunn-Horng; Slot, Ole; Cimmino, Marco A.; Uhlig, Till; Neogi, Tuhina

2015-01-01

Objective To determine which clinical, laboratory and imaging features most accurately distinguished gout from non-gout. Methods A cross-sectional study of consecutive rheumatology clinic patients with at least one swollen joint or subcutaneous tophus. Gout was defined by synovial fluid or tophus aspirate microscopy by certified examiners in all patients. The sample was randomly divided into a model development (2/3) and test sample (1/3). Univariate and multivariate association between clinical features and MSU-defined gout was determined using logistic regression modelling. Shrinkage of regression weights was performed to prevent over-fitting of the final model. Latent class analysis was conducted to identify patterns of joint involvement. Results In total, 983 patients were included. Gout was present in 509 (52%). In the development sample (n=653), these features were selected for the final model (multivariate OR) joint erythema (2.13), difficulty walking (7.34), time to maximal pain < 24 hours (1.32), resolution by 2 weeks (3.58), tophus (7.29), MTP1 ever involved (2.30), location of currently tender joints: Other foot/ankle (2.28), MTP1 (2.82), serum urate level > 6 mg/dl (0.36 mmol/l) (3.35), ultrasound double contour sign (7.23), Xray erosion or cyst (2.49). The final model performed adequately in the test set with no evidence of misfit, high discrimination and predictive ability. MTP1 involvement was the most common joint pattern (39.4%) in gout cases. Conclusion Ten key discriminating features have been identified for further evaluation for new gout classification criteria. Ultrasound findings and degree of uricemia add discriminating value, and will significantly contribute to more accurate classification criteria. PMID:25777045

A universal deep learning approach for modeling the flow of patients under different severities.

PubMed

Jiang, Shancheng; Chin, Kwai-Sang; Tsui, Kwok L

2018-02-01

The Accident and Emergency Department (A&ED) is the frontline for providing emergency care in hospitals. Unfortunately, relative A&ED resources have failed to keep up with continuously increasing demand in recent years, which leads to overcrowding in A&ED. Knowing the fluctuation of patient arrival volume in advance is a significant premise to relieve this pressure. Based on this motivation, the objective of this study is to explore an integrated framework with high accuracy for predicting A&ED patient flow under different triage levels, by combining a novel feature selection process with deep neural networks. Administrative data is collected from an actual A&ED and categorized into five groups based on different triage levels. A genetic algorithm (GA)-based feature selection algorithm is improved and implemented as a pre-processing step for this time-series prediction problem, in order to explore key features affecting patient flow. In our improved GA, a fitness-based crossover is proposed to maintain the joint information of multiple features during iterative process, instead of traditional point-based crossover. Deep neural networks (DNN) is employed as the prediction model to utilize their universal adaptability and high flexibility. In the model-training process, the learning algorithm is well-configured based on a parallel stochastic gradient descent algorithm. Two effective regularization strategies are integrated in one DNN framework to avoid overfitting. All introduced hyper-parameters are optimized efficiently by grid-search in one pass. As for feature selection, our improved GA-based feature selection algorithm has outperformed a typical GA and four state-of-the-art feature selection algorithms (mRMR, SAFS, VIFR, and CFR). As for the prediction accuracy of proposed integrated framework, compared with other frequently used statistical models (GLM, seasonal-ARIMA, ARIMAX, and ANN) and modern machine models (SVM-RBF, SVM-linear, RF, and R-LASSO), the proposed integrated "DNN-I-GA" framework achieves higher prediction accuracy on both MAPE and RMSE metrics in pairwise comparisons. The contribution of our study is two-fold. Theoretically, the traditional GA-based feature selection process is improved to have less hyper-parameters and higher efficiency, and the joint information of multiple features is maintained by fitness-based crossover operator. The universal property of DNN is further enhanced by merging different regularization strategies. Practically, features selected by our improved GA can be used to acquire an underlying relationship between patient flows and input features. Predictive values are significant indicators of patients' demand and can be used by A&ED managers to make resource planning and allocation. High accuracy achieved by the present framework in different cases enhances the reliability of downstream decision makings. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep Learning for Population Genetic Inference.

PubMed

Sheehan, Sara; Song, Yun S

2016-03-01

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

Deep Learning for Population Genetic Inference

PubMed Central

Sheehan, Sara; Song, Yun S.

2016-01-01

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908

Philosophies Applied in the Selection of Space Suit Joint Range of Motion Requirements

NASA Technical Reports Server (NTRS)

Aitchison, Lindsway; Ross, Amy; Matty, Jennifer

2009-01-01

Space suits are the most important tool for astronauts working in harsh space and planetary environments; suits keep crewmembers alive and allow them to perform exploration, construction, and scientific tasks on a routine basis over a period of several months. The efficiency with which the tasks are performed is largely dictated by the mobility features of the space suit. For previous space suit development programs, the mobility requirements were written as pure functional mobility requirements that did not separate joint ranges of motion from the joint torques. The Constellation Space Suit Element has the goal to make more quantitative mobility requirements that focused on the individual components of mobility to enable future suit designers to build and test systems more effectively. This paper details the test planning and selection process for the Constellation space suit pressure garment range of motion requirements.

Task representation in individual and joint settings

PubMed Central

Prinz, Wolfgang

2015-01-01

This paper outlines a framework for task representation and discusses applications to interference tasks in individual and joint settings. The framework is derived from the Theory of Event Coding (TEC). This theory regards task sets as transient assemblies of event codes in which stimulus and response codes interact and shape each other in particular ways. On the one hand, stimulus and response codes compete with each other within their respective subsets (horizontal interactions). On the other hand, stimulus and response code cooperate with each other (vertical interactions). Code interactions instantiating competition and cooperation apply to two time scales: on-line performance (i.e., doing the task) and off-line implementation (i.e., setting the task). Interference arises when stimulus and response codes overlap in features that are irrelevant for stimulus identification, but relevant for response selection. To resolve this dilemma, the feature profiles of event codes may become restructured in various ways. The framework is applied to three kinds of interference paradigms. Special emphasis is given to joint settings where tasks are shared between two participants. Major conclusions derived from these applications include: (1) Response competition is the chief driver of interference. Likewise, different modes of response competition give rise to different patterns of interference; (2) The type of features in which stimulus and response codes overlap is also a crucial factor. Different types of such features give likewise rise to different patterns of interference; and (3) Task sets for joint settings conflate intraindividual conflicts between responses (what), with interindividual conflicts between responding agents (whom). Features of response codes may, therefore, not only address responses, but also responding agents (both physically and socially). PMID:26029085

Development of Vision Based Multiview Gait Recognition System with MMUGait Database

PubMed Central

Ng, Hu; Tan, Wooi-Haw; Tong, Hau-Lee

2014-01-01

This paper describes the acquisition setup and development of a new gait database, MMUGait. This database consists of 82 subjects walking under normal condition and 19 subjects walking with 11 covariate factors, which were captured under two views. This paper also proposes a multiview model-based gait recognition system with joint detection approach that performs well under different walking trajectories and covariate factors, which include self-occluded or external occluded silhouettes. In the proposed system, the process begins by enhancing the human silhouette to remove the artifacts. Next, the width and height of the body are obtained. Subsequently, the joint angular trajectories are determined once the body joints are automatically detected. Lastly, crotch height and step-size of the walking subject are determined. The extracted features are smoothened by Gaussian filter to eliminate the effect of outliers. The extracted features are normalized with linear scaling, which is followed by feature selection prior to the classification process. The classification experiments carried out on MMUGait database were benchmarked against the SOTON Small DB from University of Southampton. Results showed correct classification rate above 90% for all the databases. The proposed approach is found to outperform other approaches on SOTON Small DB in most cases. PMID:25143972

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

PubMed Central

2015-01-01

Background Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. Results and discussion Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large ‘omics’ datasets are increasingly being used in the area of rheumatology. Conclusions Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery. PMID:25923811

On the use of information theory for the analysis of synchronous nociceptive withdrawal reflexes and somatosensory evoked potentials elicited by graded electrical stimulation.

PubMed

Arguissain, Federico G; Biurrun Manresa, José A; Mørch, Carsten D; Andersen, Ole K

2015-01-30

To date, few studies have combined the simultaneous acquisition of nociceptive withdrawal reflexes (NWR) and somatosensory evoked potentials (SEPs). In fact, it is unknown whether the combination of these two signals acquired simultaneously could provide additional information on somatosensory processing at spinal and supraspinal level compared to individual NWR and SEP signals. By using the concept of mutual information (MI), it is possible to quantify the relation between electrical stimuli and simultaneous elicited electrophysiological responses in humans based on the estimated stimulus-response signal probability distributions. All selected features from NWR and SEPs were informative in regard to the stimulus when considered individually. Specifically, the information carried by NWR features was significantly higher than the information contained in the SEP features (p<0.05). Moreover, the joint information carried by the combination of features showed an overall redundancy compared to the sum of the individual contributions. Comparison with existing methods MI can be used to quantify the information that single-trial NWR and SEP features convey, as well as the information carried jointly by NWR and SEPs. This is a model-free approach that considers linear and non-linear correlations at any order and is not constrained by parametric assumptions. The current study introduces a novel approach that allows the quantification of the individual and joint information content of single-trial NWR and SEP features. This methodology could be used to decode and interpret spinal and supraspinal interaction in studies modulating the responsiveness of the nociceptive system. Copyright © 2014 Elsevier B.V. All rights reserved.

Reconstructing for joint angles on the shoulder and elbow from non-invasive electroencephalographic signals through electromyography

PubMed Central

Choi, Kyuwan

2013-01-01

In this study, first the cortical activities over 2240 vertexes on the brain were estimated from 64 channels electroencephalography (EEG) signals using the Hierarchical Bayesian estimation while 5 subjects did continuous arm reaching movements. From the estimated cortical activities, a sparse linear regression method selected only useful features in reconstructing the electromyography (EMG) signals and estimated the EMG signals of 9 arm muscles. Then, a modular artificial neural network was used to estimate four joint angles from the estimated EMG signals of 9 muscles: one for movement control and the other for posture control. The estimated joint angles using this method have the correlation coefficient (CC) of 0.807 (±0.10) and the normalized root-mean-square error (nRMSE) of 0.176 (±0.29) with the actual joint angles. PMID:24167469

Selection of optimal multispectral imaging system parameters for small joint arthritis detection

NASA Astrophysics Data System (ADS)

Dolenec, Rok; Laistler, Elmar; Stergar, Jost; Milanic, Matija

2018-02-01

Early detection and treatment of arthritis is essential for a successful outcome of the treatment, but it has proven to be very challenging with existing diagnostic methods. Novel methods based on the optical imaging of the affected joints are becoming an attractive alternative. A non-contact multispectral imaging (MSI) system for imaging of small joints of human hands and feet is being developed. In this work, a numerical simulation of the MSI system is presented. The purpose of the simulation is to determine the optimal design parameters. Inflamed and unaffected human joint models were constructed with a realistic geometry and tissue distributions, based on a MRI scan of a human finger with a spatial resolution of 0.2 mm. The light transport simulation is based on a weighted-photon 3D Monte Carlo method utilizing CUDA GPU acceleration. An uniform illumination of the finger within the 400-1100 nm spectral range was simulated and the photons exiting the joint were recorded using different acceptance angles. From the obtained reflectance and transmittance images the spectral and spatial features most indicative of inflammation were identified. Optimal acceptance angle and spectral bands were determined. This study demonstrates that proper selection of MSI system parameters critically affects ability of a MSI system to discriminate the unaffected and inflamed joints. The presented system design optimization approach could be applied to other pathologies.

Joint Spatial-Spectral Feature Space Clustering for Speech Activity Detection from ECoG Signals

PubMed Central

Kanas, Vasileios G.; Mporas, Iosif; Benz, Heather L.; Sgarbas, Kyriakos N.; Bezerianos, Anastasios; Crone, Nathan E.

2014-01-01

Brain machine interfaces for speech restoration have been extensively studied for more than two decades. The success of such a system will depend in part on selecting the best brain recording sites and signal features corresponding to speech production. The purpose of this study was to detect speech activity automatically from electrocorticographic signals based on joint spatial-frequency clustering of the ECoG feature space. For this study, the ECoG signals were recorded while a subject performed two different syllable repetition tasks. We found that the optimal frequency resolution to detect speech activity from ECoG signals was 8 Hz, achieving 98.8% accuracy by employing support vector machines (SVM) as a classifier. We also defined the cortical areas that held the most information about the discrimination of speech and non-speech time intervals. Additionally, the results shed light on the distinct cortical areas associated with the two syllable repetition tasks and may contribute to the development of portable ECoG-based communication. PMID:24658248

Prediction of Response to Neoadjuvant Chemotherapy and Radiation Therapy with Baseline and Restaging 18F-FDG PET Imaging Biomarkers in Patients with Esophageal Cancer.

PubMed

Beukinga, Roelof J; Hulshoff, Jan Binne; Mul, Véronique E M; Noordzij, Walter; Kats-Ugurlu, Gursah; Slart, Riemer H J A; Plukker, John T M

2018-06-01

Purpose To assess the value of baseline and restaging fluorine 18 ( 18 F) fluorodeoxyglucose (FDG) positron emission tomography (PET) radiomics in predicting pathologic complete response to neoadjuvant chemotherapy and radiation therapy (NCRT) in patients with locally advanced esophageal cancer. Materials and Methods In this retrospective study, 73 patients with histologic analysis-confirmed T1/N1-3/M0 or T2-4a/N0-3/M0 esophageal cancer were treated with NCRT followed by surgery (Chemoradiotherapy for Esophageal Cancer followed by Surgery Study regimen) between October 2014 and August 2017. Clinical variables and radiomic features from baseline and restaging 18 F-FDG PET were selected by univariable logistic regression and least absolute shrinkage and selection operator. The selected variables were used to fit a multivariable logistic regression model, which was internally validated by using bootstrap resampling with 20 000 replicates. The performance of this model was compared with reference prediction models composed of maximum standardized uptake value metrics, clinical variables, and maximum standardized uptake value at baseline NCRT radiomic features. Outcome was defined as complete versus incomplete pathologic response (tumor regression grade 1 vs 2-5 according to the Mandard classification). Results Pathologic response was complete in 16 patients (21.9%) and incomplete in 57 patients (78.1%). A prediction model combining clinical T-stage and restaging NCRT (post-NCRT) joint maximum (quantifying image orderliness) yielded an optimism-corrected area under the receiver operating characteristics curve of 0.81. Post-NCRT joint maximum was replaceable with five other redundant post-NCRT radiomic features that provided equal model performance. All reference prediction models exhibited substantially lower discriminatory accuracy. Conclusion The combination of clinical T-staging and quantitative assessment of post-NCRT 18 F-FDG PET orderliness (joint maximum) provided high discriminatory accuracy in predicting pathologic complete response in patients with esophageal cancer. © RSNA, 2018 Online supplemental material is available for this article.

Phylogenetic divergence of cell biological features

PubMed Central

2018-01-01

Most cellular features have a range of states, but understanding the mechanisms responsible for interspecific divergence is a challenge for evolutionary cell biology. Models are developed for the distribution of mean phenotypes likely to evolve under the joint forces of mutation and genetic drift in the face of constant selection pressures. Mean phenotypes will deviate from optimal states to a degree depending on the effective population size, potentially leading to substantial divergence in the absence of diversifying selection. The steady-state distribution for the mean can even be bimodal, with one domain being largely driven by selection and the other by mutation pressure, leading to the illusion of phenotypic shifts being induced by movement among alternative adaptive domains. These results raise questions as to whether lineage-specific selective pressures are necessary to account for interspecific divergence, providing a possible platform for the establishment of null models for the evolution of cell-biological traits. PMID:29927740

Photoanthropometric face iridial proportions for age estimation: An investigation using features selected via a joint mutual information criterion.

PubMed

Borges, Díbio L; Vidal, Flávio B; Flores, Marta R P; Melani, Rodolfo F H; Guimarães, Marco A; Machado, Carlos E P

2018-03-01

Age assessment from images is of high interest in the forensic community because of the necessity to establish formal protocols to identify child pornography, child missing and abuses where visual evidences are the mostly admissible. Recently, photoanthropometric methods have been found useful for age estimation correlating facial proportions in image databases with samples of some age groups. Notwithstanding the advances, newer facial features and further analysis are needed to improve accuracy and establish larger applicability. In this investigation, frontal images of 1000 individuals (500 females, 500 males), equally distributed in five age groups (6, 10, 14, 18, 22 years old) were used in a 10 fold cross-validated experiment for three age thresholds classifications (<10, <14, <18 years old). A set of novel 40 features, based on a relation between landmark distances and the iris diameter, is proposed and joint mutual information is used to select the most relevant and complementary features for the classification task. In a civil image identification database with diverse ancestry, receiver operating characteristic (ROC) curves were plotted to verify accuracy, and the resultant AUCs achieved 0.971, 0.969, and 0.903 for the age classifications (<10, <14, <18 years old), respectively. These results add support to continuing research in age assessment from images using the metric approach. Still, larger samples are necessary to evaluate reliability in extensive conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Radiological and Radionuclide Imaging of Degenerative Disease of the Facet Joints

PubMed Central

Shur, Natalie; Corrigan, Alexis; Agrawal, Kanhaiyalal; Desai, Amidevi; Gnanasegaran, Gopinath

2015-01-01

The facet joint has been increasingly implicated as a potential source of lower back pain. Diagnosis can be challenging as there is not a direct correlation between facet joint disease and clinical or radiological features. The purpose of this article is to review the diagnosis, treatment, and current imaging modality options in the context of degenerative facet joint disease. We describe each modality in turn with a pictorial review using current evidence. Newer hybrid imaging techniques such as single photon emission computed tomography/computed tomography (SPECT/CT) provide additional information relative to the historic gold standard magnetic resonance imaging. The diagnostic benefits of SPECT/CT include precise localization and characterization of spinal lesions and improved diagnosis for lower back pain. It may have a role in selecting patients for local therapeutic injections, as well as guiding their location with increased precision. PMID:26170560

Joint Counterair and Theater Missile Defense Doctrine to Defend against Unmanned Aerial Vehicles and Cruise Missiles in Asymmetric Warfare

DTIC Science & Technology

2009-02-12

features an Active Electronic Scan Array ( ASEA ) radar and improved electronics to enhance the capability of current front line fighter aircraft to...equipped with the APG-79 ASEA radar and selected squadrons of Air Force F-16 and F-15E have been approved for ASEA upgrades. Next generation fighter

Feature and Region Selection for Visual Learning.

PubMed

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

PubMed

Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification

PubMed Central

Feng, Yang; Jiang, Jiancheng; Tong, Xin

2015-01-01

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing. PMID:27185970

Label-aligned Multi-task Feature Learning for Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zu, Chen; Jie, Biao; Liu, Mingxia; Chen, Songcan

2015-01-01

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI. PMID:26572145

Strategies to Improve Activity Recognition Based on Skeletal Tracking: Applying Restrictions Regarding Body Parts and Similarity Boundaries †

PubMed Central

Gutiérrez-López-Franca, Carlos; Hervás, Ramón; Johnson, Esperanza

2018-01-01

This paper aims to improve activity recognition systems based on skeletal tracking through the study of two different strategies (and its combination): (a) specialized body parts analysis and (b) stricter restrictions for the most easily detectable activities. The study was performed using the Extended Body-Angles Algorithm, which is able to analyze activities using only a single key sample. This system allows to select, for each considered activity, which are its relevant joints, which makes it possible to monitor the body of the user selecting only a subset of the same. But this feature of the system has both advantages and disadvantages. As a consequence, in the past we had some difficulties with the recognition of activities that only have a small subset of the joints of the body as relevant. The goal of this work, therefore, is to analyze the effect produced by the application of several strategies on the results of an activity recognition system based on skeletal tracking joint oriented devices. Strategies that we applied with the purpose of improve the recognition rates of the activities with a small subset of relevant joints. Through the results of this work, we aim to give the scientific community some first indications about which considered strategy is better. PMID:29789478

Integrated residential photovoltaic array development

NASA Technical Reports Server (NTRS)

Shepard, N. F., Jr.

1981-01-01

The design details of an optimized integrated residential photovoltaic module/array are presented. This selected design features a waterproofing and mounting scheme which was devised to simplify the installation procedures by the avoidance of complex gasketed or caulked joints, while still maintaining a high confidence that the watertight integrity of the integral roofing surface will be achieved for the design lifetime of the system. The production and installation costs for the selected module/array design are reported for a range of annual production rates as a function of the cost of solar cells.

Judicious use of biologicals in juvenile idiopathic arthritis.

PubMed

Zhao, Yongdong; Wallace, Carol

2014-11-01

Juvenile idiopathic arthritis (JIA) is a chronic inflammatory disorder that may cause joint destruction. Biological treatments targeting specific cytokines and cell interactions have transformed the outcomes of JIA. This review focuses on the selection of patients for and the timing and selection of biological treatment in JIA. Tumor necrosis factor (TNF) inhibitors remain the first choice for polyarticular JIA, followed by abatacept and tocilizumab. Monoclonal-antibody TNF inhibitors and abatacept are usually chosen for methotrexate-resistant uveitis. Recent clinical trials of canakinumab, rilonacept, and tocilizumab have obtained great improvement in both systemic and arthritic features in chronic systemic JIA patients. Current guidelines support the early use of a short-acting IL-1 antagonist for macrophage activation syndrome, a life-threatening complication. TREAT and ACUTE studies suggest that a therapeutic window of opportunity during early disease may exist in JIA. Early initiation of biological therapy may be associated with slower progression of joint damage and longer remission.

Return to Work After Lumbar Microdiscectomy - Personalizing Approach Through Predictive Modeling.

PubMed

Papić, Monika; Brdar, Sanja; Papić, Vladimir; Lončar-Turukalo, Tatjana

2016-01-01

Lumbar disc herniation (LDH) is the most common disease among working population requiring surgical intervention. This study aims to predict the return to work after operative treatment of LDH based on the observational study including 153 patients. The classification problem was approached using decision trees (DT), support vector machines (SVM) and multilayer perception (MLP) combined with RELIEF algorithm for feature selection. MLP provided best recall of 0.86 for the class of patients not returning to work, which combined with the selected features enables early identification and personalized targeted interventions towards subjects at risk of prolonged disability. The predictive modeling indicated at the most decisive risk factors in prolongation of work absence: psychosocial factors, mobility of the spine and structural changes of facet joints and professional factors including standing, sitting and microclimate.

Discriminative analysis of lip motion features for speaker identification and speech-reading.

PubMed

Cetingül, H Ertan; Yemez, Yücel; Erzin, Engin; Tekalp, A Murat

2006-10-01

There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to lip intensity and/or geometry information, for speaker identification and speech-reading within a unified feature selection and discrimination analysis framework, and addresses two important issues: 1) Is using explicit lip motion information useful, and, 2) if so, what are the best lip motion features for these two applications? The best lip motion features for speaker identification are considered to be those that result in the highest discrimination of individual speakers in a population, whereas for speech-reading, the best features are those providing the highest phoneme/word/phrase recognition rate. Several lip motion feature candidates have been considered including dense motion features within a bounding box about the lip, lip contour motion features, and combination of these with lip shape features. Furthermore, a novel two-stage, spatial, and temporal discrimination analysis is introduced to select the best lip motion features for speaker identification and speech-reading applications. Experimental results using an hidden-Markov-model-based recognition system indicate that using explicit lip motion information provides additional performance gains in both applications, and lip motion features prove more valuable in the case of speech-reading application.

Optimization of laser butt welding parameters with multiple performance characteristics

NASA Astrophysics Data System (ADS)

Sathiya, P.; Abdul Jaleel, M. Y.; Katherasan, D.; Shanmugarajan, B.

2011-04-01

This paper presents a study carried out on 3.5 kW cooled slab laser welding of 904 L super austenitic stainless steel. The joints have butts welded with different shielding gases, namely argon, helium and nitrogen, at a constant flow rate. Super austenitic stainless steel (SASS) normally contains high amount of Mo, Cr, Ni, N and Mn. The mechanical properties are controlled to obtain good welded joints. The quality of the joint is evaluated by studying the features of weld bead geometry, such as bead width (BW) and depth of penetration (DOP). In this paper, the tensile strength and bead profiles (BW and DOP) of laser welded butt joints made of AISI 904 L SASS are investigated. The Taguchi approach is used as a statistical design of experiment (DOE) technique for optimizing the selected welding parameters. Grey relational analysis and the desirability approach are applied to optimize the input parameters by considering multiple output variables simultaneously. Confirmation experiments have also been conducted for both of the analyses to validate the optimized parameters.

Feature-extracted joint transform correlation.

PubMed

Alam, M S

1995-12-10

A new technique for real-time optical character recognition that uses a joint transform correlator is proposed. This technique employs feature-extracted patterns for the reference image to detect a wide range of characters in one step. The proposed technique significantly enhances the processing speed when compared with the presently available joint transform correlator architectures and shows feasibility for multichannel joint transform correlation.

A probabilistic model of cross-categorization.

PubMed

Shafto, Patrick; Kemp, Charles; Mansinghka, Vikash; Tenenbaum, Joshua B

2011-07-01

Most natural domains can be represented in multiple ways: we can categorize foods in terms of their nutritional content or social role, animals in terms of their taxonomic groupings or their ecological niches, and musical instruments in terms of their taxonomic categories or social uses. Previous approaches to modeling human categorization have largely ignored the problem of cross-categorization, focusing on learning just a single system of categories that explains all of the features. Cross-categorization presents a difficult problem: how can we infer categories without first knowing which features the categories are meant to explain? We present a novel model that suggests that human cross-categorization is a result of joint inference about multiple systems of categories and the features that they explain. We also formalize two commonly proposed alternative explanations for cross-categorization behavior: a features-first and an objects-first approach. The features-first approach suggests that cross-categorization is a consequence of attentional processes, where features are selected by an attentional mechanism first and categories are derived second. The objects-first approach suggests that cross-categorization is a consequence of repeated, sequential attempts to explain features, where categories are derived first, then features that are poorly explained are recategorized. We present two sets of simulations and experiments testing the models' predictions about human categorization. We find that an approach based on joint inference provides the best fit to human categorization behavior, and we suggest that a full account of human category learning will need to incorporate something akin to these capabilities. Copyright © 2011 Elsevier B.V. All rights reserved.

Automated Feature and Event Detection with SDO AIA and HMI Data

NASA Astrophysics Data System (ADS)

Davey, Alisdair; Martens, P. C. H.; Attrill, G. D. R.; Engell, A.; Farid, S.; Grigis, P. C.; Kasper, J.; Korreck, K.; Saar, S. H.; Su, Y.; Testa, P.; Wills-Davey, M.; Savcheva, A.; Bernasconi, P. N.; Raouafi, N.-E.; Delouille, V. A.; Hochedez, J. F..; Cirtain, J. W.; Deforest, C. E.; Angryk, R. A.; de Moortel, I.; Wiegelmann, T.; Georgouli, M. K.; McAteer, R. T. J.; Hurlburt, N.; Timmons, R.

The Solar Dynamics Observatory (SDO) represents a new frontier in quantity and quality of solar data. At about 1.5 TB/day, the data will not be easily digestible by solar physicists using the same methods that have been employed for images from previous missions. In order for solar scientists to use the SDO data effectively they need meta-data that will allow them to identify and retrieve data sets that address their particular science questions. We are building a comprehensive computer vision pipeline for SDO, abstracting complete metadata on many of the features and events detectable on the Sun without human intervention. Our project unites more than a dozen individual, existing codes into a systematic tool that can be used by the entire solar community. The feature finding codes will run as part of the SDO Event Detection System (EDS) at the Joint Science Operations Center (JSOC; joint between Stanford and LMSAL). The metadata produced will be stored in the Heliophysics Event Knowledgebase (HEK), which will be accessible on-line for the rest of the world directly or via the Virtual Solar Observatory (VSO) . Solar scientists will be able to use the HEK to select event and feature data to download for science studies.

A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.

PubMed

Fernández, Alberto; Carmona, Cristobal José; José Del Jesus, María; Herrera, Francisco

2017-09-01

Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.

Foot Structure in Boys with Down Syndrome.

PubMed

Puszczałowska-Lizis, Ewa; Nowak, Krzysztof; Omorczyk, Jarosław; Ambroży, Tadeusz; Bujas, Przemysław; Nosiadek, Leszek

2017-01-01

Down syndrome (DS) is associated with numerous developmental abnormalities, some of which cause dysfunctions of the posture and the locomotor system. The analysis of selected features of the foot structure in boys with DS versus their peers without developmental disorders is done. The podoscopic examination was performed on 30 boys with DS aged 14-15 years. A control group consisted of 30 age- and gender-matched peers without DS. The feet of boys with DS are flatter compared to their healthy peers. The hallux valgus angle is not the most important feature differentiating the shape of the foot in the boys with DS and their healthy peers. In terms of the V toe setting, healthy boys had poorer results. Specialized therapeutic treatment in individuals with DS should involve exercises to increase the muscle strength around the foot joints, enhancing the stabilization in the joints and proprioception. Introducing orthotics and proper footwear is also important. It is also necessary to monitor the state of the foot in order to modify undertaken therapies.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

PubMed

Rodriguez Gutierrez, D; Awwad, A; Meijer, L; Manita, M; Jaspan, T; Dineen, R A; Grundy, R G; Auer, D P

2014-05-01

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology. © 2014 by American Journal of Neuroradiology.

Generalized Models for Rock Joint Surface Shapes

PubMed Central

Du, Shigui; Hu, Yunjin; Hu, Xiaofei

2014-01-01

Generalized models of joint surface shapes are the foundation for mechanism studies on the mechanical effects of rock joint surface shapes. Based on extensive field investigations of rock joint surface shapes, generalized models for three level shapes named macroscopic outline, surface undulating shape, and microcosmic roughness were established through statistical analyses of 20,078 rock joint surface profiles. The relative amplitude of profile curves was used as a borderline for the division of different level shapes. The study results show that the macroscopic outline has three basic features such as planar, arc-shaped, and stepped; the surface undulating shape has three basic features such as planar, undulating, and stepped; and the microcosmic roughness has two basic features such as smooth and rough. PMID:25152901

Characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts

NASA Astrophysics Data System (ADS)

Chen, Siyue; Leung, Henry; Dondo, Maxwell

2014-05-01

As computer network security threats increase, many organizations implement multiple Network Intrusion Detection Systems (NIDS) to maximize the likelihood of intrusion detection and provide a comprehensive understanding of intrusion activities. However, NIDS trigger a massive number of alerts on a daily basis. This can be overwhelming for computer network security analysts since it is a slow and tedious process to manually analyse each alert produced. Thus, automated and intelligent clustering of alerts is important to reveal the structural correlation of events by grouping alerts with common features. As the nature of computer network attacks, and therefore alerts, is not known in advance, unsupervised alert clustering is a promising approach to achieve this goal. We propose a joint optimization technique for feature selection and clustering to aggregate similar alerts and to reduce the number of alerts that analysts have to handle individually. More precisely, each identified feature is assigned a binary value, which reflects the feature's saliency. This value is treated as a hidden variable and incorporated into a likelihood function for clustering. Since computing the optimal solution of the likelihood function directly is analytically intractable, we use the Expectation-Maximisation (EM) algorithm to iteratively update the hidden variable and use it to maximize the expected likelihood. Our empirical results, using a labelled Defense Advanced Research Projects Agency (DARPA) 2000 reference dataset, show that the proposed method gives better results than the EM clustering without feature selection in terms of the clustering accuracy.

First metatarsophalangeal joint motion in Homo sapiens: theoretical association of two-axis kinematics and specific morphometrics.

PubMed

Durrant, Michael N; McElroy, Tucker; Durrant, Lara

2012-01-01

The metatarsal head and proximal phalanx exhibit considerable asymmetry in their shape and geometry, but there is little documentation in the literature regarding the prevalence of structural characteristics that occur in a given population. Although there is a considerable volume of in vivo and in vitro experiments demonstrating first metatarsal inversion around its longitudinal axis with dorsiflexion, little is known regarding the applicability of specific morphometrics to these motions. Nine distinctive osseous characteristics in the metatarsal head and phalanx were selected based on their location, geometry, and perceived functional relationship to previous studies describing metatarsal motion as inversion with dorsiflexion. The prevalences of the chosen characteristics were determined in a cohort of 21 randomly selected skeletal specimens, 19 of which were provided by the anatomical preparation office at the University of California, San Diego, and two of which were in the possession of one of us (M.D.). The frequency of occurrence of each selected morphological characteristic in this sample and the relevant summary statistics confirm a strong association between the selected features and a conceptual two-axis kinematic model of the metatarsophalangeal joint. The selected morphometrics are consistent with inversion of the metatarsal around its longitudinal axis as it dorsiflexes.

Hand pose estimation in depth image using CNN and random forest

NASA Astrophysics Data System (ADS)

Chen, Xi; Cao, Zhiguo; Xiao, Yang; Fang, Zhiwen

2018-03-01

Thanks to the availability of low cost depth cameras, like Microsoft Kinect, 3D hand pose estimation attracted special research attention in these years. Due to the large variations in hand`s viewpoint and the high dimension of hand motion, 3D hand pose estimation is still challenging. In this paper we propose a two-stage framework which joint with CNN and Random Forest to boost the performance of hand pose estimation. First, we use a standard Convolutional Neural Network (CNN) to regress the hand joints` locations. Second, using a Random Forest to refine the joints from the first stage. In the second stage, we propose a pyramid feature which merges the information flow of the CNN. Specifically, we get the rough joints` location from first stage, then rotate the convolutional feature maps (and image). After this, for each joint, we map its location to each feature map (and image) firstly, then crop features at each feature map (and image) around its location, put extracted features to Random Forest to refine at last. Experimentally, we evaluate our proposed method on ICVL dataset and get the mean error about 11mm, our method is also real-time on a desktop.

Intrapartum fetal heart rate classification from trajectory in Sparse SVM feature space.

PubMed

Spilka, J; Frecon, J; Leonarduzzi, R; Pustelnik, N; Abry, P; Doret, M

2015-01-01

Intrapartum fetal heart rate (FHR) constitutes a prominent source of information for the assessment of fetal reactions to stress events during delivery. Yet, early detection of fetal acidosis remains a challenging signal processing task. The originality of the present contribution are three-fold: multiscale representations and wavelet leader based multifractal analysis are used to quantify FHR variability ; Supervised classification is achieved by means of Sparse-SVM that aim jointly to achieve optimal detection performance and to select relevant features in a multivariate setting ; Trajectories in the feature space accounting for the evolution along time of features while labor progresses are involved in the construction of indices quantifying fetal health. The classification performance permitted by this combination of tools are quantified on a intrapartum FHR large database (≃ 1250 subjects) collected at a French academic public hospital.

DefenseLink Feature: Berlin Airlift

Science.gov Websites

Services Open House at Andrews Air Force Base FEATURE STORIES Wiesbaden Celebrates Airlift Anniversary Airlift Anniversary This year's Joint Service Open House commemorates the 60th anniversary of the Berlin Open House 2008 Joint Service Open House This year's Joint Service Open House commemorated the 60th

A Multidisciplinary Approach to Health Monitoring and Materials Damage Prognosis for Metallic Aerospace Systems

DTIC Science & Technology

2013-03-01

framework of orientation distribution functions and crack-induced texture o Quantify effects of temperature on damage behavior and damage monitoring...measurement model was obtained from hidden Markov modeling (HMM) of joint time-frequency (TF) features extracted from the PZT sensor signals using the...considered PZT sensor signals recorded from a bolted aluminum plate. About only 20% of the samples of a signal were first randomly selected as

Algorithm For Solution Of Subset-Regression Problems

NASA Technical Reports Server (NTRS)

Verhaegen, Michel

1991-01-01

Reliable and flexible algorithm for solution of subset-regression problem performs QR decomposition with new column-pivoting strategy, enables selection of subset directly from originally defined regression parameters. This feature, in combination with number of extensions, makes algorithm very flexible for use in analysis of subset-regression problems in which parameters have physical meanings. Also extended to enable joint processing of columns contaminated by noise with those free of noise, without using scaling techniques.

Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait.

PubMed

Martins, Maria; Costa, Lino; Frizera, Anselmo; Ceres, Ramón; Santos, Cristina

2014-03-01

Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Multi-degree of freedom joystick for virtual reality simulation.

PubMed

Head, M J; Nelson, C A; Siu, K C

2013-11-01

A modular control interface and simulated virtual reality environment were designed and created in order to determine how the kinematic architecture of a control interface affects minimally invasive surgery training. A user is able to selectively determine the kinematic configuration of an input device (number, type and location of degrees of freedom) for a specific surgical simulation through the use of modular joints and constraint components. Furthermore, passive locking was designed and implemented through the use of inflated latex tubing around rotational joints in order to allow a user to step away from a simulation without unwanted tool motion. It is believed that these features will facilitate improved simulation of a variety of surgical procedures and, thus, improve surgical skills training.

Explaining Andean Potato Weevils in Relation to Local and Landscape Features: A Facilitated Ecoinformatics Approach

PubMed Central

Parsa, Soroush; Ccanto, Raúl; Olivera, Edgar; Scurrah, María; Alcázar, Jesús; Rosenheim, Jay A.

2012-01-01

Background Pest impact on an agricultural field is jointly influenced by local and landscape features. Rarely, however, are these features studied together. The present study applies a “facilitated ecoinformatics” approach to jointly screen many local and landscape features of suspected importance to Andean potato weevils (Premnotrypes spp.), the most serious pests of potatoes in the high Andes. Methodology/Principal Findings We generated a comprehensive list of predictors of weevil damage, including both local and landscape features deemed important by farmers and researchers. To test their importance, we assembled an observational dataset measuring these features across 138 randomly-selected potato fields in Huancavelica, Peru. Data for local features were generated primarily by participating farmers who were trained to maintain records of their management operations. An information theoretic approach to modeling the data resulted in 131,071 models, the best of which explained 40.2–46.4% of the observed variance in infestations. The best model considering both local and landscape features strongly outperformed the best models considering them in isolation. Multi-model inferences confirmed many, but not all of the expected patterns, and suggested gaps in local knowledge for Andean potato weevils. The most important predictors were the field's perimeter-to-area ratio, the number of nearby potato storage units, the amount of potatoes planted in close proximity to the field, and the number of insecticide treatments made early in the season. Conclusions/Significance Results underscored the need to refine the timing of insecticide applications and to explore adjustments in potato hilling as potential control tactics for Andean weevils. We believe our study illustrates the potential of ecoinformatics research to help streamline IPM learning in agricultural learning collaboratives. PMID:22693551

MNASA as a Test for Carbon Fiber Thermal Barrier Development

NASA Technical Reports Server (NTRS)

Bauer, Paul; McCool, Alex (Technical Monitor)

2001-01-01

A carbon fiber rope thermal barrier is being evaluated as a replacement for the conventional room temperature vulcanizing (RTV) thermal barrier that is currently used to protect o-rings in Reusable Solid Rocket Motor (RSRM) nozzle joints. Performance requirements include its ability to cool any incoming, hot propellant gases that fill and pressurize the nozzle joints, filter slag and particulates, and to perform adequately in various joint assembly conditions as well as dynamic flight motion. Modified National Aeronautics and Space Administration (MNASA) motors, with their inherent and unique ability to replicate select RSRM internal environment features, were an integral step in the development path leading to full scale RSRM static test demonstration of the carbon fiber rope (CFR) joint concept. These 1/4 scale RSRM motors serve to bridge the gap between the other classes of subscale test motors (extremely small and moderate duration, or small scale and short duration) and the critical asset RSRM static test motors. A series of MNASA tests have been used to demonstrate carbon fiber rope performance and have provided rationale for implementation into a full-scale static motor and flight qualification.

Development and reliability of a preliminary Foot Osteoarthritis Magnetic Resonance Imaging Score

PubMed Central

Halstead, Jill; Martín-Hervás, Carmen; Hensor, Elizabeth MA; McGonagle, Dennis; Keenan, Anne-Maree

2017-01-01

Objective Foot osteoarthritis (OA) is very common but under-investigated musculoskeletal condition and there is little consensus as to common MRI imaging features. The aim of this study was to develop a preliminary foot OA MRI score (FOAMRIS) and evaluate its reliability. Methods This preliminary semi-quantitative score included the hindfoot, midfoot and metatarsophalangeal joints. Joints were scored for joint space narrowing (JSN, 0-3), osteophytes (0-3), joint effusion-synovitis and bone cysts (present/absent). Erosions and bone marrow lesions (BMLs) were scored (0-3) and BMLs were evaluated adjacent to entheses and at sub-tendon sites (present/absent). Additionally, tenosynovitis was scored (0-3) and midfoot ligament pathology was scored (present/absent). Reliability was evaluated in 15 people with foot pain and MRI-detected OA using 3.0T MRI multi-sequence protocols and assessed using intraclass correlation coefficients (ICC) as an overall score and per anatomical site (see supplementary data). Results Intra-reader agreement (ICC) was generally good to excellent across the foot in joint features (JSN 0.94, osteophytes 0.94, effusion-synovitis 0.62 and cysts 0.93), bone features (BML 0.89, erosion 0.78, BML-entheses 0.79, BML sub-tendon 0.75) and soft-tissue features (tenosynovitis 0.90, ligaments 0.87). Inter-reader agreement was lower for joint features (JSN 0.60, osteophytes 0.41, effusion-synovitis 0.03) and cysts 0.65, bone features (BML 0.80, erosion 0.00, BML-entheses 0.49, BML sub-tendon -0.24) and soft-tissue features (tenosynovitis 0.48, ligaments 0.50). Conclusion This preliminary FOAMRIS demonstrated good intra-reader reliability and fair inter-reader reliability when assessing the total feature scores. Further development is required in cohorts with a range of pathologies and to assess the psychometric measurement properties. PMID:28572462

Kernel-Based Relevance Analysis with Enhanced Interpretability for Detection of Brain Activity Patterns

PubMed Central

Alvarez-Meza, Andres M.; Orozco-Gutierrez, Alvaro; Castellanos-Dominguez, German

2017-01-01

We introduce Enhanced Kernel-based Relevance Analysis (EKRA) that aims to support the automatic identification of brain activity patterns using electroencephalographic recordings. EKRA is a data-driven strategy that incorporates two kernel functions to take advantage of the available joint information, associating neural responses to a given stimulus condition. Regarding this, a Centered Kernel Alignment functional is adjusted to learning the linear projection that best discriminates the input feature set, optimizing the required free parameters automatically. Our approach is carried out in two scenarios: (i) feature selection by computing a relevance vector from extracted neural features to facilitating the physiological interpretation of a given brain activity task, and (ii) enhanced feature selection to perform an additional transformation of relevant features aiming to improve the overall identification accuracy. Accordingly, we provide an alternative feature relevance analysis strategy that allows improving the system performance while favoring the data interpretability. For the validation purpose, EKRA is tested in two well-known tasks of brain activity: motor imagery discrimination and epileptic seizure detection. The obtained results show that the EKRA approach estimates a relevant representation space extracted from the provided supervised information, emphasizing the salient input features. As a result, our proposal outperforms the state-of-the-art methods regarding brain activity discrimination accuracy with the benefit of enhanced physiological interpretation about the task at hand. PMID:29056897

Multi-channel feature dictionaries for RGB-D object recognition

NASA Astrophysics Data System (ADS)

Lan, Xiaodong; Li, Qiming; Chong, Mina; Song, Jian; Li, Jun

2018-04-01

Hierarchical matching pursuit (HMP) is a popular feature learning method for RGB-D object recognition. However, the feature representation with only one dictionary for RGB channels in HMP does not capture sufficient visual information. In this paper, we propose multi-channel feature dictionaries based feature learning method for RGB-D object recognition. The process of feature extraction in the proposed method consists of two layers. The K-SVD algorithm is used to learn dictionaries in sparse coding of these two layers. In the first-layer, we obtain features by performing max pooling on sparse codes of pixels in a cell. And the obtained features of cells in a patch are concatenated to generate patch jointly features. Then, patch jointly features in the first-layer are used to learn the dictionary and sparse codes in the second-layer. Finally, spatial pyramid pooling can be applied to the patch jointly features of any layer to generate the final object features in our method. Experimental results show that our method with first or second-layer features can obtain a comparable or better performance than some published state-of-the-art methods.

Study on the Flexibility in Cross-Border Water Resources Cooperation Governance

NASA Astrophysics Data System (ADS)

Liu, Zongrui; Wang, Teng; Zhou, Li

2018-02-01

Flexible strategy is very important to cross-border cooperation in international rivers water resources, which may be employed to reconcile contradictions and ease conflicts. Flexible characters of cross-border cooperation in international rivers water resources could be analyzed and revealed, using flexible strategic management framework, by taking international cooperation protocols related to water from Transboundary Freshwater Disputes Database (TFDD) as samples from the number of cooperation issues, the amount of management layers and regulator agencies in cooperation organization and the categories of income (cost) distribution (allocation) mode. The research demonstrates that there are some flexible features of cross-border cooperation in international rivers water resources: Riparian countries would select relative diversification strategies related to water, tend to construct a flexible cooperation organization featured with moderate hierarchies from vertical perspective and simplified administrations from horizontal perspective, and adopt selective inducement modes to respect ‘joint and several liability’.

Correlation between radiographic findings of osteoarthritis and arthroscopic findings of articular cartilage degeneration within the patellofemoral joint.

PubMed

Kijowski, Richard; Blankenbaker, Donna; Stanton, Paul; Fine, Jason; De Smet, Arthur

2006-12-01

To correlate radiographic findings of osteoarthritis on axial knee radiographs with arthroscopic findings of articular cartilage degeneration within the patellofemoral joint in patients with chronic knee pain. The study group consisted of 104 patients with osteoarthritis of the patellofemoral joint and 30 patients of similar age with no osteoarthritis of the patellofemoral joint. All patients in the study group had an axial radiograph of the knee performed prior to arthroscopic knee surgery. At the time of arthroscopy, each articular surface of the patellofemoral joint was graded using the Noyes classification system. Two radiologists retrospectively reviewed the knee radiographs to determine the presence of marginal osteophytes, joint-space narrowing, subchondral sclerosis, and subchondral cysts. The sensitivity and specificity of the various radiographic features of osteoarthritis for the detection of articular cartilage degeneration within the patellofemoral joint were determined. The sensitivity of marginal osteophytes, joint-space narrowing, subchondral sclerosis, and subchondral cysts for the detection of articular cartilage degeneration within the patellofemoral joint was 73%, 37%, 4%, and 0% respectively. The specificity of marginal osteophytes, joint-space narrowing, subchondral sclerosis, and subchondral cysts for the detection of articular cartilage degeneration within the patellofemoral joint was 67%, 90%, 100%, and 100% respectively. Marginal osteophytes were the most sensitive radiographic feature for the detection of articular cartilage degeneration within the patellofemoral joint. Joint-space narrowing, subchondral sclerosis, and subchondral cysts were insensitive radiographic features of osteoarthritis, and rarely occurred in the absence of associated osteophyte formation.

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

PubMed

Mognon, Andrea; Jovicich, Jorge; Bruzzone, Lorenzo; Buiatti, Marco

2011-02-01

A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event-related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal. Copyright © 2010 Society for Psychophysiological Research.

Working Together to Educate about the Environment. Selected Papers from the Joint Conference of the North American Association for Environmental Education and the Conservation Education Association (Estes Park, Colorado, August 18-23, 1989).

ERIC Educational Resources Information Center

Gross, Michael P., Ed.; And Others

Proceedings of a conference on environmental education are presented in this document. Featured at the conference were four general sessions, a number of additional invited presentations, three symposia, four workshops, and over 170 contributed presentations. The purpose of this volume is to provide a record of the papers presented at the…

The Joint Chiefs of Staff Video Collections

Science.gov Websites

Senior Enlisted Advisor Joint Staff History Joint Staff Inspector General Joint Staff Structure Origin of J8 | Force Structure, Resources & Assessment Contact Home : Media : Videos Featured Videos Gen

No associations between self-reported knee joint instability and radiographic features in knee osteoarthritis patients prior to Total Knee Arthroplasty: A cross-sectional analysis of the Longitudinal Leiden Orthopaedics Outcomes of Osteo-Arthritis study (LOAS) data.

PubMed

Leichtenberg, Claudia S; Meesters, Jorit J L; Kroon, Herman M; Verdegaal, Suzan H M; Tilbury, Claire; Dekker, Joost; Nelissen, Rob G H H; Vliet Vlieland, Thea P M; van der Esch, Martin

2017-08-01

To describe the prevalence of self-reported knee joint instability in patients with pre-surgery knee osteoarthritis (OA) and to explore the associations between self-reported knee joint instability and radiological features. A cross-sectional study including patients scheduled for primary Total Knee Arthroplasty (TKA). Self-reported knee instability was examined by questionnaire. Radiological features consisted of osteophyte formation and joint space narrowing (JSN), both scored on a 0 to three scale. Scores >1 are defined as substantial JSN or osteophyte formation. Regression analyses were provided to identify associations of radiological features with self-reported knee joint instability. Two hundred and sixty-five patients (mean age 69years and 170 females) were included. Knee instability was reported by 192 patients (72%). Substantial osteophyte formation was present in 78 patients (41%) reporting and 33 patients (46%) not reporting knee joint instability. Substantial JSN was present in 137 (71%) and 53 patients (73%), respectively. Self-reported knee instability was not associated with JSN (relative to score 0, odds ratios (95% CI) of score 1, 2 and 3 were 0.87 (0.30-2.54), 0.98 (0.38-2.52), 0.68 (0.25-1.86), respectively) or osteophyte formation (relative to score 0, odds ratios (95% CI) of score 1, 2 and 3 were 0.77 (0.36-1.64), 0.69 (0.23-1.45), 0.89 (0.16-4.93), respectively). Stratified analysis for pain, age and BMI showed no associations between self-reported knee joint instability and radiological features. Self-reported knee joint instability is not associated with JSN or osteophyte formation. Copyright © 2017 Elsevier B.V. All rights reserved.

Central Sensitization and Neuropathic Features of Ongoing Pain in a Rat Model of Advanced Osteoarthritis.

PubMed

Havelin, Joshua; Imbert, Ian; Cormier, Jennifer; Allen, Joshua; Porreca, Frank; King, Tamara

2016-03-01

Osteoarthritis (OA) pain is most commonly characterized by movement-triggered joint pain. However, in advanced disease, OA pain becomes persistent, ongoing and resistant to treatment with nonsteroidal anti-inflammatory drugs (NSAIDs). The mechanisms underlying ongoing pain in advanced OA are poorly understood. We recently showed that intra-articular (i.a.) injection of monosodium iodoacetate (MIA) into the rat knee joint produces concentration-dependent outcomes. Thus, a low dose of i.a. MIA produces NSAID-sensitive weight asymmetry without evidence of ongoing pain and a high i.a. MIA dose produces weight asymmetry and NSAID-resistant ongoing pain. In the present study, palpation of the ipsilateral hind limb of rats treated 14 days previously with high, but not low, doses of i.a. MIA produced expression of the early oncogene, FOS, in the spinal dorsal horn. Inactivation of descending pain facilitatory pathways using a microinjection of lidocaine within the rostral ventromedial medulla induced conditioned place preference selectively in rats treated with the high dose of MIA. Conditioned place preference to intra-articular lidocaine was blocked by pretreatment with duloxetine (30 mg/kg, intraperitoneally at -30 minutes). These observations are consistent with the likelihood of a neuropathic component of OA that elicits ongoing, NSAID-resistant pain and central sensitization that is mediated, in part, by descending modulatory mechanisms. This model provides a basis for exploration of underlying mechanisms promoting neuropathic components of OA pain and for the identification of mechanisms that might guide drug discovery for treatment of advanced OA pain without the need for joint replacement. Difficulty in managing advanced OA pain often results in joint replacement therapy in these patients. Improved understanding of mechanisms driving NSAID-resistant ongoing OA pain might facilitate development of alternatives to joint replacement therapy. Our findings suggest that central sensitization and neuropathic features contribute to NSAID-resistant ongoing OA joint pain. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Foot Structure in Boys with Down Syndrome

PubMed Central

Nowak, Krzysztof; Omorczyk, Jarosław; Ambroży, Tadeusz; Nosiadek, Leszek

2017-01-01

Introduction and Aim Down syndrome (DS) is associated with numerous developmental abnormalities, some of which cause dysfunctions of the posture and the locomotor system. The analysis of selected features of the foot structure in boys with DS versus their peers without developmental disorders is done. Materials and Methods The podoscopic examination was performed on 30 boys with DS aged 14-15 years. A control group consisted of 30 age- and gender-matched peers without DS. Results The feet of boys with DS are flatter compared to their healthy peers. The hallux valgus angle is not the most important feature differentiating the shape of the foot in the boys with DS and their healthy peers. In terms of the V toe setting, healthy boys had poorer results. Conclusions Specialized therapeutic treatment in individuals with DS should involve exercises to increase the muscle strength around the foot joints, enhancing the stabilization in the joints and proprioception. Introducing orthotics and proper footwear is also important. It is also necessary to monitor the state of the foot in order to modify undertaken therapies. PMID:28904967

Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controls.

PubMed

Yoo, Youngjin; Tang, Lisa Y W; Brosch, Tom; Li, David K B; Kolind, Shannon; Vavasour, Irene; Rauscher, Alexander; MacKay, Alex L; Traboulsee, Anthony; Tam, Roger C

2018-01-01

Myelin imaging is a form of quantitative magnetic resonance imaging (MRI) that measures myelin content and can potentially allow demyelinating diseases such as multiple sclerosis (MS) to be detected earlier. Although focal lesions are the most visible signs of MS pathology on conventional MRI, it has been shown that even tissues that appear normal may exhibit decreased myelin content as revealed by myelin-specific images (i.e., myelin maps). Current methods for analyzing myelin maps typically use global or regional mean myelin measurements to detect abnormalities, but ignore finer spatial patterns that may be characteristic of MS. In this paper, we present a machine learning method to automatically learn, from multimodal MR images, latent spatial features that can potentially improve the detection of MS pathology at early stage. More specifically, 3D image patches are extracted from myelin maps and the corresponding T1-weighted (T1w) MRIs, and are used to learn a latent joint myelin-T1w feature representation via unsupervised deep learning. Using a data set of images from MS patients and healthy controls, a common set of patches are selected via a voxel-wise t -test performed between the two groups. In each MS image, any patches overlapping with focal lesions are excluded, and a feature imputation method is used to fill in the missing values. A feature selection process (LASSO) is then utilized to construct a sparse representation. The resulting normal-appearing features are used to train a random forest classifier. Using the myelin and T1w images of 55 relapse-remitting MS patients and 44 healthy controls in an 11-fold cross-validation experiment, the proposed method achieved an average classification accuracy of 87.9% (SD = 8.4%), which is higher and more consistent across folds than those attained by regional mean myelin (73.7%, SD = 13.7%) and T1w measurements (66.7%, SD = 10.6%), or deep-learned features in either the myelin (83.8%, SD = 11.0%) or T1w (70.1%, SD = 13.6%) images alone, suggesting that the proposed method has strong potential for identifying image features that are more sensitive and specific to MS pathology in normal-appearing brain tissues.

Efficient robust conditional random fields.

PubMed

Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A

2015-10-01

Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.

Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

NASA Astrophysics Data System (ADS)

Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

2017-07-01

Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

MRI features of cervical articular process degenerative joint disease in Great Dane dogs with cervical spondylomyelopathy.

PubMed

Gutierrez-Quintana, Rodrigo; Penderis, Jacques

2012-01-01

Cervical spondylomyelopathy or Wobbler syndrome commonly affects the cervical vertebral column of Great Dane dogs. Degenerative changes affecting the articular process joints are a frequent finding in these patients; however, the correlation between these changes and other features of cervical spondylomyelopathy are uncertain. We described and graded the degenerative changes evident in the cervical articular process joints from 13 Great Danes dogs with cervical spondylomyelopathy using MR imaging, and evaluated the relationship between individual features of cervical articular process joint degeneration and the presence of spinal cord compression, vertebral foraminal stenosis, intramedullary spinal cord changes, and intervertebral disc degenerative changes. Degenerative changes affecting the articular process joints were common, with only 13 of 94 (14%) having no degenerative changes. The most severe changes were evident between C4-C5 and C7-T1 intervertebral spaces. Reduction or loss of the hyperintense synovial fluid signal on T2-weighted MR images was the most frequent feature associated with articular process joint degenerative changes. Degenerative changes of the articular process joints affecting the synovial fluid or articular surface, or causing lateral hypertrophic tissue, were positively correlated with lateral spinal cord compression and vertebral foraminal stenosis. Dorsal hypertrophic tissue was positively correlated with dorsal spinal cord compression. Disc-associated spinal cord compression was recognized less frequently. © 2011 Veterinary Radiology & Ultrasound.

[Juvenile rheumatoid diseases: Endoprosthetic care of destroyed hip joints].

PubMed

Rehart, S; Henniger, M

2015-07-01

Patients with juvenile idiopathic arthritis (JIA) often suffer from involvement of the hip joints, with joint destruction and related functional limitations, making hip replacement necessary. To discover what special features are to be expected in patients with JIA and hip arthroplasty and what impact they have on surgical indication, choice of implant, and technique. Selective literature review and evaluation of our patient population. Compared with osteoarthritis patients, JIA patients are on average much younger at the time of hip replacement. Owing to the onset of the disease in childhood or adolescence and the frequent glucocorticoid therapy, growth disorders or abnormal anatomical findings are common in these patients. Bone density is often reduced at an early age. The perioperative management of medication has to be planned. Special implants for patients with rheumatic diseases do not exist, but the above peculiarities of this group of patients should be considered for surgical procedure and choice of implant and material. Overall, the results of hip arthroplasty in juvenile rheumatic diseases, in terms of pain relief and functional improvement, are good. The limited life of the arthroplasty is problematic. By relieving pain, improvement of the range of motion and activity level very high patient satisfaction is usually achieved by hip arthroplasty in JIA patients. In the case of involvement of the contralateral hip or the ipsilateral knee joint it may be useful to perform a simultaneous, single-stage joint replacement of both joints.

Novel Ultrasound Joint Selection Methods Using a Reduced Joint Number Demonstrate Inflammatory Improvement when Compared to Existing Methods and Disease Activity Score at 28 Joints.

PubMed

Tan, York Kiat; Allen, John C; Lye, Weng Kit; Conaghan, Philip G; D'Agostino, Maria Antonietta; Chew, Li-Ching; Thumboo, Julian

2016-01-01

A pilot study testing novel ultrasound (US) joint-selection methods in rheumatoid arthritis. Responsiveness of novel [individualized US (IUS) and individualized composite US (ICUS)] methods were compared with existing US methods and the Disease Activity Score at 28 joints (DAS28) for 12 patients followed for 3 months. IUS selected up to 7 and 12 most ultrasonographically inflamed joints, while ICUS additionally incorporated clinically symptomatic joints. The existing, IUS, and ICUS methods' standardized response means were -0.39, -1.08, and -1.11, respectively, for 7 joints; -0.49, -1.00, and -1.16, respectively, for 12 joints; and -0.94 for DAS28. Novel methods effectively demonstrate inflammatory improvement when compared with existing methods and DAS28.

Serum N-propeptide of collagen IIA (PIIANP) as a marker of radiographic osteoarthritis burden.

PubMed

Daghestani, Hikmat N; Jordan, Joanne M; Renner, Jordan B; Doherty, Michael; Wilson, A Gerry; Kraus, Virginia B

2017-01-01

Cartilage homeostasis relies on a balance of catabolism and anabolism of cartilage matrix. Our goal was to evaluate the burden of radiographic osteoarthritis and serum levels of type IIA procollagen amino terminal propeptide (sPIIANP), a biomarker representing type II collagen synthesis, in osteoarthritis. OA burden was quantified on the basis of radiographic features as total joint faces with an osteophyte, joint space narrowing, or in the spine, disc space narrowing. sPIIANP was measured in 1,235 participants from the Genetics of Generalized Osteoarthritis study using a competitive enzyme-linked immunosorbent assay. Separate multivariable linear regression models, adjusted for age, sex, and body mass index and additionally for ipsilateral osteophytes or joint/disc space narrowing, were used to assess the independent association of sPIIANP with osteophytes and with joint/disc space narrowing burden in knees, hips, hands and spine, individually and together. After full adjustment, sPIIANP was significantly associated with a lesser burden of hip joint space narrowing and knee osteophytes. sPIIANP was associated with a lesser burden of hand joint space narrowing but a greater burden of hand osteophytes; these results were only evident upon adjustment for osteoarthritic features in all other joints. There were no associations of sPIIANP and features of spine osteoarthritis. Higher cartilage collagen synthesis, as reflected in systemic PIIANP concentrations, was associated with lesser burden of osteoarthritic features in lower extremity joints (knees and hips), even accounting for osteoarthritis burden in hands and spine, age, sex and body mass index. These results suggest that pro-anabolic agents may be appropriate for early treatment to prevent severe lower extremity large joint osteoarthritis.

Application of Fuzzy c-Means and Joint-Feature-Clustering to Detect Redundancies of Image-Features in Drug Combinations Studies of Breast Cancer

NASA Astrophysics Data System (ADS)

Brandl, Miriam B.; Beck, Dominik; Pham, Tuan D.

2011-06-01

The high dimensionality of image-based dataset can be a drawback for classification accuracy. In this study, we propose the application of fuzzy c-means clustering, cluster validity indices and the notation of a joint-feature-clustering matrix to find redundancies of image-features. The introduced matrix indicates how frequently features are grouped in a mutual cluster. The resulting information can be used to find data-derived feature prototypes with a common biological meaning, reduce data storage as well as computation times and improve the classification accuracy.

Special Features of Induction Annealing of Friction Stir Welded Joints of Medium-Alloy Steels

NASA Astrophysics Data System (ADS)

Priymak, E. Yu.; Stepanchukova, A. V.; Bashirova, E. V.; Fot, A. P.; Firsova, N. V.

2018-01-01

Welded joints of medium-alloy steels XJY750 and 40KhN2MA are studied in the initial condition and after different variants of annealing. Special features of the phase transformations occurring in the welded steels are determined. Optimum modes of annealing are recommended for the studied welded joints of drill pipes, which provide a high level of mechanical properties including the case of impact loading.

Phenotypic variability in developmental coordination disorder: Clustering of generalized joint hypermobility with attention deficit/hyperactivity disorder, atypical swallowing and narrative difficulties.

PubMed

Celletti, Claudia; Mari, Giorgia; Ghibellini, Giulia; Celli, Mauro; Castori, Marco; Camerota, Filippo

2015-03-01

Developmental coordination disorder (DCD) is a recognized childhood disorder mostly characterized by motor coordination difficulties. Joint hypermobility syndrome, alternatively termed Ehlers-Danlos syndrome, hypermobility type (JHS/EDS-HT), is a hereditary connective tissue disorder mainly featuring generalized joint hypermobility (gJHM), musculoskeletal pain, and minor skin features. Although these two conditions seem apparently unrelated, recent evidence highlights a high rate of motor and coordination findings in children with gJHM or JHS/EDS-HT. Here, we investigated the prevalence of gJHM in 41 Italian children with DCD in order to check for the existence of recognizable phenotypic subgroups of DCD in relation to the presence/absence of gJHM. All patients were screened for Beighton score and a set of neuropsychological tests for motor competences (Movement Assessment Battery for Children and Visual-Motor Integration tests), and language and learning difficulties (Linguistic Comprehension Test, Peabody Picture Vocabulary Test, Boston Naming Test, Bus Story Test, and Memoria-Training tests). All patients were also screening for selected JHS/EDS-HT-associated features and swallowing problems. Nineteen (46%) children showed gJHM and 22 (54%) did not. Children with DCD and gJHM showed a significant excess of frequent falls (95 vs. 18%), easy bruising (74 vs. 0%), motor impersistence (89 vs. 23%), sore hands for writing (53 vs. 9%), attention deficit/hyperactivity disorder (89 vs. 36%), constipation (53 vs. 0%), arthralgias/myalgias (58 vs. 4%), narrative difficulties (74 vs. 32%), and atypical swallowing (74 vs. 18%). This study confirms the non-causal association between DCD and gJHM, which, in turn, seems to increase the risk for non-random additional features. The excess of language, learning, and swallowing difficulties in patients with DCD and gJHM suggests a wider effect of lax tissues in the development of the nervous system. © 2015 Wiley Periodicals, Inc.

Culture - joint fluid

MedlinePlus

... this page: //medlineplus.gov/ency/article/003742.htm Culture - joint fluid To use the sharing features on this page, please enable JavaScript. Joint fluid culture is a laboratory test to detect infection-causing ...

Sacroiliac joint pain - aftercare

MedlinePlus

... this page: //medlineplus.gov/ency/patientinstructions/000610.htm Sacroiliac joint pain - aftercare To use the sharing features on this page, please enable JavaScript. The sacroiliac joint (SIJ) is a term used to describe ...

Weighted score-level feature fusion based on Dempster-Shafer evidence theory for action recognition

NASA Astrophysics Data System (ADS)

Zhang, Guoliang; Jia, Songmin; Li, Xiuzhi; Zhang, Xiangyin

2018-01-01

The majority of human action recognition methods use multifeature fusion strategy to improve the classification performance, where the contribution of different features for specific action has not been paid enough attention. We present an extendible and universal weighted score-level feature fusion method using the Dempster-Shafer (DS) evidence theory based on the pipeline of bag-of-visual-words. First, the partially distinctive samples in the training set are selected to construct the validation set. Then, local spatiotemporal features and pose features are extracted from these samples to obtain evidence information. The DS evidence theory and the proposed rule of survival of the fittest are employed to achieve evidence combination and calculate optimal weight vectors of every feature type belonging to each action class. Finally, the recognition results are deduced via the weighted summation strategy. The performance of the established recognition framework is evaluated on Penn Action dataset and a subset of the joint-annotated human metabolome database (sub-JHMDB). The experiment results demonstrate that the proposed feature fusion method can adequately exploit the complementarity among multiple features and improve upon most of the state-of-the-art algorithms on Penn Action and sub-JHMDB datasets.

Weighted fusion of depth and inertial data to improve view invariance for real-time human action recognition

NASA Astrophysics Data System (ADS)

Chen, Chen; Hao, Huiyan; Jafari, Roozbeh; Kehtarnavaz, Nasser

2017-05-01

This paper presents an extension to our previously developed fusion framework [10] involving a depth camera and an inertial sensor in order to improve its view invariance aspect for real-time human action recognition applications. A computationally efficient view estimation based on skeleton joints is considered in order to select the most relevant depth training data when recognizing test samples. Two collaborative representation classifiers, one for depth features and one for inertial features, are appropriately weighted to generate a decision making probability. The experimental results applied to a multi-view human action dataset show that this weighted extension improves the recognition performance by about 5% over equally weighted fusion deployed in our previous fusion framework.

Support and Development of Workflow Protocols for High Throughput Single-Lap-Joint Testing-Experimental

DTIC Science & Technology

2013-04-01

preparation, and presence of an overflow fillet for a high strength epoxy and ductile methacylate adhesive. A unique feature of this study was the...of expanding adhesive joint test configurations as part of the GEMS program. 15. SUBJECT TERMS single lap joint, adhesion, aluminum, epoxy ... epoxy and ductile methacylate adhesive. A unique feature of this study was the use of untrained GEMS (Gains in the Education of Mathematics and Sci

The Value of Phenotypes in Knee Osteoarthritis Research.

PubMed

Nelson, Fred R T

2018-01-01

Over the past decade, phenotypes have been used to help categorize knee osteoarthritis patients relative to being subject to disease, disease progression, and treatment response. A review of potential phenotype selection is now appropriate. The appeal of using phenotypes is that they most rely on simple physical examination, clinically routine imaging, and demographics. The purpose of this review is to describe the panoply of phenotypes that can be potentially used in osteoarthritis research. A search of PubMed was used singularly to review the literature on knee osteoarthritis phenotypes. Four phenotype assembly groups were based on physical features and noninvasive imaging. Demographics included metabolic syndrome (dyslipidemia, hypertension, obesity, and diabetes). Mechanical characteristics included joint morphology, alignment, the effect of injury, and past and present history. Associated musculoskeletal disorder characteristics included multiple joint involvement, spine disorders, neuromuscular diseases, and osteoporosis. With the knee as an organ, tissue characteristics were used to focus on synovium, meniscus, articular cartilage, patella fat pad, bone sclerosis, bone cysts, and location of pain. Many of these phenotype clusters require further validation studies. There is special emphasis on knee osteoarthritis phenotypes due to its predominance in osteoarthritic disorders and the variety of tissues in that joint. More research will be required to determine the most productive phenotypes for future studies. The selection and assignment of phenotypes will take on an increasing role in osteoarthritis research in the future.

2007 Joint Chemical Biological, Radiological and Nuclear (CBRN) Conference and Exhibition - Combating Weapons of Mass Destruction

DTIC Science & Technology

2007-06-27

Selected CB Defense Systems SHAPESENSE Joint Warning and Reporting Network JSLIST CB Protected Shelter Joint Vaccine Acquisition Program Joint Effects...military can operate in any environment, unconstrained by chemical or biological weapons. 21 SHIELD SUSTAIN Selected CB Defense Systems SHAPESENSE Joint...28070625_JCBRN_Conference_Reeves UNCLASSIFIED Decontamination Vision Strippable Barriers Self-Decontaminating Fabrics/Coatings Reduce Logistics Burden

Classification of Partial Discharge Measured under Different Levels of Noise Contamination.

PubMed

Jee Keen Raymond, Wong; Illias, Hazlee Azil; Abu Bakar, Ab Halim

2017-01-01

Cable joint insulation breakdown may cause a huge loss to power companies. Therefore, it is vital to diagnose the insulation quality to detect early signs of insulation failure. It is well known that there is a correlation between Partial discharge (PD) and the insulation quality. Although many works have been done on PD pattern recognition, it is usually performed in a noise free environment. Also, works on PD pattern recognition in actual cable joint are less likely to be found in literature. Therefore, in this work, classifications of actual cable joint defect types from partial discharge data contaminated by noise were performed. Five cross-linked polyethylene (XLPE) cable joints with artificially created defects were prepared based on the defects commonly encountered on site. Three different types of input feature were extracted from the PD pattern under artificially created noisy environment. These include statistical features, fractal features and principal component analysis (PCA) features. These input features were used to train the classifiers to classify each PD defect types. Classifications were performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM). It was found that the classification accuracy decreases with higher noise level but PCA features used in SVM and ANN showed the strongest tolerance against noise contamination.

Joint association discovery and diagnosis of Alzheimer's disease by supervised heterogeneous multiview learning.

PubMed

Zhe, Shandian; Xu, Zenglin; Qi, Yuan; Yu, Peng

2014-01-01

A key step for Alzheimer's disease (AD) study is to identify associations between genetic variations and intermediate phenotypes (e.g., brain structures). At the same time, it is crucial to develop a noninvasive means for AD diagnosis. Although these two tasks-association discovery and disease diagnosis-have been treated separately by a variety of approaches, they are tightly coupled due to their common biological basis. We hypothesize that the two tasks can potentially benefit each other by a joint analysis, because (i) the association study discovers correlated biomarkers from different data sources, which may help improve diagnosis accuracy, and (ii) the disease status may help identify disease-sensitive associations between genetic variations and MRI features. Based on this hypothesis, we present a new sparse Bayesian approach for joint association study and disease diagnosis. In this approach, common latent features are extracted from different data sources based on sparse projection matrices and used to predict multiple disease severity levels based on Gaussian process ordinal regression; in return, the disease status is used to guide the discovery of relationships between the data sources. The sparse projection matrices not only reveal the associations but also select groups of biomarkers related to AD. To learn the model from data, we develop an efficient variational expectation maximization algorithm. Simulation results demonstrate that our approach achieves higher accuracy in both predicting ordinal labels and discovering associations between data sources than alternative methods. We apply our approach to an imaging genetics dataset of AD. Our joint analysis approach not only identifies meaningful and interesting associations between genetic variations, brain structures, and AD status, but also achieves significantly higher accuracy for predicting ordinal AD stages than the competing methods.

Aging changes in the bones - muscles - joints

MedlinePlus

... ency/article/004015.htm Aging changes in the bones - muscles - joints To use the sharing features on ... to the body. Joints are the areas where bones come together. They allow the skeleton to be ...

Analysis and application of ERTS-1 data for regional geological mapping

NASA Technical Reports Server (NTRS)

Gold, D. P.; Parizek, R. R.; Alexander, S. A.

1973-01-01

Combined visual and digital techniques of analysing ERTS-1 data for geologic information have been tried on selected areas in Pennsylvania. The major physiolographic and structural provinces show up well. Supervised mapping, following the imaged expression of known geologic features on ERTS band 5 enlargements (1:250,000) of parts of eastern Pennsylvania, delimited the Diabase Sills and the Precambrian rocks of the Reading Prong with remarkable accuracy. From unsupervised mapping, transgressive linear features are apparent in unexpected density, and exhibit strong control over river valley and stream channel directions. They are unaffected by bedrock type, age, or primary structural boundaries, which suggests they are either rejuvenated basement joint directions on different scales, or they are a recently impressed structure possibly associated with a drifting North American plate. With ground mapping and underflight data, 6 scales of linear features have been recognized.

Post-Traumatic Osteoarthritis in Mice Following Mechanical Injury to the Synovial Joint

PubMed Central

Rai, Muhammad Farooq; Duan, Xin; Quirk, James D.; Holguin, Nilsson; Schmidt, Eric J.; Chinzei, Nobuaki; Silva, Matthew J.; Sandell, Linda J.

2017-01-01

We investigated the spectrum of lesions characteristic of post-traumatic osteoarthritis (PTOA) across the knee joint in response to mechanical injury. We hypothesized that alteration in knee joint stability in mice reproduces molecular and structural features of PTOA that would suggest potential therapeutic targets in humans. The right knees of eight-week old male mice from two recombinant inbred lines (LGXSM-6 and LGXSM-33) were subjected to axial tibial compression. Three separate loading magnitudes were applied: 6N, 9N, and 12N. Left knees served as non-loaded controls. Mice were sacrificed at 5, 9, 14, 28, and 56 days post-loading and whole knee joint changes were assessed by histology, immunostaining, micro-CT, and magnetic resonance imaging. We observed that tibial compression disrupted joint stability by rupturing the anterior cruciate ligament (except for 6N) and instigated a cascade of temporal and topographical features of PTOA. These features included cartilage extracellular matrix loss without proteoglycan replacement, chondrocyte apoptosis at day 5, synovitis present at day 14, osteophytes, ectopic calcification, and meniscus pathology. These findings provide a plausible model and a whole-joint approach for how joint injury in humans leads to PTOA. Chondrocyte apoptosis, synovitis, and ectopic calcification appear to be targets for potential therapeutic intervention. PMID:28345597

Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Hanson, Andrea; Reed, Erik; Cavanagh, Peter

2011-01-01

Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

Parallel elastic elements improve energy efficiency on the STEPPR bipedal walking robot

DOE PAGES

Mazumdar, Anirban; Spencer, Steven J.; Hobart, Clinton; ...

2016-11-23

This study describes how parallel elastic elements can be used to reduce energy consumption in the electric motor driven, fully-actuated, STEPPR bipedal walking robot without compromising or significantly limiting locomotive behaviors. A physically motivated approach is used to illustrate how selectively-engaging springs for hip adduction and ankle flexion predict benefits for three different flat ground walking gaits: human walking, human-like robot walking and crouched robot walking. Based on locomotion data, springs are designed and substantial reductions in power consumption are demonstrated using a bench dynamometer. These lessons are then applied to STEPPR (Sandia Transmission-Efficient Prototype Promoting Research), a fully actuatedmore » bipedal robot designed to explore the impact of tailored joint mechanisms on walking efficiency. Featuring high-torque brushless DC motors, efficient low-ratio transmissions, and high fidelity torque control, STEPPR provides the ability to incorporate novel joint-level mechanisms without dramatically altering high level control. Unique parallel elastic designs are incorporated into STEPPR, and walking data shows that hip adduction and ankle flexion springs significantly reduce the required actuator energy at those joints for several gaits. These results suggest that parallel joint springs offer a promising means of supporting quasi-static joint torques due to body mass during walking, relieving motors of the need to support these torques and substantially improving locomotive energy efficiency.« less

Parallel elastic elements improve energy efficiency on the STEPPR bipedal walking robot

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mazumdar, Anirban; Spencer, Steven J.; Hobart, Clinton

This study describes how parallel elastic elements can be used to reduce energy consumption in the electric motor driven, fully-actuated, STEPPR bipedal walking robot without compromising or significantly limiting locomotive behaviors. A physically motivated approach is used to illustrate how selectively-engaging springs for hip adduction and ankle flexion predict benefits for three different flat ground walking gaits: human walking, human-like robot walking and crouched robot walking. Based on locomotion data, springs are designed and substantial reductions in power consumption are demonstrated using a bench dynamometer. These lessons are then applied to STEPPR (Sandia Transmission-Efficient Prototype Promoting Research), a fully actuatedmore » bipedal robot designed to explore the impact of tailored joint mechanisms on walking efficiency. Featuring high-torque brushless DC motors, efficient low-ratio transmissions, and high fidelity torque control, STEPPR provides the ability to incorporate novel joint-level mechanisms without dramatically altering high level control. Unique parallel elastic designs are incorporated into STEPPR, and walking data shows that hip adduction and ankle flexion springs significantly reduce the required actuator energy at those joints for several gaits. These results suggest that parallel joint springs offer a promising means of supporting quasi-static joint torques due to body mass during walking, relieving motors of the need to support these torques and substantially improving locomotive energy efficiency.« less

Joint involvement in systemic lupus erythematosus: From pathogenesis to clinical assessment.

PubMed

Ceccarelli, Fulvia; Perricone, Carlo; Cipriano, Enrica; Massaro, Laura; Natalucci, Francesco; Capalbo, Giuseppe; Leccese, Ilaria; Bogdanos, Dimitrios; Spinelli, Francesca Romana; Alessandri, Cristiano; Valesini, Guido; Conti, Fabrizio

2017-08-01

In the present review, the different phenotypes, clinimetric and imaging tools able to assess joint involvement in patients affected by Systemic Lupus Erythematosus (SLE) have been described and summarized. Furthermore, the current knowledge about the pathogenic mechanism and the potential biomarkers of this feature is reported. A literature search was done in PubMed, accessed via the National Library of Medicine PubMed interface (http://www.ncbi.nlm.nih.gov/pubmed). Firstly, PubMed was searched using the term "systemic lupus erythematosus" OR "lupus" in combination with (AND) "joint" OR "articular".Secondly, the same PubMed research was combined with other terms, such as "pathogenesis" OR "genetic" OR "antibodies" OR "biomarkers" OR "cytokines" OR "imaging" OR "ultrasonography" OR "magnetic resonance" OR "clinimetry". After a stringent selection, we evaluated in the present review 13 papers concerning clinical phenotypes of SLE joint involvement, 14 concerning clinimetric assessment, 20 concerning imaging, and finally, 28 concerning pathogenesis and biomarkers. Further relevant data were obtained from the reference lists of articles returned using these search terms and from authors own experience and knowledge of the literature. Despite the prevalence and severity of SLE joint involvement, more awareness and a deeper evaluation of the clinical heterogeneity of this manifestation are mandatory. Moreover, longitudinal studies are needed to assess the progression of this manifestation and to provide standard definitions and examination/recording protocols. Copyright © 2017 Elsevier Inc. All rights reserved.

Feature Screening in Ultrahigh Dimensional Cox's Model.

PubMed

Yang, Guangren; Yu, Ye; Li, Runze; Buu, Anne

Survival data with ultrahigh dimensional covariates such as genetic markers have been collected in medical studies and other fields. In this work, we propose a feature screening procedure for the Cox model with ultrahigh dimensional covariates. The proposed procedure is distinguished from the existing sure independence screening (SIS) procedures (Fan, Feng and Wu, 2010, Zhao and Li, 2012) in that the proposed procedure is based on joint likelihood of potential active predictors, and therefore is not a marginal screening procedure. The proposed procedure can effectively identify active predictors that are jointly dependent but marginally independent of the response without performing an iterative procedure. We develop a computationally effective algorithm to carry out the proposed procedure and establish the ascent property of the proposed algorithm. We further prove that the proposed procedure possesses the sure screening property. That is, with the probability tending to one, the selected variable set includes the actual active predictors. We conduct Monte Carlo simulation to evaluate the finite sample performance of the proposed procedure and further compare the proposed procedure and existing SIS procedures. The proposed methodology is also demonstrated through an empirical analysis of a real data example.

Physiological asymmetry of trunk ranging and pelvis motility: an anatomo-functional study in 80 healthy subjects.

PubMed

Macchi, Claudio; Biricolti, Claudia; Cappelli, Lorenza; Galli, Francesca; Molino-Lova, Raffaele; Cecchi, Francesca; Corigliano, Alvaro; Miniati, Benedetta; Conti, Andrea A; Gulisano, Massimo; Catini, Claudio; Gensini, Gian Franco

2002-01-01

A key feature in physiotherapeutic treatment of patients with motion disturbances is the appropriate ranging of the trunk and pelvis motility. Eighty subjects randomly selected and free from known pathology of the muscular-skeletal and/or of the neurological system classed into four groups according to the age and the sex have been assessed, by using a new, simple and easy administrable tool. Our results demonstrate that the new measurement tool showed a very low intra- and inter-observer variability, that healthy subjects showed a more adduced and elevated right scapula if compared to the contralateral one and, as regard as the pelvic motion, a broader joint excursion in passive motion compared with active motion in the overall group, a broader joint excursion in young subjects compared with elderly ones, and a broader joint excursion in female subjects compared with males subjects. In conclusion our study allowed to identify a range of physiological asymmetry and pelvis motility. Such a range of physiological asymmetry might be useful as a reference for the physiotherapists.

Joint and collaborative representation with local Volterra kernels convolution feature for face recognition

NASA Astrophysics Data System (ADS)

Feng, Guang; Li, Hengjian; Dong, Jiwen; Chen, Xi; Yang, Huiru

2018-04-01

In this paper, we proposed a joint and collaborative representation with Volterra kernel convolution feature (JCRVK) for face recognition. Firstly, the candidate face images are divided into sub-blocks in the equal size. The blocks are extracted feature using the two-dimensional Voltera kernels discriminant analysis, which can better capture the discrimination information from the different faces. Next, the proposed joint and collaborative representation is employed to optimize and classify the local Volterra kernels features (JCR-VK) individually. JCR-VK is very efficiently for its implementation only depending on matrix multiplication. Finally, recognition is completed by using the majority voting principle. Extensive experiments on the Extended Yale B and AR face databases are conducted, and the results show that the proposed approach can outperform other recently presented similar dictionary algorithms on recognition accuracy.

Exploiting Acoustic and Syntactic Features for Automatic Prosody Labeling in a Maximum Entropy Framework

PubMed Central

Sridhar, Vivek Kumar Rangarajan; Bangalore, Srinivas; Narayanan, Shrikanth S.

2009-01-01

In this paper, we describe a maximum entropy-based automatic prosody labeling framework that exploits both language and speech information. We apply the proposed framework to both prominence and phrase structure detection within the Tones and Break Indices (ToBI) annotation scheme. Our framework utilizes novel syntactic features in the form of supertags and a quantized acoustic–prosodic feature representation that is similar to linear parameterizations of the prosodic contour. The proposed model is trained discriminatively and is robust in the selection of appropriate features for the task of prosody detection. The proposed maximum entropy acoustic–syntactic model achieves pitch accent and boundary tone detection accuracies of 86.0% and 93.1% on the Boston University Radio News corpus, and, 79.8% and 90.3% on the Boston Directions corpus. The phrase structure detection through prosodic break index labeling provides accuracies of 84% and 87% on the two corpora, respectively. The reported results are significantly better than previously reported results and demonstrate the strength of maximum entropy model in jointly modeling simple lexical, syntactic, and acoustic features for automatic prosody labeling. PMID:19603083

Joint Applied Optics and Chinese Optics Letters feature introduction: digital holography and three-dimensional imaging.

PubMed

Poon, Ting-Chung

2011-12-01

This feature issue serves as a pilot issue promoting the joint issue of Applied Optics and Chinese Optics Letters. It focuses upon topics of current relevance to the community working in the area of digital holography and 3-D imaging. © 2011 Optical Society of America

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities

NASA Astrophysics Data System (ADS)

Vallières, M.; Freeman, C. R.; Skamene, S. R.; El Naqa, I.

2015-07-01

This study aims at developing a joint FDG-PET and MRI texture-based model for the early evaluation of lung metastasis risk in soft-tissue sarcomas (STSs). We investigate if the creation of new composite textures from the combination of FDG-PET and MR imaging information could better identify aggressive tumours. Towards this goal, a cohort of 51 patients with histologically proven STSs of the extremities was retrospectively evaluated. All patients had pre-treatment FDG-PET and MRI scans comprised of T1-weighted and T2-weighted fat-suppression sequences (T2FS). Nine non-texture features (SUV metrics and shape features) and forty-one texture features were extracted from the tumour region of separate (FDG-PET, T1 and T2FS) and fused (FDG-PET/T1 and FDG-PET/T2FS) scans. Volume fusion of the FDG-PET and MRI scans was implemented using the wavelet transform. The influence of six different extraction parameters on the predictive value of textures was investigated. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved imbalance-adjusted bootstrap resampling in the following four steps leading to final prediction model construction: (1) feature set reduction; (2) feature selection; (3) prediction performance estimation; and (4) computation of model coefficients. Univariate analysis showed that the isotropic voxel size at which texture features were extracted had the most impact on predictive value. In multivariable analysis, texture features extracted from fused scans significantly outperformed those from separate scans in terms of lung metastases prediction estimates. The best performance was obtained using a combination of four texture features extracted from FDG-PET/T1 and FDG-PET/T2FS scans. This model reached an area under the receiver-operating characteristic curve of 0.984 ± 0.002, a sensitivity of 0.955 ± 0.006, and a specificity of 0.926 ± 0.004 in bootstrapping evaluations. Ultimately, lung metastasis risk assessment at diagnosis of STSs could improve patient outcomes by allowing better treatment adaptation.

Spectrum of mucocutaneous manifestations in 277 patients with joint hypermobility syndrome/Ehlers-Danlos syndrome, hypermobility type.

PubMed

Castori, Marco; Dordoni, Chiara; Morlino, Silvia; Sperduti, Isabella; Ritelli, Marco; Valiante, Michele; Chiarelli, Nicola; Zanca, Arianna; Celletti, Claudia; Venturini, Marina; Camerota, Filippo; Calzavara-Pinton, Piergiacomo; Grammatico, Paola; Colombi, Marina

2015-03-01

Cutaneous manifestations are a diagnostic criterion of Ehlers-Danlos syndrome, hypermobility type (EDS-HT) and joint hypermobility syndrome (JHS). These two conditions, originally considered different disorders, are now accepted as clinically indistinguishable and often segregate as a single-familial trait. EDS-HT and JHS are still exclusion diagnoses not supported by any specific laboratory test. Accuracy of clinical diagnosis is, therefore, crucial for appropriate patients' classification and management, but it is actually hampered by the low consistency of many applied criteria including the cutaneous one. We report on mucocutaneous findings in 277 patients with JHS/EDS-HT with both sexes and various ages. Sixteen objective and five anamnestic items were selected and ascertained in two specialized outpatient clinics. Feature rates were compared by sex and age by a series of statistical tools. Data were also used for a multivariate correspondence analysis with the attempt to identify non-causal associations of features depicting recognizable phenotypic clusters. Our findings identified a few differences between sexes and thus indicated an attenuated sexual dimorphism for mucocutaneous features in JHS/EDS-HT. Ten features showed significantly distinct rates at different ages and this evidence corroborated the concept of an evolving phenotype in JHS/EDS-HT also affecting the skin. Multivariate correspondence analysis identified three relatively discrete phenotypic profiles, which may represent the cutaneous counterparts of the three disease phases previously proposed for JHS/EDS-HT. These findings could be used for revising the cutaneous criterion in a future consensus for the clinical diagnosis of JHS/EDS-HT. © 2015 Wiley Periodicals, Inc.

Classification of Partial Discharge Measured under Different Levels of Noise Contamination

PubMed Central

2017-01-01

Cable joint insulation breakdown may cause a huge loss to power companies. Therefore, it is vital to diagnose the insulation quality to detect early signs of insulation failure. It is well known that there is a correlation between Partial discharge (PD) and the insulation quality. Although many works have been done on PD pattern recognition, it is usually performed in a noise free environment. Also, works on PD pattern recognition in actual cable joint are less likely to be found in literature. Therefore, in this work, classifications of actual cable joint defect types from partial discharge data contaminated by noise were performed. Five cross-linked polyethylene (XLPE) cable joints with artificially created defects were prepared based on the defects commonly encountered on site. Three different types of input feature were extracted from the PD pattern under artificially created noisy environment. These include statistical features, fractal features and principal component analysis (PCA) features. These input features were used to train the classifiers to classify each PD defect types. Classifications were performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM). It was found that the classification accuracy decreases with higher noise level but PCA features used in SVM and ANN showed the strongest tolerance against noise contamination. PMID:28085953

Objective evaluation of female feet and leg joint conformation at time of selection and post first parity in swine.

PubMed

Stock, J D; Calderón Díaz, J A; Rothschild, M F; Mote, B E; Stalder, K J

2018-06-09

Feet and legs of replacement females were objectively evaluated at selection, i.e. approximately 150 days of age (n=319) and post first parity, i.e. any time after weaning of first litter and before 2nd parturition (n=277) to 1) compare feet and leg joint angle ranges between selection and post first parity; 2) identify feet and leg joint angle differences between selection and first three weeks of second gestation; 3) identify feet and leg join angle differences between farms and gestation days during second gestation; and 4) obtain genetic variance components for conformation angles for the two time points measured. Angles for carpal joint (knee), metacarpophalangeal joint (front pastern), metatarsophalangeal joint (rear pastern), tarsal joint (hock), and rear stance were measured using image analysis software. Between selection and post first parity significant differences were observed for all joints measured (P < 0.05). Knee, front and rear pastern angles were less (more flexion), and hock angles were greater (less flexion) as age progressed (P < 0.05), while the rear stance pattern was less (feet further under center) at selection than post first parity (only including measures during first three weeks of second gestation). Only using post first parity leg conformation information, farm was a significant source of variation for front and rear pasterns and rear stance angle measurements (P < 0.05). Knee angle was less (more flexion) (P < 0.05) as gestation age progressed. Heritability estimates were low to moderate (0.04 - 0.35) for all traits measured across time points. Genetic correlations between the same joints at different time points were high (> 0.8) between the front leg joints and low (<0.2) between the rear leg joints. High genetic correlations between time points indicate that the trait can be considered the same at either time point, and low genetic correlations indicate that the trait at different time points should be considered as two separate traits. Minimal change in the front leg suggests conformation traits that remain between selection and post first parity, while larger changes in rear leg indicate that rear leg conformation traits should be evaluated at multiple time periods.

Joint Patch and Multi-label Learning for Facial Action Unit Detection

PubMed Central

Zhao, Kaili; Chu, Wen-Sheng; De la Torre, Fernando; Cohn, Jeffrey F.; Zhang, Honggang

2016-01-01

The face is one of the most powerful channel of nonverbal communication. The most commonly used taxonomy to describe facial behaviour is the Facial Action Coding System (FACS). FACS segments the visible effects of facial muscle activation into 30+ action units (AUs). AUs, which may occur alone and in thousands of combinations, can describe nearly all-possible facial expressions. Most existing methods for automatic AU detection treat the problem using one-vs-all classifiers and fail to exploit dependencies among AU and facial features. We introduce joint-patch and multi-label learning (JPML) to address these issues. JPML leverages group sparsity by selecting a sparse subset of facial patches while learning a multi-label classifier. In four of five comparisons on three diverse datasets, CK+, GFT, and BP4D, JPML produced the highest average F1 scores in comparison with state-of-the art. PMID:27382243

Severity mapping of the proximal femur: a new method for assessing hip osteoarthritis with computed tomography.

PubMed

Turmezei, T D; Lomas, D J; Hopper, M A; Poole, K E S

2014-10-01

Plain radiography has been the mainstay of imaging assessment in osteoarthritis for over 50 years, but it does have limitations. Here we present the methodology and results of a new technique for identifying, grading, and mapping the severity and spatial distribution of osteoarthritic disease features at the hip in 3D with clinical computed tomography (CT). CT imaging of 456 hips from 230 adult female volunteers (mean age 66 ± 17 years) was reviewed using 3D multiplanar reformatting to identify bone-related radiological features of osteoarthritis, namely osteophytes, subchondral cysts and joint space narrowing. Scoresheets dividing up the femoral head, head-neck region and the joint space were used to register the location and severity of each feature (scored from 0 to 3). Novel 3D cumulative feature severity maps were then created to display where the most severe disease features from each individual were anatomically located across the cohort. Feature severity maps showed a propensity for osteophytes at the inferoposterior and superolateral femoral head-neck junction. Subchondral cysts were a less common and less localised phenomenon. Joint space narrowing <1.5 mm was recorded in at least one sector of 83% of hips, but most frequently in the posterolateral joint space. This is the first description of hip osteoarthritis using unenhanced clinical CT in which we describe the co-localisation of posterior osteophytes and joint space narrowing for the first time. We believe this technique can perform several important roles in future osteoarthritis research, including phenotyping and sensitive disease assessment in 3D. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Imaging diagnosis--temporomandibular joint dysplasia in a Basset Hound.

PubMed

Lerer, Assaf; Chalmers, Heather J; Moens, Noel M M; Mackenzie, Shawn D; Kry, Kristin

2014-01-01

A 5-month-old intact male Basset Hound presented for evaluation of pain and crepitation during manipulation of the temporomandibular joint, worse on the right side. A computed tomography (CT) scan of the head was performed. The CT images demonstrated the osseous features of temporomandibular joint dysplasia and facilitated a 3D reconstruction, which allowed better visualization of the dysplastic features. The patient responded to conservative management with a tape muzzle with no recurrence reported by the owner 6 months after presentation. © 2013 American College of Veterinary Radiology.

Rehabilitation of jointed Portland cement concrete pavements : SPS-6--initial evaluation and analysis

DOT National Transportation Integrated Search

2005-10-01

The Specific Pavement Studies 6 (SPS-6) experiment, "Rehabilitation of Jointed Portland Cement Concrete Pavements," was designed as a controlled field experiment that focuses on the study of specific rehabilitation design features of jointed plain co...

Haemorrhoids and joint hypermobility: a new extra-articular association.

PubMed

Yousif, Uqba N; Bird, Howard A

2013-04-01

An association has been demonstrated between haemorrhoids and joint hypermobility. Reasons for this are discussed. Many performing artists are hypermobile and the extra-articular features of joint hypermobility should not be forgotten or underestimated as a potential constraint upon performance.

Inferring the Mode of Selection from the Transient Response to Demographic Perturbations

NASA Astrophysics Data System (ADS)

Balick, Daniel; Do, Ron; Reich, David; Sunyaev, Shamil

2014-03-01

Despite substantial recent progress in theoretical population genetics, most models work under the assumption of a constant population size. Deviations from fixed population sizes are ubiquitous in natural populations, many of which experience population bottlenecks and re-expansions. The non-equilibrium dynamics introduced by a large perturbation in population size are generally viewed as a confounding factor. In the present work, we take advantage of the transient response to a population bottleneck to infer features of the mode of selection and the distribution of selective effects. We develop an analytic framework and a corresponding statistical test that qualitatively differentiates between alleles under additive and those under recessive or more general epistatic selection. This statistic can be used to bound the joint distribution of selective effects and dominance effects in any diploid sexual organism. We apply this technique to human population genetic data, and severely restrict the space of allowed selective coefficients in humans. Additionally, one can test a set of functionally or medically relevant alleles for the primary mode of selection, or determine the local regional variation in dominance coefficients along the genome.

Dichotomous versus semi-quantitative scoring of ultrasound joint inflammation in rheumatoid arthritis using novel individualized joint selection methods.

PubMed

Tan, York Kiat; Allen, John C; Lye, Weng Kit; Conaghan, Philip G; Chew, Li-Ching; Thumboo, Julian

2017-05-01

The aim of the study is to compare the responsiveness of two joint inflammation scoring systems (dichotomous scoring (DS) versus semi-quantitative scoring (SQS)) using novel individualized ultrasound joint selection methods and existing ultrasound joint selection methods. Responsiveness measured by the standardized response means (SRMs) using the DS and the SQS system (for both the novel and existing ultrasound joint selection methods) was derived using the baseline and the 3-month total inflammatory scores from 20 rheumatoid arthritis patients. The relative SRM gain ratios (SRM-Gains) for both scoring system (DS and SQS) comparing the novel to the existing methods were computed. Both scoring systems (DS and SQS) demonstrated substantial SRM-Gains (ranged from 3.31 to 5.67 for the DS system and ranged from 1.82 to 3.26 for the SQS system). The SRMs using the novel methods ranged from 0.94 to 1.36 for the DS system and ranged from 0.89 to 1.11 for the SQS system. The SRMs using the existing methods ranged from 0.24 to 0.32 for the DS system and ranged from 0.34 to 0.49 for the SQS system. The DS system appears to achieve high responsiveness comparable to SQS for the novel individualized ultrasound joint selection methods.

Are ultrasound features at the first metatarsophalangeal joint associated with clinically-assessed pain and function? A study of people with gout, asymptomatic hyperuricaemia and normouricaemia.

PubMed

Stewart, Sarah; Dalbeth, Nicola; Vandal, Alain C; Allen, Bruce; Miranda, Rhian; Rome, Keith

2017-01-01

The first metatatarsophalangeal joint (1st MTP joint) is a common location for sonographic evidence of urate deposition in people with gout and asymptomatic hyperuricaemia. However, it is unclear whether these are related to clinically-assessed pain and function. This study aimed to determine the association between ultrasound features and clinical characteristics of the 1st MTP joint in people with gout, asymptomatic hyperuricaemia and age- and sex-matched normouricaemic individuals. Twenty-three people with gout, 29 with asymptomatic hyperuricaemia and 34 with normouricaemia participated in a cross-sectional study. No participant had clinical evidence of acute inflammatory arthritis at the time of assessment. Four sonographic features at the 1st MTP joint were analysed: double contour sign, tophus, bone erosion and synovitis. Clinical characteristics included in the analysis were 1st MTP joint pain, overall foot pain and disability, 1st MTP joint temperature, 1st MTP joint range of motion and gait velocity. Statistical analyses adjusted for the diagnostic group of the participant. After accounting for the diagnostic group, double contour sign was associated with higher foot pain and disability scores ( P  < 0.001). Ultrasound tophus was associated with higher foot pain and disability scores ( P  < 0.001), increased temperature ( P  = 0.005), and reduced walking velocity ( P  = 0.001). No associations were observed between ultrasound synovitis or erosion and the clinical characteristics. Ultrasound features of urate crystal deposition, rather than soft tissue inflammation or bone erosion, are associated with clinical measures of foot-related functional impairment and disability even in the absence of clinical evidence of current acute inflammatory arthritis. This association persisted regardless of the diagnosis of the participant as having gout or asymptomatic hyperuricaemia.

Qualification of the RSRM field joint CF case-to-insulation bondline inspection using the Thiokol Corporation ultrasonic RSRM bondline inspection system

NASA Technical Reports Server (NTRS)

Cook, M.

1990-01-01

Qualification testing of Combustion Engineering's AMDATA Intraspect/98 Data Acquisition and Imaging System that applies to the redesigned solid rocket motor field joint capture feature case-to-insulation bondline inspection was performed. Testing was performed at M-111, the Thiokol Corp. Inert Parts Preparation Building. The purpose of the inspection was to verify the integrity of the capture feature area case-to-insulation bondline. The capture feature scanner was calibrated over an intentional 1.0 to 1.0 in. case-to-insulation unbond. The capture feature scanner was then used to scan 60 deg of a capture feature field joint. Calibration of the capture feature scanner was then rechecked over the intentional unbond to ensure that the calibration settings did not change during the case scan. This procedure was successfully performed five times to qualify the unbond detection capability of the capture feature scanner. The capture feature scanner qualified in this test contains many points of mechanical instability that can affect the overall ultrasonic signal response. A new generation scanner, designated the sigma scanner, should be implemented to replace the current configuration scanner. The sigma scanner eliminates the unstable connection points of the current scanner and has additional inspection capabilities.

Haemochromatosis: unexplained metacarpophalangeal or ankle arthropathy should prompt diagnostic tests: findings from two UK observational cohort studies.

PubMed

Richardson, A; Prideaux, A; Kiely, P

2017-01-01

To examine demographic and clinical features leading to the diagnosis of hereditary haemochromatosis and assess factors that might enhance earlier diagnosis, with particular attention to arthritic symptoms. Diagnostic features were captured directly from patients with haemochromatosis attending a specialist rheumatology clinic (group 1) and from analysis of a specifically designed questionnaire circulated to members of the UK Haemochromatosis Society (group 2). In groups 1 (n = 62) and 2 (n = 470), respectively, the diagnosis of haemochromatosis was made at a mean age of 52.8 and 56.4 years with 77% and 76% reporting joint symptoms with a mean duration of 8.3 and 8.1 years. The first joints to be affected in group 1 were the metacarpophalangeal (MCP; 38.5%) and ankle (29.5%) followed by the knee, hip, and proximal interphalangeal (PIP) joints. At the time of clinical assessment or questionnaire completion, the most prevalent regions with arthropathy in group 1 were PIP (64.5%), knee (64%), ankle (61%), and MCP (60%) and in group 2 the most prevalent joint regions self-reported were the first carpometacarpal (CMC; 59%), wrist (52%), PIP (47%), MCP (46%), knee (42%), and ankle (35%). Data from both cohorts confirm the high prevalence of joint symptoms in haemochromatosis predating the diagnosis by many years. Discriminatory features of the arthropathy include the involvement of MCP joints and ankles at a relatively young age in the absence of trauma, all of which are unusual features of primary osteoarthritis (OA). The finding of this presentation should prompt diagnostic tests for haemochromatosis.

Real-time ultrasound image classification for spine anesthesia using local directional Hadamard features.

PubMed

Pesteie, Mehran; Abolmaesumi, Purang; Ashab, Hussam Al-Deen; Lessoway, Victoria A; Massey, Simon; Gunka, Vit; Rohling, Robert N

2015-06-01

Injection therapy is a commonly used solution for back pain management. This procedure typically involves percutaneous insertion of a needle between or around the vertebrae, to deliver anesthetics near nerve bundles. Most frequently, spinal injections are performed either blindly using palpation or under the guidance of fluoroscopy or computed tomography. Recently, due to the drawbacks of the ionizing radiation of such imaging modalities, there has been a growing interest in using ultrasound imaging as an alternative. However, the complex spinal anatomy with different wave-like structures, affected by speckle noise, makes the accurate identification of the appropriate injection plane difficult. The aim of this study was to propose an automated system that can identify the optimal plane for epidural steroid injections and facet joint injections. A multi-scale and multi-directional feature extraction system to provide automated identification of the appropriate plane is proposed. Local Hadamard coefficients are obtained using the sequency-ordered Hadamard transform at multiple scales. Directional features are extracted from local coefficients which correspond to different regions in the ultrasound images. An artificial neural network is trained based on the local directional Hadamard features for classification. The proposed method yields distinctive features for classification which successfully classified 1032 images out of 1090 for epidural steroid injection and 990 images out of 1052 for facet joint injection. In order to validate the proposed method, a leave-one-out cross-validation was performed. The average classification accuracy for leave-one-out validation was 94 % for epidural and 90 % for facet joint targets. Also, the feature extraction time for the proposed method was 20 ms for a native 2D ultrasound image. A real-time machine learning system based on the local directional Hadamard features extracted by the sequency-ordered Hadamard transform for detecting the laminae and facet joints in ultrasound images has been proposed. The system has the potential to assist the anesthesiologists in quickly finding the target plane for epidural steroid injections and facet joint injections.

Fukunaga-Koontz feature transformation for statistical structural damage detection and hierarchical neuro-fuzzy damage localisation

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2017-07-01

Considering jointly damage sensitive features (DSFs) of signals recorded by multiple sensors, applying advanced transformations to these DSFs and assessing systematically their contribution to damage detectability and localisation can significantly enhance the performance of structural health monitoring systems. This philosophy is explored here for partial autocorrelation coefficients (PACCs) of acceleration responses. They are interrogated with the help of the linear discriminant analysis based on the Fukunaga-Koontz transformation using datasets of the healthy and selected reference damage states. Then, a simple but efficient fast forward selection procedure is applied to rank the DSF components with respect to statistical distance measures specialised for either damage detection or localisation. For the damage detection task, the optimal feature subsets are identified based on the statistical hypothesis testing. For damage localisation, a hierarchical neuro-fuzzy tool is developed that uses the DSF ranking to establish its own optimal architecture. The proposed approaches are evaluated experimentally on data from non-destructively simulated damage in a laboratory scale wind turbine blade. The results support our claim of being able to enhance damage detectability and localisation performance by transforming and optimally selecting DSFs. It is demonstrated that the optimally selected PACCs from multiple sensors or their Fukunaga-Koontz transformed versions can not only improve the detectability of damage via statistical hypothesis testing but also increase the accuracy of damage localisation when used as inputs into a hierarchical neuro-fuzzy network. Furthermore, the computational effort of employing these advanced soft computing models for damage localisation can be significantly reduced by using transformed DSFs.

Extension joints: a tool to infer the active stress field orientation (case study from southern Italy)

NASA Astrophysics Data System (ADS)

De Guidi, Giorgio; Caputo, Riccardo; Scudero, Salvatore; Perdicaro, Vincenzo

2013-04-01

An intense tectonic activity in eastern Sicily and southern Calabria is well documented by the differential uplift of Late Quaternary coastlines and by the record of the strong historical earthquakes. The extensional belt that crosses this area is dominated by a well established WNW-ESE-oriented extensional direction. However, this area is largely lacking of any structural analysis able to define the tectonics at a more local scale. In the attempt to fill this gap of knowledge, we carried out a systematic analysis of extension joint sets. In fact, the systematic field collection of these extensional features, coupled with an appropriate inversion technique, allows to determine the characteristic of the causative tectonic stress field. Joints are defined as outcrop-scale mechanical discontinuities showing no evidence of shear motion and being originated as purely extensional fractures. Such tectonic features are one of the most common deformational structures in every tectonic environment and particularly abundant in the study area. A particular arrangement of joints, called "fracture grid-lock system", and defined as an orthogonal joint system where mutual abutting and crosscutting relationships characterize two geologically coeval joint sets, allow to infer the direction and the magnitude of the tectonic stress field. We performed the analyses of joints only on Pleistocene deposits of Eastern Sicily and Southern Calabria. Moreover we investigated only calcarenite sediments and cemented deposits, avoiding claysh and loose matrix-supported clastic sediments where the deformation is generally accomodated in a distributed way through the relative motion between the single particles. In the selection of the sites, we also took into account the possibility to clearly observe the geometric relationships among the joints. For this reason we chose curvilinear road cuts or cliffs, wide coastal erosional surfaces and quarries. The numerical inversions show a similar stress tensors at all the investigated sites. Indeed, the maximum principal stress axis σ1 is vertical or subvertical, while the intermediate and the least axes (σ2 and σ3) lie on the horizontal plane or show low plunging values. The main direction of extension (σ3) at each site is in general agreement with the first-order regional stress field (WNW-ESE) even though some local perturbations have been recognized. These are interpreted as due to interferences between large active faults and their particular geometrical arrangement. In particular local stress deflections and stress swaps systematically occur in zones characterized by two overlapping fault segments or close to their tips.

Microstructure and Hardness Profiles of Bifocal Laser-Welded DP-HSLA Steel Overlap Joints

NASA Astrophysics Data System (ADS)

Grajcar, A.; Matter, P.; Stano, S.; Wilk, Z.; Różański, M.

2017-04-01

The article presents results related to the bifocal laser welding of overlap joints made of HSLA and DP high-strength steels. The joints were made using a disk laser and a head enabling the 50-50% distribution of laser power. The effects of the laser welding rates and the distance between laser spots on morphological features and hardness profiles were analyzed. It was established that the positioning of beams at angles of 0° or 90° determined the hardness of the individual zones of the joints, without causing significant differences in microstructures of the steels. Microstructural features were inspected using scanning electron microscopy. Both steels revealed primarily martensitic-bainitic microstructures in the fusion zone and in the heat-affected zone. Mixed multiphase microstructures were revealed in the inter-critical heat-affected zone of the joint. The research involved the determination of parameters making it possible to reduce the hardness of joints and prevent the formation of the soft zone in the dual-phase steel.

An 8-DOF dual-arm system for advanced teleoperation performance experiments

NASA Technical Reports Server (NTRS)

Bejczy, Antal K.; Szakaly, Zoltan F.

1992-01-01

This paper describes the electro-mechanical and control features of an 8-DOF manipulator manufactured by AAI Corporation and installed at the Jet Propulsion Lab. (JPL) in a dual-arm setting. The 8-DOF arm incorporates a variety of features not found in other lab or industrial manipulators. Some of the unique features are: 8-DOF revolute configuration with no lateral offsets at joint axes; 1 to 5 payload to weight ratio with 20 kg (44 lb) payload at a 1.75 m (68.5 in.) reach; joint position measurement with dual relative encoders and potentiometer; infinite roll of joint 8 with electrical and fiber optic slip rings; internal fiber optic link of 'smart' end effectors; four-axis wrist; graphite epoxy links; high link and joint stiffness; use of an upgraded JPL Universal Motor Controller (UMC) capable of driving up to 16 joints. The 8-DOF arm is equipped with a 'smart' end effector which incorporates a 6-DOF forcemoment sensor at the end effector base and grasp force sensors at the base of the parallel jaws. The 8-DOF arm is interfaced to a 6 DOF force reflecting hand controller. The same system is duplicated for and installed at NASA-Langley.

Clinical features of symptomatic patellofemoral joint osteoarthritis

PubMed Central

2012-01-01

Introduction Patellofemoral joint osteoarthritis (OA) is common and leads to pain and disability. However, current classification criteria do not distinguish between patellofemoral and tibiofemoral joint OA. The objective of this study was to provide empirical evidence of the clinical features of patellofemoral joint OA (PFJOA) and to explore the potential for making a confident clinical diagnosis in the community setting. Methods This was a population-based cross-sectional study of 745 adults aged ≥50 years with knee pain. Information on risk factors and clinical signs and symptoms was gathered by a self-complete questionnaire, and standardised clinical interview and examination. Three radiographic views of the knee were obtained (weight-bearing semi-flexed posteroanterior, supine skyline and lateral) and individuals were classified into four subsets (no radiographic OA, isolated PFJOA, isolated tibiofemoral joint OA, combined patellofemoral/tibiofemoral joint OA) according to two different cut-offs: 'any OA' and 'moderate to severe OA'. A series of binary logistic and multinomial regression functions were performed to compare the clinical features of each subset and their ability in combination to discriminate PFJOA from other subsets. Results Distinctive clinical features of moderate to severe isolated PFJOA included a history of dramatic swelling, valgus deformity, markedly reduced quadriceps strength, and pain on patellofemoral joint compression. Mild isolated PFJOA was barely distinguished from no radiographic OA (AUC 0.71, 95% CI 0.66, 0.76) with only difficulty descending stairs and coarse crepitus marginally informative over age, sex and body mass index. Other cardinal signs of knee OA - the presence of effusion, bony enlargement, reduced flexion range of movement, mediolateral instability and varus deformity - were indicators of tibiofemoral joint OA. Conclusions Early isolated PFJOA is clinically manifest in symptoms and self-reported functional limitation but has fewer clear clinical signs. More advanced disease is indicated by a small number of simple-to-assess signs and the relative absence of classic signs of knee OA, which are predominantly manifestations of tibiofemoral joint OA. Confident diagnosis of even more advanced PFJOA may be limited in the community setting. PMID:22417687

Assessment of Gait Characteristics in Total Knee Arthroplasty Patients Using a Hierarchical Partial Least Squares Method.

PubMed

Wang, Wei; Ackland, David C; McClelland, Jodie A; Webster, Kate E; Halgamuge, Saman

2018-01-01

Quantitative gait analysis is an important tool in objective assessment and management of total knee arthroplasty (TKA) patients. Studies evaluating gait patterns in TKA patients have tended to focus on discrete data such as spatiotemporal information, joint range of motion and peak values of kinematics and kinetics, or consider selected principal components of gait waveforms for analysis. These strategies may not have the capacity to capture small variations in gait patterns associated with each joint across an entire gait cycle, and may ultimately limit the accuracy of gait classification. The aim of this study was to develop an automatic feature extraction method to analyse patterns from high-dimensional autocorrelated gait waveforms. A general linear feature extraction framework was proposed and a hierarchical partial least squares method derived for discriminant analysis of multiple gait waveforms. The effectiveness of this strategy was verified using a dataset of joint angle and ground reaction force waveforms from 43 patients after TKA surgery and 31 healthy control subjects. Compared with principal component analysis and partial least squares methods, the hierarchical partial least squares method achieved generally better classification performance on all possible combinations of waveforms, with the highest classification accuracy . The novel hierarchical partial least squares method proposed is capable of capturing virtually all significant differences between TKA patients and the controls, and provides new insights into data visualization. The proposed framework presents a foundation for more rigorous classification of gait, and may ultimately be used to evaluate the effects of interventions such as surgery and rehabilitation.

Together I Can! Joint Attention Boosts 3- to 4-Year-Olds' Performance in a Verbal False-Belief Test.

PubMed

Psouni, Elia; Falck, Andreas; Boström, Leni; Persson, Martin; Sidén, Lisa; Wallin, Maria

2018-04-20

Effects of joint attention were addressed on 3- to 4-year-olds' performance in a verbal false-Belief Test (FBT), featuring the experimenter as co-watcher rather than narrator. In two experiments, children (N = 183) watched a filmed-FBT jointly with a test leader, disjointed from a test leader, or alone. Children attending jointly with a test leader were more likely to pass the FBT compared with normative data and to spontaneously recall information indicating false-belief understanding, suggesting that joint attention strengthens the plausibility of the FBT and renders plot-critical information more salient. In a third experiment (N = 59), results were replicated using a typical, image-based FBT. Overall findings highlight the profound impact of experimenter as social context in verbal FBTs, and link recall of specific story features to false-belief understanding. © 2018 Society for Research in Child Development.

Sacroiliac joint dysfunction as a reason for the development of acetabular retroversion: a new theory.

PubMed

Cibulka, Michael T

2014-05-01

Acetabular retroversion has been recently implicated as an important factor in the development of femoral acetabular impingement and hip osteoarthritis. The proper function of the hip joint requires that the anatomic features of the acetabulum and femoral head complement one another. In acetabular retroversion, the alignment of the acetabulum is altered where it opens in a posterolaterally instead of anterior direction. Changes in acetabular orientation can occur with alterations in pelvic tilt (anterior/posterior), and pelvic rotation (left/right). An overlooked problem that alters pelvic tilt and rotation, often seen by physical therapists, is sacroiliac joint dysfunction. A unique feature that develops in patients with sacroiliac joint dysfunction (SIJD) is asymmetry between the left and right innominate bones that can alter pelvic tilt and rotation. This article puts forth a theory suggesting that acetabular retroversion may be produced by sacroiliac joint dysfunction.

Mixed-effects location and scale Tobit joint models for heterogeneous longitudinal data with skewness, detection limits, and measurement errors.

PubMed

Lu, Tao

2017-01-01

The joint modeling of mean and variance for longitudinal data is an active research area. This type of model has the advantage of accounting for heteroscedasticity commonly observed in between and within subject variations. Most of researches focus on improving the estimating efficiency but ignore many data features frequently encountered in practice. In this article, we develop a mixed-effects location scale joint model that concurrently accounts for longitudinal data with multiple features. Specifically, our joint model handles heterogeneity, skewness, limit of detection, measurement errors in covariates which are typically observed in the collection of longitudinal data from many studies. We employ a Bayesian approach for making inference on the joint model. The proposed model and method are applied to an AIDS study. Simulation studies are performed to assess the performance of the proposed method. Alternative models under different conditions are compared.

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer's Disease.

PubMed

Cheng, Bo; Liu, Mingxia; Shen, Dinggang; Li, Zuoyong; Zhang, Daoqiang

2017-04-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer's Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multi-domain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods.

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer’s Disease

PubMed Central

Cheng, Bo; Liu, Mingxia; Li, Zuoyong

2017-01-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer’s Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multidomain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods. PMID:27928657

Linear feature projection-based real-time decoding of limb state from dorsal root ganglion recordings.

PubMed

Han, Sungmin; Chu, Jun-Uk; Park, Jong Woong; Youn, Inchan

2018-05-15

Proprioceptive afferent activities recorded by a multichannel microelectrode have been used to decode limb movements to provide sensory feedback signals for closed-loop control in a functional electrical stimulation (FES) system. However, analyzing the high dimensionality of neural activity is one of the major challenges in real-time applications. This paper proposes a linear feature projection method for the real-time decoding of ankle and knee joint angles. Single-unit activity was extracted as a feature vector from proprioceptive afferent signals that were recorded from the L7 dorsal root ganglion during passive movements of ankle and knee joints. The dimensionality of this feature vector was then reduced using a linear feature projection composed of projection pursuit and negentropy maximization (PP/NEM). Finally, a time-delayed Kalman filter was used to estimate the ankle and knee joint angles. The PP/NEM approach had a better decoding performance than did other feature projection methods, and all processes were completed within the real-time constraints. These results suggested that the proposed method could be a useful decoding method to provide real-time feedback signals in closed-loop FES systems.

Visual attention mitigates information loss in small- and large-scale neural codes

PubMed Central

Sprague, Thomas C; Saproo, Sameer; Serences, John T

2015-01-01

Summary The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires processing sensory signals in a manner that protects information about relevant stimuli from degradation. Such selective processing – or selective attention – is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. PMID:25769502

The neuromuscular differential diagnosis of joint hypermobility.

PubMed

Donkervoort, S; Bonnemann, C G; Loeys, B; Jungbluth, H; Voermans, N C

2015-03-01

Joint hypermobility is the defining feature of various inherited connective tissue disorders such as Marfan syndrome and various types of Ehlers-Danlos syndrome and these will generally be the first conditions to be considered by geneticists and pediatricians in the differential diagnosis of a patient presenting with such findings. However, several congenital and adult-onset inherited myopathies also present with joint hypermobility in the context of often only mild-to-moderate muscle weakness and should, therefore, be included in the differential diagnosis of joint hypermobility. In fact, on the molecular level disorders within both groups represent different ends of the same spectrum of inherited extracellular matrix (ECM) disorders. In this review we will summarize the measures of joint hypermobility, illustrate molecular mechanisms these groups of disorders have in common, and subsequently discuss the clinical features of: 1) the most common connective tissue disorders with myopathic or other neuromuscular features: Ehlers-Danlos syndrome, Marfan syndrome and Loeys-Dietz syndrome; 2) myopathy and connective tissue overlap disorders (muscle extracellular matrix (ECM) disorders), including collagen VI related dystrophies and FKBP14 related kyphoscoliotic type of Ehlers-Danlos syndrome; and 3) various (congenital) myopathies with prominent joint hypermobility including RYR1- and SEPN1-related myopathy. The aim of this review is to assist clinical geneticists and other clinicians with recognition of these disorders. © 2015 Wiley Periodicals, Inc.

Hierarchical clustering of EMD based interest points for road sign detection

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

2014-04-01

This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

Grid and non-grid cells in medial entorhinal cortex represent spatial location and environmental features with complementary coding schemes

PubMed Central

Diehl, Geoffrey W.; Hon, Olivia J.; Leutgeb, Stefan; Leutgeb, Jill K.

2017-01-01

Summary The medial entorhinal cortex (mEC) has been identified as a hub for spatial information processing by the discovery of grid, border, and head-direction cells. Here we find that in addition to these well characterized classes, nearly all of the remaining two thirds of mEC cells can be categorized as spatially selective. We refer to these cells as non-grid spatial cells and confirmed that their spatial firing patterns were unrelated to running speed and highly reproducible within the same environment. However, in response to manipulations of environmental features, such as box shape or box color, non-grid spatial cells completely reorganized their spatial firing patterns. At the same time, grid cells retained their spatial alignment and predominantly responded with redistributed firing rates across their grid fields. Thus, mEC contains a joint representation of both spatial and environmental feature content, with specialized cell types showing different types of integrated coding of multimodal information. PMID:28343867

Correlation of the Features of the Lumbar Multifidus Muscle With Facet Joint Osteoarthritis.

PubMed

Yu, Bo; Jiang, Kaibiao; Li, Xinfeng; Zhang, Jidong; Liu, Zude

2017-09-01

Facet joint osteoarthritis is considered a consequence of the aging process; however, there is evidence that it may be associated with degenerative changes of other structures. The goal of this study was to investigate the correlation between lumbar multifidus muscle features and facet joint osteoarthritis. This retrospective study included 160 patients who had acute or chronic low back pain and were diagnosed with facet joint osteoarthritis on computed tomography scan. Morphometric parameters, including cross-sectional area, muscle-fat index, and percentage of bilateral multifidus asymmetry at L3-L4, L4-L5, and L5-S1, were evaluated with T2-weighted magnetic resonance imaging. Patients with facet joint osteoarthritis had a smaller cross-sectional area and a higher muscle-fat index than those without facet joint osteoarthritis (P<.001). In multivariate regression analysis, older age and higher muscle-fat index were independently associated with facet joint osteoarthritis at all 3 spinal levels (P<.001). Smaller cross-sectional area was independently associated with facet joint osteoarthritis only at L4-L5 (P=.005). Asymmetry of the bilateral multifidus cross-sectional area was independently associated with facet joint osteoarthritis at L5-S1 (P=.009), but did not seem to be responsible for asymmetric degeneration of the bilateral facet joints. A higher multifidus muscle-fat index was independently associated with facet joint osteoarthritis, and bilateral multifidus size asymmetry was associated with the development of facet joint osteoarthritis at L5-S1. It seems more accurate to consider facet joint osteoarthritis a failure of the whole joint structure, including the paraspinal musculature, rather than simply a failure of the facet joint cartilage. [Orthopedics. 2017; 40(5):e793-e800.]. Copyright 2017, SLACK Incorporated.

24 CFR 943.148 - What procurement standards apply to PHAs selecting partners for a joint venture?

Code of Federal Regulations, 2010 CFR

2010-04-01

... INDIAN HOUSING, DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT PUBLIC HOUSING AGENCY CONSORTIA AND JOINT... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false What procurement standards apply to PHAs selecting partners for a joint venture? 943.148 Section 943.148 Housing and Urban Development...

The use of ultrasound in the assessment of the glenoid labrum of the glenohumeral joint. Part II: Examples of labral pathologies.

PubMed

Krzyżanowski, Wojciech; Tarczyńska, Marta

2012-09-01

Labral pathologies of the glenohumeral joint are most commonly caused by trauma. The majority of lesions affect the anterior part of labrum, resulting from much higher frequency of anterior shoulder dislocations over posterior ones. Another subgroup of labral lesions, not directly related to joint instability, are SLAP tears. Other findings include degenerative changes of labrum and paralabral cysts. Diagnostic imaging is crucial for making a decision regarding operative treatment. Apart from a standard X-ray examination, the imaging mainly relies on magnetic resonance or computed tomography arthrography. Based on their own experience, the authors propose the use of ultrasound in the assessment of labral tears of the glenohumeral joint. Different signs indicating labral pathology may be discovered and assessed during ultrasound examination. They include permanent displacement of the labrum onto the glenoid, labral instability during dynamic examination, lack of the labrum in the anatomical position, hypoechoic zone at the base of the labrum >2 mm in width, residual or swollen labrum as well as paralabral cyst(s). The most frequent appearance of labral pathology is displacement of the anteroinferior labrum onto the external aspect of the glenoid typically seen after anterior shoulder dislocation. The another most important US feature is labral instability while dynamically examined. The swelling or reduced size of the labrum usually indicates degeneration. This article presents sonographic images of selected labral pathologies.

[Diagnosis and treatment of diffuse tenosynovial giant cell tumor arising from temporomandibular joints].

PubMed

Meng, J H; Guo, Y X; Luo, H Y; Guo, C B; Ma, X C

2016-12-18

To retrospectively analyze the clinical features, treatment and prognosis to the diffuse tenosynovial giant cell tumor (D-TSGCT) arising from the temporomandibular joint (TMJ), and to give a reference for the early diagnosis and treatment of this disease. In this study, 15 patients finally diagnosed as D-TSGCT of TMJ histopathologically at the Peking University Hospital of Stomatology from October 2003 to August 2015 were selected and reviewed. Their clinical manifestations, imaging and histological features, diagnoses and differential diagnoses, treatments and follow-ups were summarized and discussed. D-TSGCT of TMJ showed obvious female predominance (12/15), the main symptoms included painful preauricular swelling or mass, limited mouth-opening and mandibular deviation with movement. D-TSGCT on computed tomography (CT) scan often showed ill-defined soft tissue masses around TMJ, enhancement after contrast administration, usually with widening of the joint spaces and with bone destruction of the condyle, the fossa and even the skull base. On magnetic resonance images (MRI), the majority of lesions on T1 weighted images and T2 weighted images both showed the characteristics of low signals (6/11). The lesions could extend beyond the joints (9/11) and into the infratemporal fossa (4/11) and the middle cranial fossa (4/11). Surgical resection was performed in 14 cases and biopsy in 1 case. Postoperative radiotherapy was performed in 3 cases. In follow-ups, 3 cases showed recurrence postoperatively. D-TSGCT arising from TMJ should be differentiated with TMJ disorders, other tumors and tumor-like lesions of TMJ and parotid neoplasms, etc. CT and MRI examinations have important values in the diagnosis and treatment design of D-TSGCT. Because of the local aggressive and extensive behavior, complete resection should be performed as soon as possible. Postoperative radiotherapy was helpful for the extensive lesions including destruction of skull base and may be a good supplementary therapy. Because of the possibility of recurrence and malignancy, long-term follow-up was suggested.

Joint ventures: to pursue or not to pursue?

PubMed

Blaszyk, Michael D; Hill-Mischel, Jody

2007-11-01

Hospitals should carefully select joint venture partners. The joint venture evaluation process should involve a high-level screen of strategic opportunities. Hospitals should develop a full business plan for the joint venture.

Interphalangeal Osteoarthritis Radiographic Simplified (iOARS) score: a radiographic method to detect osteoarthritis of the interphalangeal finger joints based on its histopathological alterations.

PubMed

Sunk, Ilse-Gerlinde; Amoyo-Minar, Love; Stamm, Tanja; Haider, Stefanie; Niederreiter, Birgit; Supp, Gabriela; Soleiman, Afschin; Kainberger, Franz; Smolen, Josef S; Bobacz, Klaus

2014-11-01

To develop a radiographic score for assessment of hand osteoarthritis (OA) that is based on histopathological alterations of the distal (DIP) and proximal (PIP) interphalangeal joints. DIP and PIP joints were obtained from corpses (n=40). Plain radiographies of these joints were taken. Joint samples were prepared for histological analysis; cartilage damage was graded according to the Mankin scoring system. A 2×2 Fisher's exact test was applied to define those radiographic features most likely to be associated with histological alterations. Receiver operating characteristic curves were analysed to determine radiographic thresholds. Intraclass correlation coefficients (ICC) estimated intra- and inter-reader variability. Spearman's correlation was applied to examine the relationship between our score and histopathological changes. Differences between groups were determined by a Student's t test. The Interphalangeal Osteoarthritis Radiographic Simplified (iOARS) score is presented. The score is based on histopathological changes of DIP and PIP joints and follows a simple dichotomy whether OA is present or not. The iOARS score relies on three equally ranked radiographic features (osteophytes, joint space narrowing and subchondral sclerosis). For both DIP and PIP joints, the presence of one x-ray features reflects interphalangeal OA. Sensitivity and specificity for DIP joints were 92.3% and 90.9%, respectively, and 75% and 100% for PIP joints. All readers were able to reproduce their own readings in DIP and PIP joints after 4 weeks. The overall agreement between the three readers was good; ICCs ranged from 0.945 to 0.586. Additionally, outcomes of the iOARS score in a hand OA cohort revealed a higher prevalence of interphalangeal joint OA compared with the Kellgren and Lawrence score. The iOARS score is uniquely based on histopathological alterations of the interphalangeal joints in order to reliably determine OA of the DIP and PIP joints radiographically. Its high specificity and sensitivity together with the dichotomous approach renders the iOARS score reliable, fast to perform and easy to apply. This tool may not only be valuable in daily clinical practice but also in clinical and epidemiological trials. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Discriminative clustering on manifold for adaptive transductive classification.

PubMed

Zhang, Zhao; Jia, Lei; Zhang, Min; Li, Bing; Zhang, Li; Li, Fanzhang

2017-10-01

In this paper, we mainly propose a novel adaptive transductive label propagation approach by joint discriminative clustering on manifolds for representing and classifying high-dimensional data. Our framework seamlessly combines the unsupervised manifold learning, discriminative clustering and adaptive classification into a unified model. Also, our method incorporates the adaptive graph weight construction with label propagation. Specifically, our method is capable of propagating label information using adaptive weights over low-dimensional manifold features, which is different from most existing studies that usually predict the labels and construct the weights in the original Euclidean space. For transductive classification by our formulation, we first perform the joint discriminative K-means clustering and manifold learning to capture the low-dimensional nonlinear manifolds. Then, we construct the adaptive weights over the learnt manifold features, where the adaptive weights are calculated through performing the joint minimization of the reconstruction errors over features and soft labels so that the graph weights can be joint-optimal for data representation and classification. Using the adaptive weights, we can easily estimate the unknown labels of samples. After that, our method returns the updated weights for further updating the manifold features. Extensive simulations on image classification and segmentation show that our proposed algorithm can deliver the state-of-the-art performance on several public datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clinical Presentation, Risk Factors, and Outcomes of Hematogenous Prosthetic Joint Infection in Patients with Staphylococcus aureus Bacteremia.

PubMed

Tande, Aaron J; Palraj, Bharath Raj; Osmon, Douglas R; Berbari, Elie F; Baddour, Larry M; Lohse, Christine M; Steckelberg, James M; Wilson, Walter R; Sohail, M Rizwan

2016-02-01

Staphylococcus aureus bacteremia is a life-threatening condition that may lead to metastatic infection, including prosthetic joint infection. To assess clinical factors associated with hematogenous prosthetic joint infection, we retrospectively reviewed all patients with a joint arthroplasty in place at the time of a first episode of S. aureus bacteremia over a 5-year period at our institution. Patients with postsurgical prosthetic joint infection without hematogenous prosthetic joint infection were excluded. There were 85 patients (143 arthroplasties) with either no prosthetic joint infection (n = 50; 58.8%) or hematogenous prosthetic joint infection in at least one arthroplasty (n = 35; 41.2%). The odds of hematogenous prosthetic joint infection was significantly increased among patients with community-acquired S. aureus bacteremia (odds ratio [OR] 18.07; 95% confidence interval [CI] 2.64-infinity; P = .001), as compared with nosocomial S. aureus bacteremia, in which there were no patients with hematogenous prosthetic joint infection. After adjusting for S. aureus bacteremia classification, the presence of ≥3 joint arthroplasties in place was associated with a nearly ninefold increased odds of hematogenous prosthetic joint infection as compared with those with 1-2 joint arthroplasties in place (OR 8.55; 95% CI 1.44-95.71; P = .012). All but one joint with prosthetic joint infection demonstrated at least one clinical feature suggestive of infection. There were 4 additional S. aureus prosthetic joint infections diagnosed during a median of 3.4 years of follow-up post hospitalization for S. aureus bacteremia. Prosthetic joint infection is frequent in patients with existing arthroplasties and concomitant S. aureus bacteremia, particularly with community-acquired S. aureus bacteremia and multiple prostheses. In contrast, occult S. aureus prosthetic joint infection without clinical features suggestive of prosthetic joint infection at the time of S. aureus bacteremia is rare. Copyright © 2016 Elsevier Inc. All rights reserved.

Keys and seats: Spatial response coding underlying the joint spatial compatibility effect.

PubMed

Dittrich, Kerstin; Dolk, Thomas; Rothe-Wulf, Annelie; Klauer, Karl Christoph; Prinz, Wolfgang

2013-11-01

Spatial compatibility effects (SCEs) are typically observed when participants have to execute spatially defined responses to nonspatial stimulus features (e.g., the color red or green) that randomly appear to the left and the right. Whereas a spatial correspondence of stimulus and response features facilitates response execution, a noncorrespondence impairs task performance. Interestingly, the SCE is drastically reduced when a single participant responds to one stimulus feature (e.g., green) by operating only one response key (individual go/no-go task), whereas a full-blown SCE is observed when the task is distributed between two participants (joint go/no-go task). This joint SCE (a.k.a. the social Simon effect) has previously been explained by action/task co-representation, whereas alternative accounts ascribe joint SCEs to spatial components inherent in joint go/no-go tasks that allow participants to code their responses spatially. Although increasing evidence supports the idea that spatial rather than social aspects are responsible for joint SCEs emerging, it is still unclear to which component(s) the spatial coding refers to: the spatial orientation of response keys, the spatial orientation of responding agents, or both. By varying the spatial orientation of the responding agents (Exp. 1) and of the response keys (Exp. 2), independent of the spatial orientation of the stimuli, in the present study we found joint SCEs only when both the seating and the response key alignment matched the stimulus alignment. These results provide evidence that spatial response coding refers not only to the response key arrangement, but also to the-often neglected-spatial orientation of the responding agents.

Research into automatic recognition of joints in human symmetrical movements

NASA Astrophysics Data System (ADS)

Fan, Yifang; Li, Zhiyu

2008-03-01

High speed photography is a major means of collecting data from human body movement. It enables the automatic identification of joints, which brings great significance to the research, treatment and recovery of injuries, the analysis to the diagnosis of sport techniques and the ergonomics. According to the features that when the adjacent joints of human body are in planetary motion, their distance remains the same, and according to the human body joint movement laws (such as the territory of the articular anatomy and the kinematic features), a new approach is introduced to process the image thresholding of joints filmed by the high speed camera, to automatically identify the joints and to automatically trace the joint points (by labeling markers at the joints). Based upon the closure of marking points, automatic identification can be achieved through thresholding treatment. Due to the screening frequency and the laws of human segment movement, when the marking points have been initialized, their automatic tracking can be achieved with the progressive sequential images.Then the testing results, the data from three-dimensional force platform and the characteristics that human body segment will only rotate around the closer ending segment when the segment has no boding force and only valid to the conservative force all tell that after being analyzed kinematically, the approach is approved to be valid.

Joint Attention in Infant-Toddler Early Childhood Programs: Its Dynamics and Potential for Collaborative Learning

ERIC Educational Resources Information Center

Degotardi, Sheila

2017-01-01

This article examines how joint attention episodes constitute a core feature of relational pedagogy for infants and toddlers. It draws on social interactionist approaches to language and cognitive development to propose that joint attention may afford significant current and future potential for young children's learning. However, most joint…

Resealing concrete pavement joints

DOT National Transportation Integrated Search

1999-07-01

The primary objective of this study was to evaluate the relative performance of the selected joint sealant materials. Other objectives were to determine the effect of selected sealant configurations and installation methods, and to identify sealant m...

A method of depth image based human action recognition

NASA Astrophysics Data System (ADS)

Li, Pei; Cheng, Wanli

2017-05-01

In this paper, we propose an action recognition algorithm framework based on human skeleton joint information. In order to extract the feature of human motion, we use the information of body posture, speed and acceleration of movement to construct spatial motion feature that can describe and reflect the joint. On the other hand, we use the classical temporal pyramid matching algorithm to construct temporal feature and describe the motion sequence variation from different time scales. Then, we use bag of words to represent these actions, which is to present every action in the histogram by clustering these extracted feature. Finally, we employ Hidden Markov Model to train and test the extracted motion features. In the experimental part, the correctness and effectiveness of the proposed model are comprehensively verified on two well-known datasets.

Low-Stroke Actuation for a Serial Robot

NASA Technical Reports Server (NTRS)

Ihrke, Chris A. (Inventor); Gao, Dalong (Inventor)

2014-01-01

A serial robot includes a base, first and second segments, a proximal joint joining the base to the first segment, and a distal joint. The distal joint that joins the segments is serially arranged and distal with respect to the proximal joint. The robot includes first and second actuators. A first tendon extends from the first actuator to the proximal joint and is selectively moveable via the first actuator. A second tendon extends from the second actuator to the distal joint and is selectively moveable via the second actuator. The robot includes a transmission having at least one gear element which assists rotation of the distal joint when an input force is applied to the proximal and/or distal joints by the first and/or second actuators. A robotic hand having the above robot is also disclosed, as is a robotic system having a torso, arm, and the above-described hand.

Joint source based analysis of multiple brain structures in studying major depressive disorder

NASA Astrophysics Data System (ADS)

Ramezani, Mahdi; Rasoulian, Abtin; Hollenstein, Tom; Harkness, Kate; Johnsrude, Ingrid; Abolmaesumi, Purang

2014-03-01

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show signi cant di erences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave- one-out experiment, we use a Fisher Linear Discriminant (FLD) classi er to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.

Dissolution-Enlarged Fractures Imaging Using Electrical Resistivity Tomography (ERT)

NASA Astrophysics Data System (ADS)

Siami-Irdemoosa, Elnaz

In recent years the electrical imaging techniques have been largely applied to geotechnical and environmental investigations. These techniques have proven to be the best geophysical methods for site investigations in karst terrain, particularly when the overburden soil is clay-dominated. Karst is terrain with a special landscape and distinctive hydrological system developed by dissolution of rocks, particularly carbonate rocks such as limestone and dolomite, made by enlarging fractures into underground conduits that can enlarge into caverns, and in some cases collapse to form sinkholes. Bedding planes, joints, and faults are the principal structural guides for underground flow and dissolution in almost all karstified rocks. Despite the important role of fractures in karst development, the geometry of dissolution-enlarged fractures remain poorly unknown. These features are characterized by an strong contrast with the surrounding formations in terms of physical properties, such as electrical resistivity. Electrical resistivity tomography (ERT) was used as the primary geophysical tool to image the subsurface in a karst terrain in Greene County, Missouri. Pattern, orientation and density of the joint sets were interpreted from ERT data in the investigation site. The Multi-channel Analysis of Surface Wave (MASW) method and coring were employed to validate the interpretation results. Two sets of orthogonal visually prominent joints have been identified in the investigation site: north-south trending joint sets and west-east trending joint sets. However, most of the visually prominent joint sets are associated with either cultural features that concentrate runoff, natural surface drainage features or natural surface drainage.

[The clinical characteristics of 26 cases of hypophosphatemia osteomalacia misdiagnosed as spondyloarthritis].

PubMed

Jin, Jingyu; Sun, Fei; Wang, Gang; Yang, Jinshui; Luo, Gui; Ma, Hua; Zhao, Zheng; Feng, Lixia; Wang, Yanyan; Zhao, Wei; Zhang, Jianglin; Zhu, Jian; Huang, Feng

2014-11-01

To study and summarize the clinical features of hypophosphatemia osteomalacia (HO) misdiagnosed as spondyloarthritis (SpA), aiming to analyze the reasons of misdiagnosis and improve the prognosis of such patients. A total of 26 cases of HO misdiagnosed as SpA were selected. Clinical features, laboratory tests, and image presentations were analyzed. Related literatures were reviewed. (1) Clinical characters: 26 patients were included (12 males and 14 females) with a median age of 38 years (range 20-60). The mean disease duration was 3.2 years (range 0.75 to 10 years). Of all the patients, 15 were diagnosed as tumor-induced HO, 4 were long-term oral adefovir dipivoxil-related HO, 3 were associated with Fanconi syndrome, 2 were related to hyperparathyroidism, while 2 were Sjogren's syndrome complicated with renal tubular acidosis. All of the 26 patients presented with low back pain including 15 with night pain. The time of morning stiffness was about 30 minutes. Non-steroidal anti-inflammatory drugs were given to each patient whereas with poor efficacy, neither did other agents work well, such as glucocorticoids, disease modifying anti-rheumatic drugs and biologics. (2) LABORATORY FINDINGS: the platelet count and inflammatory markers such as erythrocyte sedimentation rate, C-reactive protein (CRP) were usually normal. The level of serum calcium was normal or slightly lower, nevertheless, all patients had hypophosphatemia and increased level of alkaline phosphatase (ALP). Patients with adefovir dipivoxil-related HO, Fanconi syndrome or Sjogren's syndrome complicated with renal tubular acidosis were characterized by hypokalemia, hyperchloremia and alkaline urine. Patients with hyperparathyroidism had elevated parathyroid hormone (PTH). Positive antinuclear antibodies (ANA) (titer ≥ 1: 320), anti-SSA/SSB antibodies were found in patients with Sjogren's syndrome. (3) Radiographic features: sacroiliac joint lesions were found in X-ray, CT, positron emission tomography (PET-CT) or MRI, however the lesions in sacrum or ilium were predominant rather than in joints. Abnormal bone imaging in ribs, long bones and soft tissues in addition to joints could be detected by bone scintigraphy. HO is not uncommon in daily practice. Besides SpA, other diseases should be considered in the setting of low-back pain and diseased sacroiliac joints. Comprehensive screening of bone metabolic parameters contributes to the timely diagnosis of HO.

[Temporo-mandibular joint. Morpho-functional considerations].

PubMed

Scutariu, M D; Indrei, Anca

2004-01-01

The temporo-mandibular joint is distinguished from most other synovial joints of the body by two features: 1. the two jointed components carry teeth whose position and occlusion introduce a very strong influence on the movements of the temporo-mandibular joint and 2. its articular surfaces are not covered by hyaline cartilage, but by a dense, fibrous tissue. This paper describes the parts of the temporo-mandibular joint: the articular surfaces (the condylar process of the mandible and the glenoid part of the temporal bone), the fibrocartilaginous disc which is interposed between the mandibular and the temporal surface, the fibrous capsule of the temporo-mandibular joint and the ligaments of this joint. All these parts present a very strong adaptation at the important functions of the temporo-mandibular joint.

Visual attention mitigates information loss in small- and large-scale neural codes.

PubMed

Sprague, Thomas C; Saproo, Sameer; Serences, John T

2015-04-01

The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires that sensory signals are processed in a manner that protects information about relevant stimuli from degradation. Such selective processing--or selective attention--is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, thereby providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

PubMed

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

Application of improved wavelet total variation denoising for rolling bearing incipient fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, W.; Jia, M. P.

2018-06-01

When incipient fault appear in the rolling bearing, the fault feature is too small and easily submerged in the strong background noise. In this paper, wavelet total variation denoising based on kurtosis (Kurt-WATV) is studied, which can extract the incipient fault feature of the rolling bearing more effectively. The proposed algorithm contains main steps: a) establish a sparse diagnosis model, b) represent periodic impulses based on the redundant wavelet dictionary, c) solve the joint optimization problem by alternating direction method of multipliers (ADMM), d) obtain the reconstructed signal using kurtosis value as criterion and then select optimal wavelet subbands. This paper uses overcomplete rational-dilation wavelet transform (ORDWT) as a dictionary, and adjusts the control parameters to achieve the concentration in the time-frequency plane. Incipient fault of rolling bearing is used as an example, and the result shows that the effectiveness and superiority of the proposed Kurt- WATV bearing fault diagnosis algorithm.

[Review and prospect of analysis on UHMWPE wear debris in artificial hip joints].

PubMed

Wu, Jingping; Yuan, Chengqing; Yan, Xinping

2010-02-01

This paper briefly reviews the latest progress in the analyses of the technologies for artificial hip joints; and in the researches directed to the features of UHMWPE debris obtained from all kinds of experimental conditions, to the wear process and wear mechanism, and to the factors which influence the wear mechanism. Furthermore, the signification of debris atlas was illustrated. Finally, future directions to be furthered were considered and envisaged. It is suggested that emphases be laid on the relationship between the UHMWPE debris feature and the wear mechanism, and be laid synergistic effects of biochemical environment and loading environment so as to establish the predictive wear models of artificial hip joints.

Common Bolted Joint Analysis Tool

NASA Technical Reports Server (NTRS)

Imtiaz, Kauser

2011-01-01

Common Bolted Joint Analysis Tool (comBAT) is an Excel/VB-based bolted joint analysis/optimization program that lays out a systematic foundation for an inexperienced or seasoned analyst to determine fastener size, material, and assembly torque for a given design. Analysts are able to perform numerous what-if scenarios within minutes to arrive at an optimal solution. The program evaluates input design parameters, performs joint assembly checks, and steps through numerous calculations to arrive at several key margins of safety for each member in a joint. It also checks for joint gapping, provides fatigue calculations, and generates joint diagrams for a visual reference. Optimum fastener size and material, as well as correct torque, can then be provided. Analysis methodology, equations, and guidelines are provided throughout the solution sequence so that this program does not become a "black box:" for the analyst. There are built-in databases that reduce the legwork required by the analyst. Each step is clearly identified and results are provided in number format, as well as color-coded spelled-out words to draw user attention. The three key features of the software are robust technical content, innovative and user friendly I/O, and a large database. The program addresses every aspect of bolted joint analysis and proves to be an instructional tool at the same time. It saves analysis time, has intelligent messaging features, and catches operator errors in real time.

Design and evaluation of a modular lower limb exoskeleton for rehabilitation.

PubMed

Dos Santos, Wilian M; Nogueira, Samuel L; de Oliveira, Gustavo C; Pena, Guido G; Siqueira, Adriano A G

2017-07-01

This paper deals with the evaluation of an exoskeleton designed for assisting individuals to rehabilitate compromised lower limb movements resulting from stroke or incomplete spinal cord injury. The exoskeleton is composed of lightweight tubular structures and six free joints that provide a modular feature to the system. This feature allows the exoskeleton to be adapted to assist the movement of one or more patient joints. The actuation of the exoskeleton is also modular, and can be performed passively, by means of springs and dampers, or actively through actuators. In addition, its telescopic tubular links, developed to adjust the size of the links in order to align the joints of the exoskeleton with patient joints, allows the exoskeleton to be adjustable to fit different patients. Experiments considering the interaction between a healthy subject and the exoskeleton are performed to evaluate the influence of the exoskeleton structure on kinematic and muscular activity profiles during walking.

Animal behaviour and algal camouflage jointly structure predation and selection.

PubMed

Start, Denon

2018-05-01

Trait variation can structure interactions between individuals, thus shaping selection. Although antipredator strategies are an important component of many aquatic systems, how multiple antipredator traits interact to influence consumption and selection remains contentious. Here, I use a common larval dragonfly (Epitheca canis) and its predator (Anax junius) to test for the joint effects of activity rate and algal camouflage on predation and survival selection. I found that active and poorly camouflaged Epitheca were more likely to be consumed, and thus, survival selection favoured inactive and well-camouflaged individuals. Notably, camouflage dampened selection on activity rate, likely by reducing attack rates when Epitheca encountered a predator. Correlational selection is therefore conferred by the ecological interaction of traits, rather than by opposing selection acting on linked traits. I suggest that antipredator traits with different adaptive functions can jointly structure patterns of consumption and selection. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Autonomous Quality Control of Joint Orientation Measured with Inertial Sensors.

PubMed

Lebel, Karina; Boissy, Patrick; Nguyen, Hung; Duval, Christian

2016-07-05

Clinical mobility assessment is traditionally performed in laboratories using complex and expensive equipment. The low accessibility to such equipment, combined with the emerging trend to assess mobility in a free-living environment, creates a need for body-worn sensors (e.g., inertial measurement units-IMUs) that are capable of measuring the complexity in motor performance using meaningful measurements, such as joint orientation. However, accuracy of joint orientation estimates using IMUs may be affected by environment, the joint tracked, type of motion performed and velocity. This study investigates a quality control (QC) process to assess the quality of orientation data based on features extracted from the raw inertial sensors' signals. Joint orientation (trunk, hip, knee, ankle) of twenty participants was acquired by an optical motion capture system and IMUs during a variety of tasks (sit, sit-to-stand transition, walking, turning) performed under varying conditions (speed, environment). An artificial neural network was used to classify good and bad sequences of joint orientation with a sensitivity and a specificity above 83%. This study confirms the possibility to perform QC on IMU joint orientation data based on raw signal features. This innovative QC approach may be of particular interest in a big data context, such as for remote-monitoring of patients' mobility.

Karst development in central Butler County, Kansas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bain, B.A.

1993-02-01

Research was conducted to study the geology and hydrology of sinkholes, springs, and caves formed in Lower Permian, Fort Riley Limestone, located in central Butler County, Kansas. The goal was to better understand the controlling factors of these karst features and the processes that produce them in a portion of Kansas that is undergoing rapid population growth and increased groundwater usage. Research was accomplished in seven phases: literature search, locating karst features, measuring bedrock fracture joint trends, surveying major caves, estimating discharge of springs, dye tracing, and water chemistry analysis. Recognizable karst landforms within the study area were plotted ontomore » a base map to demonstrate their geographic, geologic, and hydrologic relationships. Karst features identified were 125 sinkholes, a major cave system composed of at least three enterable cave segments, and one large spring. The karst terrain found within the study area is clearly a system of interrelated features and processes. Long-term solution of the bedrock allows karst features to form, joints and bedding planes to enlarge, and creates an efficient network of subsurface drainage. Factors that control karst development in the study area are lithology, thickness, and dip of the bedrock; presence of well defined joints and bedding planes; relatively level topography; nearby entrenched river valleys; lack of thick surficial cover; and climate. Of these influences, solutional activity at joints plays a major role in the formation of sinkholes and cave passages; however, a complex combination of all the controlling factors is responsible for the present, unique, and dynamic karst system.« less

Automatic segmentation of low-visibility moving objects through energy analyis of the local 3D spectrum

NASA Astrophysics Data System (ADS)

Nestares, Oscar; Miravet, Carlos; Santamaria, Javier; Fonolla Navarro, Rafael

1999-05-01

Automatic object segmentation in highly noisy image sequences, composed by a translating object over a background having a different motion, is achieved through joint motion-texture analysis. Local motion and/or texture is characterized by the energy of the local spatio-temporal spectrum, as different textures undergoing different translational motions display distinctive features in their 3D (x,y,t) spectra. Measurements of local spectrum energy are obtained using a bank of directional 3rd order Gaussian derivative filters in a multiresolution pyramid in space- time (10 directions, 3 resolution levels). These 30 energy measurements form a feature vector describing texture-motion for every pixel in the sequence. To improve discrimination capability and reduce computational cost, we automatically select those 4 features (channels) that best discriminate object from background, under the assumptions that the object is smaller than the background and has a different velocity or texture. In this way we reject features irrelevant or dominated by noise, that could yield wrong segmentation results. This method has been successfully applied to sequences with extremely low visibility and for objects that are even invisible for the eye in absence of motion.

Going Deeper With Contextual CNN for Hyperspectral Image Classification.

PubMed

Lee, Hyungtae; Kwon, Heesung

2017-10-01

In this paper, we describe a novel deep convolutional neural network (CNN) that is deeper and wider than other existing deep networks for hyperspectral image classification. Unlike current state-of-the-art approaches in CNN-based hyperspectral image classification, the proposed network, called contextual deep CNN, can optimally explore local contextual interactions by jointly exploiting local spatio-spectral relationships of neighboring individual pixel vectors. The joint exploitation of the spatio-spectral information is achieved by a multi-scale convolutional filter bank used as an initial component of the proposed CNN pipeline. The initial spatial and spectral feature maps obtained from the multi-scale filter bank are then combined together to form a joint spatio-spectral feature map. The joint feature map representing rich spectral and spatial properties of the hyperspectral image is then fed through a fully convolutional network that eventually predicts the corresponding label of each pixel vector. The proposed approach is tested on three benchmark data sets: the Indian Pines data set, the Salinas data set, and the University of Pavia data set. Performance comparison shows enhanced classification performance of the proposed approach over the current state-of-the-art on the three data sets.

Static knee alignment and its association with radiographic knee osteoarthritis.

PubMed

Teichtahl, A J; Cicuttini, F M; Janakiramanan, N; Davis, S R; Wluka, A E

2006-09-01

Although knee alignment is associated with the progression of knee osteoarthritis (OA), it is unclear which features that characterize radiographic OA are related to alignment. The aim of this study was to examine the relationship between static knee joint alignment (measured as a continuous variable) and the radiographic features of knee OA (joint space narrowing and osteophytes). One hundred and twenty one adults with symptomatic knee OA were recruited using a combined strategy including referral from specialist centres, arthritis support groups and media advertising. X-rays were performed to classify the severity of disease and to determine static knee alignment. Increasing varus knee alignment was associated with increasing risk of medial compartment joint space narrowing (P < 0.001) and osteophytes (P = 0.005). Increasing valgus knee alignment was associated with an increased risk for lateral compartment joint space narrowing (P < 0.001) and osteophytes (P = 0.002). This study has demonstrated that the static knee angle, measured as a continuous variable, is an important determinant of the compartment-specific features of radiographic knee OA. Further work is required to determine whether interventions aimed at correcting these relatively minor levels of varus and valgus angulation will have an effect on the risk of tibiofemoral OA.

Deep learning and shapes similarity for joint segmentation and tracing single neurons in SEM images

NASA Astrophysics Data System (ADS)

Rao, Qiang; Xiao, Chi; Han, Hua; Chen, Xi; Shen, Lijun; Xie, Qiwei

2017-02-01

Extracting the structure of single neurons is critical for understanding how they function within the neural circuits. Recent developments in microscopy techniques, and the widely recognized need for openness and standardization provide a community resource for automated reconstruction of dendritic and axonal morphology of single neurons. In order to look into the fine structure of neurons, we use the Automated Tape-collecting Ultra Microtome Scanning Electron Microscopy (ATUM-SEM) to get images sequence of serial sections of animal brain tissue that densely packed with neurons. Different from other neuron reconstruction method, we propose a method that enhances the SEM images by detecting the neuronal membranes with deep convolutional neural network (DCNN) and segments single neurons by active contour with group shape similarity. We joint the segmentation and tracing together and they interact with each other by alternate iteration that tracing aids the selection of candidate region patch for active contour segmentation while the segmentation provides the neuron geometrical features which improve the robustness of tracing. The tracing model mainly relies on the neuron geometrical features and is updated after neuron being segmented on the every next section. Our method enables the reconstruction of neurons of the drosophila mushroom body which is cut to serial sections and imaged under SEM. Our method provides an elementary step for the whole reconstruction of neuronal networks.

Moving Beyond ERP Components: A Selective Review of Approaches to Integrate EEG and Behavior

PubMed Central

Bridwell, David A.; Cavanagh, James F.; Collins, Anne G. E.; Nunez, Michael D.; Srinivasan, Ramesh; Stober, Sebastian; Calhoun, Vince D.

2018-01-01

Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address this gap in this article by highlighting the utility of linking EEG and behavior, with an emphasis on approaches for EEG analysis that move beyond focusing on peaks or “components” derived from averaging EEG responses across trials and subjects (generating the event-related potential, ERP). First, we review methods for deriving features from EEG in order to enhance the signal within single-trials. These methods include filtering based on user-defined features (i.e., frequency decomposition, time-frequency decomposition), filtering based on data-driven properties (i.e., blind source separation, BSS), and generating more abstract representations of data (e.g., using deep learning). We then review cognitive models which extract latent variables from experimental tasks, including the drift diffusion model (DDM) and reinforcement learning (RL) approaches. Next, we discuss ways to access associations among these measures, including statistical models, data-driven joint models and cognitive joint modeling using hierarchical Bayesian models (HBMs). We think that these methodological tools are likely to contribute to theoretical advancements, and will help inform our understandings of brain dynamics that contribute to moment-to-moment cognitive function. PMID:29632480

Radiographic Analysis of Simulated First Dorsal Interosseous and Opponens Pollicis Loading Upon Thumb CMC Joint Subluxation: A Cadaver Study.

PubMed

Adams, Julie E; O'Brien, Virginia; Magnusson, Erik; Rosenstein, Benjamin; Nuckley, David J

2018-01-01

Therapy programs to treat thumb carpometacarpal (CMC) arthritis may engage selective activation and reeducation of thenar muscles, particularly the first dorsal interosseous (FDI) and opponens pollicis (OP) to reduce subluxation of the joint. We describe the effect of simulated selective activation of the FDI and OP muscles upon radiographic subluxation of the thumb CMC joint. In a cadaver model of CMC subluxation, loads were applied to the FDI, the OP, and then concomitantly at 0%, 25%, 50%, 75%, and 100% maximal loads and radial subluxation of the joint and reduction in subluxation was measured. Selective activation of the OP, alone, improved the subluxation ratio (SR) in a dose-dependent manner. Selective activation of FDI, alone, demonstrated minimal effects on SR. Concomitant activation of OP and FDI improved the SR across all loading states, and activation of 75% and greater, when compared with FDI activation alone, resulted in a statistically significant improvement in SR to within 10% of the presubluxed joint. Concomitant activation of the FDI and OP acts to reduce subluxation of the thumb CMC joint in a dose-dependent fashion. The OP is likely the predominant reducing force. Hand therapy programs that focus on selective strengthening programs likely function in part to encourage patients to activate the easily palpable and easily understood FDI. Concomitant coactivation of the OP may be the major reducing force to elicit clinical and radiographic reduction of subluxation, improved thumb positioning, and reduction of pain and arthritic symptoms.

A descriptive analysis of 14 cases of progressive-psuedorheumatoid-arthropathy of childhood from south India: review of literature in comparison with juvenile idiopathic arthritis.

PubMed

Ekbote, Alka V; Danda, Debashish; Kumar, Sathish; Danda, Sumita; Madhuri, Vrisha; Gibikote, Sridhar

2013-06-01

Progressive-psuedorheumatoid-arthropathy of childhood (PPAC) is an autosomal recessive single gene skeletal dysplasia involving joints. The gene attributed to its cause is WNT1-inducible-signaling pathway protein3 (WISP3). To study the clinical and radiographic presentation of PPAC in Indian patients and to compare with described features of PPAC and Juvenile Idiopathic Arthritis (JIA) from published literature. All cases (n = 14) of PPAC seen in the Rheumatology and Clinical Genetics outpatient clinic between 2008 and 2011 with classical, clinical, and radiological features were studied. The demographic and clinical data were obtained from medical records of the outpatient visits. Slight female preponderance (57%) and history of consanguinity in parents (43%) was observed in this group. The median age at onset was 4.5 years (range from birth to 9 years of age). Early presentation below the age of 3 years was seen in 3/14 patients (21%) in this group. The growth of all the patients fell below the 3rd percentile for the age. Historically, hip joint involvement was the most common presenting feature; however, elbow, wrist, knees, feet, spine, shoulder joints and small joints, namely proximal interphalangeal (PIP), distal interphalangeal (DIP), metacarpophalangeal (MCP), metatarsophalangeal joints (MTP), and interphalangeal joints (IP) of the feet, were also involved, either clinically or radiologically in varying proportions. Platyspondyly was noted in all. Molecular analysis of the WISP3 gene identified mutations in all the 5 individuals in whom it was done. This descriptive case series of PPAC from India reports distinctly differentiating clinical, radiological, and molecular markers in contrast with classically described features of JIA, its mimic. Early presentation (age of onset below 3 years) with involvement of interphalangeal joints seen in three patients (21%) was a unique finding, with missense WISP3 gene mutations in all of them. Timely diagnosis of this entity can spare the patient from unnecessary investigations and toxic medications. Copyright © 2013 Elsevier Inc. All rights reserved.

Change in joint space width: hyaline articular cartilage loss or alteration in meniscus?

PubMed

Hunter, D J; Zhang, Y Q; Tu, X; Lavalley, M; Niu, J B; Amin, S; Guermazi, A; Genant, H; Gale, D; Felson, D T

2006-08-01

To explore the relative contribution of hyaline cartilage morphologic features and the meniscus to the radiographic joint space. The Boston Osteoarthritis of the Knee Study is a natural history study of symptomatic knee osteoarthritis (OA). Baseline and 30-month followup assessments included knee magnetic resonance imaging (MRI) and fluoroscopically positioned weight-bearing knee radiographs. Cartilage and meniscal degeneration were scored on MRI in the medial and lateral tibiofemoral joints using a semiquantitative grading system. Meniscal position was measured to the nearest millimeter. The dependent variable was joint space narrowing (JSN) on the plain radiograph (possible range 0-3). The predictor variables were MRI cartilage score, meniscal degeneration, and meniscal position measures. We first conducted a cross-sectional analysis using multivariate regression to determine the relative contribution of meniscal factors and cartilage morphologic features to JSN, adjusting for body mass index (BMI), age, and sex. The same approach was used for change in JSN and change in predictor variables. We evaluated 264 study participants with knee OA (mean age 66.7 years, 59% men, mean BMI 31.4 kg/m(2)). The results from the models demonstrated that meniscal position and meniscal degeneration each contributed to prediction of JSN, in addition to the contribution by cartilage morphologic features. For change in medial joint space, both change in meniscal position and change in articular cartilage score contributed substantially to narrowing of the joint space. The meniscus (both its position and degeneration) accounts for a substantial proportion of the variance explained in JSN, and the change in meniscal position accounts for a substantial proportion of change in JSN.

The use of ultrasound in the assessment of the glenoid labrum of the glenohumeral joint. Part II: Examples of labral pathologies

PubMed Central

Tarczyńska, Marta

2012-01-01

Labral pathologies of the glenohumeral joint are most commonly caused by trauma. The majority of lesions affect the anterior part of labrum, resulting from much higher frequency of anterior shoulder dislocations over posterior ones. Another subgroup of labral lesions, not directly related to joint instability, are SLAP tears. Other findings include degenerative changes of labrum and paralabral cysts. Diagnostic imaging is crucial for making a decision regarding operative treatment. Apart from a standard X-ray examination, the imaging mainly relies on magnetic resonance or computed tomography arthrography. Based on their own experience, the authors propose the use of ultrasound in the assessment of labral tears of the glenohumeral joint. Different signs indicating labral pathology may be discovered and assessed during ultrasound examination. They include permanent displacement of the labrum onto the glenoid, labral instability during dynamic examination, lack of the labrum in the anatomical position, hypoechoic zone at the base of the labrum >2 mm in width, residual or swollen labrum as well as paralabral cyst(s). The most frequent appearance of labral pathology is displacement of the anteroinferior labrum onto the external aspect of the glenoid typically seen after anterior shoulder dislocation. The another most important US feature is labral instability while dynamically examined. The swelling or reduced size of the labrum usually indicates degeneration. This article presents sonographic images of selected labral pathologies. PMID:26672471

Joint sparsity based heterogeneous data-level fusion for target detection and estimation

NASA Astrophysics Data System (ADS)

Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

2017-05-01

Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

A competitive interaction theory of attentional selection and decision making in brief, multielement displays.

PubMed

Smith, Philip L; Sewell, David K

2013-07-01

We generalize the integrated system model of Smith and Ratcliff (2009) to obtain a new theory of attentional selection in brief, multielement visual displays. The theory proposes that attentional selection occurs via competitive interactions among detectors that signal the presence of task-relevant features at particular display locations. The outcome of the competition, together with attention, determines which stimuli are selected into visual short-term memory (VSTM). Decisions about the contents of VSTM are made by a diffusion-process decision stage. The selection process is modeled by coupled systems of shunting equations, which perform gated where-on-what pathway VSTM selection. The theory provides a computational account of key findings from attention tasks with near-threshold stimuli. These are (a) the success of the MAX model of visual search and spatial cuing, (b) the distractor homogeneity effect, (c) the double-target detection deficit, (d) redundancy costs in the post-stimulus probe task, (e) the joint item and information capacity limits of VSTM, and (f) the object-based nature of attentional selection. We argue that these phenomena are all manifestations of an underlying competitive VSTM selection process, which arise as a natural consequence of our theory. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Patellofemoral Arthroplasty: Current Concepts and Review of the Literature

PubMed Central

Pisanu, Gabriele; Rosso, Federica; Bertolo, Corrado; Dettoni, Federico; Blonna, Davide; Bonasia, Davide Edoardo; Rossi, Roberto

2017-01-01

Patellofemoral osteoarthritis (PFOA) can be associated with anterior knee pain, stiffness, and functional impairment. Some authors report that PFOA affects approximately 9% of patients older than 40 years with a greater prevalence in females. Etiology of PFOA is multifactorial and is related to the presence of abnormal stresses at the PF joint due to knee- and patient-related factors. The need for a joint preserving treatment by isolated replacement of the injured compartment of the knee led to the development of PF arthroplasty (PFA). When a correct PF replacement is performed, PFA preserves physiologic tibiofemoral joint, thus allowing patients for a rapid recovery with a high satisfaction. The outcomes for PFA are quite variable with a trend toward good to excellent results, mainly owing to the improvement in surgical techniques, patient selection, and implant design. The development of the second generation of PFA improved the outcomes, which is attributed to the different trochlear designs. Recently, encouraging results have been provided by the association of PFA and unicompartmental knee arthroplasty (UKA). In many studies, the main cause of PFA failure is progression of tibiofemoral OA. The aim of this brief review of literature is to summarize the clinical features, indications and contraindications, surgical techniques, complications, and outcomes of PFA. PMID:29270562

Biological aspects of early osteoarthritis.

PubMed

Madry, Henning; Luyten, Frank P; Facchini, Andrea

2012-03-01

Early OA primarily affects articular cartilage and involves the entire joint, including the subchondral bone, synovial membrane, menisci and periarticular structures. The aim of this review is to highlight the molecular basis and histopathological features of early OA. Selective review of literature. Risk factors for developing early OA include, but are not limited to, a genetic predisposition, mechanical factors such as axial malalignment, and aging. In early OA, the articular cartilage surface is progressively becoming discontinuous, showing fibrillation and vertical fissures that extend not deeper than into the mid-zone of the articular cartilage, reflective of OARSI grades 1.0-3.0. Early changes in the subchondral bone comprise a progressive increase in subchondral plate and subarticular spongiosa thickness. Early OA affects not only the articular cartilage and the subchondral bone but also other structures of the joint, such as the menisci, the synovial membrane, the joint capsule, ligaments, muscles and the infrapatellar fat pad. Genetic markers or marker combinations may become useful in the future to identify early OA and patients at risk. The high socioeconomic impact of OA suggests that a better insight into the mechanisms of early OA may be a key to develop more targeted reconstructive therapies at this first stage of the disease. Systematic review, Level II.

The Functional Anatomy of the Carpometacarpal Complex in Anthropoids and Its Implications for the Evolution of the Hominoid Hand.

PubMed

Selby, Michael S; Simpson, Scott W; Lovejoy, C Owen

2016-05-01

Previously, we described several features of the carpometacarpal joints in extant large-bodied apes that are likely adaptations to the functional demands of vertical climbing and suspension. We observed that all hominids, including modern humans and the 4.4-million-year-old hominid Ardipithecus ramidus, lacked these features. Here, we assess the uniqueness of these features in a large sample of monkey, ape, and human hands. These new data provide additional insights into the functional adaptations and evolution of the anthropoid hand. Our survey highlights a series of anatomical adaptations that restrict motion between the second and third metacarpals (MC2 and MC3) and their associated carpals in extant apes, achieved via joint reorganization and novel energy dissipation mechanisms. Their hamate-MC4 and -MC5 joint surface morphologies suggest limited mobility, at least in Pan. Gibbons and spider monkeys have several characters (angled MC3, complex capitate-MC3 joint topography, variably present capitate-MC3 ligaments) that suggest functional convergence in response to suspensory locomotion. Baboons have carpometacarpal morphology suggesting flexion/extension at these joints beyond that observed in most other Old World monkeys, probably as an energy dissipating mechanism minimizing collision forces during terrestrial locomotion. All hominids lack these specializations of the extant great apes, suggesting that vertical climbing was never a central feature of our ancestral locomotor repertoire. Furthermore, the reinforced carpometacarpus of vertically climbing African apes was likely appropriated for knuckle-walking in concert with other novel potential energy dissipating mechanisms. The most parsimonious explanation of the structural similarity of these carpometacarpal specializations in great apes is that they evolved independently. © 2016 Wiley Periodicals, Inc.

Space shuttle Production Verification Motor 1 (PV-1) static fire

NASA Technical Reports Server (NTRS)

1989-01-01

All inspection and instrumentation data indicate that the PV-1 static test firing conducted 18 Aug. 1988 was successful. With the exception of the intentionally flawed joints and static test modifications, PV-1 was flight configuration. Fail-safe flaws guaranteeing pressure to test the sealing capability of primary O-rings were included in the aft field joint, case-to-nozzle joint, and nozzle internal Joint 5. The test was conducted at ambient conditions, with the exception of the field joints and case/nozzle joints which were maintained at a minimum of 75 F. Ballistics performance values were within specification requirements. The PV-1 motor exhibited chamber pressure oscillations similar to previously tested Space Shuttle redesigned solid rocket motors, particularly QM-7. The first longitudinal mode oscillations experienced by PV-1 were the strongest ever measured in a Space Shuttle motor. Investigation into this observation is being conducted. Joint insulation performed as designed with no evidence of gas flow within unflawed forward field joints. The intentionally flawed center and aft case field joint insulation performance was excellent. There was no evidence of hot gas past the center field joint capture feature O-ring, the case-to-nozzle joint primary O-ring, or the aft field joint primary O-ring. O-ring seals and barriers with assured pressure at the flaws showed erosion and heat effect, but all sealed against passage of hot gases with the exception of the aft field joint capture feature O-ring. There was no evidence of erosion, heat effect, or blowby on any O-ring seals or barriers at the unflawed joints. Nozzle performance was nominal with typical erosion. Post-test examination revealed that the forward nose ring was of the old high performance motor design configuration with the 150-deg ply angle. All nozzle components remained intact for post-test evaluation. The thrust vector control system operated correctly. The water deluge system, CO2 quench, and other test equipment performed as planned during all required test operations.

Automated Depression Analysis Using Convolutional Neural Networks from Speech.

PubMed

He, Lang; Cao, Cui

2018-05-28

To help clinicians to efficiently diagnose the severity of a person's depression, the affective computing community and the artificial intelligence field have shown a growing interest in designing automated systems. The speech features have useful information for the diagnosis of depression. However, manually designing and domain knowledge are still important for the selection of the feature, which makes the process labor consuming and subjective. In recent years, deep-learned features based on neural networks have shown superior performance to hand-crafted features in various areas. In this paper, to overcome the difficulties mentioned above, we propose a combination of hand-crafted and deep-learned features which can effectively measure the severity of depression from speech. In the proposed method, Deep Convolutional Neural Networks (DCNN) are firstly built to learn deep-learned features from spectrograms and raw speech waveforms. Then we manually extract the state-of-the-art texture descriptors named median robust extended local binary patterns (MRELBP) from spectrograms. To capture the complementary information within the hand-crafted features and deep-learned features, we propose joint fine-tuning layers to combine the raw and spectrogram DCNN to boost the depression recognition performance. Moreover, to address the problems with small samples, a data augmentation method was proposed. Experiments conducted on AVEC2013 and AVEC2014 depression databases show that our approach is robust and effective for the diagnosis of depression when compared to state-of-the-art audio-based methods. Copyright © 2018. Published by Elsevier Inc.

Mobile ankle and knee perturbator.

PubMed

Andersen, Jacob Buus; Sinkjaer, Thomas

2003-10-01

A mobile ankle and knee perturbator has been developed. It consists of a functional joint with an integrated clutch. Four Bowden wires connect the joint to a powerful motor and a double pneumatic cylinder. When needed during any time of the gait cycle, it is possible to impose an ankle rotation by engaging the clutch and rotating the ankle or knee joint with a predefined displacement. The system is designed to investigate electrophysiological and biomechanical features of the human ankle or knee joint during gait.

A Novel Approach for Lie Detection Based on F-Score and Extreme Learning Machine

PubMed Central

Gao, Junfeng; Wang, Zhao; Yang, Yong; Zhang, Wenjia; Tao, Chunyi; Guan, Jinan; Rao, Nini

2013-01-01

A new machine learning method referred to as F-score_ELM was proposed to classify the lying and truth-telling using the electroencephalogram (EEG) signals from 28 guilty and innocent subjects. Thirty-one features were extracted from the probe responses from these subjects. Then, a recently-developed classifier called extreme learning machine (ELM) was combined with F-score, a simple but effective feature selection method, to jointly optimize the number of the hidden nodes of ELM and the feature subset by a grid-searching training procedure. The method was compared to two classification models combining principal component analysis with back-propagation network and support vector machine classifiers. We thoroughly assessed the performance of these classification models including the training and testing time, sensitivity and specificity from the training and testing sets, as well as network size. The experimental results showed that the number of the hidden nodes can be effectively optimized by the proposed method. Also, F-score_ELM obtained the best classification accuracy and required the shortest training and testing time. PMID:23755136

Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

PubMed

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

2016-10-05

Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

The impact of office chair features on lumbar lordosis, intervertebral joint and sacral tilt angles: a radiographic assessment.

PubMed

De Carvalho, Diana; Grondin, Diane; Callaghan, Jack

2017-10-01

The purpose of this study was to determine which office chair feature is better at improving spine posture in sitting. Participants (n = 28) were radiographed in standing, maximum flexion and seated in four chair conditions: control, lumbar support, seat pan tilt and backrest with scapular relief. Measures of lumbar lordosis, intervertebral joint angles and sacral tilt were compared between conditions and sex. Sitting consisted of approximately 70% of maximum range of spine flexion. No differences in lumbar flexion were found between the chair features or control. Significantly more anterior pelvic rotation was found with the lumbar support (p = 0.0028) and seat pan tilt (p < 0.0001). Males had significantly more anterior pelvic rotation and extended intervertebral joint angles through L1-L3 in all conditions (p < 0.0001). No one feature was statistically superior with respect to minimising spine flexion, however, seat pan tilt resulted in significantly improved pelvic posture. Practitioner Summary: Seat pan tilt, and to some extent lumbar supports, appear to improve seated postures. However, sitting, regardless of chair features used, still involves near end range flexion of the spine. This will increase stresses to the spine and could be a potential injury generator during prolonged seated exposures.

Effect of Sacroiliac Joint Manipulation on Selected Gait Parameters in Healthy Subjects.

PubMed

Wójtowicz, Sebastian; Sajko, Igor; Hadamus, Anna; Mosiołek, Anna; Białoszewski, Dariusz

2017-08-31

The sacroiliac joints have complicated biomechanics. While the movements in the joints are small, they exert a significant effect on gait. This study aimed to assess how sacroiliac joint manipulation influences selected gait parameters. The study enrolled 57 healthy subjects. The experimental group consisted of 26 participants diagnosed with dysfunction of one sacroiliac joint. The control group was composed of 31 persons. All subjects from the experimental group underwent sacroiliac joint manipulation. The experimental group showed significant lengthening of the step on both sides and the stride length in this group increased as well. Moreover, the duration of the stride increased (p=0.000826). The maximum midfoot pressure was higher and maximum heel pressure decreased. The differences were statistically significant. 1. Subclinical dysfunctions of the sacroiliac joints may cause functional gait disturbance. 2. Manipulation of the iliosacral joint exerts a significant effect on gait parameters, which may lead to improved gait economy and effec-tiveness. 3. Following manipulation of one iliosacral joint, altered gait parameters are noted on both the manipulated side and the contralateral side, which may translate into improved quality of locomotion.

Analysis of underlying causes of inter-expert disagreement in retinopathy of prematurity diagnosis. Application of machine learning principles.

PubMed

Ataer-Cansizoglu, E; Kalpathy-Cramer, J; You, S; Keck, K; Erdogmus, D; Chiang, M F

2015-01-01

Inter-expert variability in image-based clinical diagnosis has been demonstrated in many diseases including retinopathy of prematurity (ROP), which is a disease affecting low birth weight infants and is a major cause of childhood blindness. In order to better understand the underlying causes of variability among experts, we propose a method to quantify the variability of expert decisions and analyze the relationship between expert diagnoses and features computed from the images. Identification of these features is relevant for development of computer-based decision support systems and educational systems in ROP, and these methods may be applicable to other diseases where inter-expert variability is observed. The experiments were carried out on a dataset of 34 retinal images, each with diagnoses provided independently by 22 experts. Analysis was performed using concepts of Mutual Information (MI) and Kernel Density Estimation. A large set of structural features (a total of 66) were extracted from retinal images. Feature selection was utilized to identify the most important features that correlated to actual clinical decisions by the 22 study experts. The best three features for each observer were selected by an exhaustive search on all possible feature subsets and considering joint MI as a relevance criterion. We also compared our results with the results of Cohen's Kappa [36] as an inter-rater reliability measure. The results demonstrate that a group of observers (17 among 22) decide consistently with each other. Mean and second central moment of arteriolar tortuosity is among the reasons of disagreement between this group and the rest of the observers, meaning that the group of experts consider amount of tortuosity as well as the variation of tortuosity in the image. Given a set of image-based features, the proposed analysis method can identify critical image-based features that lead to expert agreement and disagreement in diagnosis of ROP. Although tree-based features and various statistics such as central moment are not popular in the literature, our results suggest that they are important for diagnosis.

Prosthetic elbow joint

NASA Technical Reports Server (NTRS)

Weddendorf, Bruce C. (Inventor)

1994-01-01

An artificial, manually positionable elbow joint for use in an upper extremity, above-elbow, prosthetic is described. The prosthesis provides a locking feature that is easily controlled by the wearer. The instant elbow joint is very strong and durable enough to withstand the repeated heavy loadings encountered by a wearer who works in an industrial, construction, farming, or similar environment. The elbow joint of the present invention comprises a turntable, a frame, a forearm, and a locking assembly. The frame generally includes a housing for the locking assembly and two protruding ears. The forearm includes an elongated beam having a cup-shaped cylindrical member at one end and a locking wheel having a plurality of holes along a circular arc on its other end with a central bore for pivotal attachment to the protruding ears of the frame. The locking assembly includes a collar having a central opening with a plurality of internal grooves, a plurality of internal cam members each having a chamfered surface at one end and a V-shaped slot at its other end; an elongated locking pin having a crown wheel with cam surfaces and locking lugs secured thereto; two coiled compression springs; and a flexible filament attached to one end of the elongated locking pin and extending from the locking assembly for extending and retracting the locking pin into the holes in the locking wheel to permit selective adjustment of the forearm relative to the frame. In use, the turntable is affixed to the upper arm part of the prosthetic in the conventional manner, and the cup-shaped cylindrical member on one end of the forearm is affixed to the forearm piece of the prosthetic in the conventional manner. The elbow joint is easily adjusted and locked between maximum flex and extended positions.

Effect of tool pin features on process response variables during friction stir welding of dissimilar aluminum alloys

DOE PAGES

Rabby, Reza; Tang, Wei; Reynolds, A. P.

2015-05-13

In this article, the effect of pin features and orientation/placement of the materials on advancing side were investigated for friction stir welding (FSW) of dissimilar aluminum alloys AA2050 and AA6061. Pins for FSW were produced with a 2.12 mm pitch thread having three flats/flutes. Three sets of rotational speed/welding speed were used to perform a series of welds in a butt joint arrangement. The results show that, joint quality, process response variables and welding temperature are highly affected by pin features and material orientation in FSW. Defect free joints with effective material transportation in the weld nugget zone were obtainedmore » when welding was performed with AA2050 on the advancing side. The tool also encounters less in-plane reaction force for welding with 2050 on the advancing side. Pin with thread+3 flats produces quality welds at low rotational and travel speed regardless of the location of alloys on advancing or retreating side.« less

Effect of tool pin features on process response variables during friction stir welding of dissimilar aluminum alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabby, Reza; Tang, Wei; Reynolds, A. P.

In this article, the effect of pin features and orientation/placement of the materials on advancing side were investigated for friction stir welding (FSW) of dissimilar aluminum alloys AA2050 and AA6061. Pins for FSW were produced with a 2.12 mm pitch thread having three flats/flutes. Three sets of rotational speed/welding speed were used to perform a series of welds in a butt joint arrangement. The results show that, joint quality, process response variables and welding temperature are highly affected by pin features and material orientation in FSW. Defect free joints with effective material transportation in the weld nugget zone were obtainedmore » when welding was performed with AA2050 on the advancing side. The tool also encounters less in-plane reaction force for welding with 2050 on the advancing side. Pin with thread+3 flats produces quality welds at low rotational and travel speed regardless of the location of alloys on advancing or retreating side.« less

Joint Duty Prerequisite for Promotion to 07 (Brigadier General

DTIC Science & Technology

1989-03-13

NUMBER)(O LTC Julius E. Coats, Jr. 9. PERFORMING ORGANIZATIN NAME AND ADDRESS I0. PROGRAM ELEMENT. PROJECT. tASK U.S. Army War College AREA 4 WORK...new personnel policy; to wit, the Army leadership at all levels should view joint duty re- quirement for selection for flag officer with a positive...the Army leadership at all levels should view joint duty requirement for selection for flag officer with a positive attitude, not as a means for

Diagnostic and prognostic value of history-taking and physical examination in undifferentiated peripheral inflammatory arthritis: a systematic review.

PubMed

Kuriya, Bindee; Villeneuve, Edith; Bombardier, Claire

2011-03-01

To review the diagnostic and prognostic value of history/physical examination among patients with undifferentiated peripheral inflammatory arthritis (UPIA). We conducted a systematic review evaluating the association between history/physical examination features and a diagnostic or prognostic outcome. Nineteen publications were included. Advanced age, female sex, and morning stiffness were predictive of a diagnosis of rheumatoid arthritis (RA) from UPIA. A higher number of tender and swollen joints, small/large joint involvement in the upper/lower extremities, and symmetrical involvement were associated with progression to RA. Similar features were associated with persistent disease and erosions, while disability at baseline and extraarticular features were predictive of future disability. History/physical examination features are heterogeneously reported. Several features predict progression from UPIA to RA or a poor prognosis. Continued measurements in the UPIA population are needed to determine if these features are valid and reliable predictors of outcomes, especially as new definitions for RA and disease states emerge.

Rejection Sensitivity and Executive Control: Joint predictors of Borderline Personality features

PubMed Central

Ayduk, Özlem; Zayas, Vivian; Downey, Geraldine; Cole, Amy Blum; Shoda, Yuichi; Mischel, Walter

2008-01-01

Two studies tested the hypothesis that rejection sensitivity (RS) and executive control (EC) jointly predict borderline personality (BP) features. We expected high RS to be related to increased vulnerability for BP features specifically in people who also had difficulties in executive control (EC). Study 1 tested this hypothesis using a sample of college students (N = 379) whereas Study 2 (N = 104) was conducted using a community sample of adults. Both studies operationalized EC by a self-report measure. For a subsample in Study 2 (N = 80), ability to delay gratification at age 4 was also used as an early behavioral precursor of EC in adulthood. In both studies, high RS was associated with increased BP features among people low in self-reported EC. Among those high in self-reported EC, the relationship between RS and BP features was attenuated. Study 2 found parallel findings using preschool delay ability as a behavioral index of EC. These findings suggest that EC may protect high RS people against BP features. PMID:18496604

Space shuttle development Motor No. 9 (DM-9), volume 1

NASA Technical Reports Server (NTRS)

Garecht, Diane M.

1990-01-01

The results obtained during the December 23, 1987 static firing of the DM-9 test article are presented. The DM-9 full-scale static test article employed redesigned solid rocket motor (RSRM) field joint capture feature hardware with J-seal insulation configuration, and nozzle-to-case joint radial bolt design with bonded insulation configuration. The nozzle incorporated RSRM components, including a thicker cowl with involuted outer boot ring. The nozzle employed redundant and verifiable seals in all five joints, and room temperature vulcanization backfill in three joints. With very few exceptions, the DM-9 test article was flight configuration. The test was conducted under extreme weather conditions: temperature of 25 F and wind at 15 to 20 mph. Ballistics performance values were within specification requirements. The RSRM field joint (J-seal) insulation configuration functioned as predicted with no indication of hot gases reaching the capture feature O-rings. There was a blowhole in the polysulfide adhesive in the nozzle-to-case joint, but no evidence of hot gases past the wiper O-ring. Nozzle design changes appeared to perform nominally, with the exception of the outer boot ring, which suffered partial structural breakup late in the test. Field joint heaters maintained the controlling resistance temperature device temperature within the specified requirements during heater operation. The thrust vector control system operated properly. The redesigned water deluge system, temperature conditioning equipment, and other test support equipment performed as planned.

The influence of the Japanese waving cat on the joint spatial compatibility effect: A replication and extension of Dolk, Hommel, Prinz, and Liepelt (2013).

PubMed

Puffe, Lydia; Dittrich, Kerstin; Klauer, Karl Christoph

2017-01-01

In a joint go/no-go Simon task, each of two participants is to respond to one of two non-spatial stimulus features by means of a spatially lateralized response. Stimulus position varies horizontally and responses are faster and more accurate when response side and stimulus position match (compatible trial) than when they mismatch (incompatible trial), defining the social Simon effect or joint spatial compatibility effect. This effect was originally explained in terms of action/task co-representation, assuming that the co-actor's action is automatically co-represented. Recent research by Dolk, Hommel, Prinz, and Liepelt (2013) challenged this account by demonstrating joint spatial compatibility effects in a task-setting in which non-social objects like a Japanese waving cat were present, but no real co-actor. They postulated that every sufficiently salient object induces joint spatial compatibility effects. However, what makes an object sufficiently salient is so far not well defined. To scrutinize this open question, the current study manipulated auditory and/or visual attention-attracting cues of a Japanese waving cat within an auditory (Experiment 1) and a visual joint go/no-go Simon task (Experiment 2). Results revealed that joint spatial compatibility effects only occurred in an auditory Simon task when the cat provided auditory cues while no joint spatial compatibility effects were found in a visual Simon task. This demonstrates that it is not the sufficiently salient object alone that leads to joint spatial compatibility effects but instead, a complex interaction between features of the object and the stimulus material of the joint go/no-go Simon task.

The geomorphic impact of glaciers as indicated by tors in North Sweden (Aurivaara, 68° N)

NASA Astrophysics Data System (ADS)

André, Marie-Françoise

2004-02-01

Geomorphological investigations carried out on 15 tor-like features located on the Aurivaara plateau (North Sweden, 68° N) provide new insights in the greatly debated age of these landforms. Erratics and till trapped deep in the tor joints support a pre-Weichselian age for tor formation. Moreover, the occurrence of various weathering stages in allochtonous material, the joint width up to 1.5 m (requiring long-term weathering), and the frequent association of tors with pediment-like forms, suggest pre-Quaternary tor formation. The juxtaposition of fresh erratics and in situ old weathering features (mushroom rocks, concentrically weathered well-rounded corestones, and grus) indicates a predominantly cold-based regime for the Scandinavian ice sheet, with erratics carried by the overlying moving ice being repeatedly deposited on tor summits during deglaciation phases. The relationships between tors and ice action indicated for the Aurivaara plateau result in the proposal of a morphodynamical succession of five tor subtypes ranging from the preservation of well-rounded corestones still embedded in grus (suggesting negligible glacial erosion) to the almost complete removal of tor features by ice scouring. A comparison with tors in similar geological and topographical contexts from the unglaciated Dartmoor area allows a tentative evaluation of an average overall glacial erosion of 0-10 m on the northern Sweden plateaus, in sharp contrast with the 190 m overdeepening of the nearby Torneträsk basin. Thus, this case study of Swedish tors provides additional support to the recent interpretations of relict landscapes in previously glaciated areas and is in accordance with the classical «model» of glacial selective erosion established in the Nordic and Arctic mountains.

Progression of cartilage damage and meniscal pathology over 30 months is associated with an increase in radiographic tibiofemoral joint space narrowing in persons with knee OA--the MOST study.

PubMed

Crema, M D; Nevitt, M C; Guermazi, A; Felson, D T; Wang, K; Lynch, J A; Marra, M D; Torner, J; Lewis, C E; Roemer, F W

2014-10-01

To determine the association of MRI-assessed worsening of tibiofemoral cartilage damage, meniscal damage, meniscal extrusion, separately and together, with progression of radiographic joint space narrowing (JSN). The Multicenter Osteoarthitis Study (MOST) Study is a cohort study of subjects with or at risk for knee osteoarthritis (OA). Knees with radiographic OA Kellgren-Lawrence grade 2 at baseline and with baseline and 30-month 1.0 T MRIs were selected for reading using the WORMS system for cartilage damage, meniscal damage, and meniscal extrusion. The association of worsening of cartilage damage, meniscal damage, and/or meniscal extrusion with increases in the JSN was performed using logistic regression. A total of 276 knees (one per subject) were included (women 68.5%, mean age 62.9 ± 7.8, mean body mass index (BMI) 30.2 ± 5.0). Worsening of each MRI feature was associated with any increase in JSN (P < 0.01). Worsening of cartilage damage was more frequently observed than worsening of meniscal damage and extrusion, and was significantly associated with both slow and fast progression of JSN. An increasing risk of JSN worsening was associated with increasing number of worsening MRI features (P for trend < 0.0001). Worsening of tibiofemoral cartilage damage, meniscal damage, and meniscal extrusion are independent predictors of JSN progression in the same compartment. Worsening of cartilage damage is more frequently observed in JSN when compared to meniscal worsening. A strong cumulative effect on JSN progression is observed for worsening of more than one MRI feature. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

A semisupervised support vector regression method to estimate biophysical parameters from remotely sensed images

NASA Astrophysics Data System (ADS)

Castelletti, Davide; Demir, Begüm; Bruzzone, Lorenzo

2014-10-01

This paper presents a novel semisupervised learning (SSL) technique defined in the context of ɛ-insensitive support vector regression (SVR) to estimate biophysical parameters from remotely sensed images. The proposed SSL method aims to mitigate the problems of small-sized biased training sets without collecting any additional samples with reference measures. This is achieved on the basis of two consecutive steps. The first step is devoted to inject additional priors information in the learning phase of the SVR in order to adapt the importance of each training sample according to distribution of the unlabeled samples. To this end, a weight is initially associated to each training sample based on a novel strategy that defines higher weights for the samples located in the high density regions of the feature space while giving reduced weights to those that fall into the low density regions of the feature space. Then, in order to exploit different weights for training samples in the learning phase of the SVR, we introduce a weighted SVR (WSVR) algorithm. The second step is devoted to jointly exploit labeled and informative unlabeled samples for further improving the definition of the WSVR learning function. To this end, the most informative unlabeled samples that have an expected accurate target values are initially selected according to a novel strategy that relies on the distribution of the unlabeled samples in the feature space and on the WSVR function estimated at the first step. Then, we introduce a restructured WSVR algorithm that jointly uses labeled and unlabeled samples in the learning phase of the WSVR algorithm and tunes their importance by different values of regularization parameters. Experimental results obtained for the estimation of single-tree stem volume show the effectiveness of the proposed SSL method.

Geophysical imaging of karst features in Missouri

NASA Astrophysics Data System (ADS)

Obi, Jeremiah Chukwunonso

Automated electrical resistivity tomography (ERT) supported with multichannel analysis of surface waves (MASW) and boring data were used to map karst related features in Missouri in order to understand karst processes better in Missouri. Previous works on karst in Missouri were mostly surficial mapping of bedrock outcrops and joints, which are not enough to define the internal structure of karst system, since most critical processes in karst occur underground. To understand these processes better, the density, placement and pattern of karst related features like solution-widened joints and voids, as well as top of bedrock were mapped. In the course of the study, six study sites were visited in Missouri. The sites were in Nixa, Gasconade River Bridge in Lebanon, Battlefield, Aurora, Protem and Richland. The case studies reflect to a large extent some of the problems inherent in karst terrain, ranging from environmental problems to structural problems especially sinkhole collapses. The result of the study showed that karst in Missouri is mostly formed as a result of piping of sediments through solution-widened joints, with a pattern showing that the joints/fractures are mostly filled with moist clay-sized materials of low resistivity values. The highest density of mapped solution-widened joints was one in every one hundred and fifty feet, and these areas are where intense dissolution is taking place, and bedrock pervasively fractured. The study also showed that interpreted solution-widened joints trend in different directions, and often times conform with known structural lineaments in the area. About 40% of sinkhole collapses in the study areas are anthropogenic. Karst in Missouri varies, and can be classified as a combination of kI (juvenile), kIII (mature) and kIV (complex) karsts.

Spacesuit mobility knee joints

NASA Technical Reports Server (NTRS)

Vykukal, H. C. (Inventor)

1979-01-01

Pressure suit mobility joints are for use in interconnecting adjacent segments of an hermetically sealed spacesuit in which low torques, low leakage and a high degree of reliability are required. Each of the joints is a special purpose joint characterized by substantially constant volume and low torque characteristics and includes linkages which restrain the joint from longitudinal distension and includes a flexible, substantially impermeable diaphragm of tubular configuration spanning the distance between pivotally supported annuli. The diaphragms of selected joints include rolling convolutions for balancing the joints, while various joints include wedge-shaped sections which enhance the range of motion for the joints.

Joint probabilities and quantum cognition

NASA Astrophysics Data System (ADS)

de Barros, J. Acacio

2012-12-01

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

Migrating lumbar facet joint cysts.

PubMed

Palmieri, Francesco; Cassar-Pullicino, Victor N; Lalam, Radhesh K; Tins, Bernhard J; Tyrrell, Prudencia N M; McCall, Iain W

2006-04-01

The majority of lumbar facet joint cysts (LFJCs) are located in the spinal canal, on the medial aspect of the facet joint with characteristic diagnostic features. When they migrate away from the joint of origin, they cause diagnostic problems. In a 7-year period we examined by computed tomography (CT) and magnetic resonance (MR) imaging five unusual cases of facet joint cysts which migrated from the facet joint of origin. Three LFJCs were identified in the right S1 foramen, one in the right L5-S1 neural foramen and one in the left erector spinae and multifidus muscles between the levels of L2-L4 spinous process. Awareness that spinal lesions identified at MRI and CT could be due to migrating facet joint cyst requires a high level of suspicion. The identification of the appositional contact of the cyst and the facet joint needs to be actively sought in the presence of degenerative facet joints.

Joint modelling of potentially avoidable hospitalisation for five diseases accounting for spatiotemporal effects: A case study in New South Wales, Australia.

PubMed

Baker, Jannah; White, Nicole; Mengersen, Kerrie; Rolfe, Margaret; Morgan, Geoffrey G

2017-01-01

Three variant formulations of a spatiotemporal shared component model are proposed that allow examination of changes in shared underlying factors over time. Models are evaluated within the context of a case study examining hospitalisation rates for five chronic diseases for residents of a regional area in New South Wales: type II diabetes mellitus (DMII), chronic obstructive pulmonary disease (COPD), coronary arterial disease (CAD), hypertension (HT) and congestive heart failure (CHF) between 2001-2006. These represent ambulatory care sensitive (ACS) conditions, often used as a proxy for avoidable hospitalisations. Using a selected model, the effects of socio-economic status (SES) as a shared component are estimated and temporal patterns in the influence of the residual shared spatial component are examined. Choice of model depends upon the application. In the featured application, a model allowing for changing influence of the shared spatial component over time was found to have the best fit and was selected for further analyses. Hospitalisation rates were found to be increasing for COPD and DMII, decreasing for CHF and stable for CAD and HT. SES was substantively associated with hospitalisation rates, with differing degrees of influence for each disease. In general, most of the spatial variation in hospitalisation rates was explained by disease-specific spatial components, followed by the residual shared spatial component. Appropriate selection of a joint disease model allows for the examination of temporal patterns of disease outcomes and shared underlying spatial factors, and distinction between different shared spatial factors.

Object-Part Attention Model for Fine-Grained Image Classification

NASA Astrophysics Data System (ADS)

Peng, Yuxin; He, Xiangteng; Zhao, Junjie

2018-03-01

Fine-grained image classification is to recognize hundreds of subcategories belonging to the same basic-level category, such as 200 subcategories belonging to the bird, which is highly challenging due to large variance in the same subcategory and small variance among different subcategories. Existing methods generally first locate the objects or parts and then discriminate which subcategory the image belongs to. However, they mainly have two limitations: (1) Relying on object or part annotations which are heavily labor consuming. (2) Ignoring the spatial relationships between the object and its parts as well as among these parts, both of which are significantly helpful for finding discriminative parts. Therefore, this paper proposes the object-part attention model (OPAM) for weakly supervised fine-grained image classification, and the main novelties are: (1) Object-part attention model integrates two level attentions: object-level attention localizes objects of images, and part-level attention selects discriminative parts of object. Both are jointly employed to learn multi-view and multi-scale features to enhance their mutual promotions. (2) Object-part spatial constraint model combines two spatial constraints: object spatial constraint ensures selected parts highly representative, and part spatial constraint eliminates redundancy and enhances discrimination of selected parts. Both are jointly employed to exploit the subtle and local differences for distinguishing the subcategories. Importantly, neither object nor part annotations are used in our proposed approach, which avoids the heavy labor consumption of labeling. Comparing with more than 10 state-of-the-art methods on 4 widely-used datasets, our OPAM approach achieves the best performance.

Engine Load Path Calculations - Project Neo

NASA Technical Reports Server (NTRS)

Fisher, Joseph

2014-01-01

A mathematical model of the engine and actuator geometry was developed and used to perform a static force analysis of the system with the engine at different pitch and yaw angles. This analysis yielded the direction and magnitude of the reaction forces at the mounting points of the engine and actuators. These data were used to validate the selection of the actuators installed in the system and to design a new spherical joint to mount the engine on the test fixture. To illustrate the motion of the system and to further interest in the project, a functional 3D printed version of the system was made, featuring the full mobility of the real system.

Digital Holography and 3D Imaging: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America B.

PubMed

Banerjee, Partha P; Osten, Wolfgang; Picart, Pascal; Cao, Liangcai; Nehmetallah, George

2017-05-01

The OSA Topical Meeting on Digital Holography and 3D Imaging (DH) was held 25-28 July 2016 in Heidelberg, Germany, as part of the Imaging Congress. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year, AO and the Journal of the Optical Society of America B (JOSA B) jointly decided to have one such feature issue in each journal. This feature issue includes 31 papers in AO and 11 in JOSA B, and covers a large range of topics, reflecting the rapidly expanding techniques and applications of digital holography and 3D imaging. The upcoming DH meeting (DH 2017) will be held from 29 May to 1 June in Jeju Island, South Korea.

Anaerobic prosthetic joint infection.

PubMed

Shah, Neel B; Tande, Aaron J; Patel, Robin; Berbari, Elie F

2015-12-01

In an effort to improve mobility and alleviate pain from degenerative and connective tissue joint disease, an increasing number of individuals are undergoing prosthetic joint replacement in the United States. Joint replacement is a highly effective intervention, resulting in improved quality of life and increased independence [1]. By 2030, it is predicted that approximately 4 million total hip and knee arthroplasties will be performed yearly in the United States [2]. One of the major complications associated with this procedure is prosthetic joint infection (PJI), occurring at a rate of 1-2% [3-7]. In 2011, the Musculoskeletal Infectious Society created a unifying definition for prosthetic joint infection [8]. The following year, the Infectious Disease Society of America published practice guidelines that focused on the diagnosis and management of PJI. These guidelines focused on the management of commonly encountered organisms associated with PJI, including staphylococci, streptococci and select aerobic Gram-negative bacteria. However, with the exception of Propionibacterium acnes, management of other anaerobic organisms was not addressed in these guidelines [1]. Although making up approximately 3-6% of PJI [9,10], anaerobic microorganisms cause devastating complications, and similar to the more common organisms associated with PJI, these bacteria also result in significant morbidity, poor outcomes and increased health-care costs. Data on diagnosis and management of anaerobic PJI is mostly derived from case reports, along with a few cohort studies [3]. There is a paucity of published data outlining factors associated with risks, diagnosis and management of anaerobic PJI. We therefore reviewed available literature on anaerobic PJI by systematically searching the PubMed database, and collected data from secondary searches to determine information on pathogenesis, demographic data, clinical features, diagnosis and management. We focused our search on five commonly encountered anaerobic organisms associated with PJI. Since anaerobic PJI has also been linked to dental procedures, we also reviewed information on the use of dental procedures and prophylaxis, when available. Copyright © 2015 Elsevier Ltd. All rights reserved.

Joint inversion of teleseismic receiver functions and magnetotelluric data using a genetic algorithm: Are seismic velocities and electrical conductivities compatible?

NASA Astrophysics Data System (ADS)

Moorkamp, M.; Jones, A. G.; Eaton, D. W.

2007-08-01

Joint inversion of different kinds of geophysical data has the potential to improve model resolution, under the assumption that the different observations are sensitive to the same subsurface features. Here, we examine the compatibility of P-wave teleseismic receiver functions and long-period magnetotelluric (MT) observations, using joint inversion, to infer one-dimensional lithospheric structure. We apply a genetic algorithm to invert teleseismic and MT data from the Slave craton; a region where previous independent analyses of these data have indicated correlated layering of the lithosphere. Examination of model resolution and parameter trade-off suggests that the main features of this area, the Moho, Central Slave Mantle Conductor and the Lithosphere-Asthenosphere boundary, are sensed to varying degrees by both methods. Thus, joint inversion of these two complementary data sets can be used to construct improved models of the lithosphere. Further studies will be needed to assess whether the approach can be applied globally.

Geometric features of workspace and joint-space paths of 3D reaching movements.

PubMed

Klein Breteler, M D; Meulenbroek, R G; Gielen, S C

1998-11-01

The present study focuses on geometric features of workspace and joint-space paths of three-dimensional reaching movements. Twelve subjects repeatedly performed a three-segment, triangular-shaped movement pattern in an approximately 60 degrees tilted horizontal plane. Task variables elicited movement patterns that varied in position, rotational direction and speed. Trunk, arm, hand and finger-tip movements were recorded by means of a 3D motion-tracking system. Angular excursions of the shoulder and elbow joints were extracted from position data. Analyses of the shape of 3D workspace and joint-space paths focused on the extent to which the submovements were produced in a plane, and on the curvature of the central parts of the submovements. A systematic tendency to produce movements in a plane was found in addition to an increase of finger-tip path curvature with increasing speed. The findings are discussed in relation to the role of optimization principles in trajectory-formation models.

Texture, microstructure, and fractal features of the low-cycle fatigue failure of the metal in pipeline welded joints

NASA Astrophysics Data System (ADS)

Usov, V. V.; Gopkalo, E. E.; Shkatulyak, N. M.; Gopkalo, A. P.; Cherneva, T. S.

2015-09-01

Crystallographic texture and fracture features are studied after low-cycle fatigue tests of laboratory specimens cut from the base metal and the characteristic zones of a welded joint in a pipeline after its longterm operation. The fractal dimensions of fracture surfaces are determined. The fractal dimension is shown to increase during the transition from ductile to quasi-brittle fracture, and a relation between the fractal dimension of a fracture surface and the fatigue life of the specimen is found.

A Lossless Multichannel Bio-Signal Compression Based on Low-Complexity Joint Coding Scheme for Portable Medical Devices

PubMed Central

Kim, Dong-Sun; Kwon, Jin-San

2014-01-01

Research on real-time health systems have received great attention during recent years and the needs of high-quality personal multichannel medical signal compression for personal medical product applications are increasing. The international MPEG-4 audio lossless coding (ALS) standard supports a joint channel-coding scheme for improving compression performance of multichannel signals and it is very efficient compression method for multi-channel biosignals. However, the computational complexity of such a multichannel coding scheme is significantly greater than that of other lossless audio encoders. In this paper, we present a multichannel hardware encoder based on a low-complexity joint-coding technique and shared multiplier scheme for portable devices. A joint-coding decision method and a reference channel selection scheme are modified for a low-complexity joint coder. The proposed joint coding decision method determines the optimized joint-coding operation based on the relationship between the cross correlation of residual signals and the compression ratio. The reference channel selection is designed to select a channel for the entropy coding of the joint coding. The hardware encoder operates at a 40 MHz clock frequency and supports two-channel parallel encoding for the multichannel monitoring system. Experimental results show that the compression ratio increases by 0.06%, whereas the computational complexity decreases by 20.72% compared to the MPEG-4 ALS reference software encoder. In addition, the compression ratio increases by about 11.92%, compared to the single channel based bio-signal lossless data compressor. PMID:25237900

Selection of test paths for solder joint intermittent connection faults under DC stimulus

NASA Astrophysics Data System (ADS)

Huakang, Li; Kehong, Lv; Jing, Qiu; Guanjun, Liu; Bailiang, Chen

2018-06-01

The test path of solder joint intermittent connection faults under direct-current stimulus is examined in this paper. According to the physical structure of the circuit, a network model is established first. A network node is utilised to represent the test node. The path edge refers to the number of intermittent connection faults in the path. Then, the selection criteria of the test path based on the node degree index are proposed and the solder joint intermittent connection faults are covered using fewer test paths. Finally, three circuits are selected to verify the method. To test if the intermittent fault is covered by the test paths, the intermittent fault is simulated by a switch. The results show that the proposed method can detect the solder joint intermittent connection fault using fewer test paths. Additionally, the number of detection steps is greatly reduced without compromising fault coverage.

Selective buckling via states of self-stress in topological metamaterials

PubMed Central

Paulose, Jayson; Meeussen, Anne S.; Vitelli, Vincenzo

2015-01-01

States of self-stress—tensions and compressions of structural elements that result in zero net forces—play an important role in determining the load-bearing ability of structures ranging from bridges to metamaterials with tunable mechanical properties. We exploit a class of recently introduced states of self-stress analogous to topological quantum states to sculpt localized buckling regions in the interior of periodic cellular metamaterials. Although the topological states of self-stress arise in the linear response of an idealized mechanical frame of harmonic springs connected by freely hinged joints, they leave a distinct signature in the nonlinear buckling behavior of a cellular material built out of elastic beams with rigid joints. The salient feature of these localized buckling regions is that they are indistinguishable from their surroundings as far as material parameters or connectivity of their constituent elements are concerned. Furthermore, they are robust against a wide range of structural perturbations. We demonstrate the effectiveness of this topological design through analytical and numerical calculations as well as buckling experiments performed on two- and three-dimensional metamaterials built out of stacked kagome lattices. PMID:26056303

Effects of squats accompanied by hip joint adduction on the selective activity of the vastus medialis oblique.

PubMed

Hyong, In Hyouk

2015-06-01

[Purpose] This study evaluated the effective selective activation method of the vastus medialis oblique for knee joint stabilization in patients with patellofemoral pain syndrome. [Subjects and Methods] Fifteen healthy college students (9 males, 6 females); mean age, height, and weight: 22.2 years, 167.8 cm, and 61.4 kg, respectively) participated. The knee angle was held at 60°. Muscle activities were measured once each during an ordinary squat and a squat accompanied by hip joint adduction. The muscle activities of the vastus medialis oblique and vastus lateralis were measured by electromyography for five seconds while maintaining 60° knee flexion. Electromyography signals were obtained at a sampling rate of 1,000 Hz and band pass filtering at 20-50 Hz. The obtained raw root mean square was divided by the maximal voluntary isometric contraction and expressed as a percentage. The selective activity of the vastus medialis oblique was assessed according to the muscle activity ratio of the vastus medialis oblique to the vastus lateralis. [Results] The activity ratio of the vastus medialis oblique was higher during a squat with hip joint adduction than without. [Conclusion] A squat accompanied by hip joint adduction is effective for the selective activation of the vastus medialis oblique.

Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach.

PubMed

Armañanzas, Rubén; Bielza, Concha; Chaudhuri, Kallol Ray; Martinez-Martin, Pablo; Larrañaga, Pedro

2013-07-01

Is it possible to predict the severity staging of a Parkinson's disease (PD) patient using scores of non-motor symptoms? This is the kickoff question for a machine learning approach to classify two widely known PD severity indexes using individual tests from a broad set of non-motor PD clinical scales only. The Hoehn & Yahr index and clinical impression of severity index are global measures of PD severity. They constitute the labels to be assigned in two supervised classification problems using only non-motor symptom tests as predictor variables. Such predictors come from a wide range of PD symptoms, such as cognitive impairment, psychiatric complications, autonomic dysfunction or sleep disturbance. The classification was coupled with a feature subset selection task using an advanced evolutionary algorithm, namely an estimation of distribution algorithm. Results show how five different classification paradigms using a wrapper feature selection scheme are capable of predicting each of the class variables with estimated accuracy in the range of 72-92%. In addition, classification into the main three severity categories (mild, moderate and severe) was split into dichotomic problems where binary classifiers perform better and select different subsets of non-motor symptoms. The number of jointly selected symptoms throughout the whole process was low, suggesting a link between the selected non-motor symptoms and the general severity of the disease. Quantitative results are discussed from a medical point of view, reflecting a clear translation to the clinical manifestations of PD. Moreover, results include a brief panel of non-motor symptoms that could help clinical practitioners to identify patients who are at different stages of the disease from a limited set of symptoms, such as hallucinations, fainting, inability to control body sphincters or believing in unlikely facts. Copyright © 2013 Elsevier B.V. All rights reserved.

Space station rotary joint mechanisms

NASA Technical Reports Server (NTRS)

Driskill, Glen W.

1986-01-01

The mechanism which will be used on the space station to position the solar arrays and radiator panels for Sun pointing and Sun avoidance is described. The unique design features will be demonstrated on advanced development models of two of the joints being fabricated under contract to NASA-MSFC.

Functional anatomy of the temporomandibular joint (I).

PubMed

Sava, Anca; Scutariu, Mihaela Monica

2012-01-01

Jaw movement is analyzed as the action between two rigid components jointed together in a particular way, the movable mandible against the stabilized cranium. Jaw articulation distinguishes form most other synovial joints of the body by the coincidence of certain characteristic features. Its articular surfaces are not covered by hyaline cartilage as elsewhere. The two jointed components carry teeth the shape, position and occlusion of which having a unique influence on specific positions and movements within the joint. A fibrocartilaginous disc is interposed between upper and lower articular surfaces; this disc compensates for the incongruities in opposing parts and allows sliding, pivoting, and rotating movements between the bony components. These are the reasons for our review of the functional anatomy of the temporomandibular joint.

Fires, A Joint Professional Bulletin for US Field & Air Defense Artillerymen. March-April 2008

DTIC Science & Technology

2008-04-01

actions. However, if the effects synchronization division were not added to the lineup , just the teaming of joint fires division and IO division still...ADAFCO would be the liaison between the two Services who coordinates fires and facilitates track identification thus preventing fratricide. Joint...decisions to be made based on current air users versus planned control measures. Interoperability. Identification is a key feature that enables AC2 nodes

Spent Fuel Test-Climax: core logging for site investigation and instrumentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilder, D.G.; Yow, J.L. Jr.; Thorpe, R.K.

1982-05-28

As an integral part of the Spent Fuel Test-Climax 5150 ft (1570 m) of granite core was obtained. This core was diamond drilled in various sizes, mainly 38-mm and 76-mm diameters. The core was teken with single tube core barrels and was unoriented. Techniques used to drill and log this core are discussed, as well as techniques to orient the core. Of the 5150 ft (1570 m) of core more than 3645 ft (1111 m) was retained and logged in some detail. As a result of the core logging, geologic discontinuities were identified, joint frequency and spacing characterized. Discontinuities identifiedmore » included several joint sets, shear zones and faults. Correlations based on coring along were generally found to be impossible, even for the more prominent features. The only feature properly correlated from the exploratory drilling was the fault system at the end of the facility, but it was not identified from the exploratory core as a fault. Identification of discontinuities was later helped by underground mapping that identified several different joint sets with different characteristics. It was found that joint frequency varied from 0.3 to 1.1 joint per foot of core for open fractures and from 0.3 to 3.3/ft for closed or healed fractures. Histograms of fracture spacing indicate that there is likely a random distribution of spacing superimposed upon uniformly spaced fractures. It was found that a low angle joint set had a persistent mean orientation. These joints were healed and had pervasive wall rock alteration which made identification of joints in this set possible. The recognition of a joint set with known attitude allowed orientation of much of the core. This orientation technique was found to be effective. 10 references, 25 figures, 4 tables.« less

Correlations between the feature of sagittal spinopelvic alignment and facet joint degeneration: a retrospective study.

PubMed

Lv, Xin; Liu, Yuan; Zhou, Song; Wang, Qiang; Gu, Houyun; Fu, Xiaoxing; Ding, Yi; Zhang, Bin; Dai, Min

2016-08-15

Sagittal spinopelvic alignment changes associated with degenerative facet joint arthritis have been assessed in a few studies. It has been documented that patients with facet joint degeneration have higher pelvic incidence, but the relationship between facet joint degeneration and other sagittal spinopelvic alignment parameters is still disputed. Our purpose was to evaluate the correlation between the features of sagittal spinopelvic alignment and facet joint degeneration. Imaging data of 140 individuals were retrospectively analysed. Lumbar lordosis, pelvic tilt (PT), pelvic incidence (PI), sacral slope, and height of the lumbar intervertebral disc were measured on lumbar X-ray plates. Grades of facet joint degeneration were evaluated from the L2 to S1 on CT scans. Spearman's rank correlation coefficient and Student's t-test were used for statistical analyses, and a P-value <0.05 was considered statistically significant. PI was positively associated with degeneration of the facet joint at lower lumbar levels (p < 0.001 r = 0.50 at L5/S1 and P = 0.002 r = 0.25 at L4/5). A significant increase of PT was found in the severe degeneration group compared with the mild degeneration group: 22.0° vs 15.7°, P = 0.034 at L2/3;21.4°vs 15.1°, P = 0.006 at L3/4; 21.0° vs 13.5°, P = 0.000 at L4/5; 20.8° vs 12.1°, P = 0.000 at L5/S1. Our results indicate that a high PI is a predisposing factor for facet joint degeneration at the lower lumbar spine, and that severe facet joint degeneration may accompany with greater PT at lumbar spine.

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning.

PubMed

Kia, Seyed Mostafa; Pedregosa, Fabian; Blumenthal, Anna; Passerini, Andrea

2017-06-15

The use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. To facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. Our experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. We compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. These results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models. Copyright © 2017 Elsevier B.V. All rights reserved.

Walk and roll robot

NASA Technical Reports Server (NTRS)

Wilson, Andrew (Inventor); Punnoose, Andrew (Inventor); Strausser, Katherine (Inventor); Parikh, Neil (Inventor)

2011-01-01

A mobile robotic unit features a main body, a plurality of legs for supporting the main body on and moving the main body in forward and reverse directions about a base surface, and a drive assembly. According to an exemplary embodiment each leg includes a respective pivotal hip joint, a pivotal knee joint, and a wheeled foot adapted to roll along the base surface. Also according to an exemplary embodiments the drive assembly includes a motor operatively associated with the hip and knee joints and the wheeled foot for independently driving pivotal movement of the hip joint and the knee joint and rolling motion of the wheeled foot. The hip joint may include a ball-and-socket-type joint interconnecting top portion of the leg to the main body, such that the hip joint is adapted to pivot said leg in a direction transverse to a forward-and-reverse direction.

Salient in space, salient in time: Fixation probability predicts fixation duration during natural scene viewing.

PubMed

Einhäuser, Wolfgang; Nuthmann, Antje

2016-09-01

During natural scene viewing, humans typically attend and fixate selected locations for about 200-400 ms. Two variables characterize such "overt" attention: the probability of a location being fixated, and the fixation's duration. Both variables have been widely researched, but little is known about their relation. We use a two-step approach to investigate the relation between fixation probability and duration. In the first step, we use a large corpus of fixation data. We demonstrate that fixation probability (empirical salience) predicts fixation duration across different observers and tasks. Linear mixed-effects modeling shows that this relation is explained neither by joint dependencies on simple image features (luminance, contrast, edge density) nor by spatial biases (central bias). In the second step, we experimentally manipulate some of these features. We find that fixation probability from the corpus data still predicts fixation duration for this new set of experimental data. This holds even if stimuli are deprived of low-level images features, as long as higher level scene structure remains intact. Together, this shows a robust relation between fixation duration and probability, which does not depend on simple image features. Moreover, the study exemplifies the combination of empirical research on a large corpus of data with targeted experimental manipulations.

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

NASA Astrophysics Data System (ADS)

Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

Fusion reactor blanket/shield design study

NASA Astrophysics Data System (ADS)

Smith, D. L.; Clemmer, R. G.; Harkness, S. D.; Jung, J.; Krazinski, J. L.; Mattas, R. F.; Stevens, H. C.; Youngdahl, C. K.; Trachsel, C.; Bowers, D.

1979-07-01

A joint study of Tokamak reactor first wall/blanket/shield technology was conducted to identify key technological limitations for various tritium breeding blanket design concepts, establishment of a basis for assessment and comparison of the design features of each concept, and development of optimized blanket designs. The approach used involved a review of previously proposed blanket designs, analysis of critical technological problems and design features associated with each of the blanket concepts, and a detailed evaluation of the most tractable design concepts. Tritium breeding blanket concepts were evaluated according to the proposed coolant. The effort concentrated on evaluation of lithium and water cooled blanket designs and helium and molten salt cooled designs. Generalized nuclear analysis of the tritium breeding performance, an analysis of tritium breeding requirements, and a first wall stress analysis were conducted as part of the study. The impact of coolant selection on the mechanical design of a Tokamak reactor was evaluated. Reference blanket designs utilizing the four candidate coolants are presented.

Accumulating pyramid spatial-spectral collaborative coding divergence for hyperspectral anomaly detection

NASA Astrophysics Data System (ADS)

Sun, Hao; Zou, Huanxin; Zhou, Shilin

2016-03-01

Detection of anomalous targets of various sizes in hyperspectral data has received a lot of attention in reconnaissance and surveillance applications. Many anomaly detectors have been proposed in literature. However, current methods are susceptible to anomalies in the processing window range and often make critical assumptions about the distribution of the background data. Motivated by the fact that anomaly pixels are often distinctive from their local background, in this letter, we proposed a novel hyperspectral anomaly detection framework for real-time remote sensing applications. The proposed framework consists of four major components, sparse feature learning, pyramid grid window selection, joint spatial-spectral collaborative coding and multi-level divergence fusion. It exploits the collaborative representation difference in the feature space to locate potential anomalies and is totally unsupervised without any prior assumptions. Experimental results on airborne recorded hyperspectral data demonstrate that the proposed methods adaptive to anomalies in a large range of sizes and is well suited for parallel processing.

Mixture Rasch Models with Joint Maximum Likelihood Estimation

ERIC Educational Resources Information Center

Willse, John T.

2011-01-01

This research provides a demonstration of the utility of mixture Rasch models. Specifically, a model capable of estimating a mixture partial credit model using joint maximum likelihood is presented. Like the partial credit model, the mixture partial credit model has the beneficial feature of being appropriate for analysis of assessment data…

University Research and Development Activities: The Federal Income Tax Consequences of Research Contracts, Research Subsidiaries and Joint Ventures.

ERIC Educational Resources Information Center

Kertz, Consuelo Lauda; Hasson, James K., Jr.

1986-01-01

Features of the federal income tax law applying to income received from commercially funded university-based scientific research and development activities are discussed, including: industry-sponsored research contracts, separately incorporated entities, partnerships and joint ventures, subsidiaries and unrelated income consequences of…

[Epiphyseal osteoid osteoma].

PubMed

Villas, C; Garbayo, A J; Martínez Denegri, J; Cañadell, J

1990-01-01

Three more cases of osteoid osteoma located in epiphysis are presented. All of them had special features, as a reactive synovitis due to the proximity of the lesion to the joint and the lower movility arch of these joints. The x-ray was essential for the diagnosis and definitive treatment was surgical resection.

High‐resolution ultrasonography of the first metatarsal phalangeal joint in gout: a controlled study

PubMed Central

Wright, Stephen A; Filippucci, Emilio; McVeigh, Claire; Grey, Arthur; McCarron, Maura; Grassi, Walter; Wright, Gary D; Taggart, Allister J

2007-01-01

Objective To compare high‐resolution ultrasound (HRUS) with conventional radiography in the detection of erosions in the first metatarsophalangeal joints (1st MTPJs) of patients with gout and to identify the characteristic sonographic features of gout. Methods HRUS examination of the 1st MTPJs of both feet was performed by two independent sonographers. The presence of joint and soft‐tissue pathology was recorded. x Ray examination of the feet was performed on the same day and reported by the same radiologist. Results 39 male patients with gout and 22 age‐matched control subjects (14 with an inflammatory arthropathy and 8 disease free) were studied. The agreement on erosion between HRUS and x ray was poor, κ = 0.229 (non‐weighted), with McNemar's test being significant (p<0.001) indicating a large number of false negative x rays. 22 MTPJs in patients with gout had never been subjected to a clinical attack of acute gout. In these MTPJs, there were 10 erosions detected by HRUS and 3 erosions on x ray. HRUS features significantly more prevalent in the patients with gout were hard and soft tophus‐like lesions (p<0.01) and the double contour sign (p<0.01). Conclusions These data show that HRUS may assist in the management of gout in two ways: first, by aiding in the diagnosis by identifying the sonographic features that may be representative of the disease, and, second, by allowing the early detection of erosive joint damage and/or tophaceous deposits even in clinically silent joints. PMID:17185326

Features that exacerbate fatigue severity in joint hypermobility syndrome/Ehlers-Danlos syndrome - hypermobility type.

PubMed

Krahe, Anne Maree; Adams, Roger David; Nicholson, Leslie Lorenda

2018-08-01

To assess the prevalence, severity and impact of fatigue on individuals with joint hypermobility syndrome (JHS)/Ehlers-Danlos syndrome - hypermobility type (EDS-HT) and establish potential determinants of fatigue severity in this population. Questionnaires on symptoms and signs related to fatigue, quality of life, mental health, physical activity participation and sleep quality were completed by people with JHS/EDS-HT recruited through two social media sites. Multiple regression analysis was performed to identify predictors of fatigue in this population. Significant fatigue was reported by 79.5% of the 117 participants. Multiple regression analysis identified five predictors of fatigue severity, four being potentially modifiable, accounting for 52.3% of the variance in reported fatigue scores. Predictors of fatigue severity were: the self-perceived extent of joint hypermobility, orthostatic dizziness related to heat and exercise, levels of participation in personal relationships and community, current levels of physical activity and dissatisfaction with the diagnostic process and management options provided for their condition. Fatigue is a significant symptom associated with JHS/EDS-HT. Assessment of individuals with this condition should include measures of fatigue severity to enable targeted management of potentially modifiable factors associated with fatigue severity. Implications for rehabilitation Fatigue is a significant symptom reported by individuals affected by joint hypermobility syndrome/Ehlers-Danlos syndrome - hypermobility type. Potentially modifiable features that contribute to fatigue severity in this population have been identified. Targeted management of these features may decrease the severity and impact of fatigue in joint hypermobility syndrome/Ehlers-Danlos syndrome - hypermobility type.

Digital Holography and 3D Imaging: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America A.

PubMed

Kang, Hoonjong; Lee, Byoungho; Kozacki, Tomasz; Picart, Pascal; Situ, Guohai

2018-01-01

The OSA Topical Meeting on Digital Holography and 3D Imaging (DH) was held 29 May to 1 June 2017 in Jeju Island, South Korea. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year, AO and the Journal of the Optical Society of America A (JOSA A) jointly decided to have one such feature issue in each journal. This feature issue includes 33 papers in AO and 9 in JOSA A and covers a large range of topics, reflecting the rapidly expanding techniques and applications of digital holography and 3D imaging. The upcoming DH meeting (DH 2018) will be held 25-28 June 2018 in Orlando, Florida, USA, as part of the OSA Imaging and Applied Optics Congress.

Digital Holography and 3D Imaging: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America A.

PubMed

Kang, Hoonjong; Lee, Byoungho; Kozacki, Tomasz; Picart, Pascal; Situ, Guohai

2018-01-01

The OSA Topical Meeting on Digital Holography and 3D Imaging (DH) was held 29 May to 1 June 2017 on Jeju Island, South Korea. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year, AO and the Journal of the Optical Society of America A (JOSA A) jointly decided to have one such feature issue in each journal. This feature issue includes 33 papers in AO and 9 in JOSA A and covers a large range of topics, reflecting the rapidly expanding techniques and applications of digital holography and 3D imaging. The upcoming DH meeting (DH 2018) will be held 25-28 June 2018 in Orlando, Florida, as part of the OSA Imaging and Applied Optics Congress.

Knee Joint Vibration Signal Analysis with Matching Pursuit Decomposition and Dynamic Weighted Classifier Fusion

PubMed Central

Cai, Suxian; Yang, Shanshan; Zheng, Fang; Lu, Meng; Wu, Yunfeng; Krishnan, Sridhar

2013-01-01

Analysis of knee joint vibration (VAG) signals can provide quantitative indices for detection of knee joint pathology at an early stage. In addition to the statistical features developed in the related previous studies, we extracted two separable features, that is, the number of atoms derived from the wavelet matching pursuit decomposition and the number of significant signal turns detected with the fixed threshold in the time domain. To perform a better classification over the data set of 89 VAG signals, we applied a novel classifier fusion system based on the dynamic weighted fusion (DWF) method to ameliorate the classification performance. For comparison, a single leastsquares support vector machine (LS-SVM) and the Bagging ensemble were used for the classification task as well. The results in terms of overall accuracy in percentage and area under the receiver operating characteristic curve obtained with the DWF-based classifier fusion method reached 88.76% and 0.9515, respectively, which demonstrated the effectiveness and superiority of the DWF method with two distinct features for the VAG signal analysis. PMID:23573175

Effect of window length on performance of the elbow-joint angle prediction based on electromyography

NASA Astrophysics Data System (ADS)

Triwiyanto; Wahyunggoro, Oyas; Adi Nugroho, Hanung; Herianto

2017-05-01

The high performance of the elbow joint angle prediction is essential on the development of the devices based on electromyography (EMG) control. The performance of the prediction depends on the feature of extraction parameters such as window length. In this paper, we evaluated the effect of the window length on the performance of the elbow-joint angle prediction. The prediction algorithm consists of zero-crossing feature extraction and second order of Butterworth low pass filter. The feature was used to extract the EMG signal by varying window length. The EMG signal was collected from the biceps muscle while the elbow was moved in the flexion and extension motion. The subject performed the elbow motion by holding a 1-kg load and moved the elbow in different periods (12 seconds, 8 seconds and 6 seconds). The results indicated that the window length affected the performance of the prediction. The 250 window lengths yielded the best performance of the prediction algorithm of (mean±SD) root mean square error = 5.68%±1.53% and Person’s correlation = 0.99±0.0059.

Association between Patient History and Physical Examination and Osteoarthritis after Ankle Sprain.

PubMed

van Ochten, John M; de Vries, Anja D; van Putte, Nienke; Oei, Edwin H G; Bindels, Patrick J E; Bierma-Zeinstra, Sita M A; van Middelkoop, Marienke

2017-09-01

Structural abnormalities on MRI are frequent after an ankle sprain. To determine the association between patient history, physical examination and early osteoarthritis (OA) in patients after a previous ankle sprain, 98 patients with persistent complaints were selected from a cross-sectional study. Patient history taking and physical examination were applied and MRI was taken. Univariate and multivariable analyses were used to test possible associations. Signs of OA (cartilage loss, osteophytes and bone marrow edema) were seen in the talocrural joint (TCJ) in 40% and the talonavicular joint (TNJ) in 49%. Multivariable analysis showed a significant positive association between swelling (OR 3.58, 95%CI 1.13;11.4), a difference in ROM of passive plantar flexion (OR 1.09, 95%CI 1.01;1.18) and bone edema in the TCJ. A difference in ROM of passive plantar flexion (OR 1.07, 95%CI 1.00;1.15) and pain at the end range of dorsiflexion/plantar flexion (OR 5.23, 95%CI 1.88;14.58) were associated with osteophytes in the TNJ. Pain at the end of dorsiflexion/plantar flexion, a difference in ROM of passive plantar flexion and swelling seem to be associated with features of OA (bone marrow edema, osteophytes) in the TCJ and TNJ. Our findings may guide physicians to predict structural joint abnormalities as signs of osteoarthritis. 1b. © Georg Thieme Verlag KG Stuttgart · New York.

Structural Mapping and Geomorphology of Ireland's Southwest Continental Shelf Using High Resolution Sonar

NASA Astrophysics Data System (ADS)

Bowden, S.; Wireman, R.

2016-02-01

Bathymetric surveys were conducted on the continental shelf off the southwest coast of County Cork, Ireland by the Marine Institute of Ireland, the Geological Survey of Ireland, and the INFOMAR project. Data were collected from July 2006 through September 2014 using a Kongsberg EM2040 multibeam echosounder aboard the R/Vs Celtic Voyager and Keary, and a Kongsberg EM1002 on the R/V Celtic Explorer. Sonar data were post-processed with CARIS HIPS and SIPS 9.0 to create 2D and 3D bathymetric and backscatter intensity surfaces with a resolution of 1 m. The offshore study site is part of the 286 Ma western Variscian orogenic front and has several massive outcrops, exhibiting 5 to 20 m of near-vertical relief. These outcrops were structurally mapped and relatively aged, and exhibit significant folding, rotation, tilting, and joint systems. Google Earth, ArcGIS, and previous terrestrial studies were used to further analyze how geomorphology is controlled by seafloor composition and structural features. Rock type and age were interpreted by comparing fracture analysis of the joints and fold trends to similar onshore outcrops documented previously, to determine an age of 416-299 Ma for the shelf's outcropping strata and associated structural features. The oldest features observed are regional anticlines and synclines containing Upper Devonian Old Red Sandstone and Lower Carboniferous shales. Within the shale layers are NE-SW plunging parasitic chevron folds. Jointing is observed in both sandstone and shale layers and is superimposed on chevron folding, with cross joints appearing to influence shallow current patterns. Rotation of the regional folds is the youngest structural feature, as both the parasitic folds and joint systems are warped. Our study shows that high resolution sonar is an effective tool for offshore structural mapping and is an important resource for understanding the geomorphology and geologic history of submerged outcrops on continental shelf systems.

A neural joint model for entity and relation extraction from biomedical text.

PubMed

Li, Fei; Zhang, Meishan; Fu, Guohong; Ji, Donghong

2017-03-31

Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above. Our model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction. The proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

Effect of Different Connection Modes on Bolt Structural Properties of TC4 Alloy in Selective Laser Melting

NASA Astrophysics Data System (ADS)

Li, Xiaodan; Huang, Shuangjun; Xu, Liang; Hui, Li; Zhou, Song

2017-12-01

The bolt structural properties of selective laser melted (SLM) samples produced from TC4 powder metal has been investigated. Two different connection molds relative to single lap joint and bilateral lap joint as well as two different state of surface quality were considered. Samples and test procedures were designed in accordance with HB 5143 and HB 5287 standard. The results show that there is a strong influence of connection molds on the dynamic behavior of SLM produced TC4. The mechanical properties of bilateral lap joint are better than those of the single lap joint. Meanwhile the fatigue performance of the bilateral lap joint is much stronger than that of the single lap joint which it is a symmetrical structure of the two-shear test on both sides of the force evenly, while the single lap joint is a single shear sample of the uneven force. There are two kinds of fracture form most of which are broken in the first row of screw and a small part in the middle of the connecting plate.

Turbine component casting core with high resolution region

DOEpatents

Kamel, Ahmed; Merrill, Gary B.

2014-08-26

A hollow turbine engine component with complex internal features can include a first region and a second, high resolution region. The first region can be defined by a first ceramic core piece formed by any conventional process, such as by injection molding or transfer molding. The second region can be defined by a second ceramic core piece formed separately by a method effective to produce high resolution features, such as tomo lithographic molding. The first core piece and the second core piece can be joined by interlocking engagement that once subjected to an intermediate thermal heat treatment process thermally deform to form a three dimensional interlocking joint between the first and second core pieces by allowing thermal creep to irreversibly interlock the first and second core pieces together such that the joint becomes physically locked together providing joint stability through thermal processing.

Lamb wave-based damage quantification and probability of detection modeling for fatigue life assessment of riveted lap joint

NASA Astrophysics Data System (ADS)

He, Jingjing; Wang, Dengjiang; Zhang, Weifang

2015-03-01

This study presents an experimental and modeling study for damage detection and quantification in riveted lap joints. Embedded lead zirconate titanate piezoelectric (PZT) ceramic wafer-type sensors are employed to perform in-situ non-destructive testing during fatigue cyclical loading. A multi-feature integration method is developed to quantify the crack size using signal features of correlation coefficient, amplitude change, and phase change. In addition, probability of detection (POD) model is constructed to quantify the reliability of the developed sizing method. Using the developed crack size quantification method and the resulting POD curve, probabilistic fatigue life prediction can be performed to provide comprehensive information for decision-making. The effectiveness of the overall methodology is demonstrated and validated using several aircraft lap joint specimens from different manufactures and under different loading conditions.

Supai salt karst features: Holbrook Basin, Arizona

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neal, J.T.

1994-12-31

More than 300 sinkholes, fissures, depressions, and other collapse features occur along a 70 km (45 mi) dissolution front of the Permian Supai Formation, dipping northward into the Holbrook Basin, also called the Supai Salt Basin. The dissolution front is essentially coincident with the so-called Holbrook Anticline showing local dip reversal; rather than being of tectonic origin, this feature is likely a subsidence-induced monoclinal flexure caused by the northward migrating dissolution front. Three major areas are identified with distinctive attributes: (1) The Sinks, 10 km WNW of Snowflake, containing some 200 sinkholes up to 200 m diameter and 50 mmore » depth, and joint controlled fissures and fissure-sinks; (2) Dry Lake Valley and contiguous areas containing large collapse fissures and sinkholes in jointed Coconino sandstone, some of which drained more than 50 acre-feet ({approximately}6 {times} 10{sup 4} m{sup 3}) of water overnight; and (3) the McCauley Sinks, a localized group of about 40 sinkholes 15 km SE of Winslow along Chevelon Creek, some showing essentially rectangular jointing in the surficial Coconino Formation. Similar salt karst features also occur between these three major areas. The range of features in Supai salt are distinctive, yet similar to those in other evaporate basins. The wide variety of dissolution/collapse features range in development from incipient surface expression to mature and old age. The features began forming at least by Pliocene time and continue to the present, with recent changes reportedly observed and verified on airphotos with 20 year repetition. The evaporate sequence along interstate transportation routes creates a strategic location for underground LPG storage in leached caverns. The existing 11 cavern field at Adamana is safely located about 25 miles away from the dissolution front, but further expansion initiatives will require thorough engineering evaluation.« less

Adhesive Bonding Characterization of Composite Joints for Cryogenic Usage

NASA Technical Reports Server (NTRS)

Graf, Neil A.; Schieleit, Gregory F.; Biggs, Robert

2000-01-01

The development of polymer composite cryogenic tanks is a critical step in creating the next generation of launch vehicles. Future reusable launch vehicles need to minimize the gross liftoff weight (GLOW). This weight reduction is possible due to the large reduction in weight that composite materials can provide over current aluminum technology. In addition to composite technology, adhesively bonded joints potentially have several benefits over mechanically fastened joints, such as weight savings and cryogenic fluid containment. Adhesively bonded joints may be used in several areas of these cryogenic tanks, such as in lobe-to-lobe joints (in a multi-lobe concept), skirt-to-tank joint, strut-to-tank joint, and for attaching stringers and ring frames. The bonds, and the tanks themselves, must be able to withstand liquid cryogenic fuel temperatures that they contain. However, the use of adhesively bonded composite joints at liquid oxygen and hydrogen temperatures is largely unknown and must be characterized. Lockheed Martin Space Systems Company, Michoud Operations performed coupon-level tests to determine effects of material selection, cure process parameters, substrate surface preparation, and other factors on the strength of these composite joints at cryogenic temperatures. This led to the selection of a material and process that would be suitable for a cryogenic tank. KEY WORDS: Composites, Adhesive Bonding, Cryogenics

Image segmentation using joint spatial-intensity-shape features: application to CT lung nodule segmentation

NASA Astrophysics Data System (ADS)

Ye, Xujiong; Siddique, Musib; Douiri, Abdel; Beddoe, Gareth; Slabaugh, Greg

2009-02-01

Automatic segmentation of medical images is a challenging problem due to the complexity and variability of human anatomy, poor contrast of the object being segmented, and noise resulting from the image acquisition process. This paper presents a novel feature-guided method for the segmentation of 3D medical lesions. The proposed algorithm combines 1) a volumetric shape feature (shape index) based on high-order partial derivatives; 2) mean shift clustering in a joint spatial-intensity-shape (JSIS) feature space; and 3) a modified expectation-maximization (MEM) algorithm on the mean shift mode map to merge the neighboring regions (modes). In such a scenario, the volumetric shape feature is integrated into the process of the segmentation algorithm. The joint spatial-intensity-shape features provide rich information for the segmentation of the anatomic structures or lesions (tumors). The proposed method has been evaluated on a clinical dataset of thoracic CT scans that contains 68 nodules. A volume overlap ratio between each segmented nodule and the ground truth annotation is calculated. Using the proposed method, the mean overlap ratio over all the nodules is 0.80. On visual inspection and using a quantitative evaluation, the experimental results demonstrate the potential of the proposed method. It can properly segment a variety of nodules including juxta-vascular and juxta-pleural nodules, which are challenging for conventional methods due to the high similarity of intensities between the nodules and their adjacent tissues. This approach could also be applied to lesion segmentation in other anatomies, such as polyps in the colon.

Effect of joint mechanism on vehicle redirectional capability of water-filled road safety barrier systems.

PubMed

Thiyahuddin, M I; Thambiratnam, D P; Gu, Y T

2014-10-01

Portable water-filled barriers (PWFBs) are roadside appurtenances that prevent vehicles from penetrating into temporary construction zones on roadways. PWFBs are required to satisfy the strict regulations for vehicle re-direction in tests. However, many of the current PWFBs fail to re-direct the vehicle at high speeds due to the inability of the joints to provide appropriate stiffness. The joint mechanism hence plays a crucial role in the performance of a PWFB system at high speed impacts. This paper investigates the desired features of the joint mechanism in a PWFB system that can re-direct vehicles at high speeds, while limiting the lateral displacement to acceptable limits. A rectangular "wall" representative of a 30m long barrier system was modeled and a novel method of joining adjacent road barriers was introduced through appropriate pin-joint connections. The impact response of the barrier "wall" and the vehicle was obtained and the results show that a rotational stiffness of 3000kNm/rad at the joints seems to provide the desired features of the PWFB system to re-direct impacting vehicles and restrict the lateral deflection. These research findings will be useful to safety engineers and road barrier designers in developing a new generation of PWFBs for increased road safety. Copyright © 2014 Elsevier Ltd. All rights reserved.

A New Technique for Compensating Joint Limits in a Robot Manipulator

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Hickman, Andre; Guo, Ten-Huei

1996-01-01

A new robust, optimal, adaptive technique for compensating rate and position limits in the joints of a six degree-of-freedom elbow manipulator is presented. In this new algorithm, the unmet demand as a result of actuator saturation is redistributed among the remaining unsaturated joints. The scheme is used to compensate for inadequate path planning, problems such as joint limiting, joint freezing, or even obstacle avoidance, where a desired position and orientation are not attainable due to an unrealizable joint command. Once a joint encounters a limit, supplemental commands are sent to other joints to best track, according to a selected criterion, the desired trajectory.

24 CFR 943.148 - What procurement standards apply to PHAs selecting partners for a joint venture?

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 4 2011-04-01 2011-04-01 false What procurement standards apply to PHAs selecting partners for a joint venture? 943.148 Section 943.148 Housing and Urban Development REGULATIONS RELATING TO HOUSING AND URBAN DEVELOPMENT (CONTINUED) OFFICE OF ASSISTANT SECRETARY FOR PUBLIC AND...

Implications of the Joint Comprehensive Plan of Action

NASA Astrophysics Data System (ADS)

Perkovich, George

2017-11-01

This essay describes the background behind the July 2015 Joint Comprehensive Plan of Action that was negotiated to redress the crisis that had developed around Iran's nuclear activities, and summarizes some of the agreement's key features. The essay then highlights political and strategic factors that enabled the diplomatic breakthrough, and draws lessons that could inform approaches to future proliferation challenges. The conclusion suggests how some of the agreement's innovative features could be built upon and applied more broadly to reduce risks that civilian nuclear energy programs could be diverted for military purposes and to inform approaches to nuclear disarmament in the future.

Quantitative three-dimensional photoacoustic tomography of the finger joints: an in vivo study

NASA Astrophysics Data System (ADS)

Sun, Yao; Sobel, Eric; Jiang, Huabei

2009-11-01

We present for the first time in vivo full three-dimensional (3-D) photoacoustic tomography (PAT) of the distal interphalangeal joint in a human subject. Both absorbed energy density and absorption coefficient images of the joint are quantitatively obtained using our finite-element-based photoacoustic image reconstruction algorithm coupled with the photon diffusion equation. The results show that major anatomical features in the joint along with the side arteries can be imaged with a 1-MHz transducer in a spherical scanning geometry. In addition, the cartilages associated with the joint can be quantitatively differentiated from the phalanx. This in vivo study suggests that the 3-D PAT method described has the potential to be used for early diagnosis of joint diseases such as osteoarthritis and rheumatoid arthritis.

Lessons learnt on implementing an interdisciplinary doctoral programme in water sciences

NASA Astrophysics Data System (ADS)

Carr, Gemma; Loucks, Daniel Pete; Blaschke, Alfred Paul; Bucher, Christian; Farnleitner, Andreas; Fürnkranz-Prskawetz, Alexia; Parajka, Juraj; Pfeifer, Norbert; Rechberger, Helmut; Wagner, Wolfgang; Zessner, Matthias; Blöschl, Günter

2015-04-01

Using the Vienna Doctoral Programme on Water Resource Systems as a case study, this work describes how the characteristics of the programme can be evaluated to identify which process features are important for developing interdisciplinary research at the doctoral level. The Programme has been running since 2009, and to date has engaged 35 research students, three post-docs and ten faculty members from ten research fields (aquatic microbiology, hydrology, hydro-climatology, hydro-geology, mathematical economics, photogrammetry, remote sensing, resource management, structural mechanics, and water quality). Collaborative, multi-disciplinary research is encouraged and supported through various mechanisms - shared offices, study programme, research cluster groups that hold regular meetings, joint study sites, annual and six-month symposia that bring all members of the programme together, seminar series, joint supervision, and social events. Interviews were conducted with 12 students and recent graduates to explore individual experiences of doing interdisciplinary research within the Programme, and to identify which mechanisms are perceived to be of the greatest benefit for collaborative work. Analysis revealed four important process features. Firstly, students noted that joint supervision and supervisors who are motivated to collaborate are essential for multi-disciplinary collaborative work. Secondly, interviewees described that they work with the people they sit close to or see most regularly. Physical places for collaboration between different discipline researchers such as shared offices and shared study sites are therefore important. Thirdly, the costs and benefits to doing interdisciplinary work were highlighted. Students make a trade-off when deciding if their time investment to develop their understanding of a new research field will support them in addressing their research question. The personal characteristics of the researcher seem to be particularly relevant to this decision making process and need to be considered during student selection. Finally, communication skills are critical. Students noted that they need to be able to understand what each other are doing in order to work together and the symposia and research cluster meetings are good places for developing these skills.

Reward maximization justifies the transition from sensory selection at childhood to sensory integration at adulthood.

PubMed

Daee, Pedram; Mirian, Maryam S; Ahmadabadi, Majid Nili

2014-01-01

In a multisensory task, human adults integrate information from different sensory modalities--behaviorally in an optimal Bayesian fashion--while children mostly rely on a single sensor modality for decision making. The reason behind this change of behavior over age and the process behind learning the required statistics for optimal integration are still unclear and have not been justified by the conventional Bayesian modeling. We propose an interactive multisensory learning framework without making any prior assumptions about the sensory models. In this framework, learning in every modality and in their joint space is done in parallel using a single-step reinforcement learning method. A simple statistical test on confidence intervals on the mean of reward distributions is used to select the most informative source of information among the individual modalities and the joint space. Analyses of the method and the simulation results on a multimodal localization task show that the learning system autonomously starts with sensory selection and gradually switches to sensory integration. This is because, relying more on modalities--i.e. selection--at early learning steps (childhood) is more rewarding than favoring decisions learned in the joint space since, smaller state-space in modalities results in faster learning in every individual modality. In contrast, after gaining sufficient experiences (adulthood), the quality of learning in the joint space matures while learning in modalities suffers from insufficient accuracy due to perceptual aliasing. It results in tighter confidence interval for the joint space and consequently causes a smooth shift from selection to integration. It suggests that sensory selection and integration are emergent behavior and both are outputs of a single reward maximization process; i.e. the transition is not a preprogrammed phenomenon.

Multivariate Meta-Analysis Using Individual Participant Data

ERIC Educational Resources Information Center

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2015-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

The space shuttle advanced solid rocket motor: Quality control and testing

NASA Technical Reports Server (NTRS)

1991-01-01

The Congressional committees that authorize the activities of NASA requested that the National Research Council (NRC) review the testing and quality assurance programs for the Advanced Solid Rocket Motor (ASRM) program. The proposed ASRM design incorporates numerous features that are significant departures from the Redesigned Solid Rocket Motor (RSRM). The NRC review concentrated mainly on these features. Primary among these are the steel case material, welding rather than pinning of case factory joints, a bolted field joint designed to close upon firing the rocket, continuous mixing and casting of the solid propellant in place of the current batch processes, use of asbestos-free insulation, and a lightweight nozzle. The committee's assessment of these and other features of the ASRM are presented in terms of their potential impact on flight safety.

Reflex Responses to Ligament Loading: Implications for Knee Joint Stability

DTIC Science & Technology

2001-10-25

white noise approach", Prentice-Hall".:, 1978. [15] B. Grenfield and B. Wyke, "Reflex innervation of the temporo - mandibular joint .". Nature. 211(52...selective, depending on the magnitude of the angular perturbation. Keywords - Reflex, Periarticular tissue afferents, Joint stability I...INTRODUCTION Traditionally, joint stability has been considered to be purely mechanical in origin, with little or no consideration of neuromuscular

Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels.

PubMed

Baseer, Abdul; Weddell, Stephen J; Jones, Richard D

2017-07-01

Microsleeps are involuntary and brief instances of complete loss of responsiveness, typically of 0.5-15 s duration. They adversely affect performance in extended attention-driven jobs and can be fatal. Our aim was to predict microsleeps from 16 channel EEG signals. Two information theoretic concepts - pairwise joint entropy and mutual information - were independently used to continuously extract features from EEG signals. k-nearest neighbor (kNN) with k = 3 was used to calculate both joint entropy and mutual information. Highly correlated features were discarded and the rest were ranked using Fisher score followed by an average of 3-fold cross-validation area under the curve of the receiver operating characteristic (AUC ROC ). Leave-one-out method (LOOM) was performed to test the performance of microsleep prediction system on independent data. The best prediction for 0.25 s ahead was AUCROC, sensitivity, precision, geometric mean (GM), and φ of 0.93, 0.68, 0.33, 0.75, and 0.38 respectively with joint entropy using single linear discriminant analysis (LDA) classifier.

Three Dimensional Characterization of Tin Crystallography and Cu6Sn5 Intermetallics in Solder Joints by Multiscale Tomography

NASA Astrophysics Data System (ADS)

Kirubanandham, A.; Lujan-Regalado, I.; Vallabhaneni, R.; Chawla, N.

2016-11-01

Decreasing pitch size in electronic packaging has resulted in a drastic decrease in solder volumes. The Sn grain crystallography and fraction of intermetallic compounds (IMCs) in small-scale solder joints evolve much differently at the smaller length scales. A cross-sectional study limits the morphological analysis of microstructural features to two dimensions. This study utilizes serial sectioning technique in conjunction with electron backscatter diffraction to investigate the crystallographic orientation of both Sn grains and Cu6Sn5 IMCs in Cu/Pure Sn/Cu solder joints in three dimensional (3D). Quantification of grain aspect ratio is affected by local cooling rate differences within the solder volume. Backscatter electron imaging and focused ion beam serial sectioning enabled the visualization of morphology of both nanosized Cu6Sn5 IMCs and the hollow hexagonal morphology type Cu6Sn5 IMCs in 3D. Quantification and visualization of microstructural features in 3D thus enable us to better understand the microstructure and deformation mechanics within these small scale solder joints.

Comparison of sequence of trunk and arm motions between short and long official distance groups in javelin throwing.

PubMed

Liu, Hui; Leigh, Steve; Yu, Bing

2014-03-01

The purpose of this study was to determine the effects of sequences of the trunk and arm angular motions on the performance of javelin throwing. In this study, 32 male and 30 female elite javelin throwers participated and were separated into a short official distance group or a long official distance group in each gender. Three-dimensional coordinates of 21 body landmarks and 3 marks on the javelin in the best trial were collected for each subject. Joint center linear velocities and selected trunk and arm segment and joint angles and angular velocities were calculated. The times of the initiations of the selected segment and joint angular motions and maximum angular velocities were determined. The sequences of the initiations of the selected segment and joint angular motions and maximum angular velocities were compared between short and long official distance groups and between genders. The results demonstrated that short and long official distance groups employed similar sequences of the trunk and arm motions. Male and female javelin throwers employed different sequences of the trunk and arm motions. The sequences of the trunk and arm motions were different from those of the maximal joint center linear velocities.

Joint inversion of NMR and SIP data to estimate pore size distribution of geomaterials

NASA Astrophysics Data System (ADS)

Niu, Qifei; Zhang, Chi

2018-03-01

There are growing interests in using geophysical tools to characterize the microstructure of geomaterials because of the non-invasive nature and the applicability in field. In these applications, multiple types of geophysical data sets are usually processed separately, which may be inadequate to constrain the key feature of target variables. Therefore, simultaneous processing of multiple data sets could potentially improve the resolution. In this study, we propose a method to estimate pore size distribution by joint inversion of nuclear magnetic resonance (NMR) T2 relaxation and spectral induced polarization (SIP) spectra. The petrophysical relation between NMR T2 relaxation time and SIP relaxation time is incorporated in a nonlinear least squares problem formulation, which is solved using Gauss-Newton method. The joint inversion scheme is applied to a synthetic sample and a Berea sandstone sample. The jointly estimated pore size distributions are very close to the true model and results from other experimental method. Even when the knowledge of the petrophysical models of the sample is incomplete, the joint inversion can still capture the main features of the pore size distribution of the samples, including the general shape and relative peak positions of the distribution curves. It is also found from the numerical example that the surface relaxivity of the sample could be extracted with the joint inversion of NMR and SIP data if the diffusion coefficient of the ions in the electrical double layer is known. Comparing to individual inversions, the joint inversion could improve the resolution of the estimated pore size distribution because of the addition of extra data sets. The proposed approach might constitute a first step towards a comprehensive joint inversion that can extract the full pore geometry information of a geomaterial from NMR and SIP data.

Review of Prosthetic Joint Infection from Listeria monocytogenes.

PubMed

Bader, Gilbert; Al-Tarawneh, Mohammed; Myers, James

2016-12-01

Prosthetic joint infection from Listeria monocytogenes is rare. We decided to shed light on this illness and review the reported cases to better understand its characteristics. We conducted a comprehensive review of the English literature using PubMed. We also included one case that we had managed. We found 25 cases of prosthetic joint infection from L. monocytogenes reported individually and a retrospective study of 43 cases of joint and bone listerial infection, including 34 with prosthetic joint infection, conducted in France. We have described their clinical and para-clinical features and tried to elaborate on the pathophysiology, treatment, and prevention. Prosthetic joint infection from L. monocytogenes is mainly late. Systemic inflammation may be absent. Although rare, it must be suspected in patients at high risk for both prosthetic joint and listerial infections. In addition, those patients must be instructed on appropriate preventive measures.

Joint Effects of Ambient Air Pollutants on Pediatric Asthma Emergency Department Visits in Atlanta, 1998–2004

EPA Science Inventory

Background: Because ambient air pollution exposure occurs in the form of mixtures, consideration of joint effects of multiple pollutants may advance our understanding of air pollution health effects. Methods: We assessed the joint effect of selected ambient air pollutant com...

Quantum-enhanced feature selection with forward selection and backward elimination

NASA Astrophysics Data System (ADS)

He, Zhimin; Li, Lvzhou; Huang, Zhiming; Situ, Haozhen

2018-07-01

Feature selection is a well-known preprocessing technique in machine learning, which can remove irrelevant features to improve the generalization capability of a classifier and reduce training and inference time. However, feature selection is time-consuming, particularly for the applications those have thousands of features, such as image retrieval, text mining and microarray data analysis. It is crucial to accelerate the feature selection process. We propose a quantum version of wrapper-based feature selection, which converts a classical feature selection to its quantum counterpart. It is valuable for machine learning on quantum computer. In this paper, we focus on two popular kinds of feature selection methods, i.e., wrapper-based forward selection and backward elimination. The proposed feature selection algorithm can quadratically accelerate the classical one.

The effect of robenacoxib on the concentration of C-reactive protein in synovial fluid from dogs with osteoarthritis

PubMed Central

2013-01-01

Background Robenacoxib is a novel and highly selective inhibitor of COX-2 in dogs and cats and because of its acidic nature is regarded as being tissue-selective. Thirty four dogs with stifle osteoarthritis secondary to failure of the cranial cruciate ligament were recruited into this study. Lameness, radiographic features, synovial cytology and C-reactive protein concentrations in serum and synovial fluid were assessed before and 28 days after commencing a course of Robenacoxib at a dose of 1 mg/kg SID. Results There was a significant reduction in the lameness score (P < 0.01) and an increase in the radiographic score (P < 0.05) between pre- and post-treatment assessments. There was no difference between pre- (median 1.49 mg/l; Q1-Q3 0.56-4.24 mg/L) and post – (1.10 mg/L; 0.31-1.78 mg/L) treatment serum C-reactive protein levels although synovial fluid levels were significantly reduced (pre- : 0.44 mg/L; 0.23-1.62 mg/L; post- : 0.17 mg/L; 0.05-0.49 mg/L) (P < 0.05). There was no correlation between C-reactive protein concentrations in serum and matched synovial fluid samples. Conclusions Robenacoxib proved effective in reducing lameness in dogs with failure of the cranial cruciate ligament and osteoarthritis of the stifle joint. The drug also reduced levels of C-reactive protein in the synovial fluid taken from the affected stifle joint. Robenacoxib appears to reduce articular inflammation as assessed by C-reactive protein which supports the concept that Robenacoxib is a tissue-selective non-steroidal anti-inflammatory drug. PMID:23452411

The effect of robenacoxib on the concentration of C-reactive protein in synovial fluid from dogs with osteoarthritis.

PubMed

Bennett, David; Eckersall, Peter David; Waterston, Mary; Marchetti, Veronica; Rota, Alessandra; McCulloch, Eilidh; Sbrana, Silvia

2013-03-01

Robenacoxib is a novel and highly selective inhibitor of COX-2 in dogs and cats and because of its acidic nature is regarded as being tissue-selective. Thirty four dogs with stifle osteoarthritis secondary to failure of the cranial cruciate ligament were recruited into this study. Lameness, radiographic features, synovial cytology and C-reactive protein concentrations in serum and synovial fluid were assessed before and 28 days after commencing a course of Robenacoxib at a dose of 1 mg/kg SID. There was a significant reduction in the lameness score (P < 0.01) and an increase in the radiographic score (P < 0.05) between pre- and post-treatment assessments. There was no difference between pre- (median 1.49 mg/l; Q1-Q3 0.56-4.24 mg/L) and post - (1.10 mg/L; 0.31-1.78 mg/L) treatment serum C-reactive protein levels although synovial fluid levels were significantly reduced (pre- : 0.44 mg/L; 0.23-1.62 mg/L; post- : 0.17 mg/L; 0.05-0.49 mg/L) (P < 0.05). There was no correlation between C-reactive protein concentrations in serum and matched synovial fluid samples. Robenacoxib proved effective in reducing lameness in dogs with failure of the cranial cruciate ligament and osteoarthritis of the stifle joint. The drug also reduced levels of C-reactive protein in the synovial fluid taken from the affected stifle joint. Robenacoxib appears to reduce articular inflammation as assessed by C-reactive protein which supports the concept that Robenacoxib is a tissue-selective non-steroidal anti-inflammatory drug.

Solder Joint Health Monitoring Testbed

NASA Technical Reports Server (NTRS)

Delaney, Michael M.; Flynn, James; Browder, Mark

2009-01-01

A method of monitoring the health of selected solder joints, called SJ-BIST, has been developed by Ridgetop Group Inc. under a Small Business Innovative Research (SBIR) contract. The primary goal of this research program is to test and validate this method in a flight environment using realistically seeded faults in selected solder joints. An additional objective is to gather environmental data for future development of physics-based and data-driven prognostics algorithms. A test board is being designed using a Xilinx FPGA. These boards will be tested both in flight and on the ground using a shaker table and an altitude chamber.

Imaging and histological features of central subchondral osteophytes in racehorses with metacarpophalangeal joint osteoarthritis.

PubMed

Olive, J; D'Anjou, M A; Girard, C; Laverty, S; Theoret, C L

2009-12-01

Marginal osteophytes represent a well known component of osteoarthritis in man and animals. Conversely, central subchondral osteophytes (COs), which are commonly present in human knees with osteoarthritis, have not been reported in horses. To describe and compare computed radiography (CR), single-slice computed tomography (CT), 1.5 Tesla magnetic resonance imaging (MRI), and histological features of COs in equine metacarpophalangeal joints with macroscopic evidence of naturally-occurring osteoarthritis. MRI sequences (sagittal spoiled gradient recalled echo [SPGR] with fat saturation, sagittal T2-weighted fast spin echo with fat saturation [T2-FS], dorsal and transverse T1-weighted gradient-recalled echo [GRE], and sagittal T2*-weighted gradient echo with fast imaging employing steady state acquisition [FIESTA]), as well as transverse and reformatted sagittal CTI and 4 computed radiographic (CR) views of 20 paired metacarpophalangeal joints were acquired ex vivo. Following macroscopic evaluation, samples were harvested in predetermined sites of the metacarpal condyle for subsequent histology. The prevalence and detection level of COs was determined for each imaging modality. Abnormalities consistent with COs were clearly depicted on MRI, using the SPGR sequence, in 7/20 (35%) joints. They were identified as a focal hypointense protuberance from the subchondral plate into the cartilage, at the palmarodistal aspect (n=7) and/or at the very dorsal aspect (n=2) of the metacarpal condyle. COs were visible but less obvious in 5 of the 7 joints using FIESTA and reformatted sagittal CT, and were not identifiable on T2-FS, T1-GRE or CR. Microscopically, they consisted of dense bone protruding into the calcified cartilage and disrupting the tidemarks, and they were consistently associated with overlying cartilage defects. Subchondral osteophytes are a feature of osteoarthritis of equine metacarpophalangeal joints and they may be diagnosed using 1.5 Tesla MRI and CT. Central subchondral osteophytes on MRI represent indirect evidence of cartilage damage in horses.

Seismicity and structure of Akutan and Makushin Volcanoes, Alaska, using joint body and surface wave tomography

DOE PAGES

Syracuse, E. M.; Maceira, M.; Zhang, H.; ...

2015-02-18

Joint inversions of seismic data recover models that simultaneously fit multiple constraints while playing upon the strengths of each data type. Here, we jointly invert 14 years of local earthquake body wave arrival times from the Alaska Volcano Observatory catalog and Rayleigh wave dispersion curves based upon ambient noise measurements for local V p, V s, and hypocentral locations at Akutan and Makushin Volcanoes using a new joint inversion algorithm.The velocity structure and relocated seismicity of both volcanoes are significantly more complex than many other volcanoes studied using similar techniques. Seismicity is distributed among several areas beneath or beyond themore » flanks of both volcanoes, illuminating a variety of volcanic and tectonic features. The velocity structures of the two volcanoes are exemplified by the presence of narrow high-V p features in the near surface, indicating likely current or remnant pathways of magma to the surface. A single broad low-V p region beneath each volcano is slightly offset from each summit and centered at approximately 7 km depth, indicating a potential magma chamber, where magma is stored over longer time periods. Differing recovery capabilities of the Vp and Vs datasets indicate that the results of these types of joint inversions must be interpreted carefully.« less

Friction stir scribe welding technique for dissimilar joining of aluminium and galvanised steel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Tianhao; Sidhar, Harpreet; Mishra, Rajiv S.

Friction stir scribe technology, a derivative of friction stir welding, was applied for the dissimilar lap welding of an aluminum alloy and galvanized mild steel sheets. During the process, the rotating tool with a cobalt steel scribe first penetrated the top material — aluminum — and then the scribe cut the bottom material — steel. The steel was displaced into the upper material to produce a characteristic hook feature. Lap welds were shear tested, and their fracture paths were studied. Welding parameters affected the welding features including hook height, which turned out to be highly related to fracture position. Therefore,more » in this paper, the relationships among welding parameters, hook height, joint strength and fracture position are presented. In addition, influence of zinc coating on joint strength was also studied. Keywords: friction stir scribe technology; dissimilar material welding; zinc coating; hook height; joint strength; fracture position« less

Assessment of the Sensitivity of Welded Joints of Al -Mg - Si Alloys to Liquation Cracks Under Laser Welding

NASA Astrophysics Data System (ADS)

Ivanov, S. Yu.; Karkhin, V. A.; Mikhailov, V. G.; Martikainen, J.; Hiltunen, E.

2018-03-01

The microstructure and the distribution of chemical elements in laser-welded joints of Al - Mg - Si alloy 6005-T6 are studied. Segregations of chemical elements are detected over grain boundaries in the heat-affected zones of the welded joints. The joints fracture by the intergrain mechanism. A Gleeble 3800 device is used to determine the temperature dependences of the mechanical properties of the alloy with allowance for the special features of the welding cycle. Amethod for evaluating the sensitivity of welded joints of aluminum alloys to formation of liquation cracks with allowance for the local properties of the metal, the welding conditions, and the rigidity of the construction is suggested.

Error modeling and sensitivity analysis of a parallel robot with SCARA(selective compliance assembly robot arm) motions

NASA Astrophysics Data System (ADS)

Chen, Yuzhen; Xie, Fugui; Liu, Xinjun; Zhou, Yanhua

2014-07-01

Parallel robots with SCARA(selective compliance assembly robot arm) motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error's influence on the moving platform's pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.

Airborne and Maritime/Fixed Station Joint Tactical Radio System (AMF JTRS)

DTIC Science & Technology

2015-12-01

Selected Acquisition Report (SAR) RCS: DD-A&T(Q&A)823-421 Airborne & Maritime/Fixed Station Joint Tactical Radio System (AMF JTRS) As of FY 2017...Information Program Name Airborne & Maritime/Fixed Station Joint Tactical Radio System (AMF JTRS) DoD Component Army Responsible Office References SAR...UNCLASSIFIED 5 Mission and Description Airborne & Maritime/Fixed Station Joint Tactical Radio System (AMF JTRS) products are software programmable

An interdigit signalling centre instructs coordinate phalanx-joint formation governed by 5′Hoxd–Gli3 antagonism

PubMed Central

Huang, Bau-Lin; Trofka, Anna; Furusawa, Aki; Norrie, Jacqueline L.; Rabinowitz, Adam H.; Vokes, Steven A.; Mark Taketo, M.; Zakany, Jozsef; Mackem, Susan

2016-01-01

The number of phalanges and joints are key features of digit ‘identity' and are central to limb functionality and evolutionary adaptation. Prior chick work indicated that digit phalanges and their associated joints arise in a different manner than the more sparsely jointed long bones, and their identity is regulated by differential signalling from adjacent interdigits. Currently, there is no genetic evidence for this model, and the molecular mechanisms governing digit joint specification remain poorly understood. Using genetic approaches in mouse, here we show that functional 5′Hoxd–Gli3 antagonism acts indirectly, through Bmp signalling from the interdigital mesenchyme, to regulate specification of joint progenitors, which arise in conjunction with phalangeal precursors at the digit tip. Phalanx number, although co-regulated, can be uncoupled from joint specification. We propose that 5′Hoxd genes and Gli3 are part of an interdigital signalling centre that sets net Bmp signalling levels from different interdigits to coordinately regulate phalanx and joint formation. PMID:27713395

Feature Selection for Chemical Sensor Arrays Using Mutual Information

PubMed Central

Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.

2014-01-01

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058

The joint in psoriatic arthritis.

PubMed

Mortezavi, Mahta; Thiele, Ralph; Ritchlin, Christopher

2015-01-01

Psoriatic arthritis (PsA), a chronic inflammatory joint disease associated with psoriasis, is notable for diversity in disease presentation, course and response to treatment. Equally varied are the types of musculoskeletal involvement which include peripheral and axial joint disease, dactylitis and enthesitis. In this review, we focus on the psoriatic joint and discuss pathways that underlie synovial, cartilage and bone inflammation and highlight key histopathologic features. The pivotal inflammatory mechanisms and pathobiology of PsA parallel findings in other forms of spondyloarthritis but are distinct from disease pathways described in rheumatoid synovitis and bone disease. The diagnosis of PsA from both a clinical and imaging perspective is also discussed.

Continuously reinforced concrete pavement inventory

NASA Astrophysics Data System (ADS)

Halverson, A. D.; Hagen, M. G.

1982-09-01

A typical concrete pavement has expansion and contraction joints across and along the pavement surface. The joints allow the pavement to change in dimension with changes in temperature. A continuously reinforced concrete pavement (CRCP) does not have expansion or contraction joints. Random, closely spaced cracks are expected to develop naturally and allow for expansion and contraction due to temperature changes. The many random cracks eliminate expensive joint maintenance. This maintenance-free service life feature has not occurred in Minnesota. This CRCP inventory is a physical evaluation of the extent of corrosion on random sections of pavement. It is related to concurrent efforts which will evaluate CRCP rehabilitation techniques.

Rough sets and Laplacian score based cost-sensitive feature selection

PubMed Central

Yu, Shenglong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of “good” features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms. PMID:29912884

Rough sets and Laplacian score based cost-sensitive feature selection.

PubMed

Yu, Shenglong; Zhao, Hong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of "good" features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.

DefenseLink Feature: Travels with Mullen

Science.gov Websites

of the Joint Chiefs of Staff, after laying a memorial wreath in honor of the 17,202 troops killed in and Memorial, Republic of the Philippines, June 2, 2008. Defense Dept. photo by Petty Officer 1st Joint Chiefs of Staff placed at the American Cemetery and Memorial represented one generation of U.S

T.E.M.P.: Teacher Education Model of Partnership--A Year-Long Competency-Based Urban Elementary Teaching Internship.

ERIC Educational Resources Information Center

Concordia Coll., St. Paul, Minn.

The Teacher Education Model of Partnership (TEMP) features joint ownership, joint support, and a partner relationship between a college and a school district in planning and implementing a professional program, designed specifically for teaching in the urban classroom. A planning committee was formed, composed of representatives from the public…

Compact Telerobot Hand

NASA Technical Reports Server (NTRS)

Rosheim, Mark; Trechsel, Hans

1993-01-01

Anthropomorphic telerobotic hand contains actuators, joints, sensors, and complex wiring harnesses. Glove protects interior components of hand from dirt and damage. Imitates motions of human fingers and wrist in lifelike and dexterous way. Incorporates pitch/yaw joints in wrist and head knuckles. Hand modular; so fingers removable, interchangeable units. Feature simplifies servicing and maintenance, which must be done frequently in such complex mechanism.

Cadre Photos for Joint Test Team Feature

NASA Image and Video Library

2017-02-23

During a tour of SpaceX headquarters in Hawthorne, California, commercial crew astronauts Suni Williams, left, and Doug Hurley participate in joint test team training using mockup components of the Crew Dragon on Feb. 23, 2017. Crew Dragon is being developed and manufactured in partnership with NASA's Commercial Crew Program to return human spaceflight capabilities to the U.S.

Cadre Photos for Joint Test Team Feature

NASA Image and Video Library

2017-02-23

During a tour of SpaceX headquarters in Hawthorne, California, commercial crew astronauts Bob Behnken, left, and Eric Boe participate in joint test team training using mockup components of the Crew Dragon on Feb. 23, 2017. Crew Dragon is being developed and manufactured in partnership with NASA's Commercial Crew Program to return human spaceflight capabilities to the U.S.

Tool Measures Depths of Defects on a Case Tang Joint

NASA Technical Reports Server (NTRS)

Ream, M. Bryan; Montgomery, Ronald B.; Mecham, Brent A.; Keirstead, Bums W.

2005-01-01

A special-purpose tool has been developed for measuring the depths of defects on an O-ring seal surface. The surface lies in a specially shaped ringlike fitting, called a capture feature tang, located on an end of a cylindrical segment of a case that contains a solid-fuel booster rocket motor for launching a space shuttle. The capture feature tang is a part of a tang-and-clevis, O-ring joint between the case segment and a similar, adjacent cylindrical case segment. When the segments are joined, the tang makes an interference fit with the clevis and squeezes the O-ring at the side of the gap.

Functional-adaptive analysis of the hindlimb anatomy of extant marsupials and the paleobiology of the Paleocene marsupials Mayulestes ferox and Pucadelphys andinus.

PubMed

Argot, Christine

2002-07-01

This article analyzes the adaptations of the hindlimb of two Early Paleocene marsupials, Mayulestes ferox and Pucadelphys andinus. This analysis is based on detailed comparisons with various extant marsupials, both South American and Australian. In the case of the South American opossums, original myological data were collected and osteological-myological associations were related to their locomotor behavior. The use of Australian genera helped to improve the appraisal of the locomotory habits of the fossil taxa. Several features are indicative of the ability of Mayulestes to climb or walk on uneven surfaces (e.g., very mobile hip joint, astragalocalcaneal joint pattern), and some other features emphasize a relative agility (e.g., strongly everted iliac blades, morphology of the distal epiphysis of the femur, medially stabilized cruroastragalar joint). Pucadelphys exhibits a hindlimb relatively similar morphologically to that of Mayulestes, but with features indicating slightly increased agility and a terrestrial component that is more emphasized than in Mayulestes. The Tiupampa fossils were therefore more agile than most living didelphids and resembled the condition observed in living dasyurids more. These conclusions complement a previous study performed on the forelimb of these fossils. Copyright 2002 Wiley-Liss, Inc.

Joint hypermobility syndrome in childhood. A not so benign multisystem disorder?

PubMed

Adib, N; Davies, K; Grahame, R; Woo, P; Murray, K J

2005-06-01

Joint hypermobility (JH) or "ligamentous laxity" is felt to be an underlying risk factor for many types of musculoskeletal presentation in paediatrics, and joint hypermobility syndrome (JHS) describes such disorders where symptoms become chronic, often more generalized and associated with functional impairment. Clinical features are felt to have much in common with more severe disorders, including Ehlers-Danlos syndrome (EDS), osteogenesis imperfecta and Marfan syndrome, although this has not been formally studied in children. We defined the clinical characteristics of all patients with joint hypermobility-related presentations seen from 1999 to 2002 in a tertiary referral paediatric rheumatology unit. Patients were identified and recruited from paediatric rheumatology clinic and ward, and a dedicated paediatric rheumatology hypermobility clinic at Great Ormond Street Hospital. Data were collected retrospectively on the patients from the paediatric rheumatology clinics (1999-2002) and prospectively on patients seen in the hypermobility clinic (2000-2002). Specifically, historical details of developmental milestones, musculoskeletal or soft tissue diagnoses and symptoms, and significant past medical history were recorded. Examination features sought included measurements of joint and soft tissue laxity, and associated conditions such as scoliosis, dysmorphic features, cardiac murmurs and eye problems. One hundred and twenty-five children (64 females) were included on whom sufficient clinical data could be identified and who had clinical problems ascribed to JH present for longer than 3 months. Sixty-four were from the paediatric rheumatology clinic and 61 from the hypermobility clinic. No differences were found in any of the measures between the two populations and results are presented in a combined fashion. Three-quarters of referrals came from paediatricians and general practitioners but in only 10% was hypermobility recognized as a possible cause of joint complaint. The average age at onset of symptoms was 6.2 yr and age at diagnosis 9.0 yr, indicating a 2- to 3-yr delay in diagnosis. The major presenting complaint was arthralgia in 74%, abnormal gait in 10%, apparent joint deformity in 10% and back pain in 6%. Mean age at first walking was 15.0 months; 48% were considered "clumsy" and 36% as having poor coordination in early childhood. Twelve per cent had "clicky" hips at birth and 4% actual congenital dislocatable hip. Urinary tract infections were present in 13 and 6% of the female and male cases, respectively. Thirteen and 14%, respectively, had speech and learning difficulties diagnosed. A history of recurrent joint sprains was seen in 20% and actual subluxation/dislocation of joints in 10%. Forty per cent had experienced problems with handwriting tasks, 48% had major limitations of school-based physical education activities, 67% other physical activities and 41% had missed significant periods of schooling because of symptoms. Forty-three per cent described a history of easy bruising. Examination revealed that 94% scored > or =4/9 on the Beighton scale for generalized hypermobility, with knees (92%), elbows (87%), wrists (82%), hand metacarpophalangeal joints (79%), and ankles (75%) being most frequently involved. JHS is poorly recognized in children with a long delay in the time to diagnosis. Although there is a referral bias towards joint symptoms, a surprisingly large proportion is associated with significant neuromuscular and motor development problems. Our patients with JHS also show many overlap features with genetic disorders such as EDS and Marfan syndrome. The delay in diagnosis results in poor control of pain and disruption of normal home life, schooling and physical activities. Knowledge of the diagnosis and simple interventions are likely to be highly effective in reducing the morbidity and cost to the health and social services.

Joint Attention in Parent-Child Dyads Involving Children with Selective Mutism: A Comparison between Anxious and Typically Developing Children

ERIC Educational Resources Information Center

Nowakowski, Matilda E.; Tasker, Susan L.; Cunningham, Charles E.; McHolm, Angela E.; Edison, Shannon; St. Pierre, Jeff; Boyle, Michael H.; Schmidt, Louis A.

2011-01-01

Although joint attention processes are known to play an important role in adaptive social behavior in typical development, we know little about these processes in clinical child populations. We compared early school age children with selective mutism (SM; n = 19) versus mixed anxiety (MA; n = 18) and community controls (CC; n = 26) on joint…

Languages for Today's World. DIMENSION 2006. Selected Proceedings of the 2006 Joint Conference of the Southern Conference on Language Teaching and the Florida Foreign Language Association

ERIC Educational Resources Information Center

Wilbur, Marcia L.; LeLoup, Jean W.; Ponterio, Robert; Jones, Zachary; Nuhfer-Halten, Bernice; Gordon, Kenneth A.; Gardner, Steven M.; Mentley, Carlos; Signori, Lisa F.; Heusinkveld, Paula; Burns-Hoffman, Rebecca; Jones, Jennifer; Cohn, Christie; Cherry, C. Maurice, Ed.

2006-01-01

"Dimension" is the annual volume containing the selected, refereed, edited Proceedings of each year's conference. The theme chosen for the joint conference of the Southern Conference on Language Teaching (SCOLT) and the Florida Foreign Language Association (FFLA) in Orlando, Florida, February 16-18, 2006, was "Languages for Today's…

The Role of Joint Control in the Manded Selection Responses of Both Vocal and Non-Vocal Children with Autism

ERIC Educational Resources Information Center

Tu, Joyce C.

2006-01-01

In the present study, joint-control training was applied when teaching manded selection responses to children with autism. Four vocal children with autism participated in the first experiment, two males (ages seven and eight) and two females (ages seven and nine). The results showed that it was only after object-word naming was trained under joint…

Do joints initiate as sharp mode I fractures or finite thickness dilatancy bands? Insights from laboratory experiments and field data

NASA Astrophysics Data System (ADS)

Petit, J.; Chemenda, A. I.; Jorand, C.

2011-12-01

Terminology on fracture and discontinuities in geological objects mainly relies on distinguishing between tabular and sharp forms of deformation localization/failure structures (Aydin et al, JSG 2006; Shultz and Fossen, AAPG, 2009). On this basis joints (considered as mode I fractures) and dilation bands (very rarely observed) are distinguished among extension discontinuities. The former propagate with the separation of the fracture walls due to strong stress concentration at the fracture tips. The plumose features or hackles typical of joints (these terms cover a wide variety of diverging fractographic features) are believed to result from the fracture front breakdown due to the loading mode change (the origin of this change remains unclear). This view is called into question by recent experimental results of extension tests conducted on a synthetic physical rock analogue (granular, frictional, cohesive and dilatant) material (GRAM1) and by field observations of embryonic (not yet open) joints in highly jointed dolomicrite Chemenda et al., JGR, 2011). The initial porosity and grain size of both materials are very different, but at SEM scale, both experimental and natural unopened discontinuities reveal a comparable dilatancy (dilation) band structure with a porosity increase over a width of several grains. This suggests that the distinction between tabular and sharp is a matter of observation scale. Both axisymetric and poly-axial extension tests show that dilatancy bands form at elevated mean stress and have plumose morphology. Mode I cracking occurs only at very low mean stres and the forming fractures do not bear plumose features. Thus the absence of plumose structures can be considered as the signature of mode I fracturing. Consequently, we propose that non- plumose bearing natural joints (provided their fractography is not eroded) could originate as mode I fractures and call them "mode I joints". We call the joints formed as closed dilatancy bands propagating at relatively high pressure (depth) conditions and generating the plumose fractography "dilatancy joints". These joints obtained in poly-axial experiments can be very tight as is also often observed in nature. Joint spacing was shown to depend on the loading conditions but not on the sample thickness, which is another argument against the mode I mechanism. There are two main reasons for which the dilatancy joints were not detected previously: (1) the dilatancy band tends to open during exhumation (it is a weakness zone) leading to the separation of the two walls with destruction of the dilatancy band texture and mineral infilling; (2) if no opening occurs, as soon as the band of increased permeability is formed, diagenetic/epigenetic processes can rapidly cancel the initial structure, the trace of the band appearing at great magnification as a tiny mineralized vein. Such transformation must be very frequent in sedimentary rocks, but it can be absent when the mineral solubility is limited, as for the dolomicrite example presented.

Activities of the Boom and Chassis Group

NASA Technical Reports Server (NTRS)

Dell, Jason Scott; Meeks, Thomas Bayne; Merkel, Kelly; Nelson, Brent; Winchell, Tom

1992-01-01

Group One of the NASA Lunar Enabler Project has designed the primary chassis and boom structures for the lunar vehicle. Both components also feature V-clamps that were adapted to interface connections within the structure. The chassis features a front end, rear end section, middle cross-section, and face plate. The rear section contains an extra compartment for the engine, hydraulic pump, fuel bottles, and oil reservoir necessary for the wheel drives. Each section consists of tubular aluminum 6061-T6. The boom features four degrees of freedom system, where the minimum factor of safety of any part is 1.5 (but, normally much higher). It consists of a tapered upper boom, lower boom, and three elbows that complement the articulation joints. Each section of the boom has been constructed from aluminum 6061-T6. There are four joints and eight V-clamps in the boom assembly. The V-clamps feature support rings that prevent axial rotation. They provide easy adaptability and assembly.

Design of a Virtual Player for Joint Improvisation with Humans in the Mirror Game

PubMed Central

Zhai, Chao; Alderisio, Francesco; Tsaneva-Atanasova, Krasimira; di Bernardo, Mario

2016-01-01

Joint improvisation is often observed among humans performing joint action tasks. Exploring the underlying cognitive and neural mechanisms behind the emergence of joint improvisation is an open research challenge. This paper investigates jointly improvised movements between two participants in the mirror game, a paradigmatic joint task example. First, experiments involving movement coordination of different dyads of human players are performed in order to build a human benchmark. No designation of leader and follower is given beforehand. We find that joint improvisation is characterized by the lack of a leader and high levels of movement synchronization. Then, a theoretical model is proposed to capture some features of their interaction, and a set of experiments is carried out to test and validate the model ability to reproduce the experimental observations. Furthermore, the model is used to drive a computer avatar able to successfully improvise joint motion with a human participant in real time. Finally, a convergence analysis of the proposed model is carried out to confirm its ability to reproduce joint movements between the participants. PMID:27123927

Design of a Virtual Player for Joint Improvisation with Humans in the Mirror Game.

PubMed

Zhai, Chao; Alderisio, Francesco; Słowiński, Piotr; Tsaneva-Atanasova, Krasimira; di Bernardo, Mario

2016-01-01

Joint improvisation is often observed among humans performing joint action tasks. Exploring the underlying cognitive and neural mechanisms behind the emergence of joint improvisation is an open research challenge. This paper investigates jointly improvised movements between two participants in the mirror game, a paradigmatic joint task example. First, experiments involving movement coordination of different dyads of human players are performed in order to build a human benchmark. No designation of leader and follower is given beforehand. We find that joint improvisation is characterized by the lack of a leader and high levels of movement synchronization. Then, a theoretical model is proposed to capture some features of their interaction, and a set of experiments is carried out to test and validate the model ability to reproduce the experimental observations. Furthermore, the model is used to drive a computer avatar able to successfully improvise joint motion with a human participant in real time. Finally, a convergence analysis of the proposed model is carried out to confirm its ability to reproduce joint movements between the participants.

Imageological measurement of the sternoclavicular joint and its clinical application.

PubMed

Li, Ming; Wang, Bo; Zhang, Qi; Chen, Wei; Li, Zhi-Yong; Qin, Shi-Ji; Zhang, Ying-Ze

2012-01-01

Dislocation of the sternoclavicular joint is rare. However, posterior dislocation compressing important structures in the mediastinum may be fatal. Early diagnosis and prompt therapy of sternoclavicular joint dislocation are important. Computed tomography (CT) is an optimal means to investigate sternoclavicular joint anatomy; however, there are few reports on the imageological anatomical features of the sternoclavicular joint. The study investigated imageological anatomical features, and a new plate was devised according to these data to treat sternoclavicular joint dislocation. Fifty-three healthy Chinese volunteers examined with chest CT were included in the study. The coronal, sagittal, and axial images of the sternoclavicular region were reconstructed. The sternal head diameter in the inferolateral-to-superomedial direction, length of the clavicular notch, and angle between the clavicular notch and sternum were measured on coronal images. The angle between the presternum and trunk was measured on sagittal images. The following dimensions were measured on axial images: anteroposterior dimensions of the sternal head, clavicular notch, and presternum; width of the sternoclavicular joint; distance between bilateral clavicles; and minimal distance from the presternum to the underlying structures in the thoracic cavity. A new plate was designed according to the above data and was used to repair six sternoclavicular joint dislocations. All cases were followed up with a range of 9 to 12 months. The proximal clavicle is higher than the presternum in a horizontal position. On axial images, the anteroposterior dimension of the sternal head was longer than the presternum, and the center region of the presternum was thinner than the edges. The left sternoclavicular joint space was (0.82 ± 0.21) cm, and the right was (0.87 ± 0.22) cm. Among the structures behind the sternum, the left bilateral innominate vein ran nearest to the presternum. The distance from the anterior cortex of the sterna to the left bilateral innominate vein was (2.38 ± 0.61) cm. The dislocated joints were reduced anatomically and fixed with the new plate. All cases obtained satisfactory outcomes in follow-up visits. Normal sternoclavicular joint parameters were measured on CT images, which can facilitate treatment of sternoclavicular joint dislocation or subluxation. This newly designed plate can be used to treat sternoclavicular joint dislocation effectively and safely.

EDITORIAL: Theory of fusion plasmas: selected papers from the Joint Varenna-Lausanne International Workshop Theory of fusion plasmas: selected papers from the Joint Varenna-Lausanne International Workshop

NASA Astrophysics Data System (ADS)

Garbet, X.; Sauter, O.

2011-05-01

The 2010 edition of the joint Varenna-Lausanne workshop on the theory of fusion plasmas was undoubtedly a great success. The programme encompasses a wide variety of topics, namely turbulence, MHD, edge physics and RF wave heating. The present PPCF issue is a collection of 19 outstanding papers, which cover these topics. It follows the publication of 22 refereed contributed papers in Journal of Physics: Conference Series 2010 260. There is no doubt that the production of articles was both abundant and of high scientific quality. This is why the Varenna-Lausanne meeting takes an important place in the landscape of conferences on fusion. Indeed this is the ideal forum for exchanging ideas on theory and modelling, and for substantiating the best results obtained in our field. The tradition of the meeting is to provide a forum for numerical modelling activities. This custom was clearly respected given the large fraction of papers in this special issue which address this subject. This feature reflects the revolution we have been living through for some years with the fast growth of high-performance computers. It also appears that analytical theory is flourishing. This is important for bringing new ideas and guidance to numerical simulations. Finally, code validation and comparison to experiments are well represented. We believe that this is good news given the complexity of the non-linear physics that is at stake in fusion devices. Another subject of satisfaction was the presence of many young scientists at the meeting. The encounter between young researchers and senior scientists is certainly a strong point of the Varenna-Lausanne conference. In conclusion, we anticipate a great success for this special issue of PPCF and we hope that the readers will find therein ideas and inspiration.

Predicting timing of foot strike during running, independent of striking technique, using principal component analysis of joint angles.

PubMed

Osis, Sean T; Hettinga, Blayne A; Leitch, Jessica; Ferber, Reed

2014-08-22

As 3-dimensional (3D) motion-capture for clinical gait analysis continues to evolve, new methods must be developed to improve the detection of gait cycle events based on kinematic data. Recently, the application of principal component analysis (PCA) to gait data has shown promise in detecting important biomechanical features. Therefore, the purpose of this study was to define a new foot strike detection method for a continuum of striking techniques, by applying PCA to joint angle waveforms. In accordance with Newtonian mechanics, it was hypothesized that transient features in the sagittal-plane accelerations of the lower extremity would be linked with the impulsive application of force to the foot at foot strike. Kinematic and kinetic data from treadmill running were selected for 154 subjects, from a database of gait biomechanics. Ankle, knee and hip sagittal plane angular acceleration kinematic curves were chained together to form a row input to a PCA matrix. A linear polynomial was calculated based on PCA scores, and a 10-fold cross-validation was performed to evaluate prediction accuracy against gold-standard foot strike as determined by a 10 N rise in the vertical ground reaction force. Results show 89-94% of all predicted foot strikes were within 4 frames (20 ms) of the gold standard with the largest error being 28 ms. It is concluded that this new foot strike detection is an improvement on existing methods and can be applied regardless of whether the runner exhibits a rearfoot, midfoot, or forefoot strike pattern. Copyright © 2014 Elsevier Ltd. All rights reserved.

Phalangeal joints kinematics during ostrich (Struthio camelus) locomotion

PubMed Central

Ji, Qiaoli; Luo, Gang; Xue, Shuliang; Ma, Songsong; Li, Jianqiao

2017-01-01

The ostrich is a highly cursorial bipedal land animal with a permanently elevated metatarsophalangeal joint supported by only two toes. Although locomotor kinematics in walking and running ostriches have been examined, these studies have been largely limited to above the metatarsophalangeal joint. In this study, kinematic data of all major toe joints were collected from gaits with double support (slow walking) to running during stance period in a semi-natural setup with two selected cooperative ostriches. Statistical analyses were conducted to investigate the effect of locomotor gait on toe joint kinematics. The MTP3 and MTP4 joints exhibit the largest range of motion whereas the first phalangeal joint of the 4th toe shows the largest motion variability. The interphalangeal joints of the 3rd and 4th toes present very similar motion patterns over stance phases of slow walking and running. However, the motion patterns of the MTP3 and MTP4 joints and the vertical displacement of the metatarsophalangeal joint are significantly different during running and slow walking. Because of the biomechanical requirements, osctriches are likely to select the inverted pendulum gait at low speeds and the bouncing gait at high speeds to improve movement performance and energy economy. Interestingly, the motions of the MTP3 and MTP4 joints are highly synchronized from slow to fast locomotion. This strongly suggests that the 3rd and 4th toes really work as an “integrated system” with the 3rd toe as the main load bearing element whilst the 4th toe as the complementary load sharing element with a primary role to ensure the lateral stability of the permanently elevated metatarsophalangeal joint. PMID:28097064

Unweaving the joints in Entrada Sandstone, Arches National Park, Utah, U.S.A.

NASA Astrophysics Data System (ADS)

Cruikshank, Kenneth M.; Aydin, Atilla

1995-03-01

On the southwest limb of Salt Valley Anticline, Arches National Park, Utah three sets of joints are developed in the Entrada Sandstone covering an area of about 6 km 2. Within the 20 m thick Moab Member, a single joint set is is found in three distinct areas, separated by a second set of joints at a 35° angle to the first set. Joint interaction features show that the second set is younger than the first. This illustrates that joints of a single set do not have to fill the entire area across which the stresses that formed the joints were acting. The underlying Slickrock Member contains a third set of joints, which is at an angle of 5°-35° to joints in the Moab Member. The Slickrock set nucleated from the lower edges of joints of all orientations in the overlying Moab Member. Thus, the fracture pattern evolved both horizontally, within the same unit, and vertically between units. The sequence of jointing is determined by establishing the relative ages of each joint set. Each joint orientation is best interpreted as representing a direction of maximum compression, ruling out the possibility that the joints are a conjugate set. The joints, and an earlier set of deformation bands, record a 95° counterclockwise rotation of the direction of maximum compression.

Characterization of healthy and osteoarthritic chondrocyte cell patterns on phase contrast CT images of the knee cartilage matrix

NASA Astrophysics Data System (ADS)

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Yang, Chien-Chun; Glaser, Christian; Reiser, Maximilian F.; Wismüller, Axel

2012-03-01

The current approach to evaluating cartilage degeneration at the knee joint requires visualization of the joint space on radiographic images where indirect cues such as joint space narrowing serve as markers for osteoarthritis. A recent novel approach to visualizing the knee cartilage matrix using phase contrast CT imaging (PCI-CT) was shown to allow direct examination of chondrocyte cell patterns and their subsequent correlation to osteoarthritis. This study aims to characterize chondrocyte cell patterns in the radial zone of the knee cartilage matrix in the presence and absence of osteoarthritic damage through both gray-level co-occurrence matrix (GLCM) derived texture features as well as Minkowski Functionals (MF). Thirteen GLCM and three MF texture features were extracted from 404 regions of interest (ROI) annotated on PCI images of healthy and osteoarthritic specimens of knee cartilage. These texture features were then used in a machine learning task to classify ROIs as healthy or osteoarthritic. A fuzzy k-nearest neighbor classifier was used and its performance was evaluated using the area under the ROC curve (AUC). The best classification performance was observed with the MF features 'perimeter' and 'Euler characteristic' and with GLCM correlation features (f3 and f13). With the experimental conditions used in this study, both Minkowski Functionals and GLCM achieved a high classification performance (AUC value of 0.97) in the task of distinguishing between health and osteoarthritic ROIs. These results show that such quantitative analysis of chondrocyte patterns in the knee cartilage matrix can distinguish between healthy and osteoarthritic tissue with high accuracy.

Cross-layer Joint Relay Selection and Power Allocation Scheme for Cooperative Relaying System

NASA Astrophysics Data System (ADS)

Zhi, Hui; He, Mengmeng; Wang, Feiyue; Huang, Ziju

2018-03-01

A novel cross-layer joint relay selection and power allocation (CL-JRSPA) scheme over physical layer and data-link layer is proposed for cooperative relaying system in this paper. Our goal is finding the optimal relay selection and power allocation scheme to maximize system achievable rate when satisfying total transmit power constraint in physical layer and statistical delay quality-of-service (QoS) demand in data-link layer. Using the concept of effective capacity (EC), our goal can be formulated into an optimal joint relay selection and power allocation (JRSPA) problem to maximize the EC when satisfying total transmit power limitation. We first solving optimal power allocation (PA) problem with Lagrange multiplier approach, and then solving optimal relay selection (RS) problem. Simulation results demonstrate that CL-JRSPA scheme gets larger EC than other schemes when satisfying delay QoS demand. In addition, the proposed CL-JRSPA scheme achieves the maximal EC when relay located approximately halfway between source and destination, and EC becomes smaller when the QoS exponent becomes larger.

Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images.

PubMed

Rakotomamonjy, Alain; Petitjean, Caroline; Salaün, Mathieu; Thiberville, Luc

2014-06-01

To assess the feasibility of lung cancer diagnosis using fibered confocal fluorescence microscopy (FCFM) imaging technique and scattering features for pattern recognition. FCFM imaging technique is a new medical imaging technique for which interest has yet to be established for diagnosis. This paper addresses the problem of lung cancer detection using FCFM images and, as a first contribution, assesses the feasibility of computer-aided diagnosis through these images. Towards this aim, we have built a pattern recognition scheme which involves a feature extraction stage and a classification stage. The second contribution relies on the features used for discrimination. Indeed, we have employed the so-called scattering transform for extracting discriminative features, which are robust to small deformations in the images. We have also compared and combined these features with classical yet powerful features like local binary patterns (LBP) and their variants denoted as local quinary patterns (LQP). We show that scattering features yielded to better recognition performances than classical features like LBP and their LQP variants for the FCFM image classification problems. Another finding is that LBP-based and scattering-based features provide complementary discriminative information and, in some situations, we empirically establish that performance can be improved when jointly using LBP, LQP and scattering features. In this work we analyze the joint capability of FCFM images and scattering features for lung cancer diagnosis. The proposed method achieves a good recognition rate for such a diagnosis problem. It also performs well when used in conjunction with other features for other classical medical imaging classification problems. Copyright © 2014 Elsevier B.V. All rights reserved.

Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data.

PubMed

Zhang, Bo; Chen, Zhen; Albert, Paul S

2012-01-01

High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, we use latent risk classes to link the 2 modeling components. We characterize complex biomarker-specific differences through biomarker-specific random effects, so that different biomarkers can have different baseline (low-risk) values as well as different between-class differences. The proposed approach also accommodates data features that are common in environmental toxicology and other biomarker exposure data, including a large number of biomarkers, numerous zero values, and complex mean-variance relationship in the biomarkers levels. A Monte Carlo EM (MCEM) algorithm is proposed for parameter estimation. Both the MCEM algorithm and model selection procedures are shown to work well in simulations and applications. In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis.

United States Physical Therapists' Knowledge About Joint Hypermobility Syndrome Compared with Fibromyalgia and Rheumatoid Arthritis.

PubMed

Russek, Leslie N; LaShomb, Emily A; Ware, Amy M; Wesner, Sarah M; Westcott, Vanessa

2016-03-01

Joint hypermobility syndrome (JHS) is one of the most common inherited connective tissue disorders. It causes significant pain and disability for all age groups, ranging from developmental delay among children to widespread chronic pain in adults. Experts in JHS assert that the condition is under-recognized and poorly managed. The aim of this study was to assess US physical therapists' knowledge about JHS compared with other causes of widespread pain and activity limitations: fibromyalgia, juvenile rheumatoid arthritis and adult rheumatoid arthritis. Cross-sectional, Internet-based survey of randomly selected members of the American Physical Therapy Association and descriptive statistics were used to explore physical therapists' knowledge about JHS, fibromyalgia, juvenile rheumatoid arthritis and adult rheumatoid arthritis, and chi square was used to compare knowledge about the different conditions. The response rate was 15.5% (496). Although 36% recognized the Beighton Scale for assessing joint hypermobility, only 26.8% of respondents were familiar with the Brighton Criteria for diagnosing JHS. Few respondents (11-19%) realized that JHS has extra-articular features such as anxiety disorder, fatigue, headache, delayed motor development, easy bruising and sleep disturbance. Physical therapists working in environments most likely to see patients with JHS underestimated the likely prevalence in their patient population. The results suggest that many physical therapists in the United States are not familiar with the diagnostic criteria, prevalence or common clinical presentation of JHS. Copyright © 2014 John Wiley & Sons, Ltd.

Pathology of Gray Wolf Shoulders: Lessons in Species and Aging.

PubMed

Lawler, Dennis; Becker, Julia; Reetz, Jennifer; Goodmann, Pat; Evans, Richard; Rubin, David; Tangredi, Basil; Widga, Christopher; Sackman, Jill; Martin, Terrence; Kohn, Luci; Smith, Gail

2016-10-01

We examined scapula glenoids (n = 14) and proximal articular humeri (n = 14) of seven gray wolves that were maintained in a sanctuary park setting. Immediately after death, observations were made visually in situ and by radiography. Further observations were made in a museum laboratory setting, prior to and following clearing of soft tissues. Selected dry bone specimens were evaluated using computed tomography. Significant cartilage erosion and osteoarthropathy were identified in all shoulder joints. No single evaluation method yielded maximal information. Plain film radiography revealed only more severe changes. Computed tomography yielded more detail and clarity than standard radiography. Direct examination of articular cartilage informed about joint soft tissue, and dry bone informed about externally visible bone pathology. These data provide a basis for biological, biomedical, ecological, and archaeological scientists to improve retrospective interpretations of bone lesions. They further support developing plausible differential diagnoses for features of ancient and modern animal bones. We noted a dog-like capacity for wolf longevity in a non-free-roaming environment. However, aged wolves' life spans far exceeded those of similar-sized domestic dogs and breeds, suggesting the possibility of an important species difference that should be explored. We suggest also a hypothesis that the driving force for joint pathology in sheltered non-domestic species may relate significantly to achieving the longevity that is possible biologically, but is uncommon in the wild because of differential stochastic influences. Anat Rec, 299:1338-1347, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Metacarpophalangeal joint orientation in anthropoid manual phalanges.

PubMed

Rein, Thomas R; McCarty, Laura A

2012-12-01

The proximal articular surface angle of orientation (AO) of proximal phalanges of the hand and foot has been used to infer the locomotor profile of extinct Miocene catarrhines and early hominins. Previous work has found that joint orientation distinguishes quadrupedal from suspensory anthropoids. The purpose of this study is to expand on previous research by examining this feature within and across several primate clades, allowing us to investigate the potential influences of locomotion, substrate usage, hand posture, and phylogeny. We also report AO measurements in human proximal hand phalanges, allowing us to examine human skeletal variation within a wide comparative context. The angle of orientation was measured on manual proximal third phalanges of 21 extant anthropoid species using a Microscribe digitizer. Comparisons were made between locomotor groups within hominoids, platyrrhines, and cercopithecoids. Proximal phalanges of quadrupedal species were characterized by greater dorsal orientation than those of suspensory taxa in hominoids and atelids. In addition, arboreal quadrupeds had greater AO values than terrestrial quadrupeds within the Cercopithecoidea. However, within the terrestrial locomotor group, mean AO values did not differ between palmigrade and digitigrade taxa. Thus, while there appears to be a functional signal related to substrate usage, differences in use of hand postures when moving on the ground were not reflected in proximal joint orientation of the proximal phalanx. Finally, we measured relatively low AO values in human phalanges, which might be related to integration with serially homologous pedal phalanges that are under strong selective pressure related to bipedalism. Copyright © 2012 Wiley Periodicals, Inc.

Weld-brazing - a new joining process. [combination resistance spot welding and brazing of titanium alloys

NASA Technical Reports Server (NTRS)

Bales, T. T.; Royster, D. M.; Arnold, W. E., Jr.

1972-01-01

A joining process designated weld brazing which combines resistance spot welding and brazing has been developed. Resistance spot welding is used to position and align the parts as well as to establish a suitable faying surface gap for brazing. Fabrication is then completed by capillary flow of the braze alloy into the joint. The process has been used successfully to fabricate Ti-6Al-4V titanium alloy joints using 3003 aluminum braze alloy. Test results obtained on single overlap and hat-stiffened structural specimens show that weld brazed joints are superior in tensile shear, stress rupture, fatigue, and buckling than joint fabricated by spotwelding or brazing. Another attractive feature of the process is that the brazed joints is hermetically sealed by the braze material.

Laser Inspection Or Soldered Connections

NASA Astrophysics Data System (ADS)

Alper, Richard I.; Traub, Alan C.

1986-07-01

A sensitive infrared detection system monitors the slight warming and cooling of a solder joint on a PWB in response to a focused laser beam pulse lasting for 30 milliseconds. Heating and cooling rates depend on the surface finish of the solder and also upon its interr.1 features. Joints which are alike show similar heating rates; defects behave differently and are flagged as showing abnormal thermal signatures Defects include surface voids, cold solder, insufficient or missing solder, residual solder flux, contamination and large subsurface voids. Solder bridges can usually be found by targeting at suspected bridge locations. Feed-through joints at DIPs and lap joints at flat-pack ICs are readily inspected by this method. By use of computer-controlled tiltable optics, access is had to the "harder to see" joints such as at leadless chip carriers and other surface mounts. Inspection rates can be up to 10 joints per second.

Using speech for mode selection in control of multifunctional myoelectric prostheses.

PubMed

Fang, Peng; Wei, Zheng; Geng, Yanjuan; Yao, Fuan; Li, Guanglin

2013-01-01

Electromyogram (EMG) recorded from residual muscles of limbs is considered as suitable control information for motorized prostheses. However, in case of high-level amputations, the residual muscles are usually limited, which may not provide enough EMG for flexible control of myoelectric prostheses with multiple degrees of freedom of movements. Here, we proposed a control strategy, where the speech signals were used as additional information and combined with the EMG signals to realize more flexible control of multifunctional prostheses. By replacing the traditional "sequential mode-switching (joint-switching)", the speech signals were used to select a mode (joint) of the prosthetic arm, and then the EMG signals were applied to determine a motion class involved in the selected joint and to execute the motion. Preliminary results from three able-bodied subjects and one transhumeral amputee demonstrated the proposed strategy could achieve a high mode-selection rate and enhance the operation efficiency, suggesting the strategy may improve the control performance of commercial myoelectric prostheses.

Advanced Solid Rocket Motor case design status

NASA Technical Reports Server (NTRS)

Palmer, G. L.; Cash, S. F.; Beck, J. P.

1993-01-01

The Advanced Solid Rocket Motor (ASRM) case design aimed at achieving a safer and more reliable solid rocket motor for the Space Shuttle system is considered. The ASRM case has a 150.0 inch diameter, three equal length segment, and 9Ni-4CO-0.3C steel alloy. The major design features include bolted casebolted case joints which close during pressurization, plasma arc welded factory joints, integral stiffener for splash down and recovery, and integral External Tank attachment rings. Each mechanical joint has redundant and verifiable o-ring seals.

Rational Design of Tunnel Supports: An Interactive Graphics Based Analysis of the Support Requirements of Excavations in Jointed Rock Masses.

DTIC Science & Technology

1979-09-01

joint orientetion and joint slippage than to failure of the intact rock mass. Dixon (1971) noted the importance of including the confining influence of...dedicated computer. The area of research not covered by this investigation which holds promise for a future study is a detailed comparison of the results of...block data, type key "W". The program writes this data on Linc tapes for future retripval. This feature can be used to store the consolidated block

Welding technology transfer task/laser based weld joint tracking system for compressor girth welds

NASA Technical Reports Server (NTRS)

Looney, Alan

1991-01-01

Sensors to control and monitor welding operations are currently being developed at Marshall Space Flight Center. The laser based weld bead profiler/torch rotation sensor was modified to provide a weld joint tracking system for compressor girth welds. The tracking system features a precision laser based vision sensor, automated two-axis machine motion, and an industrial PC controller. The system benefits are elimination of weld repairs caused by joint tracking errors which reduces manufacturing costs and increases production output, simplification of tooling, and free costly manufacturing floor space.

Temporo-mandibular joint disease in ankylosing spondylitis.

PubMed Central

Davidson, C; Wojtulewski, J A; Bacon, P A; Winstock, D

1975-01-01

The occurrence of temporo-mandibular joint (TMJ) disease in ankylosing spondylitis is not widely recognized and its incidence is disputed. Seventy-nine patients attending two routine rheumatology clinics were therefore examined by dental surgeon and nine (11-5 per cent) were considered to have specific TMJ involvement. These patients were older than the remainder, and had more extensive spinal and peripheral joint disease. Symptoms were mild and the predominant clinical feature was restricted mouth opening, which could present considerable difficulties during emergency anaesthesia. Bilateral condylectomy was undertaken in one patient with some benefit. Images PMID:1124959

The Joint Effects-Based Contracting Execution System: A Proposed Enabling Concept for Future Joint Expeditionary Contracting Execution

DTIC Science & Technology

2008-12-01

average 1 hour per response, including the time for reviewing instruction, searching existing data sources , gathering and maintaining the data needed...Representative for the Contracting Officer on five contracts whose value xii exceeded $200 million and participated on four source selection committees...roles on source selection boards; Consolidated Husbanding Services for all Pacific Ports, Consolidated MWR services for the Pacific, Software

Joint interpretation of geophysical data using Image Fusion techniques

NASA Astrophysics Data System (ADS)

Karamitrou, A.; Tsokas, G.; Petrou, M.

2013-12-01

Joint interpretation of geophysical data produced from different methods is a challenging area of research in a wide range of applications. In this work we apply several image fusion approaches to combine maps of electrical resistivity, electromagnetic conductivity, vertical gradient of the magnetic field, magnetic susceptibility, and ground penetrating radar reflections, in order to detect archaeological relics. We utilize data gathered from Arkansas University, with the support of the U.S. Department of Defense, through the Strategic Environmental Research and Development Program (SERDP-CS1263). The area of investigation is the Army City, situated in Riley Country of Kansas, USA. The depth of the relics is estimated about 30 cm from the surface, yet the surface indications of its existence are limited. We initially register the images from the different methods to correct from random offsets due to the use of hand-held devices during the measurement procedure. Next, we apply four different image fusion approaches to create combined images, using fusion with mean values, wavelet decomposition, curvelet transform, and curvelet transform enhancing the images along specific angles. We create seven combinations of pairs between the available geophysical datasets. The combinations are such that for every pair at least one high-resolution method (resistivity or magnetic gradiometry) is included. Our results indicate that in almost every case the method of mean values produces satisfactory fused images that corporate the majority of the features of the initial images. However, the contrast of the final image is reduced, and in some cases the averaging process nearly eliminated features that are fade in the original images. Wavelet based fusion outputs also good results, providing additional control in selecting the feature wavelength. Curvelet based fusion is proved the most effective method in most of the cases. The ability of curvelet domain to unfold the image in terms of space, wavenumber, and orientation, provides important advantages compared with the rest of the methods by allowing the incorporation of a-priori information about the orientation of the potential targets.

Dynamic automated synovial imaging (DASI) for differential diagnosis of rheumatoid arthritis

NASA Astrophysics Data System (ADS)

Grisan, E.; Raffeiner, B.; Coran, A.; Rizzo, G.; Ciprian, L.; Stramare, R.

2014-03-01

Inflammatory rheumatic diseases are leading causes of disability and constitute a frequent medical disorder, leading to inability to work, high comorbidity and increased mortality. The gold-standard for diagnosing and differentiating arthritis is based on patient conditions and radiographic findings, as joint erosions or decalcification. However, early signs of arthritis are joint effusion, hypervascularization and synovial hypertrophy. In particular, vascularization has been shown to correlate with arthritis' destructive behavior, more than clinical assessment. Contrast Enhanced Ultrasound (CEUS) examination of the small joints is emerging as a sensitive tool for assessing vascularization and disease activity. The evaluation of perfusion pattern rely on subjective semiquantitative scales, that are able to capture the macroscopic degree of vascularization, but are unable to detect the subtler differences in kinetics perfusion parameters that might lead to a deeper understanding of disease progression and a better management of patients. We show that after a kinetic analysis of contrast agent appearance, providing the quantitative features characterizing the perfusion pattern of the joint, it is possible to accurately discriminate RA from PSA by building a random forest classifier on the computed features. We compare its accuracy with the assessment performed by expert radiologist blinded of the diagnosis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Syracuse, E. M.; Maceira, M.; Zhang, H.

Joint inversions of seismic data recover models that simultaneously fit multiple constraints while playing upon the strengths of each data type. Here, we jointly invert 14 years of local earthquake body wave arrival times from the Alaska Volcano Observatory catalog and Rayleigh wave dispersion curves based upon ambient noise measurements for local V p, V s, and hypocentral locations at Akutan and Makushin Volcanoes using a new joint inversion algorithm.The velocity structure and relocated seismicity of both volcanoes are significantly more complex than many other volcanoes studied using similar techniques. Seismicity is distributed among several areas beneath or beyond themore » flanks of both volcanoes, illuminating a variety of volcanic and tectonic features. The velocity structures of the two volcanoes are exemplified by the presence of narrow high-V p features in the near surface, indicating likely current or remnant pathways of magma to the surface. A single broad low-V p region beneath each volcano is slightly offset from each summit and centered at approximately 7 km depth, indicating a potential magma chamber, where magma is stored over longer time periods. Differing recovery capabilities of the Vp and Vs datasets indicate that the results of these types of joint inversions must be interpreted carefully.« less

Flexibility in the mouse middle ear: A finite element study of the frequency response

NASA Astrophysics Data System (ADS)

Gottlieb, Peter; Puria, Sunil

2018-05-01

The mammalian middle ear is comprised of three distinct ossicles, connected by joints, and suspended in an air-filled cavity. In most mammals, the ossicular joints are mobile synovial joints, which introduce flexibility into the ossicular chain. In some smaller rodents, however, these joints are less mobile, and in the mouse in particular, the malleus is additionally characterized by a large, thin plate known as the transversal lamina, which connects the manubrium to the incus-malleus joint (IMJ). We hypothesize that this feature acts as a functional joint, maintaining the benefits of a flexible ossicular chain despite a less-mobile IMJ, and tested this hypothesis with a finite element model of the mouse middle ear. The results showed that while fusing the ossicular joints had a negligible effect on sound transmission, stiffening the ossicular bone significantly reduced sound transmission, implying that bone flexibility plays a critical role in the normal function of the mouse middle ear.

Development Requirements for Spacesuit Elbow Joint

NASA Technical Reports Server (NTRS)

Peters, Benjamin

2017-01-01

Functional Requirements for spacesuit elbow joint:1) The system is a conformal, single-axis spacesuit pressurized joint that encloses the elbow joint of the suited user and uses a defined interface to connect to the suit systems on either side of the joint.2) The system shall be designed to bear the loads incurred from the internal pressure of the system, as well as the expected loads induced by the user while enabling the user move the joint through the required range of motion. The joint torque of the system experienced by the user shall remain at or below the required specification for the entire range of motion.3) The design shall be constructed, at a minimum, as a two-layer system. The internal, air-tight layer shall be referred to as the bladder, and the layer on the unpressurized side of the bladder shall be referred to as the restraint. The design of the system may include additional features or layers, such as axial webbing, to meet the overall requirements of the design.

Chronic bowel inflammation and inflammatory joint disease: Pathophysiology.

PubMed

Speca, Silvia; Dubuquoy, Laurent

2017-07-01

Bowel inflammation is closely linked to chronic joint inflammation. Research reported in the 1980s demonstrated bowel inflammation with gross and microscopic pathological features identical to those of Crohn's disease in over 60% of patients with spondyloarthritis (SpA). Numerous prospective studies have evidenced joint involvement in patients with chronic inflammatory bowel disease (IBD) and bowel inflammation in patients with SpA. Nevertheless, the interactions of joint disease and chronic bowel inflammation remain incompletely elucidated. Two main hypotheses have been suggested to explain potential links between inflammation of the mucosal immune system and peripheral arthritis: one identifies gut bacteria as potentially implicated in the development of joint inflammation and the other involves the recruitment of gut lymphocytes or activated macrophages to the joints. Pathophysiological investigations have established that HLA-B27 is a pivotal pathogenic factor. Here, we review current data on links between chronic bowel inflammation and inflammatory joint disease. Copyright © 2017 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

Evaluation of scattered light distributions of cw-transillumination for functional diagnostic of rheumatic disorders in interphalangeal joints

NASA Astrophysics Data System (ADS)

Prapavat, Viravuth; Schuetz, Rijk; Runge, Wolfram; Beuthan, Juergen; Mueller, Gerhard J.

1995-12-01

This paper presents in-vitro-studies using the scattered intensity distribution obtained by cw- transillumination to examine the condition of rheumatic disorders of interphalangeal joints. Inflammation of joints, due to rheumatic diseases, leads to changes in the synovial membrane, synovia composition and content, and anatomic geometrical variations. Measurements have shown that these rheumatic induced inflammation processes result in a variation in optical properties of joint systems. With a scanning system the interphalangeal joint is transilluminated with diode lasers (670 nm, 905 nm) perpendicular to the joint cavity. The detection of the entire distribution of the transmitted radiation intensity was performed with a CCD camera. As a function of the structure and optical properties of the transilluminated volume we achieved distributions of scattered radiation which show characteristic variations in intensity and shape. Using signal and image processing procedures we evaluated the measured scattered distributions regarding their information weight, shape and scale features. Mathematical methods were used to find classification criteria to determine variations of the joint condition.

tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles.

PubMed

He, Sijin; Yong, May; Matthews, Paul M; Guo, Yike

2017-03-01

TranSMART has a wide range of functionalities for translational research and a large user community, but it does not support imaging data. In this context, imaging data typically includes 2D or 3D sets of magnitude data and metadata information. Imaging data may summarise complex feature descriptions in a less biased fashion than user defined plain texts and numeric numbers. Imaging data also is contextualised by other data sets and may be analysed jointly with other data that can explain features or their variation. Here we describe the tranSMART-XNAT Connector we have developed. This connector consists of components for data capture, organisation and analysis. Data capture is responsible for imaging capture either from PACS system or directly from an MRI scanner, or from raw data files. Data are organised in a similar fashion as tranSMART and are stored in a format that allows direct analysis within tranSMART. The connector enables selection and download of DICOM images and associated resources using subjects' clinical phenotypic and genotypic criteria. tranSMART-XNAT connector is written in Java/Groovy/Grails. It is maintained and available for download at https://github.com/sh107/transmart-xnat-connector.git. sijin@ebi.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Configuration control of seven-degree-of-freedom arms

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor); Long, Mark K. (Inventor); Lee, Thomas S. (Inventor)

1992-01-01

A seven degree of freedom robot arm with a six degree of freedom end effector is controlled by a processor employing a 6 by 7 Jacobian matrix for defining location and orientation of the end effector in terms of the rotation angles of the joints, a 1 (or more) by 7 Jacobian matrix for defining 1 (or more) user specified kinematic functions constraining location or movement of selected portions of the arm in terms of the joint angles, the processor combining the two Jacobian matrices to produce an augmented 7 (or more) by 7 Jacobian matrix, the processor effecting control by computing in accordance with forward kinematics from the augmented 7 by 7 Jacobian matrix and from the seven joint angles of the arm a set of seven desired joint angles for transmittal to the joint servo loops of the arm. One of the kinematic functions constraints the orientation of the elbow plane of the arm. Another one of the kinematic functions minimizes a sum of gravitational torques on the joints. Still another kinematic function constrains the location of the arm to perform collision avoidance. Generically, one kinematic function minimizes a sum of selected mechanical parameters of at least some of the joints associated with weighting coefficients which may be changed during arm movement. The mechanical parameters may be velocity errors or gravity torques associated with individual joints.

Configuration control of seven degree of freedom arms

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1995-01-01

A seven-degree-of-freedom robot arm with a six-degree-of-freedom end effector is controlled by a processor employing a 6-by-7 Jacobian matrix for defining location and orientation of the end effector in terms of the rotation angles of the joints, a 1 (or more)-by-7 Jacobian matrix for defining 1 (or more) user-specified kinematic functions constraining location or movement of selected portions of the arm in terms of the joint angles, the processor combining the two Jacobian matrices to produce an augmented 7 (or more)-by-7 Jacobian matrix, the processor effecting control by computing in accordance with forward kinematics from the augmented 7-by-7 Jacobian matrix and from the seven joint angles of the arm a set of seven desired joint angles for transmittal to the joint servo loops of the arms. One of the kinematic functions constrains the orientation of the elbow plane of the arm. Another one of the kinematic functions minimizing a sum of gravitational torques on the joints. Still another one of the kinematic functions constrains the location of the arm to perform collision avoidance. Generically, one of the kinematic functions minimizes a sum of selected mechanical parameters of at least some of the joints associated with weighting coefficients which may be changed during arm movement. The mechanical parameters may be velocity errors or position errors or gravity torques associated with individual joints.

Radiological features of experimental staphylococcal septic arthritis by micro computed tomography scan

PubMed Central

Fatima, Farah; Fei, Ying; Ali, Abukar; Mohammad, Majd; Erlandsson, Malin C.; Bokarewa, Maria I.; Nawaz, Muhammad; Valadi, Hadi; Na, Manli

2017-01-01

Background Permanent joint dysfunction due to bone destruction occurs in up to 50% of patients with septic arthritis. Recently, imaging technologies such as micro computed tomography (μCT) scan have been widely used for preclinical models of autoimmune joint disorders. However, the radiological features of septic arthritis in mice are still largely unknown. Methods NMRI mice were intravenously or intra-articularly inoculated with S. aureus Newman or LS-1 strain. The radiological and clinical signs of septic arthritis were followed for 10 days using μCT. We assessed the correlations between joint radiological changes and clinical signs, histological changes, and serum levels of cytokines. Results On days 5–7 after intravenous infection, bone destruction verified by μCT became evident in most of the infected joints. Radiological signs of bone destruction were dependent on the bacterial dose. The site most commonly affected by septic arthritis was the distal femur in knees. The bone destruction detected by μCT was positively correlated with histological changes in both local and hematogenous septic arthritis. The serum levels of IL-6 were significantly correlated with the severity of joint destruction. Conclusion μCT is a sensitive method for monitoring disease progression and determining the severity of bone destruction in a mouse model of septic arthritis. IL-6 may be used as a biomarker for bone destruction in septic arthritis. PMID:28152087

Immediate effects of EVA midsole resilience and upper shoe structure on running biomechanics: a machine learning approach

PubMed Central

Gavião Neto, Wilson P.; Roveri, Maria Isabel; Oliveira, Wagner R.

2017-01-01

Background Resilience of midsole material and the upper structure of the shoe are conceptual characteristics that can interfere in running biomechanics patterns. Artificial intelligence techniques can capture features from the entire waveform, adding new perspective for biomechanical analysis. This study tested the influence of shoe midsole resilience and upper structure on running kinematics and kinetics of non-professional runners by using feature selection, information gain, and artificial neural network analysis. Methods Twenty-seven experienced male runners (63 ± 44 km/week run) ran in four-shoe design that combined two resilience-cushioning materials (low and high) and two uppers (minimalist and structured). Kinematic data was acquired by six infrared cameras at 300 Hz, and ground reaction forces were acquired by two force plates at 1,200 Hz. We conducted a Machine Learning analysis to identify features from the complete kinematic and kinetic time series and from 42 discrete variables that had better discriminate the four shoes studied. For that analysis, we built an input data matrix of dimensions 1,080 (10 trials × 4 shoes × 27 subjects) × 1,254 (3 joints × 3 planes of movement × 101 data points + 3 vectors forces × 101 data points + 42 discrete calculated kinetic and kinematic features). Results The applied feature selection by information gain and artificial neural networks successfully differentiated the two resilience materials using 200(16%) biomechanical variables with an accuracy of 84.8% by detecting alterations of running biomechanics, and the two upper structures with an accuracy of 93.9%. Discussion The discrimination of midsole resilience resulted in lower accuracy levels than did the discrimination of the shoe uppers. In both cases, the ground reaction forces were among the 25 most relevant features. The resilience of the cushioning material caused significant effects on initial heel impact, while the effects of different uppers were distributed along the stance phase of running. Biomechanical changes due to shoe midsole resilience seemed to be subject-dependent, while those due to upper structure seemed to be subject-independent. PMID:28265506

Immediate effects of EVA midsole resilience and upper shoe structure on running biomechanics: a machine learning approach.

PubMed

Onodera, Andrea N; Gavião Neto, Wilson P; Roveri, Maria Isabel; Oliveira, Wagner R; Sacco, Isabel Cn

2017-01-01

Resilience of midsole material and the upper structure of the shoe are conceptual characteristics that can interfere in running biomechanics patterns. Artificial intelligence techniques can capture features from the entire waveform, adding new perspective for biomechanical analysis. This study tested the influence of shoe midsole resilience and upper structure on running kinematics and kinetics of non-professional runners by using feature selection, information gain, and artificial neural network analysis. Twenty-seven experienced male runners (63 ± 44 km/week run) ran in four-shoe design that combined two resilience-cushioning materials (low and high) and two uppers (minimalist and structured). Kinematic data was acquired by six infrared cameras at 300 Hz, and ground reaction forces were acquired by two force plates at 1,200 Hz. We conducted a Machine Learning analysis to identify features from the complete kinematic and kinetic time series and from 42 discrete variables that had better discriminate the four shoes studied. For that analysis, we built an input data matrix of dimensions 1,080 (10 trials × 4 shoes × 27 subjects) × 1,254 (3 joints × 3 planes of movement × 101 data points + 3 vectors forces × 101 data points + 42 discrete calculated kinetic and kinematic features). The applied feature selection by information gain and artificial neural networks successfully differentiated the two resilience materials using 200(16%) biomechanical variables with an accuracy of 84.8% by detecting alterations of running biomechanics, and the two upper structures with an accuracy of 93.9%. The discrimination of midsole resilience resulted in lower accuracy levels than did the discrimination of the shoe uppers. In both cases, the ground reaction forces were among the 25 most relevant features. The resilience of the cushioning material caused significant effects on initial heel impact, while the effects of different uppers were distributed along the stance phase of running. Biomechanical changes due to shoe midsole resilience seemed to be subject-dependent, while those due to upper structure seemed to be subject-independent.

Online feature selection with streaming features.

PubMed

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

Influence of groove size and reinforcements addition on mechanical properties and microstructure of friction stir welded joints

NASA Astrophysics Data System (ADS)

Reddy Baridula, Ravinder; Ibrahim, Abdullah Bin; Yahya, Che Ku Mohammad Faizal Bin Che Ku; Kulkarni, Ratnakar; Varma Ramaraju, Ramgopal

2018-03-01

The butt joints fabricated by friction stir welding were found to have more strength than the joints obtained by conventional joining process. The important outcome of this process is the successful fabrication of surface composites with improved properties. Thus in order to further enhance the strength of the dissimilar alloy joints the reinforcements can be deposited in to the aluminium matrix during the process of friction stir welding. In the present study the multi-walled carbon nanotubes were embedded in to the groove by varying the width during joining of dissimilar alloys AA2024 and AA7075. Four widths were selected with constant depth and optimum process parameters were selected to fabricate the sound welded joints. The results show that the mechanical properties of the fabricated butt joints were influenced by the size of the groove, due to variation in the deposition of reinforcement in the stir zone. The microstructural study and identification of the elements of the welded joints show that the reinforcements deposition is influenced by the size of the groove. It has also been observed that the groove with minimum width is more effective than higher width. The mechanical properties are found to be improved due to the pinning of grain boundaries.

Joint Effects of Ambient Air Pollutants on Pediatric Asthma ...

EPA Pesticide Factsheets

Background: Because ambient air pollution exposure occurs in the form of mixtures, consideration of joint effects of multiple pollutants may advance our understanding of air pollution health effects. Methods: We assessed the joint effect of selected ambient air pollutant combinations (groups of oxidant, secondary, traffic, power plant, and criteria pollutants constructed using combinations of criteria gases, fine particulate matter (PM2.5) and PM2.5 components) on warm season pediatric asthma emergency department (ED) visits in Atlanta during 1998-2004. Joint effects were assessed using multi-pollutant Poisson generalized linear models controlling for time trends, meteorology and daily non-asthma respiratory ED visit counts. Rate ratios (RR) were calculated for the combined effect of an interquartile-range increment in the concentration of each pollutant. Results: Increases in all of the selected pollutant combinations were associated with increases in pediatric asthma ED visits [e.g., joint effect rate ratio=1.13 (95% confidence interval 1.06-1.21) for criteria pollutants (including ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, and PM2.5)]. Joint effect estimates were smaller than estimates calculated based on summing results from single-pollutant models, due to control for confounding. Compared with models without interactions, joint effect estimates from models including first-order pollutant interactions were similar for oxidant a

Method for selecting minimum width of leaf in multileaf adjustable collimator while inhibiting passage of particle beams of radiation through sawtooth joints between collimator leaves

DOEpatents

Ludewigt, Bernhard; Bercovitz, John; Nyman, Mark; Chu, William

1995-01-01

A method is disclosed for selecting the minimum width of individual leaves of a multileaf adjustable collimator having sawtooth top and bottom surfaces between adjacent leaves of a first stack of leaves and sawtooth end edges which are capable of intermeshing with the corresponding sawtooth end edges of leaves in a second stack of leaves of the collimator. The minimum width of individual leaves in the collimator, each having a sawtooth configuration in the surface facing another leaf in the same stack and a sawtooth end edge, is selected to comprise the sum of the penetration depth or range of the particular type of radiation comprising the beam in the particular material used for forming the leaf; plus the total path length across all the air gaps in the area of the joint at the edges between two leaves defined between lines drawn across the peaks of adjacent sawtooth edges; plus at least one half of the length or period of a single sawtooth. To accomplish this, in accordance with the method of the invention, the penetration depth of the particular type of radiation in the particular material to be used for the collimator leaf is first measured. Then the distance or gap between adjoining or abutting leaves is selected, and the ratio of this distance to the height of the sawteeth is selected. Finally the number of air gaps through which the radiation will pass between sawteeth is determined by selecting the number of sawteeth to be formed in the joint. The measurement and/or selection of these parameters will permit one to determine the minimum width of the leaf which is required to prevent passage of the beam through the sawtooth joint.

Shatter cones at the Keurusselkä impact structure and their relation to local jointing

NASA Astrophysics Data System (ADS)

Hasch, Maximilian; Reimold, Wolf Uwe; Raschke, Ulli; Zaag, Patrice Tristan

2016-08-01

Shatter cones are the only distinct meso- to macroscopic recognition criterion for impact structures, yet not all is known about their formation. The Keurusselkä impact structure, Finland, is interesting in that it presents a multitude of well-exposed shatter cones in medium- to coarse-grained granitoids. The allegedly 27 km wide Keurusselkä impact structure was formed about 1150 Ma ago in rocks of the Central Finland Granitoid Complex. Special attention was paid in this work to possible relationships between shatter cones and local, as well as regionally occurring, fracture or joint systems. A possible shatter cone find outside the previously suggested edge of the structure could mean that the Keurusselkä impact structure is larger than previously thought. The spacing between joints/fractures from regional joint systems was influenced by the impact, but impact-induced fractures strongly follow the regional joint orientation trends. There is a distinct relationship between shatter cones and joints: shatter cones occur on and against joint surfaces of varied orientations and belonging to the regional orientation trends. Planar fractures (PF) and planar deformation features (PDF) were found in three shatter cone samples from the central-most part of the impact structure, whereas other country rock samples from the same level of exposure but further from the assumed center lack shock deformation features. PDF occurrence is enhanced within 5 mm of shatter cone surfaces, which is interpreted to suggest that shock wave reverberation at preimpact joints could be responsible for this local enhancement of shock deformation. Some shatter cone surfaces are coated with a quasi-opaque material which is also found in conspicuous veinlets that branch off from shatter cone surfaces and resemble pseudotachylitic breccia veins. The vein-filling is composed of two mineral phases, one of which could be identified as a montmorillonitic phyllosilicate. The second phase could not be identified yet. The original composition of the fill could not be determined. Further work is required on this material. Observed joints and fractures were discussed against findings from Barringer impact crater. They show that impact-induced joints in the basement rock do not follow impact-specific orientations (such as radial, conical, or concentric).

Premature deterioration of jointed plain concrete pavements.

DOT National Transportation Integrated Search

2011-04-29

Six sections of jointed plain concrete pavements (JPCP)s throughout the state were selected as candidates for the evaluation of premature deterioration. The data used in performing the evaluation included manual and historic automated distress survey...

Premature deterioration of jointed plain concrete pavements.

DOT National Transportation Integrated Search

2011-04-29

Six sections of jointed plain concrete pavements (JPCP)s throughout the state were selected as : candidates for the evaluation of premature deterioration. The data used in performing the evaluation included manual : and historic automated distress su...

Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to psychiatric disorders.

PubMed

Kim, Dongchul; Kang, Mingon; Biswas, Ashis; Liu, Chunyu; Gao, Jean

2016-08-10

Inferring gene regulatory networks is one of the most interesting research areas in the systems biology. Many inference methods have been developed by using a variety of computational models and approaches. However, there are two issues to solve. First, depending on the structural or computational model of inference method, the results tend to be inconsistent due to innately different advantages and limitations of the methods. Therefore the combination of dissimilar approaches is demanded as an alternative way in order to overcome the limitations of standalone methods through complementary integration. Second, sparse linear regression that is penalized by the regularization parameter (lasso) and bootstrapping-based sparse linear regression methods were suggested in state of the art methods for network inference but they are not effective for a small sample size data and also a true regulator could be missed if the target gene is strongly affected by an indirect regulator with high correlation or another true regulator. We present two novel network inference methods based on the integration of three different criteria, (i) z-score to measure the variation of gene expression from knockout data, (ii) mutual information for the dependency between two genes, and (iii) linear regression-based feature selection. Based on these criterion, we propose a lasso-based random feature selection algorithm (LARF) to achieve better performance overcoming the limitations of bootstrapping as mentioned above. In this work, there are three main contributions. First, our z score-based method to measure gene expression variations from knockout data is more effective than similar criteria of related works. Second, we confirmed that the true regulator selection can be effectively improved by LARF. Lastly, we verified that an integrative approach can clearly outperform a single method when two different methods are effectively jointed. In the experiments, our methods were validated by outperforming the state of the art methods on DREAM challenge data, and then LARF was applied to inferences of gene regulatory network associated with psychiatric disorders.

Enhancing the Discrimination Ability of a Gas Sensor Array Based on a Novel Feature Selection and Fusion Framework.

PubMed

Deng, Changjian; Lv, Kun; Shi, Debo; Yang, Bo; Yu, Song; He, Zhiyi; Yan, Jia

2018-06-12

In this paper, a novel feature selection and fusion framework is proposed to enhance the discrimination ability of gas sensor arrays for odor identification. Firstly, we put forward an efficient feature selection method based on the separability and the dissimilarity to determine the feature selection order for each type of feature when increasing the dimension of selected feature subsets. Secondly, the K-nearest neighbor (KNN) classifier is applied to determine the dimensions of the optimal feature subsets for different types of features. Finally, in the process of establishing features fusion, we come up with a classification dominance feature fusion strategy which conducts an effective basic feature. Experimental results on two datasets show that the recognition rates of Database I and Database II achieve 97.5% and 80.11%, respectively, when k = 1 for KNN classifier and the distance metric is correlation distance (COR), which demonstrates the superiority of the proposed feature selection and fusion framework in representing signal features. The novel feature selection method proposed in this paper can effectively select feature subsets that are conducive to the classification, while the feature fusion framework can fuse various features which describe the different characteristics of sensor signals, for enhancing the discrimination ability of gas sensors and, to a certain extent, suppressing drift effect.

Access, Participation, and Supports: The Defining Features of High-Quality Inclusion

ERIC Educational Resources Information Center

Buysse, Virginia

2011-01-01

This article describes current knowledge about early childhood inclusion, summarizing research and the DEC/NAEYC joint position statement on inclusion. The article also describes effective or promising educational practices that promote access, participation, and supports--the defining features of high-quality inclusion. Future efforts to improve…

Geotechnical applications of remote sensing and remote data transmission; Proceedings of the Symposium, Cocoa Beach, FL, Jan. 31-Feb. 1, 1986

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, A.I.; Pettersson, C.B.

1988-01-01

Papers and discussions concerning the geotechnical applications of remote sensing and remote data transmission, sources of remotely sensed data, and glossaries of remote sensing and remote data transmission terms, acronyms, and abbreviations are presented. Aspects of remote sensing use covered include the significance of lineaments and their effects on ground-water systems, waste-site use and geotechnical characterization, the estimation of reservoir submerging losses using CIR aerial photographs, and satellite-based investigation of the significance of surficial deposits for surface mining operations. Other topics presented include the location of potential ground subsidence and collapse features in soluble carbonate rock, optical Fourier analysis ofmore » surface features of interest in geotechnical engineering, geotechnical applications of U.S. Government remote sensing programs, updating the data base for a Geographic Information System, the joint NASA/Geosat Test Case Project, the selection of remote data telemetry methods for geotechnical applications, the standardization of remote sensing data collection and transmission, and a comparison of airborne Goodyear electronic mapping system/SAR with satelliteborne Seasat/SAR radar imagery.« less

Osteoarticular infection in intravenous drug abusers: influence of HIV infection and differences with non drug abusers.

PubMed Central

Muñoz-Fernández, S; Maciá, M A; Pantoja, L; Cardenal, A; Peña, J M; Martín Mola, E; Balsa, A; Barbado, F J; Vázquez, J J; Gijón Baños, J

1993-01-01

OBJECTIVES--To determine (a) the influence of HIV in developing osteoarticular infections in intravenous drug abusers (IVDAs) and (b) the differences between the clinical features of osteoarticular infections in IVDAs and a control group of non-IVDAs. METHODS--A comparative study of the clinical features of osteoarticular infections in all HIV positive and HIV negative IVDAs admitted to the departments of rheumatology and internal medicine during a 10 year period was carried out. The joint infections of all IVDAs, irrespective of HIV status, were compared with those of a control group of non-IVDAs lacking risk factors for HIV infection. RESULTS--A total of 482 HIV positive and 85 HIV negative IVDAs was studied, in whom 25 (5%) and six (7%) osteoarticular infections were found respectively. There were no differences in age, sex, joints affected, and causative agents between these two groups. A comparison of the 31 (5.5%) osteoarticular infections in all IVDAs with 21 infections in 616 (3.4%) non-IVDAs showed significant differences in the mean age (27.5 v 54), the frequency of affection of the axial joints (hip, sacroiliac, and sternocostal joints) (64.5% v 16.6%), and in the incidence of Candida albicans (19% v 0%). CONCLUSIONS--(1) HIV may not predispose to osteoarticular infections in IVDAs. (2) The hip, sacroiliac, and sternocostal joints (axial joints) were most commonly affected in IVDAs. (3) In Spain, unlike other countries, Gram positive bacteria and C albicans seem to be predominant agents in osteoarticular infections in IVDAs, with a low incidence of Gram negative bacteria. PMID:8215617

Knock knee and the gait of six-year-old children.

PubMed

Pretkiewicz-Abacjew, E

2003-06-01

Knock knee (genu valgum) interferes with the locomotive and supporting function of the lower limb. In static conditions the load-bearing axis of the valgus limb is displaced laterally in relation to the middle of the joint, causing the knee joint, the ankle joint, and the foot as a whole to be weighted in the wrong way. The purpose of this work is to examine the influence of knock knee on gait kinematics. The gait of twenty-two 6-year-old children of both sexes in whom knock knee had been medically diagnosed was compared with the gait of 33 children of the same age whose knee joints conformed to the norm in formation and position. Gait was recorded separately for the sagittal and the frontal planes, using a video-computer system. The results of the examination indicated statistically significant differences in the gait of the two groups of children. These differences related mainly to the time features of gait and to data on the angles in the knee and ankle joints. Although the results obtained for other features of gait did not reveal statistical differences, these did indicate that the children with knock knee walked more slowly and with a lower cadence. The results indicate that knock knee in 6-year-old children has an adverse impact on the mechanics of the lower limb joints in gait and causes a deterioration in gait quality. Thus knock knee in children should not be treated merely as a superficial defect but should be subject to therapy and, more importantly, taken into account when introducing children to early sports training.

A systematic review of the relationship between subchondral bone features, pain and structural pathology in peripheral joint osteoarthritis.

PubMed

Barr, Andrew J; Campbell, T Mark; Hopkinson, Devan; Kingsbury, Sarah R; Bowes, Mike A; Conaghan, Philip G

2015-08-25

Bone is an integral part of the osteoarthritis (OA) process. We conducted a systematic literature review in order to understand the relationship between non-conventional radiographic imaging of subchondral bone, pain, structural pathology and joint replacement in peripheral joint OA. A search of the Medline, EMBASE and Cochrane library databases was performed for original articles reporting association between non-conventional radiographic imaging-assessed subchondral bone pathologies and joint replacement, pain or structural progression in knee, hip, hand, ankle and foot OA. Each association was qualitatively characterised by a synthesis of the data from each analysis based upon study design, adequacy of covariate adjustment and quality scoring. In total 2456 abstracts were screened and 139 papers were included (70 cross-sectional, 71 longitudinal analyses; 116 knee, 15 hip, six hand, two ankle and involved 113 MRI, eight DXA, four CT, eight scintigraphic and eight 2D shape analyses). BMLs, osteophytes and bone shape were independently associated with structural progression or joint replacement. BMLs and bone shape were independently associated with longitudinal change in pain and incident frequent knee pain respectively. Subchondral bone features have independent associations with structural progression, pain and joint replacement in peripheral OA in the hip and hand but especially in the knee. For peripheral OA sites other than the knee, there are fewer associations and independent associations of bone pathologies with these important OA outcomes which may reflect fewer studies; for example the foot and ankle were poorly studied. Subchondral OA bone appears to be a relevant therapeutic target. PROSPERO registration number: CRD 42013005009.

Fracturesis Jointitis: Causes, Symptoms, and Treatment in Groundwater Communities.

PubMed

Manda, Alex K; Horsman, Eric

2015-01-01

Fracturesis Jointitis is a grammatical disorder characterized by failure or inability to understand the difference between overarching and specific terms of brittle deformation features. The disorder leads to the use of the word "fracture" as a specific type of discontinuity rather than as an overarching term for mechanical breaks in rocks. This condition appears to be prevalent among groundwater practitioners working with fractured rocks. Common signs and symptoms of Fracturesis Jointitis include the use of terms such as "joints and fractures" and "joints, faults and fractures" when describing fractures in rocks. At best, such terms imply that a "fracture" is one of many kinds of features like joints and faults, and at worst that joints and faults are not fractures but something else. Using proper terms to identify specific fracture types is critical because fractures may act as either barriers to groundwater flow (e.g., faults or deformation bands) or conduits for flow (e.g., faults and joints), The treatment for Fracturesis Jointitis involves an education campaign highlighting to the groundwater community the different fracture types that exist, the modes by which fractures propagate and the role that these fractures play in facilitating or hindering groundwater flow. Those afflicted by Fracturesis Jointitis can be cured of the condition by avoiding the word "fractures" in phrases such as "joints and fractures" or by adding descriptive words before the word "fractures" to specify fracture types (e.g., "foliation-parallel" fractures). Only with a concerted education campaign can we rid our community of Fracturesis Jointitis. © 2014, National Ground Water Association.

Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

NASA Astrophysics Data System (ADS)

Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

2013-12-01

The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

A Simple Joint Estimation Method of Residual Frequency Offset and Sampling Frequency Offset for DVB Systems

NASA Astrophysics Data System (ADS)

Kwon, Ki-Won; Cho, Yongsoo

This letter presents a simple joint estimation method for residual frequency offset (RFO) and sampling frequency offset (STO) in OFDM-based digital video broadcasting (DVB) systems. The proposed method selects a continual pilot (CP) subset from an unsymmetrically and non-uniformly distributed CP set to obtain an unbiased estimator. Simulation results show that the proposed method using a properly selected CP subset is unbiased and performs robustly.

Joint Optimization of Receiver Placement and Illuminator Selection for a Multiband Passive Radar Network.

PubMed

Xie, Rui; Wan, Xianrong; Hong, Sheng; Yi, Jianxin

2017-06-14

The performance of a passive radar network can be greatly improved by an optimal radar network structure. Generally, radar network structure optimization consists of two aspects, namely the placement of receivers in suitable places and selection of appropriate illuminators. The present study investigates issues concerning the joint optimization of receiver placement and illuminator selection for a passive radar network. Firstly, the required radar cross section (RCS) for target detection is chosen as the performance metric, and the joint optimization model boils down to the partition p -center problem (PPCP). The PPCP is then solved by a proposed bisection algorithm. The key of the bisection algorithm lies in solving the partition set covering problem (PSCP), which can be solved by a hybrid algorithm developed by coupling the convex optimization with the greedy dropping algorithm. In the end, the performance of the proposed algorithm is validated via numerical simulations.

Joint-bounded crescentic scars formed by subglacial clast-bed contact forces: Implications for bedrock failure beneath glaciers

NASA Astrophysics Data System (ADS)

Krabbendam, M.; Bradwell, T.; Everest, J. D.; Eyles, N.

2017-08-01

Glaciers and ice sheets are important agents of bedrock erosion, yet the precise processes of bedrock failure beneath glacier ice are incompletely known. Subglacially formed erosional crescentic markings (crescentic gouges, lunate fractures) on bedrock surfaces occur locally in glaciated areas and comprise a conchoidal fracture dipping down-ice and a steep fracture that faces up-ice. Here we report morphologically distinct crescentic scars that are closely associated with preexisting joints, termed here joint-bounded crescentic scars. These hitherto unreported features are ca. 50-200 mm deep and involve considerably more rock removal than previously described crescentic markings. The joint-bounded crescentic scars were found on abraded rhyolite surfaces recently exposed (< 20 years) beneath a retreating glacier in Iceland, as well as on glacially sculpted Precambrian gneisses in NW Scotland and various Precambrian rocks in Ontario, glaciated during the Late Pleistocene. We suggest a common formation mechanism for these contemporary and relict features, whereby a boulder embedded in basal ice produces a continuously migrating clast-bed contact force as it is dragged over the hard (bedrock) bed. As the ice-embedded boulder approaches a preexisting joint in the bedrock, stress concentrations build up in the bed that exceed the intact rock strength, resulting in conchoidal fracturing and detachment of a crescentic wedge-shaped rock fragment. Subsequent removal of the rock fragment probably involves further fracturing or crushing (comminution) under high contact forces. Formation of joint-bounded crescentic scars is favoured by large boulders at the base of the ice, high basal melting rates, and the presence of preexisting subvertical joints in the bedrock bed. We infer that the relative scarcity of crescentic markings in general on deglaciated surfaces shows that fracturing of intact bedrock below ice is difficult, but that preexisting weaknesses such as joints greatly facilitate rock failure. This implies that models of glacial erosion need to take fracture patterns of bedrock into account.

An optimization method for defects reduction in fiber laser keyhole welding

NASA Astrophysics Data System (ADS)

Ai, Yuewei; Jiang, Ping; Shao, Xinyu; Wang, Chunming; Li, Peigen; Mi, Gaoyang; Liu, Yang; Liu, Wei

2016-01-01

Laser welding has been widely used in automotive, power, chemical, nuclear and aerospace industries. The quality of welded joints is closely related to the existing defects which are primarily determined by the welding process parameters. This paper proposes a defects optimization method that takes the formation mechanism of welding defects and weld geometric features into consideration. The analysis of welding defects formation mechanism aims to investigate the relationship between welding defects and process parameters, and weld features are considered to identify the optimal process parameters for the desired welded joints with minimum defects. The improved back-propagation neural network possessing good modeling for nonlinear problems is adopted to establish the mathematical model and the obtained model is solved by genetic algorithm. The proposed method is validated by macroweld profile, microstructure and microhardness in the confirmation tests. The results show that the proposed method is effective at reducing welding defects and obtaining high-quality joints for fiber laser keyhole welding in practical production.

Characteristics of Laser Beam and Friction Stir Welded AISI 409M Ferritic Stainless Steel Joints

NASA Astrophysics Data System (ADS)

Lakshminarayanan, A. K.; Balasubramanian, V.

2012-04-01

This article presents the comparative evaluation of microstructural features and mechanical properties of friction stir welded (solid-state) and laser beam welded (high energy density fusion welding) AISI 409M grade ferritic stainless steel joints. Optical microscopy, microhardness testing, transverse tensile, and impact tests were performed. The coarse ferrite grains in the base material were changed to fine grains consisting duplex structure of ferrite and martensite due to the rapid cooling rate and high strain induced by severe plastic deformation caused by frictional stirring. On the other hand, columnar dendritic grain structure was observed in fusion zone of laser beam welded joints. Tensile testing indicates overmatching of the weld metal relative to the base metal irrespective of the welding processes used. The LBW joint exhibited superior impact toughness compared to the FSW joint.

Computer-aided classification of optical images for diagnosis of osteoarthritis in the finger joints.

PubMed

Zhang, Jiang; Wang, James Z; Yuan, Zhen; Sobel, Eric S; Jiang, Huabei

2011-01-01

This study presents a computer-aided classification method to distinguish osteoarthritis finger joints from healthy ones based on the functional images captured by x-ray guided diffuse optical tomography. Three imaging features, joint space width, optical absorption, and scattering coefficients, are employed to train a Least Squares Support Vector Machine (LS-SVM) classifier for osteoarthritis classification. The 10-fold validation results show that all osteoarthritis joints are clearly identified and all healthy joints are ruled out by the LS-SVM classifier. The best sensitivity, specificity, and overall accuracy of the classification by experienced technicians based on manual calculation of optical properties and visual examination of optical images are only 85%, 93%, and 90%, respectively. Therefore, our LS-SVM based computer-aided classification is a considerably improved method for osteoarthritis diagnosis.

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation

PubMed Central

Patterson, Brent R.; Anderson, Morgan L.; Rodgers, Arthur R.; Vander Vennen, Lucas M.; Fryxell, John M.

2017-01-01

Woodland caribou (Rangifer tarandus caribou) in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water) linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon) over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression) at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism–a compensatory functional response to anthropogenic linear feature density resulting in decreased use of natural travel corridors–has negative consequences for the viability of woodland caribou. PMID:29117234

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation.

PubMed

Newton, Erica J; Patterson, Brent R; Anderson, Morgan L; Rodgers, Arthur R; Vander Vennen, Lucas M; Fryxell, John M

2017-01-01

Woodland caribou (Rangifer tarandus caribou) in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water) linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon) over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression) at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism-a compensatory functional response to anthropogenic linear feature density resulting in decreased use of natural travel corridors-has negative consequences for the viability of woodland caribou.

Joint attention in parent-child dyads involving children with selective mutism: a comparison between anxious and typically developing children.

PubMed

Nowakowski, Matilda E; Tasker, Susan L; Cunningham, Charles E; McHolm, Angela E; Edison, Shannon; Pierre, Jeff St; Boyle, Michael H; Schmidt, Louis A

2011-02-01

Although joint attention processes are known to play an important role in adaptive social behavior in typical development, we know little about these processes in clinical child populations. We compared early school age children with selective mutism (SM; n = 19) versus mixed anxiety (MA; n = 18) and community controls (CC; n = 26) on joint attention measures coded from direct observations with their parent during an unstructured free play task and two structured tasks. As predicted, the SM dyads established significantly fewer episodes of joint attention through parental initiation acts than the MA and CC dyads during the structured tasks. Findings suggest that children with SM may withdraw from their parents during stressful situations, thus missing out on opportunities for learning other coping skills. We discuss the implications of the present findings for understanding the maintenance and treatment of SM.

McTwo: a two-step feature selection algorithm based on maximal information coefficient.

PubMed

Ge, Ruiquan; Zhou, Manli; Luo, Youxi; Meng, Qinghan; Mai, Guoqin; Ma, Dongli; Wang, Guoqing; Zhou, Fengfeng

2016-03-23

High-throughput bio-OMIC technologies are producing high-dimension data from bio-samples at an ever increasing rate, whereas the training sample number in a traditional experiment remains small due to various difficulties. This "large p, small n" paradigm in the area of biomedical "big data" may be at least partly solved by feature selection algorithms, which select only features significantly associated with phenotypes. Feature selection is an NP-hard problem. Due to the exponentially increased time requirement for finding the globally optimal solution, all the existing feature selection algorithms employ heuristic rules to find locally optimal solutions, and their solutions achieve different performances on different datasets. This work describes a feature selection algorithm based on a recently published correlation measurement, Maximal Information Coefficient (MIC). The proposed algorithm, McTwo, aims to select features associated with phenotypes, independently of each other, and achieving high classification performance of the nearest neighbor algorithm. Based on the comparative study of 17 datasets, McTwo performs about as well as or better than existing algorithms, with significantly reduced numbers of selected features. The features selected by McTwo also appear to have particular biomedical relevance to the phenotypes from the literature. McTwo selects a feature subset with very good classification performance, as well as a small feature number. So McTwo may represent a complementary feature selection algorithm for the high-dimensional biomedical datasets.

Learning dictionaries of sparse codes of 3D movements of body joints for real-time human activity understanding.

PubMed

Qi, Jin; Yang, Zhiyong

2014-01-01

Real-time human activity recognition is essential for human-robot interactions for assisted healthy independent living. Most previous work in this area is performed on traditional two-dimensional (2D) videos and both global and local methods have been used. Since 2D videos are sensitive to changes of lighting condition, view angle, and scale, researchers begun to explore applications of 3D information in human activity understanding in recently years. Unfortunately, features that work well on 2D videos usually don't perform well on 3D videos and there is no consensus on what 3D features should be used. Here we propose a model of human activity recognition based on 3D movements of body joints. Our method has three steps, learning dictionaries of sparse codes of 3D movements of joints, sparse coding, and classification. In the first step, space-time volumes of 3D movements of body joints are obtained via dense sampling and independent component analysis is then performed to construct a dictionary of sparse codes for each activity. In the second step, the space-time volumes are projected to the dictionaries and a set of sparse histograms of the projection coefficients are constructed as feature representations of the activities. Finally, the sparse histograms are used as inputs to a support vector machine to recognize human activities. We tested this model on three databases of human activities and found that it outperforms the state-of-the-art algorithms. Thus, this model can be used for real-time human activity recognition in many applications.

Chronic pain in Noonan Syndrome: A previously unreported but common symptom.

PubMed

Vegunta, Sravanthi; Cotugno, Richard; Williamson, Amber; Grebe, Theresa A

2015-12-01

Noonan syndrome (NS) is a multiple malformation syndrome characterized by pulmonic stenosis, cardiomyopathy, short stature, lymphatic dysplasia, craniofacial anomalies, cryptorchidism, clotting disorders, and learning disabilities. Eight genes in the RAS/MAPK signaling pathway are implicated in NS. Chronic pain is an uncommon feature. To investigate the prevalence of pain in NS, we distributed a two-part questionnaire about pain among NS individuals at the Third International Meeting on Genetic Syndromes of the Ras/MAPK Pathway. The first part of the questionnaire queried demographic information among all NS participants. The second part was completed by individuals with chronic pain. Questions included musculoskeletal problems and clinical features of pain. Forty-five questionnaires were analyzed; 53% of subjects were female. Mean age was 17 (2-48) years; 47% had a PTPN11 mutation. Sixty-two percent (28/45) of individuals with NS experienced chronic pain. There was a significant relationship between prevalence of pain and residing in a cold climate (P = 0.004). Pain occurred commonly in extremities/joints and head/trunk, but more commonly in extremities/joints (P = 0.066). Subjects with hypermobile joints were more likely to have pain (P = 0.052). Human growth hormone treatment was not statistically significant among subjects without chronic pain (P = 0.607). We conclude that pain is a frequent and under-recognized clinical feature of NS. Chronic pain may be associated with joint hypermobility and aggravated by colder climate. Our study is a preliminary investigation that should raise awareness about pain as a common symptom in children and adults with NS. © 2015 Wiley Periodicals, Inc.

Look at That! Video Chat and Joint Visual Attention Development among Babies and Toddlers

ERIC Educational Resources Information Center

McClure, Elisabeth R.; Chentsova-Dutton, Yulia E.; Holochwost, Steven J.; Parrott, W. G.; Barr, Rachel

2018-01-01

Although many relatives use video chat to keep in touch with toddlers, key features of adult-toddler interaction like joint visual attention (JVA) may be compromised in this context. In this study, 25 families with a child between 6 and 24 months were observed using video chat at home with geographically separated grandparents. We define two types…

Altering the Prosodic Features of Motherese to Promote Joint Attention in Language-Delayed Children. EBP Briefs. Volume 12, Issue 1

ERIC Educational Resources Information Center

Fredman, Traci

2017-01-01

Clinical Question: For children ages birth to 3 years diagnosed with a language delay or disorder, to what extent does the prosodic component of motherese aid in establishing joint attention (JA)? Method: Systematic Review. Study Sources: ASHA, Web of Science, CINAHL, MEDLINE, EBSCO, PubMed, PsycINFO, and ERIC. Search Terms: motherese, infant…

Command and Control for Joint Air Operations

DTIC Science & Technology

2010-01-12

systems, to include collaborative air planning tools such as the theater battle management core system ( TBMCS ). Operational level air planning occurs in...sight communications and data exchange equipment in order to respond to joint force requirements. For example, the TBMCS is often used. The use of ATO...generation and dissemination software portions of TBMCS has been standardized. This ATO feature allows the JAOC to be interoperable with other

Texture Classification by Texton: Statistical versus Binary

PubMed Central

Guo, Zhenhua; Zhang, Zhongcheng; Li, Xiu; Li, Qin; You, Jane

2014-01-01

Using statistical textons for texture classification has shown great success recently. The maximal response 8 (Statistical_MR8), image patch (Statistical_Joint) and locally invariant fractal (Statistical_Fractal) are typical statistical texton algorithms and state-of-the-art texture classification methods. However, there are two limitations when using these methods. First, it needs a training stage to build a texton library, thus the recognition accuracy will be highly depended on the training samples; second, during feature extraction, local feature is assigned to a texton by searching for the nearest texton in the whole library, which is time consuming when the library size is big and the dimension of feature is high. To address the above two issues, in this paper, three binary texton counterpart methods were proposed, Binary_MR8, Binary_Joint, and Binary_Fractal. These methods do not require any training step but encode local feature into binary representation directly. The experimental results on the CUReT, UIUC and KTH-TIPS databases show that binary texton could get sound results with fast feature extraction, especially when the image size is not big and the quality of image is not poor. PMID:24520346

Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness.

PubMed

Balcarras, Matthew; Ardid, Salva; Kaping, Daniel; Everling, Stefan; Womelsdorf, Thilo

2016-02-01

Attention includes processes that evaluate stimuli relevance, select the most relevant stimulus against less relevant stimuli, and bias choice behavior toward the selected information. It is not clear how these processes interact. Here, we captured these processes in a reinforcement learning framework applied to a feature-based attention task that required macaques to learn and update the value of stimulus features while ignoring nonrelevant sensory features, locations, and action plans. We found that value-based reinforcement learning mechanisms could account for feature-based attentional selection and choice behavior but required a value-independent stickiness selection process to explain selection errors while at asymptotic behavior. By comparing different reinforcement learning schemes, we found that trial-by-trial selections were best predicted by a model that only represents expected values for the task-relevant feature dimension, with nonrelevant stimulus features and action plans having only a marginal influence on covert selections. These findings show that attentional control subprocesses can be described by (1) the reinforcement learning of feature values within a restricted feature space that excludes irrelevant feature dimensions, (2) a stochastic selection process on feature-specific value representations, and (3) value-independent stickiness toward previous feature selections akin to perseveration in the motor domain. We speculate that these three mechanisms are implemented by distinct but interacting brain circuits and that the proposed formal account of feature-based stimulus selection will be important to understand how attentional subprocesses are implemented in primate brain networks.

Selective plantar fascia release for nonhealing diabetic plantar ulcerations.

PubMed

Kim, J Young; Hwang, Seungkeun; Lee, Yoonjung

2012-07-18

Achilles tendon lengthening can decrease plantar pressures, leading to resolution of forefoot ulceration in patients with diabetes mellitus. However, this procedure has been reported to have a complication rate of 10% to 30% and can require a long period of postoperative immobilization. We have developed a new technique, selective plantar fascia release, as an alternative to Achilles tendon lengthening for managing these forefoot ulcers. We evaluated sixty patients with diabetes for a mean of 23.5 months after selective plantar fascia release for the treatment of nonhealing diabetic neuropathic ulcers in the forefoot. Preoperative and postoperative dorsiflexion range of motion of the affected metatarsophalangeal joint and wound-healing data were used to evaluate the effectiveness of the procedure and to determine the relationship between plantar fascia release and ulcer healing. Complications were recorded. Thirty-six (56%) of the ulcers healed within six weeks, including twenty-nine (60%) of the plantar toe ulcers and seven (44%) of the metatarsophalangeal joint ulcers. The mean range of motion of the affected metatarsophalangeal joint increased from 15.3° ± 7.8° to 30.6° ± 14.1° postoperatively (p < 0.05). All patients in whom the preoperative dorsiflexion of the affected metatarsophalangeal joint was between 5° and 30° and in whom the range of motion of that joint increased by ≥13° after the procedure experienced healing of the ulcer. No ulcer recurrence in the original location was identified during follow-up. No patients experienced any complications associated with the selective plantar fascia release. Our results suggest that selective plantar fascia release can lead to healing of neuropathic plantar forefoot ulcers in diabetic patients. Ulcers in patients in whom the preoperative dorsiflexion angle of the affected metatarsophalangeal joint is between 5° and 30° and in whom the increase in range of motion is ≥13° postoperatively have the greatest chance of being cured. Therapeutic level IV. See Instructions for Authors for a complete description of the levels of evidence.

The effect of feature selection methods on computer-aided detection of masses in mammograms

NASA Astrophysics Data System (ADS)

Hupse, Rianne; Karssemeijer, Nico

2010-05-01

In computer-aided diagnosis (CAD) research, feature selection methods are often used to improve generalization performance of classifiers and shorten computation times. In an application that detects malignant masses in mammograms, we investigated the effect of using a selection criterion that is similar to the final performance measure we are optimizing, namely the mean sensitivity of the system in a predefined range of the free-response receiver operating characteristics (FROC). To obtain the generalization performance of the selected feature subsets, a cross validation procedure was performed on a dataset containing 351 abnormal and 7879 normal regions, each region providing a set of 71 mass features. The same number of noise features, not containing any information, were added to investigate the ability of the feature selection algorithms to distinguish between useful and non-useful features. It was found that significantly higher performances were obtained using feature sets selected by the general test statistic Wilks' lambda than using feature sets selected by the more specific FROC measure. Feature selection leads to better performance when compared to a system in which all features were used.

Population Coding of Forelimb Joint Kinematics by Peripheral Afferents in Monkeys

PubMed Central

Umeda, Tatsuya; Seki, Kazuhiko; Sato, Masa-aki; Nishimura, Yukio; Kawato, Mitsuo; Isa, Tadashi

2012-01-01

Various peripheral receptors provide information concerning position and movement to the central nervous system to achieve complex and dexterous movements of forelimbs in primates. The response properties of single afferent receptors to movements at a single joint have been examined in detail, but the population coding of peripheral afferents remains poorly defined. In this study, we obtained multichannel recordings from dorsal root ganglion (DRG) neurons in cervical segments of monkeys. We applied the sparse linear regression (SLiR) algorithm to the recordings, which selects useful input signals to reconstruct movement kinematics. Multichannel recordings of peripheral afferents were performed by inserting multi-electrode arrays into the DRGs of lower cervical segments in two anesthetized monkeys. A total of 112 and 92 units were responsive to the passive joint movements or the skin stimulation with a painting brush in Monkey 1 and Monkey 2, respectively. Using the SLiR algorithm, we reconstructed the temporal changes of joint angle, angular velocity, and acceleration at the elbow, wrist, and finger joints from temporal firing patterns of the DRG neurons. By automatically selecting a subset of recorded units, the SLiR achieved superior generalization performance compared with a regularized linear regression algorithm. The SLiR selected not only putative muscle units that were responsive to only the passive movements, but also a number of putative cutaneous units responsive to the skin stimulation. These results suggested that an ensemble of peripheral primary afferents that contains both putative muscle and cutaneous units encode forelimb joint kinematics of non-human primates. PMID:23112841

Detection of artifacts from high energy bursts in neonatal EEG.

PubMed

Bhattacharyya, Sourya; Biswas, Arunava; Mukherjee, Jayanta; Majumdar, Arun Kumar; Majumdar, Bandana; Mukherjee, Suchandra; Singh, Arun Kumar

2013-11-01

Detection of non-cerebral activities or artifacts, intermixed within the background EEG, is essential to discard them from subsequent pattern analysis. The problem is much harder in neonatal EEG, where the background EEG contains spikes, waves, and rapid fluctuations in amplitude and frequency. Existing artifact detection methods are mostly limited to detect only a subset of artifacts such as ocular, muscle or power line artifacts. Few methods integrate different modules, each for detection of one specific category of artifact. Furthermore, most of the reference approaches are implemented and tested on adult EEG recordings. Direct application of those methods on neonatal EEG causes performance deterioration, due to greater pattern variation and inherent complexity. A method for detection of a wide range of artifact categories in neonatal EEG is thus required. At the same time, the method should be specific enough to preserve the background EEG information. The current study describes a feature based classification approach to detect both repetitive (generated from ECG, EMG, pulse, respiration, etc.) and transient (generated from eye blinking, eye movement, patient movement, etc.) artifacts. It focuses on artifact detection within high energy burst patterns, instead of detecting artifacts within the complete background EEG with wide pattern variation. The objective is to find true burst patterns, which can later be used to identify the Burst-Suppression (BS) pattern, which is commonly observed during newborn seizure. Such selective artifact detection is proven to be more sensitive to artifacts and specific to bursts, compared to the existing artifact detection approaches applied on the complete background EEG. Several time domain, frequency domain, statistical features, and features generated by wavelet decomposition are analyzed to model the proposed bi-classification between burst and artifact segments. A feature selection method is also applied to select the feature subset producing highest classification accuracy. The suggested feature based classification method is executed using our recorded neonatal EEG dataset, consisting of burst and artifact segments. We obtain 78% sensitivity and 72% specificity as the accuracy measures. The accuracy obtained using the proposed method is found to be about 20% higher than that of the reference approaches. Joint use of the proposed method with our previous work on burst detection outperforms reference methods on simultaneous burst and artifact detection. As the proposed method supports detection of a wide range of artifact patterns, it can be improved to incorporate the detection of artifacts within other seizure patterns and background EEG information as well. © 2013 Elsevier Ltd. All rights reserved.

Introgression of an imidazolinone-resistance gene from winter wheat (Triticum aestivum L.) into jointed goatgrass (Aegilops cylindrica Host).

PubMed

Perez-Jones, Alejandro; Mallory-Smith, Carol A; Hansen, Jennifer L; Zemetra, Robert S

2006-12-01

Imidazolinone-resistant winter wheat (Triticum aestivum L.) is being commercialized in the USA. This technology allows wheat growers to selectively control jointed goatgrass (Aegilops cylindrica Host), a weed that is especially problematic because of its close genetic relationship with wheat. However, the potential movement of the imidazolinone-resistance gene from winter wheat to jointed goatgrass is a concern. Winter wheat and jointed goatgrass have the D genome in common and can hybridize and backcross under natural field conditions. Since the imidazolinone-resistance gene (Imi1) is located on the D genome, it is possible for resistance to be transferred to jointed goatgrass via hybridization and backcrossing. To study the potential for gene movement, BC(2)S(2) plants were produced artificially using imidazolinone-resistant winter wheat (cv. FS-4) as the female parent and a native jointed goatgrass collection as the male recurrent parent. FS-4, the jointed goatgrass collection, and 18 randomly selected BC(2)S(2) populations were treated with imazamox. The percentage of survival was 100% for the FS-4, 0% for the jointed goatgrass collection and 6 BC(2)S(2) populations, 40% or less for 2 BC(2)S(2) populations, and 50% or greater for the remaining 10 BC(2)S(2) populations. Chromosome counts in BC(2)S(3) plants showed a restoration of the chromosome number of jointed goatgrass, with four out of four plants examined having 28 chromosomes. Sequencing of AHASL1D in BC(2)S(3) plants derived from BC(2)S(2)-6 revealed the sexual transmission of Imi1 from FS-4 to jointed goatgrass. Imi1 conferred resistance to the imidazolinone herbicide imazamox, as shown by the in vitro assay for acetohydroxyacid synthase (AHAS) activity.

Lamb Wave-Based Structural Health Monitoring on Composite Bolted Joints under Tensile Load

PubMed Central

Yang, Bin; Xuan, Fu-Zhen; Xiang, Yanxun; Li, Dan; Zhu, Wujun; Tang, Xiaojun; Xu, Jichao; Yang, Kang; Luo, Chengqiang

2017-01-01

Online and offline monitoring of composite bolted joints under tensile load were investigated using piezoelectric transducers. The relationships between Lamb wave signals, pre-tightening force, the applied tensile load, as well as the failure modes were investigated. Results indicated that S0/A0 wave amplitudes decrease with the increasing of load. Relationships between damage features and S0/A0 mode were built based on the finite element (FE) simulation and experimental results. The possibility of application of Lamb wave-based structure health monitoring in bolted joint-like composite structures was thus achieved. PMID:28773014

Conceptualization of an exoskeleton Continuous Passive Motion(CPM) device using a link structure.

PubMed

Kim, Kyu-Jung; Kang, Min-Sung; Choi, Youn-Sung; Han, Jungsoo; Han, Changsoo

2011-01-01

This study is about developing an exoskeleton Continuous Passive Motion (CPM) with the same Range of Motion (ROM) and instant center of rotation as the human knee. The key feature in constructing a CPM is an accurate alignment with the human knee joint enabling it to deliver the same movements as the actual body on the CPM. In this research, we proposed an exoskeleton knee joint through kinematic interpretation, measured the knee joint torque generated while using a CPM and applied it to the device. Thus, this new exoskeleton type CPM will allow precise alignment with the human knee joint, and follow the same ROM as the human knee in any position. © 2011 IEEE

Spatial Selection and Local Adaptation Jointly Shape Life-History Evolution during Range Expansion.

PubMed

Van Petegem, Katrien H P; Boeye, Jeroen; Stoks, Robby; Bonte, Dries

2016-11-01

In the context of climate change and species invasions, range shifts increasingly gain attention because the rates at which they occur in the Anthropocene induce rapid changes in biological assemblages. During range shifts, species experience multiple selection pressures. For poleward expansions in particular, it is difficult to interpret observed evolutionary dynamics because of the joint action of evolutionary processes related to spatial selection and to adaptation toward local climatic conditions. To disentangle the effects of these two processes, we integrated stochastic modeling and data from a common garden experiment, using the spider mite Tetranychus urticae as a model species. By linking the empirical data with those derived form a highly parameterized individual-based model, we infer that both spatial selection and local adaptation contributed to the observed latitudinal life-history divergence. Spatial selection best described variation in dispersal behavior, while variation in development was best explained by adaptation to the local climate. Divergence in life-history traits in species shifting poleward could consequently be jointly determined by contemporary evolutionary dynamics resulting from adaptation to the environmental gradient and from spatial selection. The integration of modeling with common garden experiments provides a powerful tool to study the contribution of these evolutionary processes on life-history evolution during range expansion.

Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang Xiaojia; Mao Qirong; Zhan Yongzhao

There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions.more » The experiments show that this method can improve the recognition rate and the time of feature extraction.« less

Analysis of the stress-strain state in single overlap joints using piezo-ceramic actuators

NASA Astrophysics Data System (ADS)

Pǎltânea, Veronica; Pǎltânea, Gheorghe; Popovici, Dorina; Jiga, Gabriel; Papanicolaou, George

2014-05-01

In this paper is presented a 2D approach to finite element modeling and an analytical calculus of a single lap bonded joint. As adherent material were selected a sheet of wood, aluminum and titanium. For adhesive part were selected Bison Super Wood D3 in case of the wood single lap joint and an epoxy resin type DGEBA-TETA for gluing together aluminum and titanium parts. In the article is described a combined method, which consists in the placement of the piezoelectric actuator inside of the adhesive part, in order to determine the tensile stress in the overlap joint. A comparison between the analytical and numerical results has been achieved through a multiphysics modeling - electrical and mechanical coupled problem. The technique used to calculate the mechanical parameters (First Principal Stress, displacements) was the three-point bending test, where different forces were applied in the mid-span of the structure, in order to maintain a constant displacement rate. The length of the overlap joint was modified from 20 to 50 mm.

Impact of Selected Parameters on the Fatigue Strength of Splices on Multiply Textile Conveyor Belts

NASA Astrophysics Data System (ADS)

Bajda, Mirosław; Błażej, Ryszard; Hardygóra, Monika

2016-10-01

Splices are the weakest points in the conveyor belt loop. The strength of these joints, and thus their design as well as the method and quality of splicing, determine the strength of the whole conveyor belt loop. A special zone in a splice exists, where the stresses in the adjacent plies or cables differ considerably from each other. This results in differences in the elongation of these elements and in additional shearing stresses in the rubber layer. The strength of the joints depends on several factors, among others on the parameters of the joined belt, on the connecting layer and the technology of joining, as well as on the materials used to make the joint. The strength of the joint constitutes a criterion for the selection of a belt suitable for the operating conditions, and therefore methods of testing such joints are of great importance. This paper presents the method of testing fatigue strength of splices made on multi-ply textile conveyor belts and the results of these studies.

Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

PubMed Central

Zhao, Yu-Xiang; Chou, Chien-Hsing

2016-01-01

In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters. PMID:27314346

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention

PubMed Central

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-01

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features. PMID:26759193

75 FR 12670 - Airworthiness Directives; The Boeing Company Model 767 Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-17

... joints, the skin at certain external approved repairs, the skin around external features such as antennas... antennas, and at locations where external decals had been cut. We are issuing this AD to detect and correct... skin at certain external approved repairs, the skin around external features such as antennas, and the...

Joint trajectories for social and physical aggression as predictors of adolescent maladjustment: internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features.

PubMed

Underwood, Marion K; Beron, Kurt J; Rosen, Lisa H

2011-05-01

This investigation examined the relation between developmental trajectories jointly estimated for social and physical aggression and adjustment problems at age 14. Teachers provided ratings of children's social and physical aggression in Grades 3, 4, 5, 6, and 7 for a sample of 255 children (131 girls, 21% African American, 52% European American, 21% Mexican American). Participants, parents, and teachers completed measures of the adolescent's adjustment to assess internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features. Results showed that membership in a high and rising trajectory group predicted rule-breaking behaviors and borderline personality features. Membership in a high desister group predicted internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features. The findings suggest that although low levels of social and physical aggression may not bode poorly for adjustment, individuals engaging in high levels of social and physical aggression in middle childhood may be at greatest risk for adolescent psychopathology, whether they increase or desist in their aggression through early adolescence.

Joint trajectories for social and physical aggression as predictors of adolescent maladjustment: Internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features

PubMed Central

UNDERWOOD, MARION K.; BERON, KURT J.; ROSEN, LISA H.

2011-01-01

This investigation examined the relation between developmental trajectories jointly estimated for social and physical aggression and adjustment problems at age 14. Teachers provided ratings of children's social and physical aggression in Grades 3, 4, 5, 6, and 7 for a sample of 255 children (131 girls, 21% African American, 52% European American, 21% Mexican American). Participants, parents, and teachers completed measures of the adolescent's adjustment to assess internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features. Results showed that membership in a high and rising trajectory group predicted rule-breaking behaviors and borderline personality features. Membership in a high desister group predicted internalizing symptoms, rule-breaking behaviors, and borderline and narcissistic personality features. The findings suggest that although low levels of social and physical aggression may not bode poorly for adjustment, individuals engaging in high levels of social and physical aggression in middle childhood may be at greatest risk for adolescent psychopathology, whether they increase or desist in their aggression through early adolescence. PMID:21532919

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

EFS: an ensemble feature selection tool implemented as R-package and web-application.

PubMed

Neumann, Ursula; Genze, Nikita; Heider, Dominik

2017-01-01

Feature selection methods aim at identifying a subset of features that improve the prediction performance of subsequent classification models and thereby also simplify their interpretability. Preceding studies demonstrated that single feature selection methods can have specific biases, whereas an ensemble feature selection has the advantage to alleviate and compensate for these biases. The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in EFS, which can be used separately or combined in an ensemble. EFS identifies relevant features while compensating specific biases of single methods due to an ensemble approach. Thereby, EFS can improve the prediction accuracy and interpretability in subsequent binary classification models. EFS can be downloaded as an R-package from CRAN or used via a web application at http://EFS.heiderlab.de.

Effects of Monoclonal Antibodies against Nerve Growth Factor on Healthy Bone and Joint Tissues in Mice, Rats, and Monkeys: Histopathologic, Biomarker, and Microcomputed Tomographic Assessments.

PubMed

Gropp, Kathryn E; Carlson, Cathy S; Evans, Mark G; Bagi, Cedo M; Reagan, William J; Hurst, Susan I; Shelton, David L; Zorbas, Mark A

2018-01-01

Tanezumab, an anti-nerve growth factor (NGF) antibody, is in development for management of chronic pain. During clinical trials of anti-NGF antibodies, some patients reported unexpected adverse events requiring total joint replacements, resulting in a partial clinical hold on all NGF inhibitors. Three nonclinical toxicology studies were conducted to evaluate the effects of tanezumab or the murine precursor muMab911 on selected bone and joint endpoints and biomarkers in cynomolgus monkeys, Sprague-Dawley rats, and C57BL/6 mice. Joint and bone endpoints included histology, immunohistochemistry, microcomputed tomography (mCT) imaging, and serum biomarkers of bone physiology. Responses of bone endpoints to tanezumab were evaluated in monkeys at 4 to 30 mg/kg/week for 26 weeks and in rats at 0.2 to 10 mg/kg twice weekly for 28 days. The effects of muMab911 at 10 mg/kg/week for 12 weeks on selected bone endpoints were determined in mice. Tanezumab and muMab911 had no adverse effects on any bone or joint parameter. There were no test article-related effects on bone or joint histology, immunohistochemistry, or structure. Reversible, higher osteocalcin concentrations occurred only in the rat study. No deleterious effects were observed in joints or bones in monkeys, rats, or mice administered high doses of tanezumab or muMab911.

Degenerative joint disease: multiple joint involvement in young and mature dogs.

PubMed

Olsewski, J M; Lust, G; Rendano, V T; Summers, B A

1983-07-01

Radiologic, pathologic, and ancillary methods were used to determine the occurrence of degenerative joint disease involving multiple joints of immature and adult dogs. Animals were selected for the development of hip joint dysplasia and chronic degenerative joint disease. Of disease-prone dogs, 82% (45 of 55 dogs) had radiologic changes, indicative of hip dysplasia, by 1 year of age. At necropsy, more abnormal joints were identified than by radiographic examination. Among 92 dogs between 3 to 11 months of age that had joint abnormalities, 71% had hip joint involvement; 38%, shoulder joint involvement; 22%, stifle joint involvement; and 40% had multiple joint involvement. Polyarthritis was asymptomatic and unexpected. Radiographic examination of older dogs also revealed evidence of degenerative joint disease in many joints. Multiple joint involvement was substantiated at necropsy of young and mature dogs. A similar pattern of polyarticular osteoarthritis was revealed in a survey (computer search) of necropsy reports from medical case records of 100 adult and elderly dogs. Usually, the joint disease was an incidental observation, unrelated to the clinical disease or to the cause of death. The frequent occurrence of degenerative changes in several joints of dogs aged 6 months to 17 years indicated that osteoarthritis may be progressive in these joints and raises the possibility that systemic factors are involved in the disease process.

Cracking in dissimilar laser welding of tantalum to molybdenum

NASA Astrophysics Data System (ADS)

Zhou, Xingwen; Huang, Yongde; Hao, Kun; Chen, Yuhua

2018-06-01

Dissimilar joining of tantalum (Ta) to molybdenum (Mo) is of great interest in high temperature structural component applications. However, few reports were found about joining of these two hard-to-weld metals. The objective of this experimental study was to assess the weldability of laser butt joining of 0.2 mm-thick Ta and Mo. In order to study cracking mechanism in Ta/Mo joint, similar Ta/Ta and Mo/Mo joints were compared under the same welding conditions. An optical microscope observation revealed presence of intergranular cracks in the Mo/Mo joint, while both transgranular and intergranular cracks were observed in Ta/Mo joint. The cracking mechanism of the Ta/Mo joint was investigated further by micro-hardness testing, micro X-ray diffraction and scanning electron microscopy. The results showed that solidification cracking tendency of Mo is a main reason for crack initiation in the Ta/Mo joint. Low ductility feature in fusion zone most certainly played a role in the transgranular propagation of cracking.

Partially linear mixed-effects joint models for skewed and missing longitudinal competing risks outcomes.

PubMed

Lu, Tao; Lu, Minggen; Wang, Min; Zhang, Jun; Dong, Guang-Hui; Xu, Yong

2017-12-18

Longitudinal competing risks data frequently arise in clinical studies. Skewness and missingness are commonly observed for these data in practice. However, most joint models do not account for these data features. In this article, we propose partially linear mixed-effects joint models to analyze skew longitudinal competing risks data with missingness. In particular, to account for skewness, we replace the commonly assumed symmetric distributions by asymmetric distribution for model errors. To deal with missingness, we employ an informative missing data model. The joint models that couple the partially linear mixed-effects model for the longitudinal process, the cause-specific proportional hazard model for competing risks process and missing data process are developed. To estimate the parameters in the joint models, we propose a fully Bayesian approach based on the joint likelihood. To illustrate the proposed model and method, we implement them to an AIDS clinical study. Some interesting findings are reported. We also conduct simulation studies to validate the proposed method.

Feature selection methods for big data bioinformatics: A survey from the search perspective.

PubMed

Wang, Lipo; Wang, Yaoli; Chang, Qing

2016-12-01

This paper surveys main principles of feature selection and their recent applications in big data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and embedded approaches to feature selection, we formulate feature selection as a combinatorial optimization or search problem and categorize feature selection methods into exhaustive search, heuristic search, and hybrid methods, where heuristic search methods may further be categorized into those with or without data-distilled feature ranking measures. Copyright © 2016 Elsevier Inc. All rights reserved.

Prevalent Role of Gene Features in Determining Evolutionary Fates of Whole-Genome Duplication Duplicated Genes in Flowering Plants1[W][OA

PubMed Central

Jiang, Wen-kai; Liu, Yun-long; Xia, En-hua; Gao, Li-zhi

2013-01-01

The evolution of genes and genomes after polyploidization has been the subject of extensive studies in evolutionary biology and plant sciences. While a significant number of duplicated genes are rapidly removed during a process called fractionation, which operates after the whole-genome duplication (WGD), another considerable number of genes are retained preferentially, leading to the phenomenon of biased gene retention. However, the evolutionary mechanisms underlying gene retention after WGD remain largely unknown. Through genome-wide analyses of sequence and functional data, we comprehensively investigated the relationships between gene features and the retention probability of duplicated genes after WGDs in six plant genomes, Arabidopsis (Arabidopsis thaliana), poplar (Populus trichocarpa), soybean (Glycine max), rice (Oryza sativa), sorghum (Sorghum bicolor), and maize (Zea mays). The results showed that multiple gene features were correlated with the probability of gene retention. Using a logistic regression model based on principal component analysis, we resolved evolutionary rate, structural complexity, and GC3 content as the three major contributors to gene retention. Cluster analysis of these features further classified retained genes into three distinct groups in terms of gene features and evolutionary behaviors. Type I genes are more prone to be selected by dosage balance; type II genes are possibly subject to subfunctionalization; and type III genes may serve as potential targets for neofunctionalization. This study highlights that gene features are able to act jointly as primary forces when determining the retention and evolution of WGD-derived duplicated genes in flowering plants. These findings thus may help to provide a resolution to the debate on different evolutionary models of gene fates after WGDs. PMID:23396833

Feature selection method based on multi-fractal dimension and harmony search algorithm and its application

NASA Astrophysics Data System (ADS)

Zhang, Chen; Ni, Zhiwei; Ni, Liping; Tang, Na

2016-10-01

Feature selection is an important method of data preprocessing in data mining. In this paper, a novel feature selection method based on multi-fractal dimension and harmony search algorithm is proposed. Multi-fractal dimension is adopted as the evaluation criterion of feature subset, which can determine the number of selected features. An improved harmony search algorithm is used as the search strategy to improve the efficiency of feature selection. The performance of the proposed method is compared with that of other feature selection algorithms on UCI data-sets. Besides, the proposed method is also used to predict the daily average concentration of PM2.5 in China. Experimental results show that the proposed method can obtain competitive results in terms of both prediction accuracy and the number of selected features.

Flight set 360H005 (STS-28) seals, volume 4

NASA Technical Reports Server (NTRS)

Curry, Jeffrey T.

1990-01-01

The performance is assessed of the 360H005, Fifth flight, Redesigned Solid Rocket Motors (RSMR) in respect to joint sealing issues as seen from post flight inspection of the seals and sealing surfaces. The factory joint disassembly inspections have resumed for 360H005. The new factory joint grease application is in effect and now can be assessed during the disassembly process. The RSRM is illustrated consisting of capture feature field joints as is the J-joint insulation configuration. The nozzle-to-case joint design is also illustrated, which includes 100, 7/8 inch radial bolts in conjunction with a wiper O-ring and modified insulation design. The ignition system seals and a cross section of the igniter are illustrated. The configuration of all the internal nozzle joints are also shown. The postflight inspection of both motors showed the seal components to be in excellent condition except for the indentation found on the inner primary seal of the right hand inner igniter gasket, aft face. Detailed inspection results, and inspections performed by the O-ring Inspection Team are presented.

Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties

PubMed Central

Adali, Tülay; Levin-Schwartz, Yuri; Calhoun, Vince D.

2015-01-01

Fusion of information from multiple sets of data in order to extract a set of features that are most useful and relevant for the given task is inherent to many problems we deal with today. Since, usually, very little is known about the actual interaction among the datasets, it is highly desirable to minimize the underlying assumptions. This has been the main reason for the growing importance of data-driven methods, and in particular of independent component analysis (ICA) as it provides useful decompositions with a simple generative model and using only the assumption of statistical independence. A recent extension of ICA, independent vector analysis (IVA) generalizes ICA to multiple datasets by exploiting the statistical dependence across the datasets, and hence, as we discuss in this paper, provides an attractive solution to fusion of data from multiple datasets along with ICA. In this paper, we focus on two multivariate solutions for multi-modal data fusion that let multiple modalities fully interact for the estimation of underlying features that jointly report on all modalities. One solution is the Joint ICA model that has found wide application in medical imaging, and the second one is the the Transposed IVA model introduced here as a generalization of an approach based on multi-set canonical correlation analysis. In the discussion, we emphasize the role of diversity in the decompositions achieved by these two models, present their properties and implementation details to enable the user make informed decisions on the selection of a model along with its associated parameters. Discussions are supported by simulation results to help highlight the main issues in the implementation of these methods. PMID:26525830

Can we have an overall osteoarthritis severity score for the patellofemoral joint using magnetic resonance imaging? Reliability and validity.

PubMed

Kobayashi, Sarah; Peduto, Anthony; Simic, Milena; Fransen, Marlene; Refshauge, Kathryn; Mah, Jean; Pappas, Evangelos

2018-04-01

This work aimed to assess inter-rater reliability and agreement of a magnetic resonance imaging (MRI)-based Kellgren and Lawrence (K&L) grading for patellofemoral joint osteoarthritis (OA) and to validate it against the MRI Osteoarthritis Knee Score (MOAKS). MRI scans from people aged 45 to 75 years with chronic knee pain participating in a randomised clinical trial evaluating dietary supplements were utilised. Fifty participants were randomly selected and scored using the MRI-based K&L grading using axial and sagittal MRI scans. Raters conducted inter-rater reliability, blinded to clinical information, radiology reports and other rater results. Intra- and inter-rater reliability and agreement were evaluated using the intra-class correlation coefficient (ICC) and Cohen's weighted kappa. There was a 2-week interval between the first and second readings for intra-rater reliability. Validity was assessed using the MOAKS and evaluated using Spearman's correlation coefficient. Intra-rater reliability of the K&L system was excellent: ICC 0.91 (95% CI 0.82-0.95); weighted kappa (ĸ = 0.69). Inter-rater reliability was high (ICC 0.88; 95% CI 0.79-0.93), while agreement between raters was moderate (ĸ = 0.49-0.57). Validity analysis demonstrated a strong correlation between the total MOAKS features score and the K&L grading system (ρ = 0.62-0.67) but weak correlations when compared with individual MOAKS features (ρ = 0.19-0.61). The high reliability and good agreement show consistency in grading the severity of patellofemoral OA with the MRI-based K&L score. Our validity results suggest that the scale may be useful, particularly in the clinical environment. Future research should validate this method against clinical findings.

Metallurgical features of the formation of a solid-phase metal joint upon electric-circuit heating

NASA Astrophysics Data System (ADS)

Latypov, R. A.; Bulychev, V. V.; Zybin, I. N.

2017-06-01

The thermodynamic conditions of formation of a joint between metals using the solid-phase methods of powder metallurgy, welding, and deposition of functional coatings upon electric-current heating of the surfaces to be joined are studied. Relations are obtained to quantitatively estimate the critical sizes of the circular and linear active centers that result in the formation of stable bonding zones.

Sciatica-like symptoms and the sacroiliac joint: clinical features and differential diagnosis.

PubMed

Visser, L H; Nijssen, P G N; Tijssen, C C; van Middendorp, J J; Schieving, J

2013-07-01

To compare the clinical features of patients with sacroiliac joint (SIJ)-related sciatica-like symptoms to those with sciatica from nerve root compression and to investigate the necessity to perform radiological imaging in patients with sciatica-like symptoms derived from the SIJ. Patients with pain radiating below the buttocks with a duration of 4 weeks to 1 year were included. After physical and radiological examinations, a diagnosis of SI joint-related pain, pain due to disk herniation, or a combination of these two causes was made. Patients with SIJ-related leg pain (n = 77/186) were significantly more often female, had shorter statue, a shorter duration of symptoms, and had more often pain radiating to the groin and a history of a fall on the buttocks. Muscle weakness, corkscrew phenomenon, finger-floor distance ≥25 cm, lumbar scoliosis, positive Bragard or Kemp sign, and positive leg raising test were more often present when radiologic nerve root compression was present. Although these investigations may help, MRI of the spine is necessary to discriminate between the groups. Sciatica-like symptoms derived from the SIJ can clinically mimic a radiculopathy. We suggest to perform a thorough physical examination of the spine, SI joints, and hips with additional radiological tests to exclude other causes.

Defect features, texture and mechanical properties of friction stir welded lap joints of 2A97 Al-Li alloy thin sheets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Haiyan

1.4 mm 2A97 Al-Li alloy thin sheets were welded by friction stir lap welding using the stirring tools with different pin length at different rotational speeds. The influence of pin length and rotational speed on the defect features and mechanical properties of lap joints were investigated in detail. Microstructure observation shows that the hook defect geometry and size mainly varies with the pin length instead of the rotational speed. The size of hook defects on both the advancing side (AS) and the retreating side (RS) increased with increasing the pin length, leading to the effective sheet thickness decreased accordingly. Electronmore » backscatter diffraction analysis reveals that the weld zones, especially the nugget zone (NZ), have the much lower texture intensity than the base metal. Some new texture components are formed in the thermo-mechanical affected zone (TMAZ) and the NZ of joint. Lap shear test results show that the failure load of joints generally decreases with increasing the pin length and the rotational speed. The joints failed during the lap shear tests at three locations: the lap interface, the RS of the top sheet and the AS of the bottom sheet. The fracture locations are mainly determined by the hook defects. - Highlights: • Hook defect size mainly varies with the pin length of stirring tool. • The proportion of LAGBs and substructured grains increases from NZ to TMAZ. • Weld zones, especially the NZ, have the much lower texture intensity than the BM. • Lap shear failure load and fracture location of joints is relative to the hook defects.« less

Distribution of finger nodes and their association with underlying radiographic features of osteoarthritis.

PubMed

Rees, Frances; Doherty, Sally; Hui, Michelle; Maciewicz, Rose; Muir, Kenneth; Zhang, Weiya; Doherty, Michael

2012-04-01

To determine the distribution of clinically palpable hand interphalangeal (IP) nodes at each finger and thumb joint in a population with nodes, the influence of left or right hand dominance and sex on the development of nodes, and the association between nodes and underlying radiographic features of osteoarthritis (OA). We performed a cross-sectional analysis of participants in the Genetics of Osteoarthritis and Lifestyle (GOAL) study who had ≥1 Heberden's nodes or Bouchard's nodes on clinical examination. Frequencies (%) of nodes were described for each IP joint in the hand. Associations between nodes and underlying radiographic OA were shown with odds ratios (ORs) and 95% confidence intervals. A logistic regression model was used to adjust for the following confounding factors: age, sex, body mass index, left or right hand dominance, hand trauma, occupation with heavy manual activity, and participation in sports. Of the 3,170 GOAL participants, 1,939 had ≥1 nodes (mean age 68 years, 54% women). The distal IP joints of the index finger were the most frequently affected, followed by the thumb IP joint. Nodes were more common in dominant hands and women. There was a significant association between nodes and underlying radiographic OA (OR range 2.26-21.23). This association was stronger for joint space narrowing than for osteophytes. A dose-response relationship was found between clinical severity of Heberden's nodes and underlying radiographic change. Our study supports the positive association between nodes and radiographic OA, especially narrowing, and the influence of sex and left or right hand dominance on development of nodes. In this age group, presence of nodes may be taken as an indication of underlying small joint OA. Copyright © 2012 by the American College of Rheumatology.

Measurement of Posterior Tibial Slope Using Magnetic Resonance Imaging.

PubMed

Karimi, Elham; Norouzian, Mohsen; Birjandinejad, Ali; Zandi, Reza; Makhmalbaf, Hadi

2017-11-01

Posterior tibial slope (PTS) is an important factor in the knee joint biomechanics and one of the bone features, which affects knee joint stability. Posterior tibial slope has impact on flexion gap, knee joint stability and posterior femoral rollback that are related to wide range of knee motion. During high tibial osteotomy and total knee arthroplasty (TKA) surgery, proper retaining the mechanical and anatomical axis is important. The aim of this study was to evaluate the value of posterior tibial slope in medial and lateral compartments of tibial plateau and to assess the relationship among the slope with age, gender and other variables of tibial plateau surface. This descriptive study was conducted on 132 healthy knees (80 males and 52 females) with a mean age of 38.26±11.45 (20-60 years) at Imam Reza hospital in Mashhad, Iran. All patients, selected and enrolled for MRI in this study, were admitted for knee pain with uncertain clinical history. According to initial physical knee examinations the study subjects were reported healthy. The mean posterior tibial slope was 7.78± 2.48 degrees in the medial compartment and 6.85± 2.24 degrees in lateral compartment. No significant correlation was found between age and gender with posterior tibial slope ( P ≥0.05), but there was significant relationship among PTS with mediolateral width, plateau area and medial plateau. Comparison of different studies revealed that the PTS value in our study is different from other communities, which can be associated with genetic and racial factors. The results of our study are useful to PTS reconstruction in surgeries.

Central sensitization and neuropathic features of ongoing pain in a rat model of advanced osteoarthritis

PubMed Central

Havelin, Joshua; Imbert, Ian; Cormier, Jennifer; Allen, Joshua; Porreca, Frank; King, Tamara

2015-01-01

Osteoarthritis (OA) pain is most commonly characterized by movement-triggered joint pain. However, in advanced disease, OA pain becomes persistent, ongoing and resistant to treatment with NSAIDs. The mechanisms underlying ongoing pain in advanced OA are poorly understood. We recently showed that intra-articular (i.a.) injection of monosodium iodoacetate (MIA) into the rat knee joint produces concentration-dependent outcomes. Thus, a low dose of i.a. MIA produces NSAID-sensitive weight asymmetry without evidence of ongoing pain while a high i.a. MIA dose produces weight asymmetry and NSAID-resistant ongoing pain. In the present studies, palpation of the ipsilateral hindlimb of rats treated 14 days previously with high, but not low, doses of i.a. MIA produced FOS expression in the spinal dorsal horn. Inactivation of descending pain facilitatory pathways by microinjection of lidocaine within the rostral ventromedial medulla (RVM) induced conditioned place preference (CPP) selectively in rats treated with the high dose of MIA. CPP to intra-articular lidocaine was blocked by pretreatment with duloxetine (30 mg/kg, i.p. at −30 min). These observations are consistent with the likelihood of a neuropathic component of OA that elicits ongoing, NSAID resistant pain and central sensitization that is mediated, in part, by descending modulatory mechanisms. This model provides a basis for exploration of underlying mechanisms promoting neuropathic components of OA pain and for the identification of mechanisms that may guide drug discovery for treatment of advanced OA pain without the need for joint replacement. PMID:26694132

Defense Acquisitions: Assessments of Selected Weapon Programs

DTIC Science & Technology

2016-03-01

Increment 3 81 Indirect Fire Protection Capability Increment 2-Intercept Block 1 (IFPC Inc 2-I Block 1) 83 Improved Turbine Engine Program (ITEP...ITEP Improved Turbine Engine Program JAGM Joint Air-to-Ground Missile JLTV Joint Light Tactical Vehicle JSTARS Recap Joint Surveillance Target...Attack Radar System Recap 09/2017 —-   Improved Turbine Engine Program 06/2018 O O O Amphibious Ship Replacement 09/2018 O O Advanced Pilot

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

[Application of temporomandibular joint dics reduction in the operation of condylar sagittal fracture].

PubMed

Wenli, Zeng; Wuchao, Zhou; Jingkun, Zhang; Yisen, Shao; Weihong, Xi

2017-10-01

To explore the selection of temporomandibular joint (TMJ) disc reduction and fixation methods in condylar sagittal fracture surgery. A total of 36 patients with condylar fractures were chosen. The follow-up period was more 6 months. All 36 cases of condylar sagittal fracture were fixed with long screw. In the operation, the displaced joint disc was repositioned and fixed. The fixed method included direct suture (22 cases) and anchorage (14 cases). Clinical followups were performed before surgery and 1 month, 3 months, 6 months and 1 year after surgery. Clinicians recorded data related to the Fricton craniomandibular index (CMI) and evaluated the postoperative joint function during followup before surgery and 6 months after surgery. In both groups, function of TMJ significantly improved after surgery. The CMI decreased from 0.213±0.162 and 0.273±0.154 to 0.059±0.072 and 0.064±0.068 (P<0.05), respectively. No statistical difference was observed between the two groups in palpation index (PI), dysfunction index (DI) and CMI (P>0.05) before or after surgery. Both methods could effectively improve the dysfunction of the TMJ caused by trauma. The selection of joint disc reduction and fixation methods is based on the displacement and damage degree of the joint disc.

In vivo effects of CB2 receptor-selective cannabinoids on the vasculature of normal and arthritic rat knee joints

PubMed Central

McDougall, J J; Yu, V; Thomson, J

2007-01-01

Background and purpose: Cannabinoids (CBs) are known to be vasoactive and to regulate tissue inflammation. The present study examined the in vivo vasomotor effects of the CB2 receptor agonists JWH015 and JWH133 in rat knee joints. The effect of acute and chronic joint inflammation on CB2 receptor-mediated responses was also tested. Experimental approach: Blood flow was assessed in rat knee joints by laser Doppler imaging both before and following topical administration of CB2 receptor agonists. Vasoactivity was measured in normal, acute kaolin/carrageenan inflamed and Freund's complete adjuvant chronically inflamed knees. Key results: In normal animals, JWH015 and JWH133 caused a concentration-dependent increase in synovial blood flow which in the case of JWH133 was blocked by the selective CB2 receptor antagonist AM630 as well as the transient receptor potential vanilloid-1 (TRPV1) antagonist SB366791. The vasodilator effect of JWH133 was significantly attenuated in both acute and chronically inflamed knees. Given alone, AM630 had no effect on joint blood flow. Conclusion and implications: In normal joints, the cannabinomimetic JWH133 causes hyperaemia via a CB2 and TRPV1 receptor mechanism. During acute and chronic inflammation, however, this vasodilatatory response is significantly attenuated. PMID:17982474

Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm.

PubMed

Martinez, Emmanuel; Alvarez, Mario Moises; Trevino, Victor

2010-08-01

Biomarker discovery is a typical application from functional genomics. Due to the large number of genes studied simultaneously in microarray data, feature selection is a key step. Swarm intelligence has emerged as a solution for the feature selection problem. However, swarm intelligence settings for feature selection fail to select small features subsets. We have proposed a swarm intelligence feature selection algorithm based on the initialization and update of only a subset of particles in the swarm. In this study, we tested our algorithm in 11 microarray datasets for brain, leukemia, lung, prostate, and others. We show that the proposed swarm intelligence algorithm successfully increase the classification accuracy and decrease the number of selected features compared to other swarm intelligence methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Selective predation and rapid evolution can jointly dampen effects of virulent parasites on Daphnia populations.

PubMed

Duffy, Meghan A; Hall, Spencer R

2008-04-01

Parasites are ubiquitous and often highly virulent, yet clear examples of parasite-driven changes in host density in natural populations are surprisingly scarce. Here, we illustrate an example of this phenomenon and offer a theoretically reasonable resolution. We document the effects of two parasites, the bacterium Spirobacillus cienkowskii and the yeast Metschnikowia bicuspidata, on a common freshwater invertebrate, Daphnia dentifera. We show that while both parasites were quite virulent to individual hosts, only bacterial epidemics were associated with significant changes in host population dynamics and density. Our theoretical results may help explain why yeast epidemics did not significantly affect population dynamics. Using a model parameterized with data we collected, we argue that two prominent features of this system, rapid evolution of host resistance to the parasite and selective predation on infected hosts, both decrease peak infection prevalence and can minimize decline in host density during epidemics. Taken together, our results show that understanding the outcomes of host-parasite interactions in this Daphnia-microparasite system may require consideration of ecological context and evolutionary processes and their interaction.

Experimental Methods in Reduced-gravity Soldering Research

NASA Technical Reports Server (NTRS)

Pettegrew, Richard D.; Struk, Peter M.; Watson, John K.; Haylett, Daniel R.

2002-01-01

The National Center for Microgravity Research, NASA Glenn Research Center, and NASA Johnson Space Center are conducting an experimental program to explore the influence of reduced gravity environments on the soldering process. An improved understanding of the effects of the acceleration environment is important to application of soldering during current and future human space missions. Solder joint characteristics that are being considered include solder fillet geometry, porosity, and microstructural features. Both through-hole and surface mounted devices are being investigated. This paper focuses on the experimental methodology employed in this project and the results of macroscopic sample examination. The specific soldering process, sample configurations, materials, and equipment were selected to be consistent with those currently on-orbit. Other apparatus was incorporated to meet requirements imposed by operation onboard NASA's KC-135 research aircraft and instrumentation was provided to monitor both the atmospheric and acceleration environments. The contingent of test operators was selected to include both highly skilled technicians and less skilled individuals to provide a population cross-section that would be representative of the skill mix that might be encountered in space mission crews.

The physics of bat biosonar

NASA Astrophysics Data System (ADS)

Müller, Rolf

2011-10-01

Bats have evolved one of the most capable and at the same time parsimonious sensory systems found in nature. Using active and passive biosonar as a major - and often sufficient - far sense, different bat species are able to master a wide variety of sensory tasks under very dissimilar sets of constraints. Given the limited computational resources of the bat's brain, this performance is unlikely to be explained as the result of brute-force, black-box-style computations. Instead, the animals must rely heavily on in-built physics knowledge in order to ensure that all required information is encoded reliably into the acoustic signals received at the ear drum. To this end, bats can manipulate the emitted and received signals in the physical domain: By diffracting the outgoing and incoming ultrasonic waves with intricate baffle shapes (i.e., noseleaves and outer ears), the animals can generate selectivity filters that are joint functions of space and frequency. To achieve this, bats employ structural features such as resonance cavities and diffracting ridges. In addition, some bat species can dynamically adjust the shape of their selectivity filters through muscular actuation.

Task-induced frequency modulation features for brain-computer interfacing.

PubMed

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects' intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects' intents with an accuracy comparable to task-induced amplitude modulation. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Enhanced treatment selection for reflective joint cracking in composite pavements : final report.

DOT National Transportation Integrated Search

2015-09-01

This research developed a decisionmaking process that can be used by INDOT to enhance identification of the condition of the : underlying concrete joints or cracks by looking at the surface distresses of the asphalt overlay in composite pavements....

Dynamics of the OH stretching mode in crystalline Ba(ClO4)2.3H2O

NASA Astrophysics Data System (ADS)

Hutzler, Daniel; Brunner, Christian; Petkov, Petko St.; Heine, Thomas; Fischer, Sighart F.; Riedle, Eberhard; Kienberger, Reinhard; Iglev, Hristo

2018-02-01

The vibrational dynamics of the OH stretching mode in Ba(ClO4)2 trihydrate are investigated by means of femtosecond infrared spectroscopy. The sample offers plane cyclic water trimers in the solid phase that feature virtually no hydrogen bond interaction between the water molecules. Selective excitation of the symmetric and asymmetric stretching leads to fast population redistribution, while simultaneous excitation yields quantum beats, which are monitored via a combination tone that dominates the overtone spectrum. The combination of steady-state and time-resolved spectroscopy with quantum chemical simulations and general theoretical considerations gives indication of various aspects of symmetry breakage. The system shows a joint population lifetime of 8 ps and a long-lived coherence between symmetric and asymmetric stretching, which decays with a time constant of 0.6 ps.

Multi-task feature selection in microarray data by binary integer programming.

PubMed

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

Minimally invasive arthrodesis for chronic sacroiliac joint dysfunction using the SImmetry SI Joint Fusion system

PubMed Central

Miller, Larry E; Block, Jon E

2014-01-01

Chronic sacroiliac (SI) joint-related low back pain (LBP) is a common, yet under-diagnosed and undertreated condition due to difficulties in accurate diagnosis and highly variable treatment practices. In patients with debilitating SI-related LBP for at least 6 months duration who have failed conservative management, arthrodesis is a viable option. The SImmetry® SI Joint Fusion System is a novel therapy for SI joint fusion, not just fixation, which utilizes a minimally invasive surgical approach, instrumented fixation for immediate stability, and joint preparation with bone grafting for a secure construct in the long term. The purpose of this report is to describe the minimally invasive SI Joint Fusion System, including patient selection criteria, implant characteristics, surgical technique, postoperative recovery, and biomechanical testing results. Advantages and limitations of this system will be discussed. PMID:24851059

Minimally invasive arthrodesis for chronic sacroiliac joint dysfunction using the SImmetry SI Joint Fusion system.

PubMed

Miller, Larry E; Block, Jon E

2014-01-01

Chronic sacroiliac (SI) joint-related low back pain (LBP) is a common, yet under-diagnosed and undertreated condition due to difficulties in accurate diagnosis and highly variable treatment practices. In patients with debilitating SI-related LBP for at least 6 months duration who have failed conservative management, arthrodesis is a viable option. The SImmetry(®) SI Joint Fusion System is a novel therapy for SI joint fusion, not just fixation, which utilizes a minimally invasive surgical approach, instrumented fixation for immediate stability, and joint preparation with bone grafting for a secure construct in the long term. The purpose of this report is to describe the minimally invasive SI Joint Fusion System, including patient selection criteria, implant characteristics, surgical technique, postoperative recovery, and biomechanical testing results. Advantages and limitations of this system will be discussed.

Development and characteristics of pannus-like soft tissue in osteoarthritic articular surface in rat osteoarthritis model.

PubMed

Duc, P A; Yudoh, K; Masuko, K; Kato, T; Nishioka, K; Nakamura, H

2008-01-01

Pannus is invasive granulation tissue found on the articular cartilage having rheumatoid arthritis (RA). However, pannus-like tissue has also been found in osteoarthritis (OA). Our previous study showed that pannus-like tissue in OA (OA pannus) was frequently found in human OA samples. The purpose of the study is to investigate the development and the characteristics of OA pannus in a rat OA model. Ligaments of the knee joint were transected in Wister rats to induce OA. The knee joints were removed at weeks 1, 2, 4 and 6, and subjected to histological study. Samples were stained with hematoxylin and eosin (HE), Safranin-O and immuno-stained for vimentin, CD34, type II collagen and MMP-3. The whole knee joint of OA rats was implanted in SCID mice and kept for a further 3 weeks. Then the histological findings were evaluated in HE sections. OA pannus appeared at week 2 and extend over the articular surface. OA pannus cells were positive for vimentin and/or CD34. At week 6, a part of articular surface was restored with matrix. OA pannus cells expressed MMP-3 as well as type II collagen. Histological study of rat OA knees implanted in SCID mice showed that OA pannus cells filled the joint space and invaded articular cartilage. The presence of OA pannus was found in a rat OA model and its features were similar to those in human OA. OA pannus had both catabolic and reparative features, and the latter feature were speculated to be dominant in the later phase of the disease under a certain environmental condition.

Joint Dictionary Learning for Multispectral Change Detection.

PubMed

Lu, Xiaoqiang; Yuan, Yuan; Zheng, Xiangtao

2017-04-01

Change detection is one of the most important applications of remote sensing technology. It is a challenging task due to the obvious variations in the radiometric value of spectral signature and the limited capability of utilizing spectral information. In this paper, an improved sparse coding method for change detection is proposed. The intuition of the proposed method is that unchanged pixels in different images can be well reconstructed by the joint dictionary, which corresponds to knowledge of unchanged pixels, while changed pixels cannot. First, a query image pair is projected onto the joint dictionary to constitute the knowledge of unchanged pixels. Then reconstruction error is obtained to discriminate between the changed and unchanged pixels in the different images. To select the proper thresholds for determining changed regions, an automatic threshold selection strategy is presented by minimizing the reconstruction errors of the changed pixels. Adequate experiments on multispectral data have been tested, and the experimental results compared with the state-of-the-art methods prove the superiority of the proposed method. Contributions of the proposed method can be summarized as follows: 1) joint dictionary learning is proposed to explore the intrinsic information of different images for change detection. In this case, change detection can be transformed as a sparse representation problem. To the authors' knowledge, few publications utilize joint learning dictionary in change detection; 2) an automatic threshold selection strategy is presented, which minimizes the reconstruction errors of the changed pixels without the prior assumption of the spectral signature. As a result, the threshold value provided by the proposed method can adapt to different data due to the characteristic of joint dictionary learning; and 3) the proposed method makes no prior assumption of the modeling and the handling of the spectral signature, which can be adapted to different data.

Attentional Selection of Feature Conjunctions Is Accomplished by Parallel and Independent Selection of Single Features.

PubMed

Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

2015-07-08

Experiments that study feature-based attention have often examined situations in which selection is based on a single feature (e.g., the color red). However, in more complex situations relevant stimuli may not be set apart from other stimuli by a single defining property but by a specific combination of features. Here, we examined sustained attentional selection of stimuli defined by conjunctions of color and orientation. Human observers attended to one out of four concurrently presented superimposed fields of randomly moving horizontal or vertical bars of red or blue color to detect brief intervals of coherent motion. Selective stimulus processing in early visual cortex was assessed by recordings of steady-state visual evoked potentials (SSVEPs) elicited by each of the flickering fields of stimuli. We directly contrasted attentional selection of single features and feature conjunctions and found that SSVEP amplitudes on conditions in which selection was based on a single feature only (color or orientation) exactly predicted the magnitude of attentional enhancement of SSVEPs when attending to a conjunction of both features. Furthermore, enhanced SSVEP amplitudes elicited by attended stimuli were accompanied by equivalent reductions of SSVEP amplitudes elicited by unattended stimuli in all cases. We conclude that attentional selection of a feature-conjunction stimulus is accomplished by the parallel and independent facilitation of its constituent feature dimensions in early visual cortex. The ability to perceive the world is limited by the brain's processing capacity. Attention affords adaptive behavior by selectively prioritizing processing of relevant stimuli based on their features (location, color, orientation, etc.). We found that attentional mechanisms for selection of different features belonging to the same object operate independently and in parallel: concurrent attentional selection of two stimulus features is simply the sum of attending to each of those features separately. This result is key to understanding attentional selection in complex (natural) scenes, where relevant stimuli are likely to be defined by a combination of stimulus features. Copyright © 2015 the authors 0270-6474/15/359912-08$15.00/0.

Osteochondral lesions in distal tarsal joints of Icelandic horses reveal strong associations between hyaline and calcified cartilage abnormalities.

PubMed

Ley, C J; Ekman, S; Hansson, K; Björnsdóttir, S; Boyde, A

2014-03-25

Osteochondral lesions in the joints of the distal tarsal region of young Icelandic horses provide a natural model for the early stages of osteoarthritis (OA) in low-motion joints. We describe and characterise mineralised and non-mineralised osteochondral lesions in left distal tarsal region joint specimens from twenty-two 30 ±1 month-old Icelandic horses. Combinations of confocal scanning light microscopy, backscattered electron scanning electron microscopy (including, importantly, iodine staining) and three-dimensional microcomputed tomography were used on specimens obtained with guidance from clinical imaging. Lesion-types were described and classified into groups according to morphological features. Their locations in the hyaline articular cartilage (HAC), articular calcified cartilage (ACC), subchondral bone (SCB) and the joint margin tissues were identified and their frequency in the joints recorded. Associations and correlations between lesion-types were investigated for centrodistal joints only. In centrodistal joints the lesion-types HAC chondrocyte loss, HAC fibrillation, HAC central chondrocyte clusters, ACC arrest and ACC advance had significant associations and strong correlations. These lesion-types had moderate to high frequency in centrodistal joints but low frequencies in tarsometatarsal and talocalcaneal-centroquartal joints. Joint margin lesion-types had no significant associations with other lesion-types in the centrodistal joints but high frequency in both the centrodistal and tarsometatarsal joints. The frequency of SCB lesion-types in all joints was low. Hypermineralised infill phase lesion-types were detected. Our results emphasise close associations between HAC and ACC lesions in equine centrodistal joints and the importance of ACC lesions in the development of OA in low-motion compression-loaded equine joints.

Musculoskeletal disease burden of hereditary hemochromatosis.

PubMed

Sahinbegovic, Enijad; Dallos, Tomáš; Aigner, Elmar; Axmann, Roland; Manger, Bernhard; Englbrecht, Matthias; Schöniger-Hekele, Maximilian; Karonitsch, Thomas; Stamm, Tanja; Farkas, Martin; Karger, Thomas; Stölzel, Ulrich; Keysser, Gernot; Datz, Christian; Schett, Georg; Zwerina, Jochen

2010-12-01

To determine the prevalence, clinical picture, and disease burden of arthritis in patients with hereditary hemochromatosis. In this cross-sectional observational study of 199 patients with hemochromatosis and iron overload, demographic and disease-specific variables, genotype, and organ involvement were recorded. The prevalence, intensity, and localization of joint pain were assessed, and a complete rheumatologic investigation was performed. Radiographs of the hands, knees, and ankles were scored for joint space narrowing, erosions, osteophytes, and chondrocalcinosis. In addition, the number and type of joint replacement surgeries were recorded. Joint pain was reported by 72.4% of the patients. Their mean ± SD age at the time of the initial joint symptoms was 45.8 ± 13.2 years. If joint pain was present, it preceded the diagnosis of hemochromatosis by a mean ± SD of 9.0 ± 10.7 years. Bony enlargement was observed in 65.8% of the patients, whereas synovitis was less common (13.6%). Joint space narrowing and osteophytes as well as chondrocalcinosis of the wrist and knee joints were frequent radiographic features of hemochromatosis. Joint replacement surgery was common, with 32 patients (16.1%) undergoing total joint replacement surgery due to severe OA. The mean ± SD age of these patients was 58.3 ± 10.4 years at time of joint replacement surgery. Female sex, metacarpophalangeal joint involvement, and the presence of chondrocalcinosis were associated with a higher risk of early joint failure (i.e., the need for joint replacement surgery). Arthritis is a frequent, early, and severe symptom of hemochromatosis. Disease is not confined to involvement of the metacarpophalangeal joints and often leads to severe damage requiring the replacement of joints. Copyright © 2010 by the American College of Rheumatology.

An unusual variety of simultaneous fracture dislocation pattern: medial swivel dislocation of talonavicular joint with displaced fractures of the fourth and fifth metatarsals.

PubMed

Inal, Sermet; Inal, Canan

2013-01-01

In published studies, a very rare, special type of Chopart dislocation termed a swivel dislocation has been reported. This injury is characterized by dislocation of the talonavicular joint, but the calcaneocuboid joint remains intact. The foot creates a typical rotational movement without inversion or eversion. The axis of rotation is the interosseous talocalcaneal ligament, which remains intact. We report the case of an 18-year-old male who had experienced a medial swivel dislocation of the talonavicular joint associated with displaced fractures of the fourth and fifth metatarsals. The occurrence, features, and method of treatment of this rare injury are presented. Copyright © 2013 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Collective feature selection to identify crucial epistatic variants.

PubMed

Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

2018-01-01

Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger's MyCode Community Health Initiative (on behalf of DiscovEHR collaboration). In this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying any single method for feature selection via simulation studies. We were able to demonstrate the effectiveness of collective feature selection along with a comparison of many methods in our simulation analysis. We also applied our method to identify non-linear networks associated with obesity.

AVC: Selecting discriminative features on basis of AUC by maximizing variable complementarity.

PubMed

Sun, Lei; Wang, Jun; Wei, Jinmao

2017-03-14

The Receiver Operator Characteristic (ROC) curve is well-known in evaluating classification performance in biomedical field. Owing to its superiority in dealing with imbalanced and cost-sensitive data, the ROC curve has been exploited as a popular metric to evaluate and find out disease-related genes (features). The existing ROC-based feature selection approaches are simple and effective in evaluating individual features. However, these approaches may fail to find real target feature subset due to their lack of effective means to reduce the redundancy between features, which is essential in machine learning. In this paper, we propose to assess feature complementarity by a trick of measuring the distances between the misclassified instances and their nearest misses on the dimensions of pairwise features. If a misclassified instance and its nearest miss on one feature dimension are far apart on another feature dimension, the two features are regarded as complementary to each other. Subsequently, we propose a novel filter feature selection approach on the basis of the ROC analysis. The new approach employs an efficient heuristic search strategy to select optimal features with highest complementarities. The experimental results on a broad range of microarray data sets validate that the classifiers built on the feature subset selected by our approach can get the minimal balanced error rate with a small amount of significant features. Compared with other ROC-based feature selection approaches, our new approach can select fewer features and effectively improve the classification performance.

A Feature and Algorithm Selection Method for Improving the Prediction of Protein Structural Class.

PubMed

Ni, Qianwu; Chen, Lei

2017-01-01

Correct prediction of protein structural class is beneficial to investigation on protein functions, regulations and interactions. In recent years, several computational methods have been proposed in this regard. However, based on various features, it is still a great challenge to select proper classification algorithm and extract essential features to participate in classification. In this study, a feature and algorithm selection method was presented for improving the accuracy of protein structural class prediction. The amino acid compositions and physiochemical features were adopted to represent features and thirty-eight machine learning algorithms collected in Weka were employed. All features were first analyzed by a feature selection method, minimum redundancy maximum relevance (mRMR), producing a feature list. Then, several feature sets were constructed by adding features in the list one by one. For each feature set, thirtyeight algorithms were executed on a dataset, in which proteins were represented by features in the set. The predicted classes yielded by these algorithms and true class of each protein were collected to construct a dataset, which were analyzed by mRMR method, yielding an algorithm list. From the algorithm list, the algorithm was taken one by one to build an ensemble prediction model. Finally, we selected the ensemble prediction model with the best performance as the optimal ensemble prediction model. Experimental results indicate that the constructed model is much superior to models using single algorithm and other models that only adopt feature selection procedure or algorithm selection procedure. The feature selection procedure or algorithm selection procedure are really helpful for building an ensemble prediction model that can yield a better performance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Commercial Crew Development Environmental Control and Life Support System Status: 2011-2012

NASA Technical Reports Server (NTRS)

Williams, David E.

2011-01-01

The National Aeronautics and Space Administration (NASA) Commercial Crew Development (CCDev) - 2 Program is managed within the new Commercial Crew Program Office (CCPO) to help develop a commercial crew transportation system to low earth orbit (LEO). It is intended to foster entrepreneurial activities with a few selected companies. The entrepreneurial activities were encouraged with these few selected companies by NASA providing only part of the total funding to complete specific tasks that were jointly agreed to by NASA and the company. These joint agreements were documented in a Space Act Agreement (SAA) that was signed jointly by NASA and the selected company. This paper will provide an overview of the CCDev - 2 Program and also it will discuss in a high level the Active Thermal Control System (ATCS) / Environmental Control and Life Support (ECLS) System tasks that were performed under CCDev - 2 from the start of CCDev - 2 to March 2012. It will also discuss the extension of the CCDev - 2 Program being proposed for the near future. 1

Non-negative matrix factorization in texture feature for classification of dementia with MRI data

NASA Astrophysics Data System (ADS)

Sarwinda, D.; Bustamam, A.; Ardaneswari, G.

2017-07-01

This paper investigates applications of non-negative matrix factorization as feature selection method to select the features from gray level co-occurrence matrix. The proposed approach is used to classify dementia using MRI data. In this study, texture analysis using gray level co-occurrence matrix is done to feature extraction. In the feature extraction process of MRI data, we found seven features from gray level co-occurrence matrix. Non-negative matrix factorization selected three features that influence of all features produced by feature extractions. A Naïve Bayes classifier is adapted to classify dementia, i.e. Alzheimer's disease, Mild Cognitive Impairment (MCI) and normal control. The experimental results show that non-negative factorization as feature selection method able to achieve an accuracy of 96.4% for classification of Alzheimer's and normal control. The proposed method also compared with other features selection methods i.e. Principal Component Analysis (PCA).

Deep learning decision fusion for the classification of urban remote sensing data

NASA Astrophysics Data System (ADS)

Abdi, Ghasem; Samadzadegan, Farhad; Reinartz, Peter

2018-01-01

Multisensor data fusion is one of the most common and popular remote sensing data classification topics by considering a robust and complete description about the objects of interest. Furthermore, deep feature extraction has recently attracted significant interest and has become a hot research topic in the geoscience and remote sensing research community. A deep learning decision fusion approach is presented to perform multisensor urban remote sensing data classification. After deep features are extracted by utilizing joint spectral-spatial information, a soft-decision made classifier is applied to train high-level feature representations and to fine-tune the deep learning framework. Next, a decision-level fusion classifies objects of interest by the joint use of sensors. Finally, a context-aware object-based postprocessing is used to enhance the classification results. A series of comparative experiments are conducted on the widely used dataset of 2014 IEEE GRSS data fusion contest. The obtained results illustrate the considerable advantages of the proposed deep learning decision fusion over the traditional classifiers.

Discovery of columnar jointing on Mars

USGS Publications Warehouse

Milazzo, M.P.; Keszthelyi, L.P.; Jaeger, W.L.; Rosiek, M.; Mattson, S.; Verba, C.; Beyer, R.A.; Geissler, P.E.; McEwen, A.S.

2009-01-01

We report on the discovery of columnar jointing in Marte Valles, Mars. These columnar lavas were discovered in the wall of a pristine, 16-km-diameter impact crater and exhibit the features of terrestrial columnar basalts. There are discontinuous outcrops along the entire crater wall, suggesting that the columnar rocks covered a surface area of at least 200 km2, assuming that the rocks obliterated by the impact event were similarly jointed. We also see columns in the walls of other fresh craters in the nearby volcanic plains of Elysium Planitia-Amazonis Planitia, which include Marte Vallis, and in a well-preserved crater in northeast Hellas. ?? 2009 The Geological Society of America.

The discovery of columnar jointing on Mars

USGS Publications Warehouse

Milazzo, M.P.; Keszthelyi, L.P.; Jaeger, W.L.; Rosiek, M.; Mattson, S.; Verba, C.; Beyer, R.A.; Geissler, P.E.; McEwen, A.S.; ,

2009-01-01

We report on the discovery of columnar jointing in Marte Valles, Mars. These columnar lavas were discovered in the wall of a pristine, 16-km-diameter impact crater and exhibit the features of terrestrial columnar basalts. There are discontinuous outcrops along the entire crater wall, suggesting that the columnar rocks covered a surface area of at least 200 km2, assuming that the rocks obliterated by the impact event were similarly jointed. We also see columns in the walls of other fresh craters in the nearby volcanic plains of Elysium Planitia–Amazonis Planitia, which include Marte Vallis, and in a well-preserved crater in northeast Hellas.

Distributed Joint Source-Channel Coding in Wireless Sensor Networks

PubMed Central

Zhu, Xuqi; Liu, Yu; Zhang, Lin

2009-01-01

Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively. To this end, we also present a practical scheme for compressing multiple correlated sources over the independent channels. The simulation results demonstrate the desired efficiency. PMID:22408560

Collections: Their Development, Management, Preservation, and Sharing. Papers from the Joint Meeting of the Association of Research Libraries and the Standing Conference of National and University Libraries (York, England, September 19-22, 1988).

ERIC Educational Resources Information Center

Daval, Nicola, Ed.

Papers from the joint meeting are assembled in this document. Each of the meeting's five program sessions featured presentations by a Standing Conference of National and Universal Libraries (SCONUL) director and an Association of Research Libraries (ARL) director. The presentations highlight perspectives from both sides of the Atlantic and are…

Comparison of Genetic Algorithm, Particle Swarm Optimization and Biogeography-based Optimization for Feature Selection to Classify Clusters of Microcalcifications

NASA Astrophysics Data System (ADS)

Khehra, Baljit Singh; Pharwaha, Amar Partap Singh

2017-04-01

Ductal carcinoma in situ (DCIS) is one type of breast cancer. Clusters of microcalcifications (MCCs) are symptoms of DCIS that are recognized by mammography. Selection of robust features vector is the process of selecting an optimal subset of features from a large number of available features in a given problem domain after the feature extraction and before any classification scheme. Feature selection reduces the feature space that improves the performance of classifier and decreases the computational burden imposed by using many features on classifier. Selection of an optimal subset of features from a large number of available features in a given problem domain is a difficult search problem. For n features, the total numbers of possible subsets of features are 2n. Thus, selection of an optimal subset of features problem belongs to the category of NP-hard problems. In this paper, an attempt is made to find the optimal subset of MCCs features from all possible subsets of features using genetic algorithm (GA), particle swarm optimization (PSO) and biogeography-based optimization (BBO). For simulation, a total of 380 benign and malignant MCCs samples have been selected from mammogram images of DDSM database. A total of 50 features extracted from benign and malignant MCCs samples are used in this study. In these algorithms, fitness function is correct classification rate of classifier. Support vector machine is used as a classifier. From experimental results, it is also observed that the performance of PSO-based and BBO-based algorithms to select an optimal subset of features for classifying MCCs as benign or malignant is better as compared to GA-based algorithm.

Diagnosis of Tempromandibular Disorders Using Local Binary Patterns.

PubMed

Haghnegahdar, A A; Kolahi, S; Khojastepour, L; Tajeripour, F

2018-03-01

Temporomandibular joint disorder (TMD) might be manifested as structural changes in bone through modification, adaptation or direct destruction. We propose to use Local Binary Pattern (LBP) characteristics and histogram-oriented gradients on the recorded images as a diagnostic tool in TMD assessment. CBCT images of 66 patients (132 joints) with TMD and 66 normal cases (132 joints) were collected and 2 coronal cut prepared from each condyle, although images were limited to head of mandibular condyle. In order to extract features of images, first we use LBP and then histogram of oriented gradients. To reduce dimensionality, the linear algebra Singular Value Decomposition (SVD) is applied to the feature vectors matrix of all images. For evaluation, we used K nearest neighbor (K-NN), Support Vector Machine, Naïve Bayesian and Random Forest classifiers. We used Receiver Operating Characteristic (ROC) to evaluate the hypothesis. K nearest neighbor classifier achieves a very good accuracy (0.9242), moreover, it has desirable sensitivity (0.9470) and specificity (0.9015) results, when other classifiers have lower accuracy, sensitivity and specificity. We proposed a fully automatic approach to detect TMD using image processing techniques based on local binary patterns and feature extraction. K-NN has been the best classifier for our experiments in detecting patients from healthy individuals, by 92.42% accuracy, 94.70% sensitivity and 90.15% specificity. The proposed method can help automatically diagnose TMD at its initial stages.

Joint Tactical Networks (JTN)

DTIC Science & Technology

2013-12-01

Selected Acquisition Report (SAR) RCS: DD-A&T(Q&A)823-284 Joint Tactical Networks (JTN) As of FY 2015 President’s Budget... Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection...to 00-00-2013 4. TITLE AND SUBTITLE Joint Tactical Networks (JTN) 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

Management of Prosthetic Joint Infection.

PubMed

Tande, Aaron J; Gomez-Urena, Eric O; Berbari, Elie F; Osmon, Douglas R

2017-06-01

Although uncommon, prosthetic joint infection is a devastating complication. This challenging condition requires a coordinated management approach to achieve good patient outcomes. This review details the general principles to consider when managing patients with prosthetic joint infection. The different medical/surgical treatment strategies and how to appropriately select a strategy are discussed. The data to support each strategy are presented, along with discussion of antimicrobial strategies in specific situations. Copyright © 2017 Elsevier Inc. All rights reserved.

Feature Selection for Classification of Polar Regions Using a Fuzzy Expert System

NASA Technical Reports Server (NTRS)

Penaloza, Mauel A.; Welch, Ronald M.

1996-01-01

Labeling, feature selection, and the choice of classifier are critical elements for classification of scenes and for image understanding. This study examines several methods for feature selection in polar regions, including the list, of a fuzzy logic-based expert system for further refinement of a set of selected features. Six Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) arctic scenes are classified into nine classes: water, snow / ice, ice cloud, land, thin stratus, stratus over water, cumulus over water, textured snow over water, and snow-covered mountains. Sixty-seven spectral and textural features are computed and analyzed by the feature selection algorithms. The divergence, histogram analysis, and discriminant analysis approaches are intercompared for their effectiveness in feature selection. The fuzzy expert system method is used not only to determine the effectiveness of each approach in classifying polar scenes, but also to further reduce the features into a more optimal set. For each selection method,features are ranked from best to worst, and the best half of the features are selected. Then, rules using these selected features are defined. The results of running the fuzzy expert system with these rules show that the divergence method produces the best set features, not only does it produce the highest classification accuracy, but also it has the lowest computation requirements. A reduction of the set of features produced by the divergence method using the fuzzy expert system results in an overall classification accuracy of over 95 %. However, this increase of accuracy has a high computation cost.

Salvage reconstruction of failed interposition arthroplasty at the base of the thumb.

PubMed

Braun, Richard M; Rechnic, Mark; Shah, Kalpit N

2012-12-01

We present an operative procedure designed to revise a failed arthroplasty at the base of the thumb. This report describes a reliable operation that corrects residual instability and malignment which results in thumbs that are weak and painful despite a previous procedure. The operation has also been used as a primary procedure for arthritis of the trapeziometacarpal joint where instability and subluxation was a major component of the problem requiring joint reconstruction. The unique features of this procedure include a reinforced double-thickness tendon graft, a unique tendon anchor, and a fascia lata allograft spacer. Significant functional improvement is anticipated when joint reconstruction provides increased proximal stability. Pinch and grip measurements improve. Pain scores also diminish after the operation. Hand function and patient satisfaction can be substantially improved with revision arthroplasty when the initial operation has failed to provide a thumb that is mobile, stable, and pain free. The technical features of the procedure address reduction of malignment, restoring of anatomic balance, and secure fixation of the proximal apex of the thumb metacarpal which restores thumb reduction position and digital balance.

Modular multimorphic kinematic arm structure and pitch and yaw joint for same

DOEpatents

Martin, H. Lee; Williams, Daniel M.; Holt, W. Eugene

1989-01-01

A multimorphic kinematic manipulator arm is provided with seven degrees of freedom and modular kinematic redundancy through identical pitch/yaw, shoulder, elbow and wrist joints and a wrist roll device at the wrist joint, which further provides to the manipulator arm an obstacle avoidance capability. The modular pitch/yaw joints are traction drive devices which provide backlash free operation with smooth torque transmission and enhanced rigidity. A dual input drive arrangement is provided for each joint resulting in a reduction of the load required to be assumed by each drive and providing selective pitch and yaw motions by control of the relative rotational directions of the input drive.

Modular multimorphic kinematic arm structure and pitch and yaw joint for same

DOEpatents

Martin, H.L.; Williams, D.M.; Holt, W.E.

1987-04-21

A multimorphic kinematic manipulator arm is provided with seven degrees of freedom and modular kinematic redundancy through identical pitch/yaw, shoulder, elbow and wrist joints and a wrist roll device at the wrist joint, which further provides to the manipulator arm an obstacle avoidance capability. The modular pitch/yaw joints are traction drive devices which provide backlash free operation with smooth torque transmission and enhanced rigidity. A dual input drive arrangement is provided for each joint resulting in a reduction of the load required to be assumed by each drive means and providing selective pitch and yaw motions by control of the relative rotational directions of the input drive means. 12 figs.

Adaptive Postural Control for Joint Immobilization during Multitask Performance

PubMed Central

Hsu, Wei-Li

2014-01-01

Motor abundance is an essential feature of adaptive control. The range of joint combinations enabled by motor abundance provides the body with the necessary freedom to adopt different positions, configurations, and movements that allow for exploratory postural behavior. This study investigated the adaptation of postural control to joint immobilization during multi-task performance. Twelve healthy volunteers (6 males and 6 females; 21–29 yr) without any known neurological deficits, musculoskeletal conditions, or balance disorders participated in this study. The participants executed a targeting task, alone or combined with a ball-balancing task, while standing with free or restricted joint motions. The effects of joint configuration variability on center of mass (COM) stability were examined using uncontrolled manifold (UCM) analysis. The UCM method separates joint variability into two components: the first is consistent with the use of motor abundance, which does not affect COM position (VUCM); the second leads to COM position variability (VORT). The analysis showed that joints were coordinated such that their variability had a minimal effect on COM position. However, the component of joint variability that reflects the use of motor abundance to stabilize COM (VUCM) was significant decreased when the participants performed the combined task with immobilized joints. The component of joint variability that leads to COM variability (VORT) tended to increase with a reduction in joint degrees of freedom. The results suggested that joint immobilization increases the difficulty of stabilizing COM when multiple tasks are performed simultaneously. These findings are important for developing rehabilitation approaches for patients with limited joint movements. PMID:25329477

Unbiased feature selection in learning random forests for high-dimensional data.

PubMed

Nguyen, Thanh-Tung; Huang, Joshua Zhexue; Nguyen, Thuy Thi

2015-01-01

Random forests (RFs) have been widely used as a powerful classification method. However, with the randomization in both bagging samples and feature selection, the trees in the forest tend to select uninformative features for node splitting. This makes RFs have poor accuracy when working with high-dimensional data. Besides that, RFs have bias in the feature selection process where multivalued features are favored. Aiming at debiasing feature selection in RFs, we propose a new RF algorithm, called xRF, to select good features in learning RFs for high-dimensional data. We first remove the uninformative features using p-value assessment, and the subset of unbiased features is then selected based on some statistical measures. This feature subset is then partitioned into two subsets. A feature weighting sampling technique is used to sample features from these two subsets for building trees. This approach enables one to generate more accurate trees, while allowing one to reduce dimensionality and the amount of data needed for learning RFs. An extensive set of experiments has been conducted on 47 high-dimensional real-world datasets including image datasets. The experimental results have shown that RFs with the proposed approach outperformed the existing random forests in increasing the accuracy and the AUC measures.

Selection of optimal welding condition for GTA pulse welding in root-pass of V-groove butt joint

NASA Astrophysics Data System (ADS)

Yun, Seok-Chul; Kim, Jae-Woong

2010-12-01

In the manufacture of high-quality welds or pipeline, a full-penetration weld has to be made along the weld joint. Therefore, root-pass welding is very important, and its conditions have to be selected carefully. In this study, an experimental method for the selection of optimal welding conditions is proposed for gas tungsten arc (GTA) pulse welding in the root pass which is done along the V-grooved butt-weld joint. This method uses response surface analysis in which the width and height of back bead are chosen as quality variables of the weld. The overall desirability function, which is the combined desirability function for the two quality variables, is used as the objective function to obtain the optimal welding conditions. In our experiments, the target values of back bead width and height are 4 mm and zero, respectively, for a V-grooved butt-weld joint of a 7-mm-thick steel plate. The optimal welding conditions could determine the back bead profile (bead width and height) as 4.012 mm and 0.02 mm. From a series of welding tests, it was revealed that a uniform and full-penetration weld bead can be obtained by adopting the optimal welding conditions determined according to the proposed method.

Application of Delphi expert panel in joint venture projects

NASA Astrophysics Data System (ADS)

Adnan, H.; Rosman, M. R.; Rashid, Z. Z. Ahmad; Mohamad Yusuwan, N.; Bakhary, N. A.

2018-02-01

This study was conducted with the aim to identify the application of the Delphi Technique in validating findings obtained from questionnaire surveys and interviews done in- depth on the subject of joint venture projects in Malaysia. The Delphi technique aims to achieve a consensus of opinion amongst expert panellist that were selected on the primary factors in JV projects. To achieve research objectives, a progressive series of questions was designed where a selected panel of expert to confirm and validate the final findings. The rationale, benefits, limitations and recommendations for the use of Delphi were given in this study. From the literature review done, twenty-one factors were identified as critical factors to the making any joint venture project successful. Detail information from contractors were obtained by using the questionnaire survey method and forty-three in-depth interviews were carried out. Trust between partners, mutual understanding, partner selection criteria, agreement of contract, objective compatibility, conflict, and commitment were confirmed by the Delphi panel to be the critical success factors besides another fourteen factors which were found to be the Failure Reduction Criteria. Delphi techniques has proven to successfully assist in recognising the main factors and would be beneficial in supplementing the success of joint venture arrangements application for construction projects in Malaysia.

Constraints on arm selection processes when reaching: degrees of freedom and joint amplitudes interact to influence limb selection.

PubMed

Kim, Wondae; Buchanan, John; Gabbard, Carl

2011-01-01

With an interest in identifying the variables that constrain arm choice when reaching, the authors had 11 right-handed participants perform free-choice and assigned-limb reaches at 9 object positions. The right arm was freely selected 100% of the time when reaching to positions at 30° and 40° into right hemispace. However, the left arm was freely selected to reach to positions at -30° and -40° in left hemispace 85% of the time. A comparison between free- and assigned-limb reaching kinematics revealed that free limb selection when reaching to the farthest positions was constrained by joint amplitude requirements and the time devoted to limb deceleration. Differences between free- and assigned-arm reaches were not evident when reaching to the midline and positions of ±10°, even though the right arm was freely selected most often for these positions. Different factors contribute to limb selection as a function of distance into a specific hemispace.

Demonstration of reconfigurable joint orbital angular momentum mode and space switching

PubMed Central

Liu, Jun; Wang, Jian

2016-01-01

We propose and demonstrate space-selective switch functions employing orbital angular momentum (OAM) modes in the space domain for switching network. One is the switching among different OAM modes having different spatial phase structures, called OAM mode switching. The other is the switching among different space locations, called space switching. The switching operation mechanism relies on linear optics. Reconfigurable 4 × 4 OAM mode switching, space switching, and joint OAM mode and space switching fabric using a single spatial light modulator (SLM) are all demonstrated in the experiment. In addition, the presented OAM-incorporated space-selective switch might be further extended to N × N joint OAM mode and space switching with fast response, scalability, cascading ability and compability to facilitate robust switching applications. PMID:27869133

Demonstration of reconfigurable joint orbital angular momentum mode and space switching

NASA Astrophysics Data System (ADS)

Liu, Jun; Wang, Jian

2016-11-01

We propose and demonstrate space-selective switch functions employing orbital angular momentum (OAM) modes in the space domain for switching network. One is the switching among different OAM modes having different spatial phase structures, called OAM mode switching. The other is the switching among different space locations, called space switching. The switching operation mechanism relies on linear optics. Reconfigurable 4 × 4 OAM mode switching, space switching, and joint OAM mode and space switching fabric using a single spatial light modulator (SLM) are all demonstrated in the experiment. In addition, the presented OAM-incorporated space-selective switch might be further extended to N × N joint OAM mode and space switching with fast response, scalability, cascading ability and compability to facilitate robust switching applications.

Demonstration of reconfigurable joint orbital angular momentum mode and space switching.

PubMed

Liu, Jun; Wang, Jian

2016-11-21

We propose and demonstrate space-selective switch functions employing orbital angular momentum (OAM) modes in the space domain for switching network. One is the switching among different OAM modes having different spatial phase structures, called OAM mode switching. The other is the switching among different space locations, called space switching. The switching operation mechanism relies on linear optics. Reconfigurable 4 × 4 OAM mode switching, space switching, and joint OAM mode and space switching fabric using a single spatial light modulator (SLM) are all demonstrated in the experiment. In addition, the presented OAM-incorporated space-selective switch might be further extended to N × N joint OAM mode and space switching with fast response, scalability, cascading ability and compability to facilitate robust switching applications.

A personalized 3D-printed prosthetic joint replacement for the human temporomandibular joint: From implant design to implantation.

PubMed

Ackland, David C; Robinson, Dale; Redhead, Michael; Lee, Peter Vee Sin; Moskaljuk, Adrian; Dimitroulis, George

2017-05-01

Personalized prosthetic joint replacements have important applications in cases of complex bone and joint conditions where the shape and size of off-the-shelf components may not be adequate. The objective of this study was to design, test and fabricate a personalized 3D-printed prosthesis for a patient requiring total joint replacement surgery of the temporomandibular joint (TMJ). The new 'Melbourne' prosthetic TMJ design featured a condylar component sized specifically to the patient and fixation screw positions that avoid potential intra-operative damage to the mandibular nerve. The Melbourne prosthetic TMJ was developed for a 58-year-old female recipient with end-stage osteoarthritis of the TMJ. The load response of the prosthesis during chewing and a maximum-force bite was quantified using a personalized musculoskeletal model of the patient's masticatory system developed using medical images. The simulations were then repeated after implantation of the Biomet Microfixation prosthetic TMJ, an established stock device. The maximum condylar stresses, screw stress and mandibular stress at the screw-bone interface were lower in the Melbourne prosthetic TMJ (259.6MPa, 312.9MPa and 198.4MPa, respectively) than those in the Biomet Microfixation device (284.0MPa, 416.0MPa and 262.2MPa, respectively) during the maximum-force bite, with similar trends also observed during the chewing bite. After trialing surgical placement and evaluating prosthetic TMJ stability using cadaveric specimens, the prosthesis was fabricated using 3D printing, sterilized, and implanted into the female recipient. Six months post-operatively, the prosthesis recipient had a normal jaw opening distance (40.0 mm), with no complications identified. The new design features and immediate load response of the Melbourne prosthetic TMJ suggests that it may provide improved clinical and biomechanical joint function compared to a commonly used stock device, and reduce risk of intra-operative nerve damage during placement. The framework presented may be useful for designing and testing customized devices for the treatment of debilitating bone and joint conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Train axle bearing fault detection using a feature selection scheme based multi-scale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin

2018-02-01

This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.

Comment Period for Proposed Remedy Selection Plan for Multiple Training Areas located at Joint Base Cape Cod

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (EPA) is seeking public comment on the EPA’s proposal indicating no further action is needed for multiple Training Areas on the Camp Edwards portion of Joint Base Cape Cod (JBCC).

Where Have all the Joint Planners Gone

DTIC Science & Technology

2009-04-01

Warfighting School that has zero say in the selection and outplacement of its graduates. The JAWS director, Colonel (Air Force) William T. “ Bigfoot ...15 January 2009. 99 Ibid. 100 Office interview between the author and Colonel William T. “ Bigfoot ” Eliason, Director, Joint Advanced Warfighting

A fully redundant power hinge for LANDSAT-D appendages

NASA Technical Reports Server (NTRS)

Mamrol, F. E.; Matteo, D. N.

1981-01-01

The configuration and testing of a power driven hinge for deployment of the solar array and antenna boom for the LANDSAT-D spacecraft is discussed. The hinge is fully mechanically and electrically redundant and, thereby, can sustain a single point failure of any one motor (or its power supply), speed reducer, or bearing set without loss of its ability to function. This design utilizes the capability of the stepper motor drive to remove the flexibility of the drive train from the joint stiffness equation when the hinge is loaded against its stop. This feature precludes gapping of the joint under spacecraft maneuver loads even in the absence of a latching feature. Thus, retraction is easily accomplished by motor reversal without the need for a solenoid function to remove the latch.

Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

PubMed

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-07-30

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

Measurement of body joint angles for physical therapy based on mean shift tracking using two low cost Kinect images.

PubMed

Chen, Y C; Lee, H J; Lin, K H

2015-08-01

Range of motion (ROM) is commonly used to assess a patient's joint function in physical therapy. Because motion capture systems are generally very expensive, physical therapists mostly use simple rulers to measure patients' joint angles in clinical diagnosis, which will suffer from low accuracy, low reliability, and subjective. In this study we used color and depth image feature from two sets of low-cost Microsoft Kinect to reconstruct 3D joint positions, and then calculate moveable joint angles to assess the ROM. A Gaussian background model is first used to segment the human body from the depth images. The 3D coordinates of the joints are reconstructed from both color and depth images. To track the location of joints throughout the sequence more precisely, we adopt the mean shift algorithm to find out the center of voxels upon the joints. The two sets of Kinect are placed three meters away from each other and facing to the subject. The joint moveable angles and the motion data are calculated from the position of joints frame by frame. To verify the results of our system, we take the results from a motion capture system called VICON as golden standard. Our 150 test results showed that the deviation of joint moveable angles between those obtained by VICON and our system is about 4 to 8 degree in six different upper limb exercises, which are acceptable in clinical environment.

Anand constitutive model of lead-free solder joints in 3D IC device

NASA Astrophysics Data System (ADS)

Zhang, Liang; Liu, Zhi-quan; Ji, Yu-tong

2016-08-01

Anand constitutive relation of SnAgCu and SnAgCu-nano Al solders were studied under uniaxial tension, and the constitutive model was used in the finite element simulation to analyze the stress-strain response of lead-free solder joints in 3D IC devices. The results showed that the nine parameters of the Anand model can be determined from separated constitutive relations and experimental results. Based on Anand model, the finite element method was selected to calculate the stress-strain response of lead-free solder joints, it was found that in the 3D IC device the maximum stress-strain concentrated in the concern solder joints, the stress-strain of SnAgCu-nano Al solder joints was lower than that of SnAgCu solder joints, which represented that the addition of nano Al particles can enhance the reliability of lead-free solder joints in 3D IC devices.

Genetic Programming and Frequent Itemset Mining to Identify Feature Selection Patterns of iEEG and fMRI Epilepsy Data

PubMed Central

Smart, Otis; Burrell, Lauren

2014-01-01

Pattern classification for intracranial electroencephalogram (iEEG) and functional magnetic resonance imaging (fMRI) signals has furthered epilepsy research toward understanding the origin of epileptic seizures and localizing dysfunctional brain tissue for treatment. Prior research has demonstrated that implicitly selecting features with a genetic programming (GP) algorithm more effectively determined the proper features to discern biomarker and non-biomarker interictal iEEG and fMRI activity than conventional feature selection approaches. However for each the iEEG and fMRI modalities, it is still uncertain whether the stochastic properties of indirect feature selection with a GP yield (a) consistent results within a patient data set and (b) features that are specific or universal across multiple patient data sets. We examined the reproducibility of implicitly selecting features to classify interictal activity using a GP algorithm by performing several selection trials and subsequent frequent itemset mining (FIM) for separate iEEG and fMRI epilepsy patient data. We observed within-subject consistency and across-subject variability with some small similarity for selected features, indicating a clear need for patient-specific features and possible need for patient-specific feature selection or/and classification. For the fMRI, using nearest-neighbor classification and 30 GP generations, we obtained over 60% median sensitivity and over 60% median selectivity. For the iEEG, using nearest-neighbor classification and 30 GP generations, we obtained over 65% median sensitivity and over 65% median selectivity except one patient. PMID:25580059

[The reference of normal values of the sacroiliac joint index in bone scintigraphy].

PubMed

Sebastjanowicz, Przemysław; Iwanowski, Jacek; Piwowarska-Bilska, Hanna; Elbl, Bogumiła; Birkenfeld, Bożena

Scintigraphy of sacroiliac joints as functional imaging provides unique information on the existing disease process. By using radiopharmaceuticals that allow imaging of the metabolic activity within the joint, it is possible to assess the stage of the disease, even when there are no lesions in radiological images. Quantitative analysis of scintigrams of sacroiliac joints is performed by comparing the uptake in both of them in relation to the uptake in the sacral bone area. The values of sacroiliac (SI/S) indices are influenced by the age of the patient, sex, state of health, and a range of individual biological features. Therefore, reference values of SI/S ratios are very important for medical specialists who describe and diagnose locomotor system diseases. The aim of this paper is to develop a reference range of sacroiliac ratios. The innovativeness of this paper involves examining sacroiliac ratios for various age groups, in children and adult patients, taking their sex into consideration. The study comprised a group of 335 people with proper bone scintigraphy. These people were divided into children and patients aged ≥21. Children were divided into 4 age groups (1–5; 6–10; 11–15; 16–20) and adults into 6 age groups (21–30; 31–40; 41–50; 51–60; 61–70; ≥71). Sacroiliac ratios were calculated using the method of three rectangular region of interests located on the left and right sacroiliac joint and on the sacral bone. The sacroiliac ratio was calculated for both joints by dividing the average number of counts within a selected sacroiliac joint by the average number of counts within the sacral bone. SI/S borderline reference values covered the range of 1.18÷2.28 that was obtained for children aged ≤5 and for the group of 11–15-year-olds. Considerable discrepancies in the values of the coefficient for women and men were seen among 31–50-year-olds. Borderline reference results for the entire control group cover the range of 1.18 ±2.28. The lower reference value applies to ≤5-year-olds, whereas the higher value applies to the group of 11–15-year-olds. The standard deviation value obtained was highest in paediatric patients. The results indicate the occurrence of significant individual differences between patients in this age group.

Correlates of low back pain in a general population sample: a multidisciplinary perspective.

PubMed

Roncarati, A; McMullen, W

1988-06-01

This study identifies correlates of low back pain in a general population sample and defines a profile of subjects with low back pain. A multidisciplinary approach was employed that required surveying and physically assessing 674 subjects on 105 variables in biographical, anatomical, strength and flexibility measurement categories. No attempt was made to select subjects from specific occupational, age, athletic, psychological and anatomical groups or subjects with specific biographical features, which may have resulted in a sample that was atypical of the general population. The results of this study based on a causal comparative ex post facto research design corroborated selected findings of previous research conducted on nongeneral population samples. These findings include relationships between low back pain and age, body type, sex, stress, smoking, selected types of physical activity, occupation and previous injuries to the neck, shoulders, back and upper legs, as well as previous episodes of low back pain. Additional correlates of low back pain that were identified and have little or controversial review in the back literature include: delayed low back pain syndrome caused by abrupt changes in running frequency, Q angle, pes cavus, leg length (right and left), trunk length, genu recurvatum and multiplane strength and flexibility limitations in the hip joints.

Finding the multipath propagation of multivariable crude oil prices using a wavelet-based network approach

NASA Astrophysics Data System (ADS)

Jia, Xiaoliang; An, Haizhong; Sun, Xiaoqi; Huang, Xuan; Gao, Xiangyun

2016-04-01

The globalization and regionalization of crude oil trade inevitably give rise to the difference of crude oil prices. The understanding of the pattern of the crude oil prices' mutual propagation is essential for analyzing the development of global oil trade. Previous research has focused mainly on the fuzzy long- or short-term one-to-one propagation of bivariate oil prices, generally ignoring various patterns of periodical multivariate propagation. This study presents a wavelet-based network approach to help uncover the multipath propagation of multivariable crude oil prices in a joint time-frequency period. The weekly oil spot prices of the OPEC member states from June 1999 to March 2011 are adopted as the sample data. First, we used wavelet analysis to find different subseries based on an optimal decomposing scale to describe the periodical feature of the original oil price time series. Second, a complex network model was constructed based on an optimal threshold selection to describe the structural feature of multivariable oil prices. Third, Bayesian network analysis (BNA) was conducted to find the probability causal relationship based on periodical structural features to describe the various patterns of periodical multivariable propagation. Finally, the significance of the leading and intermediary oil prices is discussed. These findings are beneficial for the implementation of periodical target-oriented pricing policies and investment strategies.

Method of generating features optimal to a dataset and classifier

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruillard, Paul J.; Gosink, Luke J.; Jarman, Kenneth D.

A method of generating features optimal to a particular dataset and classifier is disclosed. A dataset of messages is inputted and a classifier is selected. An algebra of features is encoded. Computable features that are capable of describing the dataset from the algebra of features are selected. Irredundant features that are optimal for the classifier and the dataset are selected.

Temporal Correlation Mechanisms and Their Role in Feature Selection: A Single-Unit Study in Primate Somatosensory Cortex

PubMed Central

Gomez-Ramirez, Manuel; Trzcinski, Natalie K.; Mihalas, Stefan; Niebur, Ernst

2014-01-01

Studies in vision show that attention enhances the firing rates of cells when it is directed towards their preferred stimulus feature. However, it is unknown whether other sensory systems employ this mechanism to mediate feature selection within their modalities. Moreover, whether feature-based attention modulates the correlated activity of a population is unclear. Indeed, temporal correlation codes such as spike-synchrony and spike-count correlations (rsc) are believed to play a role in stimulus selection by increasing the signal and reducing the noise in a population, respectively. Here, we investigate (1) whether feature-based attention biases the correlated activity between neurons when attention is directed towards their common preferred feature, (2) the interplay between spike-synchrony and rsc during feature selection, and (3) whether feature attention effects are common across the visual and tactile systems. Single-unit recordings were made in secondary somatosensory cortex of three non-human primates while animals engaged in tactile feature (orientation and frequency) and visual discrimination tasks. We found that both firing rate and spike-synchrony between neurons with similar feature selectivity were enhanced when attention was directed towards their preferred feature. However, attention effects on spike-synchrony were twice as large as those on firing rate, and had a tighter relationship with behavioral performance. Further, we observed increased rsc when attention was directed towards the visual modality (i.e., away from touch). These data suggest that similar feature selection mechanisms are employed in vision and touch, and that temporal correlation codes such as spike-synchrony play a role in mediating feature selection. We posit that feature-based selection operates by implementing multiple mechanisms that reduce the overall noise levels in the neural population and synchronize activity across subpopulations that encode the relevant features of sensory stimuli. PMID:25423284

Mid-Infrared Spectroscopy of Carbon Stars in the Small Magellanic Cloud

DTIC Science & Technology

2006-07-10

nod. Before extracting spectra from fit a variety of spectral feature shapes using MgS considerably the images, we used the imclean software package...mined from neighboring pixels. In addition to the dust features , the IRS wavelength range also To extract spectra from the cleaned and differenced...Example of the extraction of the molecular bands and the SiC dust 24 jIm, and they avoid any potential problems at the joint be- feature from the spectrum

Feature Selection Methods for Zero-Shot Learning of Neural Activity.

PubMed

Caceres, Carlos A; Roos, Matthew J; Rupp, Kyle M; Milsap, Griffin; Crone, Nathan E; Wolmetz, Michael E; Ratto, Christopher R

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

Three-dimensional reconstruction of rat knee joint using episcopic fluorescence image capture.

PubMed

Takaishi, R; Aoyama, T; Zhang, X; Higuchi, S; Yamada, S; Takakuwa, T

2014-10-01

Development of the knee joint was morphologically investigated, and the process of cavitation was analyzed by using episcopic fluorescence image capture (EFIC) to create spatial and temporal three-dimensional (3D) reconstructions. Knee joints of Wister rat embryos between embryonic day (E)14 and E20 were investigated. Samples were sectioned and visualized using an EFIC. Then, two-dimensional image stacks were reconstructed using OsiriX software, and 3D reconstructions were generated using Amira software. Cavitations of the knee joint were constructed from five divided portions. Cavity formation initiated at multiple sites at E17; among them, the femoropatellar cavity (FPC) was the first. Cavitations of the medial side preceded those of the lateral side. Each cavity connected at E20 when cavitations around the anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) were completed. Cavity formation initiated from six portions. In each portion, development proceeded asymmetrically. These results concerning anatomical development of the knee joint using EFIC contribute to a better understanding of the structural feature of the knee joint. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Characterization and treatment monitoring of inflammatory arthritis by photoacoustic imaging: a study on adjuvant-induced arthritis rat model

NASA Astrophysics Data System (ADS)

Wang, Xueding; Rajian, Justin; Shao, Xia; Chamberland, David L.; Girish, Gandikota

2014-03-01

Neovascularity also known as angiogenesis is an early feature of inflammatory arthritis disease. Therefore, identifying the development of neovascularity is one way to potentially detect and characterize arthritis. Laser-based photoacoustic imaging (PAI) is an emerging biomedical imaging modality which may aid in detection of both early and continued development of neovascularity. In this work, we investigated the feasibility of PAI to measure angiogenesis, for the purpose of evaluating and monitoring inflammatory arthritis after treatment. The imaging results on an arthritis rat model demonstrate that 1) there is noticeable enhancement in image intensity in the arthritic ankle joints when compared to the normal joints, and 2) there is noticeable decrease in image intensity in the arthritic ankle joints after treatment when compared to the untreated arthritic joints. In order to validate the findings from PAI, we performed positron emission tomography (PET) and histology on the same joints. The diameters of the ankle joints, as a clinical score of the arthritis, were also measured at each time point.

Joint Precision Approach and Landing System Increment 1A (JPALS Inc 1A)

DTIC Science & Technology

2015-12-01

Selected Acquisition Report (SAR) RCS: DD-A&T(Q&A)823-238 Joint Precision Approach and Landing System Increment 1A (JPALS Inc 1A) As of FY 2017...President’s Budget Defense Acquisition Management Information Retrieval (DAMIR) March 10, 2016 11:30:56 UNCLASSIFIED JPALS Inc 1A December 2015 SAR...Fiscal Year FYDP - Future Years Defense Program ICE - Independent Cost Estimate IOC - Initial Operational Capability Inc - Increment JROC - Joint

Multivariate EMD and full spectrum based condition monitoring for rotating machinery

NASA Astrophysics Data System (ADS)

Zhao, Xiaomin; Patel, Tejas H.; Zuo, Ming J.

2012-02-01

Early assessment of machinery health condition is of paramount importance today. A sensor network with sensors in multiple directions and locations is usually employed for monitoring the condition of rotating machinery. Extraction of health condition information from these sensors for effective fault detection and fault tracking is always challenging. Empirical mode decomposition (EMD) is an advanced signal processing technology that has been widely used for this purpose. Standard EMD has the limitation in that it works only for a single real-valued signal. When dealing with data from multiple sensors and multiple health conditions, standard EMD faces two problems. First, because of the local and self-adaptive nature of standard EMD, the decomposition of signals from different sources may not match in either number or frequency content. Second, it may not be possible to express the joint information between different sensors. The present study proposes a method of extracting fault information by employing multivariate EMD and full spectrum. Multivariate EMD can overcome the limitations of standard EMD when dealing with data from multiple sources. It is used to extract the intrinsic mode functions (IMFs) embedded in raw multivariate signals. A criterion based on mutual information is proposed for selecting a sensitive IMF. A full spectral feature is then extracted from the selected fault-sensitive IMF to capture the joint information between signals measured from two orthogonal directions. The proposed method is first explained using simple simulated data, and then is tested for the condition monitoring of rotating machinery applications. The effectiveness of the proposed method is demonstrated through monitoring damage on the vane trailing edge of an impeller and rotor-stator rub in an experimental rotor rig.

Antitumour action on human glioblastoma A1235 cells through cooperation of bee venom and cisplatin.

PubMed

Gajski, Goran; Čimbora-Zovko, Tamara; Rak, Sanjica; Osmak, Maja; Garaj-Vrhovac, Vera

2016-08-01

Cisplatin (cDDP) is one of the most widely used anticancer-drugs in both therapy and research. However, cDDP-resistance is the greatest obstacle for the successful treatment of cancer patients. In the present study, the possible joint anticancer effect of bee venom (BV), as a natural toxin, and cDDP towards human glioblastoma A1235 cells was evaluated. Treatment with BV alone in concentrations of 2.5-30 μg/ml displayed dose-dependent cytotoxicity towards A1235 cells, as evaluated with different cytotoxicity assays (MTT, Cristal violet and Trypan blue exclusion assay), with an IC50 value of 22.57 μg/ml based on the MTT results. Furthermore, BV treatment induced necrosis, which was confirmed by typical morphological features and fast staining with ethidium-bromide dye. Pre-treatment with BV induced cell sensitization to cDDP, indicating that BV could improve the killing effect of selected cells when combined with cDDP. The isobologram method used to determine the extent of synergism in combining two agents to examine their possible therapeutic effect showed that combined treatment induced an additive and/or synergistic effect towards selected cells depending on the concentration of both. Hence, a greater anticancer effect could be triggered if BV was used in the course of chemotherapy. The obtained results indicate that joint treatment with BV could be useful from the point of minimizing the cDDP concentration during chemotherapy, thus reducing and/or postponing the development of drug resistance. Our data, in accordance with previously reported results, suggests that BV could be used in the development of a new strategy for cancer treatment.

Human joint motion estimation for electromyography (EMG)-based dynamic motion control.

PubMed

Zhang, Qin; Hosoda, Ryo; Venture, Gentiane

2013-01-01

This study aims to investigate a joint motion estimation method from Electromyography (EMG) signals during dynamic movement. In most EMG-based humanoid or prosthetics control systems, EMG features were directly or indirectly used to trigger intended motions. However, both physiological and nonphysiological factors can influence EMG characteristics during dynamic movements, resulting in subject-specific, non-stationary and crosstalk problems. Particularly, when motion velocity and/or joint torque are not constrained, joint motion estimation from EMG signals are more challenging. In this paper, we propose a joint motion estimation method based on muscle activation recorded from a pair of agonist and antagonist muscles of the joint. A linear state-space model with multi input single output is proposed to map the muscle activity to joint motion. An adaptive estimation method is proposed to train the model. The estimation performance is evaluated in performing a single elbow flexion-extension movement in two subjects. All the results in two subjects at two load levels indicate the feasibility and suitability of the proposed method in joint motion estimation. The estimation root-mean-square error is within 8.3% ∼ 10.6%, which is lower than that being reported in several previous studies. Moreover, this method is able to overcome subject-specific problem and compensate non-stationary EMG properties.

CLINICAL AND TREATMENT FEATURES OF OPEN INFECTED FRACTURES IN THE KNEE JOINT REGION IN CONJUNCTION WITH RADIATION SICKNESS (EXPERIMENTAL STUDY)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakharov, B.V.

1963-08-01

Clinical aspects and the course of treatment of open infected fractures in the knee joint region against a background of moderate and severe radiation sickness are discussed. The experiment involved 35 healthy dogs of both sexes. In all, three experiments were involved: on open infected fractures in the knee joint region in conjunction with radiation sickness; open infected fractures in the knee joint region without radiation sickness; radiation sickness without trauma. Infected open injury to the knee joint against a radiation sickness background is a severe affection. The use of delayed surgical and drug treatment (antibiotics, vitamins, antihistamine preparations) affordedmore » survival of at least one-half of the animals. Oral use of phenoxymethyl-penicillin in large doses established in the blood and synovial fluid of the damaged knee joint a therapeutic concentration of antibiotic of long duration (not less than a day). In radiation damage to knee joint accompanied by fracture of the bone fragment, the best method of surgical treatment is osteosynthesis using metal parts. In open infection of a damaged knee joint against a radiation sickness background, even with proper treatment a tendency toward formation of deforming arthrosis was observed. (OTS)« less

Flight set 360T004 (STS-30)

NASA Technical Reports Server (NTRS)

Nelsen, Lowell V.

1990-01-01

The performance of 360T004, Forth Flight, Redesigned Solid Rocket Motors (RSRM) is assessed in respect to joint sealing issues as seen from post-test inspection of the seals and sealing surfaces. The factory joint disassembly inspections for this flight set were omitted. The decision was based on the rational that there is sufficient information in the present data base, and this would give H-7 refurbishment operations faster turn around time for this set of hardware. The factory joint disassembly inspections will resume for 360H005, Fifth Flight, through 360L007, Seventh Flight, due to a new grease application being in effect during the assembly process. The left hand nozzle was forced into the snubbed position upon splash down. This required unique tooling to be manufactured to perform the disassembly of the internal nozzle joints. This was completed on February 5 and 6, 1990 at the H-5 Clearfield, Utah facility. The RSRM consisting of capture feature, field joints with the J-joint insulation configuration is illustrated. The nozzle-to-case joint design, which includes 100, 7/8-inch radial bolts in conjunction with a wiper O-ring and modified insulation design is also illustrated, as is the ignition system seals and a cross section of the igniter. The configuration of all internal nozzle joints is shown.

An all-joint-control master device for single-port laparoscopic surgery robots.

PubMed

Shim, Seongbo; Kang, Taehun; Ji, Daekeun; Choi, Hyunseok; Joung, Sanghyun; Hong, Jaesung

2016-08-01

Robots for single-port laparoscopic surgery (SPLS) typically have all of their joints located inside abdomen during surgery, whereas with the da Vinci system, only the tip part of the robot arm is inserted and manipulated. A typical master device that controls only the tip with six degrees of freedom (DOFs) is not suitable for use with SPLS robots because of safety concerns. We designed an ergonomic six-DOF master device that can control all of the joints of an SPLS robot. We matched each joint of the master, the slave, and the human arm to decouple all-joint motions of the slave robot. Counterbalance masses were used to reduce operator fatigue. Mapping factors were determined based on kinematic analysis and were used to achieve all-joint control with minimal error at the tip of the slave robot. The proposed master device has two noteworthy features: efficient joint matching to the human arm to decouple each joint motion of the slave robot and accurate mapping factors, which can minimize the trajectory error of the tips between the master and the slave. We confirmed that the operator can manipulate the slave robot intuitively with the master device and that both tips have similar trajectories with minimal error.

Incidence of inadvertent intra-articular lumbar facet joint injection during fluoroscopically guided interlaminar epidural steroid injection.

PubMed

Huang, Ambrose J; Palmer, William E

2012-02-01

To determine the incidence of inadvertent lumbar facet joint injection during an interlaminar epidural steroid injection (ESI). A total of 686 interlaminar lumbar ESIs were performed from January 1, 2009 to December 31, 2009. Archived images from these cases were retrospectively reviewed on the PACS. Positive cases of inadvertent lumbar facet joint injection were identified by the characteristic sigmoid-shaped contrast pattern projecting over the posterior elements on the lateral view and/or ovoid contrast projecting over the facet joints on the anteroposterior (AP) view. Eight positive events were identified (1.2%). There was no statistically significant gender or lumbar level predilection. In 3/8 of the positive cases (37.5%), the inadvertent facet joint injection was recognized by the operator. The needle was repositioned as a result, and contrast within the posterior epidural space was documented by the end of the procedure. In 5/8 of the positive cases (62.5%), the patients reported an immediate decrease in the presenting pain. The incidence of inadvertent lumbar facet joint injection during an interlaminar epidural steroid injection is low. Recognizing the imaging features of this event permits the operator to redirect the needle tip into the epidural space and/or identify the facet joint(s) as a source of the patient's presenting pain.

Task-induced frequency modulation features for brain-computer interfacing

NASA Astrophysics Data System (ADS)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Objective. Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects’ intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects’ intents with an accuracy comparable to task-induced amplitude modulation. Approach. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. Main results. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Significance. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

23 CFR 450.330 - Project selection from the TIP.

Code of Federal Regulations, 2010 CFR

2010-04-01

... projects shall be jointly developed by the MPO, the State, and the public transportation operator(s) if requested by the MPO, the State, or the public transportation operator(s). If the State or public... the MPO, the State, and the public transportation operator(s) jointly develop expedited project...

Jointness: A Selected Bibliography

DTIC Science & Technology

2007-08-01

AD-A431-767) http://handle.dtic.mil/100.2/ADA431767 Lamb , William L. Moving beyond Goldwater-Nichols: The Case for Continued Reform of the DoD...in Support of the Joint Force’." Army Aviation 55 (May 2006): 22-24. Magnuson, Stew . "Turf Battles: Strategic Command’s Expanded Portfolio

Interphalangeal joint involvement of the big toe in gout: a rare presentation.

PubMed

Dobson, Michael; Alwahab, Yasir; Fazal, Muhammad A

2012-01-01

Atypical presentation of gout can cause diagnostic dilemmas. We report a case of gout that presented with an expansile lytic lesion involving the interphalangeal joint of the hallux, lack of a history of gout, and an associated solitary lung nodule. Magnetic resonance imaging showed an expansile destructive bony lesion with soft-tissue involvement suggestive of a possible bony metastasis. A needle biopsy was performed, and histopathologic features were diagnostic of chronic tophaceous gout.

Cadre Photos for Joint Test Team Feature

NASA Image and Video Library

2017-02-23

During a tour of SpaceX headquarters in Hawthorne, California, commercial crew astronauts Bob Behnken, left, and Eric Boe participate in joint test team training using mockup components of the Crew Dragon on Feb. 23, 2017. Mike Good, program manager for Crew Operations and Testing at Johnson Space Center in Houston, is in the background. Crew Dragon is being developed and manufactured in partnership with NASA's Commercial Crew Program to return human spaceflight capabilities to the U.S.

Erectable/deployable concepts for large space system technology

NASA Technical Reports Server (NTRS)

Agan, W. E.

1980-01-01

Erectable/deployable space structure concepts particularly relating to the development of a science and applications space platform are presented. Design and operating features for an automatic coupler clevis joint, a side latching detent joint, and a module-to-module auto lock coupler are given. An analysis of the packaging characteristics of stacked subassembly, single fold, hybrid, and double fold concepts is given for various platform structure configurations. Payload carrier systems and assembly techniques are also discussed.

MR imaging of patients with lateral epicondylitis of the elbow: is the common extensor tendon an isolated lesion?

PubMed

Qi, Liang; Zhu, Zheng-Feng; Li, Feng; Wang, Ren-Fa

2013-01-01

To investigate whether an injury of the common extensor tendon (CET) is associated with other abnormalities in the elbow joint and find the potential relationships between these imaging features by using a high-resolution magnetic resonance imaging (MRI). Twenty-three patients were examined with 3.0 T MR. Two reviewers were recruited for MR images evaluation. Image features were recorded in terms of (1) the injury degree of CET; (2) associated injuries in the elbow joint. Spearman's rank correlation analysis was performed to analyze the relationships between the injury degree of CET and associated abnormalities of the elbow joint, correlations were considered significant at p<0.05. Total 24 elbows in 23 patients were included. Various degrees of injuries were found in total 24 CETs (10 mild, 7 moderate and 7 severe). Associated abnormalities were detected in accompaniments of the elbow joints including ligaments, tendons, saccussynovialis and muscles. A significantly positive correlation (r = 0.877,p<0.01) was found in injuries of CET and lateral ulnar collateral ligament (LUCL). Injury of the CET is not an isolated lesion for lateral picondylitis, which is mostly accompanied with other abnormalities, of which the LUCL injury is the most commonly seen in lateral epicondylitis, and there is a positive correlation between the injury degree in CET and LUCL.

Functional assessment of a surgical robot for reduction of lower limb fractures.

PubMed

Hung, Shuo-Suei; Lee, Ming-Yih

2010-12-01

This paper presents a novel robot designed for reduction of lower limb fractures, with the additional features of automatic controlled flexion of the knee joint, individual traction of thigh and leg, and foot rotation. The aim of this design is to assist the orthopaedic surgeon to perform better fracture reduction through motor control, in contrast to current manual control, and the results of assessments of its functions on normal subjects are presented in this paper. The robot was designed to be mounted onto the operation table, and was controlled through open switch relay. Functional assessments were conducted on six healthy volunteers in terms of knee joint motion and lower limb traction; measurement of angle and distance was calculated from data obtained by a 3D ultrasonic motion system (Zebris(®) ). The results showed a good correlation of the flexion angle between the robot and the subjects at the knee joint. In the traction tests, a steady lengthening of the proximal as well as the distal segment of the robot was observed, and a slight increase in subjects' limb length was also recorded, which might be due to distraction in the joint space. This automatic control fracture table has distinct features compared with the conventional ones, and it is believed to be of assistance to surgeons when performing fracture fixations. Copyright © 2010 John Wiley & Sons, Ltd.

Measurements of surface layer of the articular cartilage using microscopic techniques

NASA Astrophysics Data System (ADS)

Ryniewicz, A. M.; Ryniewicz, A.; Ryniewicz, W.; Gaska, A.

2010-07-01

The articular cartilage is the structure that directly cooperates tribologically in biobearing. It belongs to the connective tissues and in the joints it assumes two basic forms: hyaline cartilage that builds joint surfaces and fibrocartilage which may create joint surfaces. From this fibrocartilage are built semilunar cartilage and joint disc are built as well. The research of articular cartilage have been done in macro, micro and nano scale. In all these measurement areas characteristic features occur which can identify biobearing tribology. The aim of the research was the identification of surface layer of articular cartilage by means of scanning electron microscopy (SEM) and atom force microscopy (AFM) and the analysis of topography of these layers. The material used in the research of surface layer was the animal articular cartilage: hyaline cartilage and fibrocartilage.

[Minimally invasive approaches to hip and knee joints for total joint replacement].

PubMed

Rittmeister, M; König, D P; Eysel, P; Kerschbaumer, F

2004-11-01

The manuscript features the different minimally invasive approaches to the hip for joint replacement. These include medial, anterior, anterolateral, and posterior approaches. The concept of minimally invasive hip arthroplasty makes sense if it is an integral part of a larger concept to lower postoperative morbidity. Besides minimal soft tissue trauma, this concept involves preoperative patient education, preemptive analgesia, and postoperative physiotherapy. It is our belief that minimal incision techniques for the hip are not suited for all patients and all surgeons. The different minimally invasive approaches to the knee joint for implantation of a knee arthroplasty are described and discussed. There have been no studies published yet that fulfill EBM criteria. The data so far show that minimally invasive approaches and implantation techniques for total knee replacements lead to quicker rehabilitation of patients.

Effect of Strain Rate on Joint Strength and Failure Mode of Lead-Free Solder Joints

NASA Astrophysics Data System (ADS)

Lin, Jian; Lei, Yongping; Fu, Hanguang; Guo, Fu

2018-03-01

In surface mount technology, the Sn-3.0Ag-0.5Cu solder joint has a shorter impact lifetime than a traditional lead-tin solder joint. In order to improve the impact property of SnAgCu lead-free solder joints and identify the effect of silver content on tensile strength and impact property, impact experiments were conducted at various strain rates on three selected SnAgCu based solder joints. It was found that joint failure mainly occurred in the solder material with large plastic deformation under low strain rate, while joint failure occurred at the brittle intermetallic compound layer without any plastic deformation at a high strain rate. Joint strength increased with the silver content in SnAgCu alloys in static tensile tests, while the impact property of the solder joint decreased with increasing silver content. When the strain rate was low, plastic deformation occurred with failure and the tensile strength of the Sn-3.0Ag-0.5Cu solder joint was higher than that of Sn-0.3Ag-0.7Cu; when the strain rate was high, joint failure mainly occurred at the brittle interface layer and the Sn-0.3Ag-0.7Cu solder joint had a better impact resistance with a thinner intermetallic compound layer.

Max-AUC Feature Selection in Computer-Aided Detection of Polyps in CT Colonography

PubMed Central

Xu, Jian-Wu; Suzuki, Kenji

2014-01-01

We propose a feature selection method based on a sequential forward floating selection (SFFS) procedure to improve the performance of a classifier in computerized detection of polyps in CT colonography (CTC). The feature selection method is coupled with a nonlinear support vector machine (SVM) classifier. Unlike the conventional linear method based on Wilks' lambda, the proposed method selected the most relevant features that would maximize the area under the receiver operating characteristic curve (AUC), which directly maximizes classification performance, evaluated based on AUC value, in the computer-aided detection (CADe) scheme. We presented two variants of the proposed method with different stopping criteria used in the SFFS procedure. The first variant searched all feature combinations allowed in the SFFS procedure and selected the subsets that maximize the AUC values. The second variant performed a statistical test at each step during the SFFS procedure, and it was terminated if the increase in the AUC value was not statistically significant. The advantage of the second variant is its lower computational cost. To test the performance of the proposed method, we compared it against the popular stepwise feature selection method based on Wilks' lambda for a colonic-polyp database (25 polyps and 2624 nonpolyps). We extracted 75 morphologic, gray-level-based, and texture features from the segmented lesion candidate regions. The two variants of the proposed feature selection method chose 29 and 7 features, respectively. Two SVM classifiers trained with these selected features yielded a 96% by-polyp sensitivity at false-positive (FP) rates of 4.1 and 6.5 per patient, respectively. Experiments showed a significant improvement in the performance of the classifier with the proposed feature selection method over that with the popular stepwise feature selection based on Wilks' lambda that yielded 18.0 FPs per patient at the same sensitivity level. PMID:24608058

Max-AUC feature selection in computer-aided detection of polyps in CT colonography.

PubMed

Xu, Jian-Wu; Suzuki, Kenji

2014-03-01

We propose a feature selection method based on a sequential forward floating selection (SFFS) procedure to improve the performance of a classifier in computerized detection of polyps in CT colonography (CTC). The feature selection method is coupled with a nonlinear support vector machine (SVM) classifier. Unlike the conventional linear method based on Wilks' lambda, the proposed method selected the most relevant features that would maximize the area under the receiver operating characteristic curve (AUC), which directly maximizes classification performance, evaluated based on AUC value, in the computer-aided detection (CADe) scheme. We presented two variants of the proposed method with different stopping criteria used in the SFFS procedure. The first variant searched all feature combinations allowed in the SFFS procedure and selected the subsets that maximize the AUC values. The second variant performed a statistical test at each step during the SFFS procedure, and it was terminated if the increase in the AUC value was not statistically significant. The advantage of the second variant is its lower computational cost. To test the performance of the proposed method, we compared it against the popular stepwise feature selection method based on Wilks' lambda for a colonic-polyp database (25 polyps and 2624 nonpolyps). We extracted 75 morphologic, gray-level-based, and texture features from the segmented lesion candidate regions. The two variants of the proposed feature selection method chose 29 and 7 features, respectively. Two SVM classifiers trained with these selected features yielded a 96% by-polyp sensitivity at false-positive (FP) rates of 4.1 and 6.5 per patient, respectively. Experiments showed a significant improvement in the performance of the classifier with the proposed feature selection method over that with the popular stepwise feature selection based on Wilks' lambda that yielded 18.0 FPs per patient at the same sensitivity level.

Feature engineering for drug name recognition in biomedical texts: feature conjunction and feature selection.

PubMed

Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong; Fan, Xiaoming

2015-01-01

Drug name recognition (DNR) is a critical step for drug information extraction. Machine learning-based methods have been widely used for DNR with various types of features such as part-of-speech, word shape, and dictionary feature. Features used in current machine learning-based methods are usually singleton features which may be due to explosive features and a large number of noisy features when singleton features are combined into conjunction features. However, singleton features that can only capture one linguistic characteristic of a word are not sufficient to describe the information for DNR when multiple characteristics should be considered. In this study, we explore feature conjunction and feature selection for DNR, which have never been reported. We intuitively select 8 types of singleton features and combine them into conjunction features in two ways. Then, Chi-square, mutual information, and information gain are used to mine effective features. Experimental results show that feature conjunction and feature selection can improve the performance of the DNR system with a moderate number of features and our DNR system significantly outperforms the best system in the DDIExtraction 2013 challenge.

Effect of feature-selective attention on neuronal responses in macaque area MT

PubMed Central

Chen, X.; Hoffmann, K.-P.; Albright, T. D.

2012-01-01

Attention influences visual processing in striate and extrastriate cortex, which has been extensively studied for spatial-, object-, and feature-based attention. Most studies exploring neural signatures of feature-based attention have trained animals to attend to an object identified by a certain feature and ignore objects/displays identified by a different feature. Little is known about the effects of feature-selective attention, where subjects attend to one stimulus feature domain (e.g., color) of an object while features from different domains (e.g., direction of motion) of the same object are ignored. To study this type of feature-selective attention in area MT in the middle temporal sulcus, we trained macaque monkeys to either attend to and report the direction of motion of a moving sine wave grating (a feature for which MT neurons display strong selectivity) or attend to and report its color (a feature for which MT neurons have very limited selectivity). We hypothesized that neurons would upregulate their firing rate during attend-direction conditions compared with attend-color conditions. We found that feature-selective attention significantly affected 22% of MT neurons. Contrary to our hypothesis, these neurons did not necessarily increase firing rate when animals attended to direction of motion but fell into one of two classes. In one class, attention to color increased the gain of stimulus-induced responses compared with attend-direction conditions. The other class displayed the opposite effects. Feature-selective activity modulations occurred earlier in neurons modulated by attention to color compared with neurons modulated by attention to motion direction. Thus feature-selective attention influences neuronal processing in macaque area MT but often exhibited a mismatch between the preferred stimulus dimension (direction of motion) and the preferred attention dimension (attention to color). PMID:22170961

Effect of feature-selective attention on neuronal responses in macaque area MT.

PubMed

Chen, X; Hoffmann, K-P; Albright, T D; Thiele, A

2012-03-01

Attention influences visual processing in striate and extrastriate cortex, which has been extensively studied for spatial-, object-, and feature-based attention. Most studies exploring neural signatures of feature-based attention have trained animals to attend to an object identified by a certain feature and ignore objects/displays identified by a different feature. Little is known about the effects of feature-selective attention, where subjects attend to one stimulus feature domain (e.g., color) of an object while features from different domains (e.g., direction of motion) of the same object are ignored. To study this type of feature-selective attention in area MT in the middle temporal sulcus, we trained macaque monkeys to either attend to and report the direction of motion of a moving sine wave grating (a feature for which MT neurons display strong selectivity) or attend to and report its color (a feature for which MT neurons have very limited selectivity). We hypothesized that neurons would upregulate their firing rate during attend-direction conditions compared with attend-color conditions. We found that feature-selective attention significantly affected 22% of MT neurons. Contrary to our hypothesis, these neurons did not necessarily increase firing rate when animals attended to direction of motion but fell into one of two classes. In one class, attention to color increased the gain of stimulus-induced responses compared with attend-direction conditions. The other class displayed the opposite effects. Feature-selective activity modulations occurred earlier in neurons modulated by attention to color compared with neurons modulated by attention to motion direction. Thus feature-selective attention influences neuronal processing in macaque area MT but often exhibited a mismatch between the preferred stimulus dimension (direction of motion) and the preferred attention dimension (attention to color).

Characteristic features of injuries due to shark attacks: a review of 12 cases.

PubMed

Ihama, Yoko; Ninomiya, Kenji; Noguchi, Masamichi; Fuke, Chiaki; Miyazaki, Tetsuji

2009-09-01

Shark attacks on humans might not occur as often as is believed and the characteristic features of shark injuries on corpses have not been extensively reviewed. We describe the characteristic features of shark injuries on 12 corpses. The analysis of these injuries might reveal the motivation behind the attacks and/or the shark species involved in the attack. Gouge marks on the bones are evidence of a shark attack, even if the corpse is decomposed. Severance of the body part at the joints without a fracture was found to be a characteristic feature of shark injuries.

Space Station alpha joint bearing

NASA Technical Reports Server (NTRS)

Everman, Michael R.; Jones, P. Alan; Spencer, Porter A.

1987-01-01

Perhaps the most critical structural system aboard the Space Station is the Solar Alpha Rotary Joint which helps align the power generation system with the sun. The joint must provide structural support and controlled rotation to the outboard transverse booms as well as power and data transfer across the joint. The Solar Alpha Rotary Joint is composed of two transition sections and an integral, large diameter bearing. Alpha joint bearing design presents a particularly interesting problem because of its large size and need for high reliability, stiffness, and on orbit maintability. The discrete roller bearing developed is a novel refinement to cam follower technology. It offers thermal compensation and ease of on-orbit maintenance that are not found in conventional rolling element bearings. How the bearing design evolved is summarized. Driving requirements are reviewed, alternative concepts assessed, and the selected design is described.

New technique of skin embedded wire double-sided laser beam welding

NASA Astrophysics Data System (ADS)

Han, Bing; Tao, Wang; Chen, Yanbin

2017-06-01

In the aircraft industry, double-sided laser beam welding is an approved method for producing skin-stringer T-joints on aircraft fuselage panels. As for the welding of new generation aluminum-lithium alloys, however, this technique is limited because of high hot cracking susceptibility and strengthening elements' uneven distributions within weld. In the present study, a new technique of skin embedded wire double-sided laser beam welding (LBW) has been developed to fabricate T-joints consisting of 2.0 mm thick 2060-T8/2099-T83 aluminum-lithium alloys using eutectic alloy AA4047 filler wire. Necessary dimension parameters of the novel groove were reasonably designed for achieving crack-free welds. Comparisons were made between the new technique welded T-joint and conventional T-joint mainly on microstructure, hot crack, elements distribution features and mechanical properties within weld. Excellent crack-free microstructure, uniform distribution of silicon and superior tensile properties within weld were found in the new skin embedded wire double-sided LBW T-joints.

Development of the weld-braze joining process

NASA Technical Reports Server (NTRS)

Bales, T. T.; Royster, D. M.; Arnold, W. E., Jr.

1973-01-01

A joining process, designated weld-brazing, was developed which combines resistance spot welding and brazing. Resistance spot welding is used to position and aline the parts, as well as to establish a suitable faying-surface gap for brazing. Fabrication is then completed at elevated temperature by capillary flow of the braze alloy into the joint. The process was used successfully to fabricate Ti-6Al-4V alloy joints by using 3003 aluminum braze alloy and should be applicable to other metal-braze systems. Test results obtained on single-overlap and hat-stiffened panel specimens show that weld-brazed joints were superior in tensile shear, stress rupture, fatigue, and buckling compared with joints fabricated by conventional means. Another attractive feature of the process is that the brazed joint is hermetically sealed by the braze material, which may eliminate many of the sealing problems encountered with riveted or spot welded structures. The relative ease of fabrication associated with the weld-brazing process may make it cost effective over conventional joining techniques.

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

PubMed

Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

Differences in manifestations of Marfan syndrome, Ehlers-Danlos syndrome, and Loeys-Dietz syndrome.

PubMed

Meester, Josephina A N; Verstraeten, Aline; Schepers, Dorien; Alaerts, Maaike; Van Laer, Lut; Loeys, Bart L

2017-11-01

Many different heritable connective tissue disorders (HCTD) have been described over the past decades. These syndromes often affect the connective tissue of various organ systems, including heart, blood vessels, skin, joints, bone, eyes, and lungs. The discovery of these HCTD was followed by the identification of mutations in a wide range of genes encoding structural proteins, modifying enzymes, or components of the TGFβ-signaling pathway. Three typical examples of HCTD are Marfan syndrome (MFS), Ehlers-Danlos syndrome (EDS), and Loeys-Dietz syndrome (LDS). These syndromes show some degree of phenotypical overlap of cardiovascular, skeletal, and cutaneous features. MFS is typically characterized by cardiovascular, ocular, and skeletal manifestations and is caused by heterozygous mutations in FBN1 , coding for the extracellular matrix (ECM) protein fibrillin-1. The most common cardiovascular phenotype involves aortic aneurysm and dissection at the sinuses of Valsalva. LDS is caused by mutations in TGBR1/2 , SMAD2/3 , or TGFB2/3 , all coding for components of the TGFβ-signaling pathway. LDS can be distinguished from MFS by the unique presence of hypertelorism, bifid uvula or cleft palate, and widespread aortic and arterial aneurysm and tortuosity. Compared to MFS, LDS cardiovascular manifestations tend to be more severe. In contrast, no association is reported between LDS and the presence of ectopia lentis, a key distinguishing feature of MFS. Overlapping features between MFS and LDS include scoliosis, pes planus, anterior chest deformity, spontaneous pneumothorax, and dural ectasia. EDS refers to a group of clinically and genetically heterogeneous connective tissue disorders and all subtypes are characterized by variable abnormalities of skin, ligaments and joints, blood vessels, and internal organs. Typical presenting features include joint hypermobility, skin hyperextensibility, and tissue fragility. Up to one quarter of the EDS patients show aortic aneurysmal disease. The latest EDS nosology distinguishes 13 subtypes. Many phenotypic features show overlap between the different subtypes, which makes the clinical diagnosis rather difficult and highlights the importance of molecular diagnostic confirmation.

Differences in manifestations of Marfan syndrome, Ehlers-Danlos syndrome, and Loeys-Dietz syndrome

PubMed Central

Meester, Josephina A. N.; Verstraeten, Aline; Schepers, Dorien; Alaerts, Maaike; Van Laer, Lut

2017-01-01

Many different heritable connective tissue disorders (HCTD) have been described over the past decades. These syndromes often affect the connective tissue of various organ systems, including heart, blood vessels, skin, joints, bone, eyes, and lungs. The discovery of these HCTD was followed by the identification of mutations in a wide range of genes encoding structural proteins, modifying enzymes, or components of the TGFβ-signaling pathway. Three typical examples of HCTD are Marfan syndrome (MFS), Ehlers-Danlos syndrome (EDS), and Loeys-Dietz syndrome (LDS). These syndromes show some degree of phenotypical overlap of cardiovascular, skeletal, and cutaneous features. MFS is typically characterized by cardiovascular, ocular, and skeletal manifestations and is caused by heterozygous mutations in FBN1, coding for the extracellular matrix (ECM) protein fibrillin-1. The most common cardiovascular phenotype involves aortic aneurysm and dissection at the sinuses of Valsalva. LDS is caused by mutations in TGBR1/2, SMAD2/3, or TGFB2/3, all coding for components of the TGFβ-signaling pathway. LDS can be distinguished from MFS by the unique presence of hypertelorism, bifid uvula or cleft palate, and widespread aortic and arterial aneurysm and tortuosity. Compared to MFS, LDS cardiovascular manifestations tend to be more severe. In contrast, no association is reported between LDS and the presence of ectopia lentis, a key distinguishing feature of MFS. Overlapping features between MFS and LDS include scoliosis, pes planus, anterior chest deformity, spontaneous pneumothorax, and dural ectasia. EDS refers to a group of clinically and genetically heterogeneous connective tissue disorders and all subtypes are characterized by variable abnormalities of skin, ligaments and joints, blood vessels, and internal organs. Typical presenting features include joint hypermobility, skin hyperextensibility, and tissue fragility. Up to one quarter of the EDS patients show aortic aneurysmal disease. The latest EDS nosology distinguishes 13 subtypes. Many phenotypic features show overlap between the different subtypes, which makes the clinical diagnosis rather difficult and highlights the importance of molecular diagnostic confirmation. PMID:29270370

SU-F-T-450: The Investigation of Radiotherapy Quality Assurance and Automatic Treatment Planning Based On the Kernel Density Estimation Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, J; Fan, J; Hu, W

Purpose: To develop a fast automatic algorithm based on the two dimensional kernel density estimation (2D KDE) to predict the dose-volume histogram (DVH) which can be employed for the investigation of radiotherapy quality assurance and automatic treatment planning. Methods: We propose a machine learning method that uses previous treatment plans to predict the DVH. The key to the approach is the framing of DVH in a probabilistic setting. The training consists of estimating, from the patients in the training set, the joint probability distribution of the dose and the predictive features. The joint distribution provides an estimation of the conditionalmore » probability of the dose given the values of the predictive features. For the new patient, the prediction consists of estimating the distribution of the predictive features and marginalizing the conditional probability from the training over this. Integrating the resulting probability distribution for the dose yields an estimation of the DVH. The 2D KDE is implemented to predict the joint probability distribution of the training set and the distribution of the predictive features for the new patient. Two variables, including the signed minimal distance from each OAR (organs at risk) voxel to the target boundary and its opening angle with respect to the origin of voxel coordinate, are considered as the predictive features to represent the OAR-target spatial relationship. The feasibility of our method has been demonstrated with the rectum, breast and head-and-neck cancer cases by comparing the predicted DVHs with the planned ones. Results: The consistent result has been found between these two DVHs for each cancer and the average of relative point-wise differences is about 5% within the clinical acceptable extent. Conclusion: According to the result of this study, our method can be used to predict the clinical acceptable DVH and has ability to evaluate the quality and consistency of the treatment planning.« less

Medicare Program; Comprehensive Care for Joint Replacement Payment Model for Acute Care Hospitals Furnishing Lower Extremity Joint Replacement Services. Final rule.

PubMed

2015-11-24

This final rule implements a new Medicare Part A and B payment model under section 1115A of the Social Security Act, called the Comprehensive Care for Joint Replacement (CJR) model, in which acute care hospitals in certain selected geographic areas will receive retrospective bundled payments for episodes of care for lower extremity joint replacement (LEJR) or reattachment of a lower extremity. All related care within 90 days of hospital discharge from the joint replacement procedure will be included in the episode of care. We believe this model will further our goals in improving the efficiency and quality of care for Medicare beneficiaries with these common medical procedures.

The Role of High-resolution Peripheral Quantitative Computed Tomography as a Biomarker for Joint Damage in Inflammatory Arthritis.

PubMed

Tam, Lai-Shan

2016-10-01

Since 2011, members of the SPECTRA Collaboration (Study grouP for xtrEme-Computed Tomography in Rheumatoid Arthritis) have investigated the validity, reliability, and responsiveness of high-resolution peripheral quantitative computed tomography (HR-pQCT) as a biomarker for joint damage in inflammatory arthritis. Presented in this series of articles are a systematic review of HR-pQCT-related findings to date, a review of selected images of cortical and subchondral trabecular bone of metacarpophalangeal (MCP) joints, results of a consensus process to standardize the definition of erosions and their quantification, as well as an examination of the effect of joint flexion on width and volume assessment of the joint space.

Effect of friction stir welding parameters on defect formation

NASA Astrophysics Data System (ADS)

Tarasov, S. Yu.; Rubtsov, V. E.; Eliseev, A. A.; Kolubaev, E. A.; Filippov, A. V.; Ivanov, A. N.

2015-10-01

Friction stir welding is a perspective method for manufacturing automotive parts, aviation and space technology. One of the major problems is the formation of welding defects and weld around the welding zone. The formation of defect is the main reason failure of the joint. A possible way to obtain defect-free welded joints is the selection of the correct welding parameters. Experimental results describing the effect of friction stir welding process parameters on the defects of welded joints on aluminum alloy AMg5M have been shown. The weld joint defects have been characterized using the non-destructive radioscopic and ultrasound phase array methods. It was shown how the type and size of defects determine the welded joint strength.

Modified Bat Algorithm for Feature Selection with the Wisconsin Diagnosis Breast Cancer (WDBC) Dataset

PubMed

Jeyasingh, Suganthi; Veluchamy, Malathi

2017-05-01

Early diagnosis of breast cancer is essential to save lives of patients. Usually, medical datasets include a large variety of data that can lead to confusion during diagnosis. The Knowledge Discovery on Database (KDD) process helps to improve efficiency. It requires elimination of inappropriate and repeated data from the dataset before final diagnosis. This can be done using any of the feature selection algorithms available in data mining. Feature selection is considered as a vital step to increase the classification accuracy. This paper proposes a Modified Bat Algorithm (MBA) for feature selection to eliminate irrelevant features from an original dataset. The Bat algorithm was modified using simple random sampling to select the random instances from the dataset. Ranking was with the global best features to recognize the predominant features available in the dataset. The selected features are used to train a Random Forest (RF) classification algorithm. The MBA feature selection algorithm enhanced the classification accuracy of RF in identifying the occurrence of breast cancer. The Wisconsin Diagnosis Breast Cancer Dataset (WDBC) was used for estimating the performance analysis of the proposed MBA feature selection algorithm. The proposed algorithm achieved better performance in terms of Kappa statistic, Mathew’s Correlation Coefficient, Precision, F-measure, Recall, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Relative Absolute Error (RAE) and Root Relative Squared Error (RRSE). Creative Commons Attribution License

Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

PubMed Central

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-01-01

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285